Innovation, Knowledge and Power in Organizations (Routledge Studies in Global Competition)

Innovation, Knowledge and Power in Organizations

This book examines discourses of knowledge and innovation in post-industrial societies and knowledge-based organizations. The author investigates the value of knowledge and the question of innovation management in a fully commercial environment for a technology company. In contrast with most of the mainstream approaches to knowledge and innovation management this volume chooses as its starting point a critical examination of these assumptions before proceeding with further suggestions on how to manage knowledge. Using brand new empirical research, the author argues for the significance of addressing the political games and power struggles enacted in managing innovation processes, which result from the opportunity certain groups seek to acquire or extend their control over valuable resources. Again, in contrast to mainstream approaches that reduce power to the ability of individuals to negotiate in order to promote their ideas, the analysis adopts an extended view on power, and seeks to reveal the ambiguities and challenges of innovation management. This work will be of most interest to researchers and students of knowledge and innovation management, namely postgraduates and second degree students, as well as managers in knowledge-based organizations. Theodora Asimakou has a PhD in Management from Manchester Business School. She has research and consulting experience in academic and commercial projects in large organizations in Greece and UK. She is currently employed as a lecturer at 1st College, Athens, Greece.

Routledge studies in global competition Edited by John Cantwell University of Reading, UK and

David Mowery University of California, Berkeley, USA

1 Japanese Firms in Europe Edited by Frédérique Sachwald 2 Technological Innovation, Multinational Corporations and New International Competitiveness The case of intermediate countries Edited by José Molero 3 Global Competition and the Labour Market Nigel Driffield 4 The Source of Capital Goods Innovation The role of user firms in Japan and Korea Kong-Rae Lee

8 Strategy in Emerging Markets Telecommunications establishments in Europe Anders Pehrsson 9 Going Multinational The Korean experience of direct investment Edited by Frédérique Sachwald 10 Multinational Firms and Impacts on Employment, Trade and Technology New perspectives for a new century Edited by Robert E. Lipsey and Jean-Louis Mucchielli

5 Climates of Global Competition Maria Bengtsson

11 Multinational Firms The global–local dilemma Edited by John H. Dunning and Jean-Louis Mucchielli

6 Multinational Enterprises and Technological Spillovers Tommaso Perez

12 MIT and the Rise of Entrepreneurial Science Henry Etzkowitz

7 Governance of International Strategic Alliances Technology and transaction costs Joanne E. Oxley

13 Technological Resources and the Logic of Corporate Diversification Brian Silverman

14 The Economics of Innovation, New Technologies and Structural Change Cristiano Antonelli 15 European Union Direct Investment in China Characteristics, challenges and perspectives Daniel Van Den Bulcke, Haiyan Zhang and Maria do Céu Esteves 16 Biotechnology in Comparative Perspective Edited by Gerhard Fuchs 17 Technological Change and Economic Performance Albert L. Link and Donald S. Siegel 18 Multinational Corporations and European Regional Systems of Innovation John Cantwell and Simona Iammarino 19 Knowledge and Innovation in Regional Industry An entrepreneurial coalition Roel Rutten 20 Local Industrial Clusters Existence, emergence and evolution Thomas Brenner 21 The Emerging Industrial Structure of the Wider Europe Edited by Francis McGowen, Slavo Radosevic and Nick Von Tunzelmann

22 Entrepreneurship A new perspective Thomas Grebel 23 Evaluating Public Research Institutions The U.S. Advanced Technology Program’s Intramural Research Initiative Albert N. Link and John T. Scott 24 Location and Competition Edited by Steven Brakman and Harry Garretsen 25 Entrepreneurship and Dynamics in the Knowledge Economy Edited by Charlie Karlsson, Börje Johansson and Roger R. Stough 26 Evolution and Design of Institutions Edited by Christian Schubert and Georg von Wangenheim 27 The Changing Economic Geography of Globalization Reinventing space Edited by Giovanna Vertova 28 Economics of the Firm Analysis, evolution and history Edited by Michael Dietrich 29 Innovation, Technology and Hypercompetition Hans Gottinger 30 Mergers and Acquisitions in Asia A global perspective Roger Y.W. Tang and Ali M. Metwalli

31 Competitiveness of New Industries Institutional framework and learning in information technology in Japan, the U.S and Germany Edited Cornelia Storz and Andreas Moerke 32 Entry and Post-Entry Performance of Newborn Firms Marco Vivarelli 33 Changes in Regional Firm Founding Activities A theoretical explanation and empirical evidence Dirk Fornahl 34 Risk Appraisal and Venture Capital in High Technology New Ventures Gavin C. Reid and Julia A. Smith 35 Competing for Knowledge Creating, connecting and growing Robert Huggins and Hiro Izushi 36 Corporate Governance, Finance and the Technological Advantage of Nations Andrew Tylecote and Francesca Visintin 37 Dynamic Capabilities Between Firm Organisation and Local Systems of Production Edited by Riccardo Leoncini and Sandro Montresor

38 Localised Technological Change Towards the economics of complexity Cristiano Antonelli 39 Knowledge Economies Innovation, organization and location Wilfred Dolfsma 40 Governance and Innovation Maria Brouwer 41 Public Policy for Regional Development Edited by Jorge Martinez-Vazquez and François Vaillancourt 42 Evolutionary Economic Geography Location of production and the European Union Miroslav Jovanovic 43 Broadband Economics Lessons from Japan Takanori Ida 44 Targeting Regional Economic Development Edited by Stephan J. Goetz, Steven C. Deller and Thomas R. Harris 45 Innovation, Knowledge and Power in Organizations Theodora Asimakou

Innovation, Knowledge and Power in Organizations

Theodora Asimakou

First published 2009 by Routledge 2 Park Square, Milton Park, Abingdon, Oxon OX14 4RN Simultaneously published in the USA and Canada by Routledge 270 Madison Ave, New York, NY 10016 Routledge is an imprint of the Taylor & Francis Group, an informa business This edition published in the Taylor & Francis e-Library, 2008. “To purchase your own copy of this or any of Taylor & Francis or Routledge’s collection of thousands of eBooks please go to www.eBookstore.tandf.co.uk.”

© 2009 Theodora Asimakou All rights reserved. No part of this book may be reprinted or reproduced or utilized in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging in Publication Data A catalog record for this book has been requested ISBN 0-203-88348-9 Master e-book ISBN

ISBN10: 0-415-42666-9 (hbk) ISBN10: 0-203-88348-9 (ebk) ISBN13: 978-0-415-42666-4 (hbk) ISBN13: 978-0-203-88348-8 (ebk)

Contents

List of illustrations

1

Introduction: a story of studying technological innovation

viii

1

PART I

Theoretical

19

2

The value of knowledge in post-industrial societies

21

3

Knowledge and innovation in organizations

45

PART II

Empirical 4

Commercialization and knowledge production: Hydro-Carbon Solutions

77

79

5

The construction of ‘commercial innovation’

110

6

The politics of innovation: Technology Group A

124

7

Innovation management in a commercial environment: Technology Group B

145

Conclusion: the commercial condition of knowledge

165

Appendix: sources of information Notes Bibliography Index

183 185 188 196

8

Illustrations

Figures 3.1 3.2 3.3

Organizations and types of knowledge Model of organizational knowledge creation Model of organizational interpretation modes

50 51 55

Tables 8.1 8.2 8.3 8.4 A.1

The sovereignty of economic rationale Strategies of invasion and resistance Re-articulation of the research language game Competing discourses of innovation Distribution of interviews

166 168 173 177 184

1

Introduction A story of studying technological innovation

Introduction It may be stating the obvious to say that knowledge is the key resource in today’s post-industrial society; a powerful discourse has been construed in the latest years, which relates the sustainability and the success of businesses to their capacity to compete on the edge of new and rare knowledge, either in the form of new products and services, or businesses, etc. This discourse has a great impact on the structural properties of society and organizations; the latter, following the prescriptions of knowledge rhetoric, have joined the pursuit of identifying their knowledge capital and supporting the processes of new knowledge generation and innovation, which are expected ultimately to return the competitive advantage. Hence, a new type of organization has emerged: the knowledge-based organization; its main feature is that the production processes are not defined by capital or labour, but knowledge. Knowledge becomes the input and the output of the production process, and its quest intensifies. Clearly, the new discourse on the value of knowledge and innovation has created the need for understanding and managing the related processes; the field of knowledge and innovation management has been approached and studied from many different disciplines and perspectives (Economics, Finance, Organization Behaviour, Information Science), which predominantly conclude the studies by developing technologies and tools to support these processes. Innovation is framed within these approaches in terms of a ‘hardcore’ technical language, which asserts the ‘performativity’, the ‘cost’ and the ‘economic benefits’ of investing in innovations. Others take a more critical stance and suggest trying and understanding the properties of the phenomenon before we reach the stage for recommendations. A phenomenon that gains increasingly great force and, considering the structural transformations it has caused, has already proved that it is not another ‘management fashion’, needs be studied carefully and from multiple standpoints. This second stream in studying innovation has formed conceptually this piece of research. The project takes a step back and studies the nature of discourse on knowledge and innovation, and its consequences for knowledge-based organizations. In particular, it questions whether innovation, defined not as product

2

Introduction

development, for this type of innovation cannot secure the sustainability of the business in the future, but as long-term and uncertain programmes, can be supported in a fully commercial environment, and, if yes, what strategies and processes are enacted to conciliate the inconsistencies that exist in the fundamental assumptions of these discourses. The argument is that knowledge and innovation have been first articulated within a different language game, therefore their translation into the language game of cost-control and profitability would meet resistance and lead to the reordering of power relations, and ultimately to the redefinition of the rules of either (or both) language game. In other words, the study adds the power factor to the analysis of innovation, a factor that mainstream approaches frequently either neglect or take a limited view on power, which reduces politics to the power of negotiation and the social networks of individuals. The empirical part of the study was conducted in a technology-based organization (which I call Hydro-Carbon Solutions), because the most appropriate site to conduct the research would be an organization where knowledge is the main resource for the business operations, and where the creation of new knowledge would be a primary concern for the organization. The rationale behind this is that in such an organization I would be able to study (a) at the macro level, the grand discourse on innovation, i.e. the discourse that allegedly guides organizational actions, and (b) at the same time, at the organizational level, the discourses on innovation that each organization constructs, according to its own history and understanding of what they should do, and other conflicting discourses that could possibly impede innovation to become the ‘one’ accepted reality. The interesting feature with these companies is that they employ a large number of ‘hard’ scientists, most of them being qualified researchers at a PhD level, who often have worked (or some of them currently have) a position in the academia, and now they are employed in an organization with commercial ends. I thought that this point would throw light on the question of knowledge from various aspects, since it would enable me to study the re-articulations within the dominant innovation discourse, as it converges to embracing a commercial rationale, and the collision between competing discourses on innovation that emerge at the limits of the commercial discourse, as well as the effects on knowledge subjects and structures – i.e. the scientists, the innovation processes, etc. Having adopted a critical position to the study of organization, the objective of the book is not to nullify rationalistic approaches on the grounds of being inadequate to study innovation; on the contrary, it asserts the opening up of the debate, for knowledge and innovation are multidimensional phenomena and need be studied from multiple perspectives; by challenging the established frame of thinking regarding management and organizational phenomena the book aspires to provoke debate and new ways of tackling management issues related to knowledge and innovation. The contribution of the book is that, by applying critical discourse analysis, i.e. an off-the-mainstream methodology for organizational studies, in the study of knowledge processes, it gains insights into the changing nature of knowledge and innovation, investigates the consequent

Introduction

3

reordering of the power relations and theorizes the consequences for the knowledge subjects and structures; in other words, the book suggests the analysis of power in the study of innovation processes by listening to the voices of various partakers.

Discourse and organizational studies Discourse theory has been developed as a response to amend the perceived weaknesses of conventional qualitative research.1 It rejects realism, suggesting instead a social constructionist view of the world, formulated by Wittgenstein’s writings on language and Marxist concepts on politics and ideology; at the same time, it does not reject the interpretative models of social research, as inspired by Weber and others. Grounded in a post-structuralist epistemology and its critique on language, discourse theory opened up new ways of thinking about the relationship between structure and agency, identities and social actions, the interweaving of meanings and practices, and the nature of social and historical change. For discourse theory all objects and actions are meaningful, and this meaning is conferred by historical specific systems of rules. Following Foucault, the meaning depends on the orders of discourse that constitute its identity and significance (Foucault, 1971, 1972); that I perceive a tree as decoration, or as first resource for economic expansion, or as an obstacle, depends upon the discourse – aesthetics, economic rationality or personal interest – from within I operate. Howarth and Stavrakakis (2000: 3–4) describe the nature of discourse as follows: we take discourse or discourses to refer to systems of meaningful practices that form the identities of subjects and objects. At this lower level of abstraction, discourses are concrete systems of social relations and practices that are intrinsically political, as their formation is an act of radical institution, which involves the construction of antagonisms and the drawing of political frontiers between ‘insiders’ and ‘outsiders’. In addition, therefore, they always involve the exercise of power, as their constitution involves the exclusion of certain possibilities and a consequent structuring of the relations between different social agents. Moreover, discourses are contingent and historical constructions, which are always vulnerable to those political forces excluded in their production, as well as the dislocatory effects of events beyond their control. This description encapsulates traces of the approaches (structuralism, Foucauldian, etc.) that have contributed in shaping the shared understanding of discourse in social interactions. Indeed, the study of discourse is being conducted from different perspectives (interpretative, critical, post-structuralist) and one can notice some variations as to what is treated as ‘discourse’. Structural

4

Introduction

linguistics defines discourse as ‘language above the sentence or the clause’, whereas functional approaches define discourse as ‘language in use’ (Schiffrin, 1994). Foucault, on the other hand, having adopted a more abstract approach to discourse analysis, treats discourse as a set of statements that formulate objects and subjects.2 Despite these differences, there are some fundamental assumptions about language that various approaches to the study of discourse treat as common ground (Potter and Wetherell, 1987: 35): • language is used for a variety of functions and its use has a variety of consequences • language is both constructed and constructive • the same phenomenon can be described in a number of ways • there will, therefore, be considerable variations in accounts • there is, as yet, no foolproof way to deal with this variation and to shift accounts which are ‘literal’ or ‘accurate’ from those which are rhetorical or merely misguided thereby escaping the problems variation raises for researchers with a ‘realistic’ model of language • the constructive and flexible ways in which language is used should themselves become a central topic of study. Discourse analysis draws attention to three key aspects of language: contradiction, construction and practice (Parker and BDN, 1999). ‘Contradiction’ searches for different meanings that are at work in the text; contradictions between different significations and contradictions between different versions of the world. This does not mean that consistencies cannot be a topic of study; patterns and repetitions are interesting as well, but they do not take upon the role of ‘normal’ uncritically. ‘Construction’ refers to the examination of how meanings have been socially constructed in a way to make sense as normal or natural to the reader. Last, ‘practice’ questions what these contradictory systems of meanings are doing; how they naturalize the people’s understanding of what ‘normal’ and ‘natural’ is, and the consequences of this naturalization on how people understand the world and act. Issues of power and ideology may be called into play, as discourse is investigated in terms of its political function. The linguistic turn towards the study of discourse in social sciences has intrigued the attention of much research in organization studies. Consequent of the vague understanding and agreement as to what ‘discourse’ refers to, the research that has been conducted from this approach, covers various areas and aspects of the organizational life. Keenoy et al. (1997), attempting to conceptualize the related work done on the field, distinguish two main streams: the first one is between authors that see discourse analysis as a methodological device for making linguistic sense of organizations and organizational phenomena; these authors focus on the study of social text, which includes the study of talk and written text in its social action contexts and highlights the ‘talked’ and ‘textual’ nature of everyday interaction in organization (Alvesson and Karreman, 2000).

Introduction

5

The second, in contrast, sees the study of discourse as a means for revealing the ambiguities of social construction and the indeterminacy of organizational experiences. From this viewpoint, social reality is discursively constructed and maintained, and analysis focuses on its determination through historically situated discursive moves. This approach introduces and studies the social and political dimensions of language, in addition to the discursive, compared to the more narrow-focused textual approaches. These latter studies have been greatly formed in the ground of a Foucauldian approach to the study of discourse (Alvesson and Karreman, 2000).

Methodology – critical discourse analysis The research adopts a language-centred view on studying innovation. From this perspective, discourse, i.e. a web of relations among elements, which provides the conditions of emergence of any meaningful object, rather than action or meaning, is the object of study. Following Van Leewen (in Wodak and Meyer, 2001) I looked at discourse both as a social practice and as a form of knowledge that shapes realities; I examined innovation, as articulated by various groups and within different webs of relationships, and then contrasted it with the normative discourse of innovation, as found in the academic literature, which supposedly shapes organizational actions. The assumptions behind this approach is that discourse is a mode of action, in other words, a way of people interacting with each other and the world, as well as a mode of representation – a representation not of the world, but of the humans’ perceptions of the world. ‘Social practice’ implies that language is neither a social product nor an entity independent of the society. Language is a part of the societal whole. There is a dialectical interaction between discourse and social structures – similar to the relationship between social practices and social structures; discourse is construed by the social structure, interest groups, institutions, etc., in other words, the social orders that shape orders of discourse. Discourse is not only shaped but also impacts and shapes social structure and orders, giving the world meaning. Actual/local discourse is determined by socially constituted orders of discourse, and sets of conventions associated with social institutions (Fairclough, 1989). I should note here that this point recognizes a degree of freedom to individuals to choose from existing discourses, according to the specific situation and their objectives each time. Fairclough (1992) distinguishes three aspects of the constructive effects of discourse: (a) discourse constructs ‘social identities’ and the self; (b) discourse constructs social relationships among people and (c) discourse contributes to the construction of knowledge and beliefs. These three functions of discourse form the keystone of the analytical framework. From the nature and functions of discourse, it follows that not only a change in social orders is represented in a change of discourse, but also a change in discourse transforms identities, relationships and systems of knowledge. Change occurs when the contested discourse – as any discourse – reaches its limits when it encounters events that cannot be explained within the current

6

Introduction

discursive system, and hence is being redefined by re-articulating the relations among its elements. Laclau and Mouffe (2001) call this failure of discourse to domesticate new events ‘dislocation’, and assert that it leads to a partial breakdown of the symbolic order. The limits of a discourse change, as it now may include new elements, lose others and rearrange their web of relations. In this process, new meanings and practices emerge, while the identities and relations of the subjects participating in this struggle are being redefined (Torfing, 2005). Discourses are not produced in a vacuum within organizations, but draw from other extra-organizational more stable discursive orders. Critical discourse analysis allows the study of more stable discourses in a Foucauldian sense together with the study of language in use; in other words, it allows the study of discourse both at the micro and the macro level, and addresses issues of conflict and power, which are fundamental concepts to interpret the findings of the present research, which studies how the dominant view is being contested by various groups that conflict over defining what innovation is. During the data collection stage, many different discourses on innovation emerged that would be linked to different actions, or sometimes the same statements would be used to do different things. Critical discourse analysis provided the appropriate interpretative framework to make sense of these findings. On this point my analysis deviated from the approach standard critical discourse analysis takes on treating meaning and cognition; even though I recognize the power of discourse in shaping subjectivity and meanings, I bracketed off cognitive elements (ideas, stable meanings, etc.) and emotions. Discourses construct versions of the world, and their mere existence does things (Potter and Wetherell, 1987). Instead of searching for the ‘real’ meaning of the texts, I adopt a phenomenological stance, which ‘brackets’ truth-value and allows the multivocal study of discourses on innovation within the organization; meaning is treated as locally constructed and transient, rather than stable and fixed. I keep the main focus on discourses (the innovation discourses), the social processes of their production, their relation with other discourses and the consequent implications for the organization (the actions taken and structures adopted). The study does not assume the interlocutors’ one fixed identity that is revealed via discourse analysis, but a ‘temporary’ identity, shaped along with the text from within it emerges (formal documents, interview, etc.) and determined by the purpose and the context of its construction, as well as participants’ subjectivity. Research design and methods The empirical research, which was part of my doctoral studies, is an ethnographic study that materialized between April 2002 and October 2003 in the research laboratories of an energy company in the UK, which I will name Hydro-Carbon Solutions. I intensively study two Business Groups, to which I will refer as Technology Group A and B. The parent company had decided to give R&D research a ‘commercial twist’, and it pushed the technical laboratories to come up with more ‘commercial ideas’ and also to compete in order to prove

Introduction

7

their commercial value to the company. The signed agreement with the company allowed me access in the field for one year starting in June 2002; informally I had access much earlier to company’s documents and I had started browsing their websites since April 2002, and I kept contact with the Business Groups and was updating my information until I finalized my project. Thus, I had the opportunity to observe and interact with the company for more than one year, and to study discourses and changes from a longer-term perspective. I applied a range of qualitative techniques to gather information; due to the language focus of the research, I looked for texts from a range of different sources (see Appendix), which could provide insights into formal and informal, dominant and weaker discourses. The main technique I used – ‘main’ in the sense that I used it to generate the largest bulk of information – was the individual interview; I also used participant observation, informal conversations, and study of desk data, such as organizational documents, newsletters, e-mails, internet and intranet websites. These techniques were employed in parallel throughout the time of data collection, in order to support and elucidate issues that were emerging while being in the field. Documentary data Most qualitative studies treat documents as secondary information, which is studied to cross-check and validate other information gathered from interviews or observations (Atkinson and Coffey, 1997). These studies use documents as a source of historical and descriptive information. However, having adopted here a discursive approach, I felt that treating documents as a secondary source misses out a lot of information that can only be generated by analysing documents as primary data in their own right; textual practices are a vital way in which organizations constitute their reality, and the study of the rules of their production is equally essential to the study of their content. Hence, a study of the processes of production and circulation gives distinct insights into the organizational realities. I treated documentary data as the source of ‘formal’ organizational discourse, which I analysed following the same methodology as the information gathered from interviews. Consistent with the phenomenological stance I have adopted, the truth-value of the material was irrelevant, since what I was searching was precisely the differences between the viewpoints and the different discourses from where these texts were drawn. The research started by gathering information regarding the history and strategy of the company, in order to familiarize myself with the organizations; a large part of the information was found on the internet, annual reports and organizational charts. The intranet and internet sites had great interest for the purpose of the study, which gave me the opportunity to observe not only the ‘discourse’ in terms of language, but also how different Business Groups were constructing and changing their website according to the changes the organizations were going through and considered important.

8

Introduction

Observations in the field Unlike normative methodologies, which request the researcher’s detachment from the field, in order to ensure the objectivity of the findings, qualitative research benefits from the possibility that its epistemological ground gives the researcher to enter the field and interact personally with the people on site, and hence to gain insights into their daily lives first hand by observing them and the accounts people construct as they interact (Burgess, 1984). The kind of information recorded this way is valuable and unique, for it involves people talking and acting naturally, hence the opportunity to observe and understand the importance and the applications of the rules that regulate their daily life, i.e. observing people following and breaking the rules, and reasoning about their actions. The observations were recorded in my field diary during the occurrence of events (e.g. meetings) or after them (e.g. informal conversations). This method allowed the interpretation of data to address eventually not only what is said or done, but also the context and the way the accounts and the observations were made. Employees at the technology site – from the security people to the senior managers – were strikingly friendly and ready for chatting. People working for the company moved frequently from one site to another, and also there were many students that came in and did short projects; hence my presence was not unusual – and especially for those who had an interest in innovation management my presence was welcome. Throughout these occasions, I was aiming initially to familiarize myself with the environment, understand the unwritten rules according to which the Business Groups work and observe naturally occurring discourse and actions. I found particularly interesting and mind-orienting the gossips, or rather the exchange of information and observations about ‘trivial’ things of everyday life and the past days, that people naturally mentioned, while having a coffee – or when bored. Individual interviews The main method I used for data generation was the in-depth interview; it is a – relatively – quick way to generate information about the themes under study, and it gives the opportunity to observe discourses as they are being produced. My aim was not to learn what knowledge and innovation are, but when, how and why the discourse on innovation and the adopted practices emerged, and the different meanings ‘innovation’ has acquired through its use. Compatible with the epistemological assumptions of the study, the truth-value of what is being said was irrelevant for the purpose of the study, and hence this stance was best reflected on the ‘active’ approach to interviewing (Silverman, 2001). The ‘active’ approach to interviewing assumes that the interview even though it has its own objectives and rules on how to proceed, ultimately is another speech event, and being a speech event it shapes the content of what is said;3 the interviewer and the interviewee interact and construct together meanings while

Introduction

9

the interview develops. For the active interview there is no ‘single’ meaning to extract during the interview; however, this is not to mean that meanings are absolutely unique for the situation from within which they are constructed and have no significance outside the situation: meanings are not built from scratch, rather the interviewee interprets what is asked and also the situation, and responds according to the knowledge resources they have about the content of the question, and about the situation (Holstein and Gubrium, 1997). The active interview gives the possibility to explore what the research topic is about, and also how knowledge about the topic is narratively constructed (Holstein and Gubrium, 1995). In other words, active interviews give insights into the research question, but also elucidate the subject’s interpretative actions. Acknowledging the situational character of the meaning-making process, the validity of answers derives not from their correspondence to an external reality, but from their ability to convey situation experienced realities in terms that are locally comprehensible (Holstein and Gubrium, 1997). The investigation started with interviewing members of the Innovation Team at Technology Group A, who were in charge of managing the Ideas Machine, in order to get an understanding of what the innovation mechanism was. Most of the interviews I conducted were semi-structured, i.e. I had an agenda of themes I wanted to study,4 but the questions were open to the interviewees to answer them as they thought it would be most relevant and insightful to the topics under investigation. The unstructured interviews were used as exploratory tools in areas that might have an impact on the topic under study. This flexible structure enabled me to include in the interview schedule and explore new questions that emerged while being in the field (Holstein and Gubrium, 1995; Mishler, 1986), and based on this schedule and findings I conducted the unstructured follow-up interviews at the end of the study. During the time of my fieldwork, I conducted in total 41 in-depth interviews from which 30 were semi-structured and 11 unstructured with individuals from three Business Groups of Hydro-Carbon Solutions. I selected the interviewees in terms of their academic and professional qualifications and years employed at the company. I was searching for differences in the discourses of managers, senior scientists, newly recruited employees and other groups who were empowered by the commercialization turn or the innovation discourse. The semistructured interviews lasted a minimum of one hour, they were tape-recorded, and run cutting across the sampled groups, in order to eliminate the impact of the participants’ perceptions on shaping my understanding and take sides. All interviews were attentively transcribed before the analysis. Interpretation of field data In qualitative research, data interpretation starts simultaneously with data generation (Burgess, 1984). While I was in the field, I was keeping notes of each event I was participating and observing (interviews, conversations, meetings, etc.), and at the end of each day I was writing in a diary a summary of the day

10

Introduction

and of the progress of the research. The result was that I was able to build an understanding of the site, the people and the relationships, as emerged by crosschecking and linking the notes; the method allowed me to observe my own position towards the site and my progress of understanding the research. By reading these data while I was doing the fieldwork, I was able to generate themes for further investigation and a preliminary interpretation of the findings at each stage. These interpretations while in the field acted as milestones in developing the research further. The second stage of interpretation took place at the end of the fieldwork; at this stage, I reread all the data I had collected, all my field notes, diary and preliminary analysis, and reconceptualized the themes through the lenses that my methodological framework suggested, searching for sensible relationships and explanations, and connecting issues between them and with the theoretical framework. Committed to my discursive approach I searched in the texts for: • • • •

strategies of dominance, neutralization and resistance, conflicting discourses and contradicting elements, dislocating events, rhetorics and grand narratives.

Reflexive research and evaluation criteria It is relevant at this point to include a final note, regarding the criteria against which a study that departs from a positivist epistemology should be evaluated. It is particularly relevant to the present study, which endorses a critical theory perspective to the analysis of organizational life. Despite the long debate upon the differences between quantitative and qualitative research in social studies, and even though qualitative research has proved its value and adequacy in exploring aspects of social life in a different light, still it has to defend itself on the ground of criteria suitable for deductive research, i.e. validity and reliability (Gill and Johnson, 2002). These criteria are difficult to be met because of the fundamental differences between the two traditions in terms of their philosophical assumptions and historical development. The first stream of responses to this limitation from the qualitative front was to try to develop further and refine the methodologies and techniques to be used, in order to meet the established criteria (Gill and Johnson, 2002; Silverman, 1997). This tactic has resulted undoubtedly in more sophisticated qualitative methodologies and techniques, as well as in deeper insights into their value and into the process of researching. However, the case remains that qualitative research is fundamentally different from quantitative, and even when it manages to satisfy these criteria, it lacks criteria to assess its value on its own ground – criteria that would address the peculiarities and objectives of qualitative research. A second stream of responses addressed the limitations and inherent weaknesses of quantitative research in studying humans and social phenomena, emphasizing at the same time the adequacy of qualitative research to overcome

Introduction

11

these limitations. The contributions of post-modernism and critical theory, together with the momentum that the linguistic turn has acquired recently, have added a great deal in developing sound arguments for this debate. First, the cornerstone of quantitative tradition, the ‘objectivity’ of the research findings has been doubted, as it has been ascertained that objectivity is a chimera: research is not value free, it will always be constructed via the researcher’s presuppositions and understanding; ironically, the less ‘objective’ research is precisely quantitative research, since by principle it pre-constructs a version of the world, which then sets out to measure without questioning the subjectivity of these claims (Deetz, 1996). From this point onwards, phenomenology has suggested that truth-value is irrelevant for the purpose of a study, as the principle of symmetry expects the outcomes of interpretation to stand on their own, regardless of truth or falsehood of data (Potter, 1996). Foucault went further in arguing for a bracketing of both truthvalue and meaning of the phenomenon under study, which indicates towards a restriction of research to the observable aspect of social phenomena and the contingencies for and consequences of their existence, avoiding like that the limitations of the subjective interpretations and cognitivism. Post-modernism, on the other hand, has argued for the existence of multiple meanings and the importance to acknowledge weak and absent voices in the interpretation of the findings. Finally, discourse studies embedding elements of the previous views have conceptualized the above debate as indeed a power/knowledge issue, where voices from different paradigms struggle to ascertain their existence, suggesting versions of the world; this means that no view is right or wrong, but rather equally important. All the previous remarks have led to reconsidering the purpose and value of science; for if we want to suggest new criteria – and thus to avoid relativistic claims – then these have to be compatible with the nature of knowledge. The criterion of internal validity, which seeks to ascertain causal relationships between phenomena, falls short, because simply research from a critical and discursive point of view does not embrace any sort of causality, but rather the contingency and the unique nature of social life. The same argument can be addressed towards the replicability of research; research from this standpoint sets out to study irregularities rather than normal and repetitive cases. Researchers from these schools of thought claim that there is as much to learn from the different and the small as from the big and normal (Silverman, 1997; Alvesson and Sköldberg, 2000). Various criteria have been suggested from this ‘reflexive’5 perspective for evaluating qualitative research (Marshall and Rossman, 1995; Potter and Wetherell, 1987). Researchers in general agree on the importance of usefulness of new knowledge, the voicing of multiple perspectives and credibility. The criterion of usefulness refers to the ability of new knowledge to guide action and to have a practical technological value (Lyotard, 1984); new knowledge is assessed based on its social relevance. Even though this criterion seems reasonable, if we look behind it, then we see the danger that the close linkage between knowledge and society gives the control of the processes of knowledge creation to the hands of the dominant group, which will use it to serve their own – economical or

12

Introduction

ideological, etc. – interests, and will turn knowledge itself into a commercial product. The second criterion asserts the empowering of weak and absent voices and is driven by the ideal of democracy. Social reality is socially constructed and research should aim to bring into play alternative versions of it. In a first glance, this view neglects that researchers are actively involved in the constructions of these alternative versions, since they can never get rid of their own presuppositions, while they are voicing the ‘weak’ alternatives. An alternative to this idea of democracy is Deetz’s (1992) claim that good research should break through fixed forms of subjectivity via constructing new discourses. Alvesson and Sköldberg (2000) challenge this extreme linguistic reduction for it loses sight of the material dimension of social life and hence lacks direction; to put simply, what is the point of breaking through and opening up new discourses if there is no linkage with the practicalities of the material world? Credibility is an adaptation of the criterion of validity; it asks what the significance of a piece of research is, and whether the researcher has demonstrated adequately the coherence of the thesis. Credibility is certainly important for assessing research; however, it is not a straightforward matter: credibility as criterion needs further elaboration before it is applied, especially in the relationship it assumes between theory and empirical data, and the role of language in signifying social realities. The linguistic turn in social science has demonstrated clearly that there is no neutral language and furthermore, language cannot mirror an external objective world, but ideas and perceptions of this world. However, Alvesson and Sköldberg (2000) warn us that accepting that language cannot mirror the world should not lead us to a complete abandonment of any empirical material from our research; on the opposite, our view on the empirical material can inspire ideas and theories, illustrate and clarify arguments and, especially in the case of building theory, provide rigour and credibility. Data do not speak for themselves, and cannot prove anything, however ‘empirical material should be seen as an argument in efforts to make a case for a particular way of understanding social reality, in the context of a never-ending debate’ (ibid.: 276). Hence, they reframe the features of good research following the lines of the previous arguments, highlighting the importance of: • • • • •

empirical arguments and coherent theoretical reasoning, open attitude to the interpretative dimension of social phenomena, critical reflection on the political and ideological context of research, awareness of the ambiguity of language and its limited capacity to convey ‘objective’ knowledge and the role of the author in this issue, theory development based on these issues, which is hopefully ‘rich in points’, i.e. goes beyond the empirical material, challenges established ways of thinking and achieves an epistemological break with common-sense knowledge.

To these criteria, I shall add the power of new knowledge to changing the existing organizational order, and rearranging power relations, by questioning neu-

Introduction

13

tralized webs of discourses. I invite this piece of research to be assessed against this epistemology of praxis.

The structure of the book I split the book into two parts: the theoretical, where I investigate the grand narratives of knowledge and innovation, as constructed via the academic literature, and the empirical, where I investigate these concepts in light of empirical data. In the first part I review the literature on the changing status of knowledge in the post-capitalist societies, and the impact of this new discourse upon the organizations – the newly emerged ‘knowledge-based’ organizations. I also discuss the literature on analysing knowledge and innovation in organizations, and suggest that since knowledge is inextricably interwoven with power, the analysis of knowledge and innovation in organizations would not be complete unless it addressed the power effects and changing order. Then, in the empirical part, I discuss the case of a technology knowledge-based company, ‘HydroCarbon Solutions’, and its trajectory through the commercialization discourse. Here, I examine how the latter has impacted on their understanding of innovation and the related practices implemented to support the need for new knowledge, like the new discourse prescribes. The research studied the discourses in two Technology Groups, which fell under the new Hydro-Carbon Solutions umbrella. The analysis addresses issues of politics and power related to innovation, conceiving power not merely as a negotiating variable, like the mainstream analysis of innovation recognizes, but as a force of creating the dominant understanding of what innovation is, what is not and what the necessary actions are to be taken, in order to comply with the new and naturalized definition of innovation. Ultimately, the question I set out to answer is whether the commercial discourse leaves space for technological innovation, and, if affirmative, what is the web of relations that innovation confers when articulated within the commercial discourse, what strategies are employed in the struggle over its articulation, and what the consequences are for an organization. The book develops over eight chapters; the first one is this introduction chapter, where I explain the rationale for undertaking this project; the research is located in the broader debate regarding knowledge and innovation, and I present the main arguments and methodology. Given that the project has adopted a language-centred view on the study of organizations, I start by explaining the necessity for this linguistic turn in social sciences, and expose the fundamental assumptions as well as different approaches to it. I next discuss my methodological framework, which conceives discourse as a means for revealing ambiguities of social construction and the indeterminacy of organizational experiences. Here I explain further the assumptions of critical discourse analysis, and how I used it for the purposes of this study. I chose to study the conflict between discourses and the power struggle between groups that are affected by the commercial innovation discourse. The research has been framed on the assumptions of critical discourse analysis, which enables the study of both grand and local

14

Introduction

discourses and the power struggles within the same framework. Then I move on to present my research design, i.e. an ethnography of the R&D laboratories of an oil company, and the methods for data collection. I conclude this chapter by discussing the challenges that a qualitative piece of research faces when needs be evaluated on the grounds of the quantitative criteria. Having adopted a critical approach to the study of knowledge and innovation management, the research naturally questions first how these discourses emerge and whether knowledge can indeed be managed, before we are in position to suggest how it can be managed. Chapter 2 asserts that since knowledge and power are the two sides of a coin, then a change in the language game of knowledge implies a change in the established power relations that produce and sustain it. I commence the chapter by examining the nature of knowledge and the differences between scientific and narrative knowledge that form two distinct language games. I discuss the structure and rules of the research game, which is one that finds legitimization for the knowledge it produces within the boundaries of its community. Once the disciplinary power of the scientific community is accepted, I move on to identifying the emergence of the discourse on knowledge and innovation rooted in the disciplines that produced it, and the force of this discourse in changing the nature of ‘knowledge’ to ‘commercial knowledge’. This transformation has led to a series of changes in the societal structure, and the roles and identities of the actors who partake in the production of knowledge, be it knowledge-based companies, universities, researchers, etc. Most importantly, the financial jargon becomes the natural language of science – the one that all scientists have now to speak, in order to be in a position to participate in the language game. I conclude the chapter with a critical discussion of the rhetoric of commercial knowledge, which I claim constructs an image of a society where everybody benefits from and is happy to trust and share information in the new order. In the third chapter, I focus the discussion about knowledge and innovation down to the organization level. Here I examine how different disciplines have conceptualized knowledge and management, and the various tools and techniques they suggest in order to control knowledge. After introducing the arguments against the manageability of knowledge, I bring the discussion to the area of innovation management. Here, I examine the main discourses, and the ways each one constructs innovation and innovation management, the main concepts and themes they suggest, and their assumptions and limitations. Having established that knowledge is always interconnected with power, and that innovation is a knowledge phenomenon, I then reiterate here my analytical framework, as one that adds the power dimension to the analysis of innovation, conceptualizing power relations through the lenses of discursive formations. Finally, I question the field of knowledge management, the practices it develops and the impact it has on organizations. Nonetheless, attributing to the knowledge management field the power of producing totalizing discourses that form managers’ frames of logic, managerial decisions and actions, does not do justice to the individual subjectivity and does not explain different courses of action and change. There-

Introduction

15

fore, I conclude the chapter by discussing why managers follow the ‘hype’ – and in the present case, the hype of ‘innovation management’. I discuss the view that managers are individuals with multiple identities and interests; in fulfilling their tasks they have the opportunity each time to choose from a range of co-existing and competing discourses. Having demonstrated conceptually the force of discourses in influencing structures, practices and identities, Chapter 4 introduces the site of empirical study, a technology knowledge-based company, Hydro-Carbon Solutions, and its trajectory towards commercialization. The study explores the formal discourse of commercialization that has given the two Business Units under study their new structure and identity. Here I identify the discursive strategies employed to neutralize the force of the change, which was presented as ‘good’ and ‘unavoidable’. The commercialization discourse has usurped values of the previously dominant scientific culture; however these values took a new meaning in the new commercial environment. I examine the changes the commercial turn brought in the two groups of focus, Technology Groups A and B, and the consequences it had on the identity of the organization – which used to be a ‘scientific site’ – and its members, as well as the changes in the work design. My argument is that the articulation of knowledge within a commercial discourse brings changes in the research language game, which ultimately affect the knowledge production structures. The question that I pose here is what kind of knowledge can actually be produced within a commercial discourse, and what is the value of it. The analysis focuses on ‘buzzwords’ of the commercial discourse, and questions their meaning and implications. I conclude this chapter with a discussion of the implications of commercialization for the research site. In this commercial now site a new discourse emerges, the commercial innovation discourse, and gains the attention of the business and of certain groups and individuals, since it promises benefits for all partakers. As a consequence of the much promising rhetoric, certain moves have been made towards supporting the innovation process from many levels of the wider organization. Chapter 5 presents and discusses Eureka, a higher-level innovation machine, which was developed in order to give strategic direction to the R&D activities of Hydro-Carbon Solutions. Here I examine the formal organizational discourse and practices of innovation, and the relationship between ‘commercialization’ and ‘innovation’. I examine closer the structure of this successful innovation machine, which was developed on the assumptions of ‘rational planning’; I discuss its aims and objectives, as well as the challenges it faces in engaging the scientific population. Throughout this chapter I focus on the language that ties together innovation with business profits, i.e. I analyse the construction of the commercial innovation discourse. The question I pose here is what the consequences of innovation are once articulated within the commercial discourse, and who the most appropriate actor is to confer it. I conclude the chapter with a discussion of a fundamental assumption of this discourse: the collaboration or, as it emerges from the findings, the challenge of collaboration between business and scientists.

16

Introduction

Eureka has not been the only innovation mechanism that tried to capture the scientists’ attention and time. Chapter 6 presents the Ideas Machine, a local innovation initiative, which was developed by Technology Group A, and intended to serve its local innovation needs. The Ideas Machine was created on the principles of innovation as culture, and set out to bring a cultural change in the group. I argue that the rhetoric of cultural changes used values of a democratic discourse, and proclaimed that innovating should not be a privilege of the scientific elite, as it had been the case in the past. Behind this rhetoric, what the Business Group was actually trying to achieve, was to make full use of all knowledge resources they had, even when those did not comply with the scientific articulation of innovation, since a commercial organization has multiple knowledge needs of many kinds. My analysis focuses on the obstacles that it met in engaging the scientists, and in particular it reveals the political games enacted at multiple levels, which emerged with the implementation of this local mechanism in a technology-based firm with a strong scientific background, and hindered the actualization of innovation. I conclude this chapter by discussing the politics of innovation management. The Ideas Machine was also implemented at Technology Group B, as I discuss in Chapter 7. In this Business Group, we have the opportunity to observe both innovation mechanisms, i.e. Ideas Machine and Eureka, how they were implemented and the problems they encountered, which largely stemmed out of the different understanding and expectations they had from an innovation system. This group did not want to break the scientific elite but, quite the opposite, to support them in generating technical ideas. I argue here that the Ideas Machine was stripped away by its cultural change rhetoric; hence it passed unnoticed. Most importantly, here by focusing on Eureka, I examine closely the scientists’ resistance to the rhetoric of commercial innovation, which collides with the scientific articulation of innovation. The question of knowledge legitimization and governance is raised clearly by the scientists, who doubted the adequacy of the business to decide upon technological innovation. I conclude this chapter by discussing the challenges that the management of technological innovation encounters in a fully commercial environment, and I track these challenges back to their structural properties and assumptions, which I argue are fundamentally incompatible. Finally, in Chapter 8, I discuss the key findings of the empirical part in light of the conceptual framework I have suggested, and form a clear answer to how technological innovation, defined as long-term and uncertain programmes, can be adequately supported in a fully commercial environment, and what the implications are for our understanding of knowledge and for organizations. I start by unravelling the construction of commercial innovation in order to support technological innovation in a commercial environment, and the resistance it has met. I move on to exposing the new pragmatics of commercial knowledge, as they emerge, by examining the transformation that occurred in the scientific language game. I argue that the desired innovation that the discourse on commercial knowledge promotes, is articulated within the scientific

Introduction

17

language game, for only hard to imitate knowledge can return the promised competitive advantage. However, this kind of knowledge and the related innovation processes cannot be supported within a short-term thinking environment and the language game of economic rationality, for their assumptions and the consequent processes that define the two discourses are not compatible. The chapter concludes by questioning the structures and processes that are developed to support innovation in a commercial environment. I stress that from the moment knowledge legitimization leaves the boundaries of the scientific community, there is a pressing need to devise appropriate mechanisms to govern the production of knowledge.

Part I

Theoretical

2

The value of knowledge in postindustrial societies

In this chapter, I examine the discourses on the value of knowledge in postindustrial, knowledge-based societies; in particular I examine the origins of the dominant discourse that gave scientific knowledge a central position in our understanding of today’s society and economy (Lyotard, 1984; Foucault, 1980; Drucker, 1993), and which turned it into a commodity, the concepts it has suggested, the new order of knowledge production and consumption it has created (Gibbons et al., 1994) and the practices that the organizations have consequently adopted. Finally, I critically discuss the ‘rationality’ of these practices. After having explored the evolution of knowledge discourse, and how knowledge is always wedded with power, then my argument is that the new discourse on commercial knowledge enacts a network of power relations that need be further and thoroughly studied. In other words, I suggest that knowledge management is essentially a political question, which has implications on the organizational structures, but also on the pragmatics of knowledge.

The nature of knowledge There is something odd when thinking and talking of knowledge: we cannot think of any civilization that has developed without being able to demonstrate a sound body of knowledge, without admiring knowledge artifacts; nevertheless, only today western(-ized) societies call themselves ‘knowledge-based’ societies, emphasizing in this way the central position knowledge has occupied in understanding economical, social and cultural phenomena and furthermore in perceiving ourselves as members or as (unfortunate?) non-members of knowledgebased societies. The suggestion that all societies are built on knowledge begs the question of what kind of knowledge is being worshipped as the knowledge today. To answer this, we have to appeal to philosophy, for it is the discipline that primarily contemplates with the subject matter, ‘what is knowledge?’ and as many scholars ask ‘what is not knowledge?’

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Theoretical

The structure of knowledge Philosophy traditionally distinguishes three types of knowledge: ‘knowing how’, which refers to the skills one develops and it is most of the times tacit; propositional knowledge or ‘knowing that’, which refers to information, as it is decontextualized, and has been the main object of philosophical thinking; and ‘knowing things’, which is knowledge of acquaintance. These two last forms of knowledge are more explicit, in the sense that they can be described verbally (Ryle, 1949; Polanyi, 1967). The distinction between tacit and explicit knowledge has become the core debate across disciplines (Information Science, Communication Studies, Cultural Studies, etc.), which fight over the correct framework of what knowledge is and how it can be supported in practice (with computers or human networks); therefore the topic is relevant to discuss here. This distinction concerning the structure of knowledge was suggested by Polanyi (1967), who argued that knowledge has two dimensions, i.e. the tacit and the explicit, and the difference between the two lies in the ability to articulate what we know: the explicit dimension refers to knowledge that can be verbally articulated and hence represented semantically – or symbolically. However, Polanyi continues that people know more than they can tell: knowledge has a dimension that cannot become explicit. This tacit dimension refers to skills and competences individuals have, which allow them to perform certain acts, however they are not conscious of how they do it. Once people concentrate on how they do it, then the act is difficult to be performed successfully. The tacit dimension brings about individual action that the individual cannot explain, and rests on the individual’s competences. Polanyi calls it ‘personal knowledge’ for it cannot be disembodied, i.e. separated from the actor’s body. For Polanyi, thus, knowledge comprises these two dimensions, which cannot replace each other – tacit cannot become explicit and vice versa – but they complement each other. Following Polanyi, Collins (1993) talked about the embrained, the embodied and the codified (in symbols) types of knowledge. Embrained (cognitive) and embodied (competences) knowledge lies in the individual, whereas codified knowledge is impersonal and lies in the physical environment. Another site of knowledge is society; by this is meant the cultural knowledge that dictates rules on how to perform successfully, or rather in a socially accepted manner, certain actions. Collins illustrates this position by adopting a Wittgensteinian argument on the socially constructed nature of language (Wittgenstein, 1958), and gives the classic example of natural language: the right way to speak is not determined by each individual, but it is a prerogative of the social group, which ultimately defines what is acceptable and what is not. One can argue that encoded knowledge is part of the encultured knowledge of a community; however, the distinction here is made on that encoded knowledge has been ‘extracted’ from the community or individuals and placed in the physical environment (stored in an object, e.g. book, floppy disks, etc.). Furthermore, from a constructivist perspective all knowledge (tacit and explicit, scientific and common sense) is rooted in society and culture, for there is no knowledge if there is no communal

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23

agreement that it is so; this point takes the discussion to where we draw the line between knowledge and non-knowledge. Legitimization as a language game So far, I have talked about what is considered to be knowledge. What I will discuss now is what knowledge is not; in other words, what are the criteria that qualify an assertion or an act as knowledge? how can we possibly distinguish between knowledge and belief? how can we tell the master of an art from the amateur? In the case of skills and competences, in a first glance things are in some sense easier: we judge the statements not by their truth-value, but by the success of conducting the specific action. Criteria are established by the community (or rather the experts) from within which competences are to be evaluated, and these criteria vary dependent on the purpose of the act each time. So, for example, if the objective is a piece of art, then aesthetic criteria are applied, evaluations as just or unjust call for ethical or juridical criteria, good and bad manners appeal to cultural and unwritten rules, etc. When we talk about cognitive knowledge, even though it is verbally articulated, it becomes difficult to distinguish between (scientific) knowledge, beliefs and stories, for they are all expressed as narration and this is the only evidence we have. Philosophy of Science has always tried to establish the criteria to evaluate ‘knowledge’. This discourse on the legitimacy of knowledge has incrementally created the perception that only ‘scientific’ knowledge can be regarded as knowledge; ‘scientific’ also implies abstract, cognitive and decontextualized knowledge, of which the production follows a rigorous methodology and the results meet certain criteria. The field of knowledge legitimization is highly contested since each paradigm suggests its own criteria of evaluation, and these criteria follow from the paradigm’s assumptions and methodologies; hence, a detailed review is beyond the purpose of this book. It suffices only to consider the science of nineteenth century, which insisted on the verification of the findings, the science of twentieth century, which insisted on the falsification, and ultimately Feyerabend’s ‘anything goes’ view and the relativistic truth claims of post-modernism (Chalmers, 1982). If even scientific assertions rely on the community in order to gain their status as knowledge, then the question of legitimization appears less an epistemological question and more a question of ethics and politics as Lyotard (1984) suggests, for it raises two questions: ‘who decides what knowledge is, and who knows what is to be decided’ (p. 9). The pragmatics of narrative knowledge As thorough and sophisticated as the criteria to distinguish ‘knowledge’ from mere stories and beliefs may be, they do not provide a convincing reason as to why scientific knowledge should have the privilege of calling its assertions ‘knowledge’, over other forms of knowledge (e.g. embodied and encultured). If the problem of distinguishing between scientific (verified and approved)

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Theoretical

knowledge and other assertions lies on their narrative form, then it is relevant to look briefly at Lyotard’s discussion on the differences in nature between narrative and scientific knowledge, as he exposed them in the Postmodern Condition: A Report on Knowledge (1984). Lyotard distinguishes five key characteristics of the folk stories told in a society – of which, I believe, the wisdom is beyond question. •

•

•

•

•

First, they shape common perceptions and feelings of beauty, justice, morality and higher ideals – they construct a shared system of values and competences. Second, they allow a great flexibility of language games that can be enacted (assertions, ironies, interrogations, wishes, etc.); they are all considered equally valuable, and interestingly co-exist, even if they suggest conflicting instances or realities. Third, each narration contains the rules of its transmission – instead of the rules being prescribed by an external structure – acquired by its narrative form, which enclose the definition of the roles of the narrator and the listener, together with the prescription of how things should be done. Narratives are sites of multiple competences (know-how, know how to tell the story, know how to listen). After the story is told, anyone who heard it has the ‘right’ to become a narrator – to pass it on; its status as narrator will not be in doubt. Fourth, interestingly and against all expectations, the relationship between traditional knowledge and time: narratives rely on the meter and rhyme, rather than on the accent of each performance and the accuracy of past events; they are not the outcome of accumulative knowledge and their role is not to remind a community of its past. Instead, they have a Lethean function, by providing at the moment of reciting a social bond for the community – instead of a bond with the past. The referent of the story may appear like belonging to the past, but it is always being enacted in the present, through the act of narration – whether the referent existed indeed in the past as such – and similar questions of accuracy are irrelevant for the time the story is told. Finally, the creation and transmission of traditional knowledge does not separate the narrators from the rest of the society and then to question the authority of performing this role; the legitimization of a narrative is endemic to its form and comes immediately from the act of reciting.

The pragmatics of scientific knowledge On the other hand, legitimization of scientific knowledge has to be constructed by an external to the statement structure, which questions each time both the validity of the statement and the speaker’s identity and competences. The scientific language game plays with different rules, which are much more rigid and narrow, and determines different roles to the participants. Lyotard develops his

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argument by distinguishing between ‘research’ and ‘teaching’, as two distinct language games, since the participants take different roles in each. To start with the ‘research game’, each statement seeks approval via its correspondence to truth, and it is the speaker’s task first to provide the proofs for it and second to be able to refute contradictory statements. The listener on the other side is supposed to have already similar competences to the speaker, as, since the moment one gives the agreement to the statement, one has to be able to perform the double task, i.e. provide proofs and be able to refute contradictory statements. In other words, in the research game speaker and listener are equal. Regarding the referent and its correspondence to truth things turn problematic: the truth-value of a scientific statement can only be supported by providing a second statement of the same order; the question is what proves that my proofstatement is true – maybe with a third statement of the same order? Attempting to resolve this, ‘verification’ and ‘falsification’ were grounded in two rules: the first is in a sense rhetorical and states that if I can produce a proof, I am allowed to claim its truth-value; the second appeals to metaphysics and asserts that the same referent cannot produce a plurality or contradictory proofs. The acceptance of these two rules allows a horizon of consensus in the scientific community; it is assumed, not that every consensus is a sign of truth but, that the truth of a statement necessarily draws consensus. The research game relies on the consensus among equal participants; non-consensus over a statement puts at stake not only the statement but also the speaker’s competences; hence the need for creating equals and consensus. The pragmatics of developing equals are different; the teaching language game relies on didactics rather than dialectics: the speaker’s competences are not in doubt, hence one is qualified to teach; the learner is assumed not to have research competences, but to be competent to learn; the truth-value of the statement is not in doubt, and hence is transmitted as ‘true’ knowledge. Once the student is approved as competent, then one is accepted as equal in the research language game. In sum, Lyotard, comparing the pragmatics of narrative and of scientific knowledge, distinguishes the following properties of the scientific language game: first, the only language game accepted is denotation, whereas all others are excluded. Interrogative and prescriptive statements are allowed only as turning points in the line of argumentation, which has to conclude with a denotative statement. In this game, the scientist is one who is competent to produce true statements about an accessible referent. Consequently, science becomes a distinct language game in the society, one that does not contribute directly in creating and sustaining the social bond among individuals; this happens indirectly, as science in modern societies becomes a profession and creates institutions, which are governed by qualified partners (the professional class). Hence, the relation between knowledge and society becomes one of mutual exteriority, i.e. precious scientific knowledge is not publicly shared but is governed by a professional class, which excludes non-members. Within the boundaries of the scientific language game, the listener is not expected to have particular competences to accomplish the role of listener; the

26

Theoretical

referent of the assertion is not expected to have particular qualities to act as referent, surprisingly enough, not even in the case of human sciences: the referent does not need know how to act according to what the statement prescribes! In terms of validity, as discussed, the statement does not gain validity by the act of being reported, neither does it secure by the same act its future recitation; accumulated knowledge can be refuted by a new statement, if the latter can provide proofs of its true-value. Consequently, the scientific language game implies a diachronic temporality, which means a memory and a project: each new statement can only be produced on the basis of what has been said so far (the existing body of knowledge) either by suggesting new insights into the subject or by refuting previous statements. Thus, the accent of each performance takes precedence over the meter and rhyme, which implies the polemical function of each performance. In the case of the scientific language game, past and memory hold a vital position; the aim is scientific development and progress, and it is achieved by remembering the past – what has been said so far. Through this short discussion about the properties of narrative and scientific knowledge, we observe that apart of differences in terms of their pragmatics, the two have some similarities as well. Both require a mixture of know-what (to talk about the referent) and know-how (the individual competences and the cultural rules to go about it). Both are language games with specific rules, which determine the participants’ identities, frames of thinking and actions, and develop with statements that act as moves prescribed from the rules of each game. The fact that scientific knowledge enjoys a higher status in western societies can only be explained in terms of historical contingencies, for scientific knowledge does not qualify by nature and in principle as superior to narrative knowledge. By this, I do not mean to doubt the value of scientific knowledge, but rather the opposite, to move from this fruitless contestation, since narrative and scientific knowledge are two distinct language games that cannot be compared in terms of value, as there are no criteria for this. Furthermore, the significance of cultural knowledge has started being re-established in the organizational world. The moves in each game are assessed with internal criteria formed by the dominant discourses, which ultimately construct a communal perception of what a ‘good’ move is or is not. Once this is accepted, we can see clearly that the rules of the scientific language are not given by a superior external order but are socially constructed. Furthermore, as mentioned above, it is a language game that puts in question the status of its participants, and non-participants as well. In other words, the scientific language game is essentially socio-political; there are questions of power and governance that affect not only the participants, but also the society at large, and deserve further consideration. Power and power relations Mainstream theories have traditionally viewed power as a ‘thing’ always associated with resource dependency. From this perspective, power has been conceptualized as ‘reward power’, ‘coercion power’, ‘legitimate power’, ‘expert power’

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and ‘referent power’ (French and Raven, 1959; Piven and Cloward, 2005). From a critical theory perspective, power does not escape the resource dependency, since again it is being defined within the framework of economic domination, which determines the division of labour – here the ownership of the means of production plays a crucial role (Clegg, 1989a; Piven and Cloward, 2005). The problem with these views, Clegg continues, is that they create a tautological explanation, according to which the cause of power is resource dependence and its exercise results to resource dependence. In other words, cause and consequence are identical. At the same time, these views are concerned with the structures that generate power, and overlook its mechanisms; i.e. they create an understanding of power as a ‘thing’ instead of a property of relations that define and allow its exercise (Foucault, 1980; Clegg, 1989b). The authors suggest that it is the mechanisms of power, instead of the structures, that should be the focus of studies, because power does not exist in its own right, but always in relations. Hence the question should move beyond the traditional ‘where power lies’ to ‘how power is exercised’, because it is there where it becomes evident. Foucault defines power as ‘relations, a more or less organized, coordinated cluster of relations’ (1980: 199, in Hodgson 2000). For Foucault ‘power is everywhere’ and imbues all relations; this does not mean that all relations are necessarily oppressive, but rather that all relations, even those that are experienced as liberated, are in fact saturated with power relations, and hence they all offer a field for contestation and resistance. Adopting this wider view on power allows its conceptualization not only as a negative force, which constrains and oppresses people, but also as a positive force that motivates people to act – and action here can be understood so much as compliance to rules and orders, as much as resistance. Hence, four aspects of power emerge (Hodgson, 2000): (a) power is productive; against the mainstream conception of power as a negative force, which constrains action and obliges people to do things against their will or against their consciousness, power creates rules, structures, knowledge and discourses; ultimately through power action and change are enabled, (b) power is polyvalent; it emerges in all interpersonal and intergroup relations, and there are as many forms of power as many relations exist; every individual and group becomes subject and the same time exercises power towards others, (c) power is capillary; it does not emanate from a sovereign authority (be it state, church, etc.), but it develops locally in the specific nature of the local relations; this is an important point in theorizing power, because it leads the studies not to examining the macro-strategies of power, but the specific, local tactics that develop, (d) and finally, power lacks a coordinating strategist; since it has a polyvalent and capillary nature, it is difficult to attribute the development of its technologies to a single individual, group or even class – as the Marxist tradition argues, since people know what they do, and most often why, but they cannot know the breadth of effects their actions may have. With this move Foucault breaks with the concept of ideology, a wellestablished notion among critical theorists, and suggests the notion of discourse

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instead, to explain local power phenomena and fragmented ideologies. As expected, this position has been the subject of great criticisms; the critiques claim that one cannot explain discourses, and economic and political relationships at a macro level without considering the ideological aspect of these relationships. Here, I agree with Clegg’s view (Clegg, 1989b) that we cannot explain, for example, the dominant neo-liberal discourse, without reference to ideological issues. However, Foucault was concerned with the study of local, micro-histories and specific forms of power and at this level the analysis can be completed without such reference (ibid.). Antagonisms and resistance Before I continue with explaining the concept of resistance for Foucault, I should briefly explain the associated concept of antagonisms. Laclau and Mouffe (2001) explain social antagonisms, as the limits of objectivity. The traditional views to antagonisms as real opposition of relations (A – B) or contradiction (A – not-A) did not achieve to explain what actually makes an antagonistic relation, and what type of relations it presupposes; it soon becomes evident that not all ‘A – B’ relations or ‘A – not-A’ are in principle antagonistic, yet they may become, and the answer should not be sought in the conditions that will allow it, but in A and B or not-A. The problem with the traditional views to antagonisms is that they assume complete and fixed identities. In contrast, it is suggested the partial fixation of identities, where A cannot become fully A because of B (or non-A). It is the Other that prevents A to become totally itself, and their actual relation negates the full potential of its being. Hence, in an organized system, antagonisms emerge in the failure of relational differences, i.e. in the limits of objectivity. Returning to Foucault, ‘resistance’ has been an object of severe criticism against his writings – especially the determination of structures on shaping individuals and the omnipresence of power; this last point, i.e. that power is everywhere, has been criticized for it leaves no space for individuals to resist, hence there is no explanation for change. However, power entails resistance, and resistance is contained by power – it is not an external, independent force. Foucault goes on to define it as ‘dispersed, polyvalent, situationally contingent and stems from a number of sources’ (Hodgson, 2000: 52) – Hodgson notices that the similarities between power and resistance are striking, as if they are the same phenomenon. By defining resistance as dispersed and polyvalent, Foucault opposes the traditional view of two forces colliding against each other, and identifies multiple forces and interest groups, which may participate in the same local power struggle. With this argument he adopts an anarchistic view to power, which undermines not only those who have the power, but also those who aim to seize it – and this group is not necessarily identified with the oppressed; thus the only true potential for resistance comes from individual, isolated struggles, and not through organized group actions.

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Discourse and power/knowledge Foucault does not provide a clear definition of discourse, rather he expands the existing understandings of what discourse is, suggesting additional meanings. He describes discourse as: ‘sometimes . . . the general domain of all statements, sometimes an individualized group of statements, and sometimes as a regulated practice that accounts for a number of statements’ (Foucault, 1972: 8). There are certain criteria that shape the nature of discourses: (a) what individualizes a discourse is not the unity of its object, but a set of rules of formation for all its objects, all its operations, all its theoretical options; (b) a set of criteria of transformation; these are a set of conditions that must have been fulfilled at a precise moment in time, for a discourse (its objects, operations and theoretical options) to form; (c) finally, criteria of correlation; these are a set of relations among discourses that distinguish a particular discursive formation as autonomous (Foucault, in Burchell et al., 1984). These criteria make it possible to understand knowledge (or what is considered to be the ‘truth’) of a period/society not as the sum of its knowledge as continuity, as macro-historic accounts do, but as the divergences, the differences and the oppositions between discourses. Discourses signify different systems of knowledge – or rather, of what is considered the truth – that happen to dominate in particular eras. This shift of focus towards discontinuity implies a suspension of causality, and an emphasis on correlations between intradiscursive, interdisursive and extradiscursive elements that allow the emergence of an order of discourse. In other words, emphasis is placed on the contingencies, the faults and errors that gave birth to those things that we value today as important (Foucault, 1977a). For Foucault, knowledge and power cannot be studied separately, as power is a precondition of knowledge – or according to Deetz (1992) ‘power in knowledge’ instead of ‘power of knowledge’. Power/knowledge in modern societies provides a way to manage populations; however, its success lies in that its machinery is not evident, but subtle and implied (Foucault, 1980). Normalization is one way power is deployed. Normalization is the process through which a particular discourse establishes the norm of what is accepted as good and what is not; it is the process through which individuals and groups of people are distinguished and characterized not simply according to an ethical judgment as good/bad, normal/abnormal, it provides the measure against which all individuals and groups, good and bad, normal and abnormal are assessed. Normalization is the process via which dominant discourses set the norms of how ‘reality’ should be read and understood, and towards which direction actions should be taken (Carabine, 2001). Clearly for Foucault (1980), knowledge has always been associated with the quest for truth – the Will to Truth – and truth is not outside power or lacking power; truth is not an ideal outside this world but a thing of this world and it is produced only by virtue of multiple forms of constraint and eventually induces regular effects of power. In any society, there are manifold relations of power that can only be established and enacted by virtue of discourses of truth; and

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truth can only be spoken through power. People must ‘speak the truth’ and power recompenses them by institutionalizing, professionalizing and rewarding its pursuit. Each society has its own regime of truth, its ‘general politics’ of truth: that is, the types of discourse which it accepts and makes function as true; the mechanisms and instances which enable one to distinguish true and false statements, the means by which each is sanctioned; the techniques and procedures accorded value in the acquisition of truth; the status of those who are charged by saying what counts as true. (Foucault, 1980: 131) These regimes of truth have a normalizing effect on phenomena and practices, making some of them appearing good, truthful, respectful, whereas others are considered harmful, wrong, shameful, etc. For Foucault, truth is always interwoven in a circular relation with systems of power that produce it and sustain it, and with effects of power, which it induces, and which extend it. Hence, truth and power – rather than science and ideology – should be the focus for understanding the conditions for the emergence and the nature of any society. I shall repeat here that for Foucault power is not a ‘something’ that lies in individuals (e.g. sovereign power) or institutions (e.g. juridical power). Power lies everywhere in all relations and employs subtle mechanisms that discipline not only minds (as the ideological conceptions of power suggest), but also bodies and time as well. It is not seen only as a negative thing that forces people to do things against their consciousness, but as positive concept (a productive force), precisely because of its subtle mechanisms that construct practices, routines and identities (Clegg, 1989b). It is disciplinary power, which lies outside any type of sovereign power and law, and it is legitimated by the will to truth. In sum, both Foucault and Lyotard have talked about the institutionalization and professionalization of the ‘truth pursuit’ in capitalist and post-capitalist societies, as being central in understanding what knowledge is, and further the relations of knowledge production, the practices shaped and the consequences they bear for the organizations and society. Next, I will discuss the status, the changes and the implications of the institutionalization of scientific knowledge in post-industrial societies.

Knowledge in the post-industrial age Knowledge has recently attracted great interest from academics, practitioners and politicians. Some like viewing it as the key resource in a post-capitalist economy (Drucker, 1993; Boisot, 1998; Blair, 1998), the ground indeed where the post-capitalist economy is based, which redefines economic relations and polity. Other theorists (Fuller, 1995; Graham and Rooney, 2001) argue that postindustrial societies are not built on the values of knowledge, but rather the opposite, knowledge societies are now being imbued with technocratic values,

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underscoring with this argument the wedding between knowledge and technology, which intensifies in the new discursive order. Nevertheless, a number of changes indicate the emergence of the phenomenon and the severity of the consequences it bears. These changes are observed at the social, economic and technological sphere and they are supported by the scientific discourses of the related disciplines. New concepts, such as ‘information society’ and ‘knowledge-based economy’, ‘knowledge worker’ etc., have been introduced into the language. The introduction of these new terms signifies the beginning of this new era, where knowledge gains a new role and a new status (Lyotard, 1984), as it is being established after all this intensive and contested talk, the keystone of society. The question that arises is how new is the phenomenon and why now. Knowledge has traditionally been highly valued at least among societies that developed considerable civilization and foremost among the western societies, where knowledge is allegedly the cornerstone of further social and economic development. Especially cognitive knowledge has always enjoyed a high status among societies of western civilization – the beginning of this grand narrative can probably be traced back in the ancient Greek civilization and the teaching of Plato, an era that acts as the cognitive basis of western civilization. However, even among western societies, knowledge has been the object of different narratives, which construe its nature each time. Clearly, knowledge changes nature and role each time according to the specific societal context (structure, values) where the grand narrative develops (Lyotard, 1984). So, for example, in the nineteenth century in Western Europe, we encounter two distinct narratives on knowledge: the French grand narrative set knowledge to be the means for emancipation and liberty – knowledge was a social good, to which all humans have a right. The popularization of knowledge and the massification of education were addressed towards the politics of primary education – higher education was a far-reaching ideal. This discourse is considered to have been led by the desire and the need to create professionals and administrators that would reassure the stability of the state, which receives now its legitimacy not by itself (like in the case of monarchy), but from people. In this narrative, we can identify discursive elements that justify the control of education by the state, in the name of Progress and Freedom, together with elements that justify the importance of administrative and managerial positions for the progress of a civic and free society. In Germany, on the other hand, the grand narrative set knowledge to be the ultimate purpose – science for Science. Describing the nature of Science as speculative, this narrative was grounded in philosophy, and inhered in the intellectual tradition of the German nation. One could argue that this narrative expressed the suspicion of the German intellectuals towards nationalism, positivism and utilitarianism that governed science at that time (Lyotard, 1984). Nevertheless, these examples demonstrate that the role attributed to knowledge each time is part of a complex network of political and economic relationships. Thus, it is fair to ask which elements of the postindustrial societies attribute knowledge its new status or, in other words, what

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the dominant discourse is that has positioned knowledge in the centre of economic activities. The evolution of knowledge discourse It is easy to tell an ‘obvious’ story about the evolution of the industrial society: industrial societies, which were based on technological evolution and massification of production, for reasons analysed extensively by Marx and his followers had to change; however, communism failed as the ideal alternative to ruthless capitalism, and Marx was proved wrong. Capitalism – incidentally supported by the French narrative of ‘knowledge to the people’ and the codification of cognitive knowledge into the first Encyclopédie – was transformed to post-capitalism, where knowledge, not capital, is the key resource (Drucker, 1993). I am not going to debate here whether Marx was actually right or wrong and whether the nullification of his writings is a valid move to understand post-capitalist societies – a move about which I have great reservations, in terms of our ability to study post-capitalist societies without reference to Marx (cf. Jessop, 2000). I will suggest, however, that the previous narrative – which represents the mainstream thinking among business circles and academia – is a classic example of what discourse and disciplinary power stands for, that is, this kind of discourse that emerges from a social scientific discipline forms truth objects and future directions. It is precisely the disciplinary power of scientific discourse – an invention of the new middle class in the industrial societies – that shapes ‘post-capitalist’ societies (cf. Foucault, 1977b, 1980).1 Capitalist societies were developed around the notions of ‘hard science’ and ‘technological progress’, and set out to develop technologies, which would increase the economic performativity, the efficiency and the output, and at the same time would minimize (or as called later, ‘optimize’) the use of resources (labour, capital, raw materials and time). The history of science and technology can demonstrate great achievements in terms of amazing machines that were invented at that time, and were introduced in the workplace, so that the massification of goods production was enabled. At the same time, ‘scientific management’ dealt with the second question of minimizing wastes, and invented the measurement and control of resources, time and bodies. ‘Rationality’ of decision making and ‘functionality’ became a fundamental working assumption of Management Science at that time – assumptions so powerful that still guide the dominant mode of doing management research – which represented the work organization as a coherent whole that can and should be controlled by the unquestioned authority of managers and with technological devices, in order to overcome deviant behaviour and achieve optimum performance. The influence of engineering and natural sciences on this mode of thinking is evident, in that they represent social organization as a ‘closed system’ and individuals as controllable elements. Nevertheless, this ‘rational and progressive’ scientific discourse matched the ethical and the political rules on the ground of which capitalism was built: in this language game ‘progress’ does not mean cultural or

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intellectual progress, but primarily and strictly ‘economic progress’ that is supported by ‘technological progress’; these concepts become the ultimate objective that should be pursued at practically any cost. Capitalism (the society of economic wealth), Science and Technology wedded together in a powerful discourse, of which the effects lay a firm social, economic and political structure for today’s post-capitalist society. The passage from capitalist to post-capitalist society was accomplished by means of a change in the value and status of knowledge. Knowledge has always been important, especially in the major innovation changes, but the novel element is the application of knowledge in developing the forces of production (Jessop, 2000), which attributes it a commercial and economic character (Rooney and McKenna, 2005; Rooney, 2004; Graham and Rooney, 2001). Graham and Rooney (2001) bring empirical evidence of this commercialization of knowledge; by means of discourse analysis they examine the language of knowledge-related public policy documents from local, state, national and supranational legislature throughout the industrialized world, and conclude that this commodity-based conceptualization of knowledge is essentially anti-intellectual and technocratic, which is at odds with the very nature of knowledge. It is clear that, capitalist society identifies an economic and political utility for knowledge, and hence the discourse on ‘progress and performativity’ is expanded and a new discursive order around ‘knowledge’ is being constructed. It is precisely the economic advantages and its political utility that made scientific knowledge dominate over narrative. Particularly during the past 50 years, first western societies and progressively the entire world witnessed rapid technological changes, which were supported by some old and new disciplines (such as Informatics, etc.) that share the same values of the economic rationale of progress that guided capitalism so far. The invasion of computers in all levels of secular life has fuelled (or coincided with) a number of changes that are currently taking place. For the ‘hegemony of computers’ – as Lyotard (1984) describes it – comes with a certain logic and a certain set of rules that prescribe what is ‘valid’, ‘good’ and ‘useful’ and what is not. Going back to the discussion about the nature of knowledge, computers operate with encoded and abstract ‘knowledge’, and hence this decontextualized form of knowledge – which falls in the same genre as information – draws a sharp line between its counterpart (tacit knowledge) and takes precedence for a while over skills and competences. Knowledge, now more than ever means ‘cognitive’, ‘scientific’ and ‘abstract’ knowledge that is encoded and easy to transfer. This narrow view has recently led scholars to challenge the need for opening up the concept (Rooney, 2004). Foucault (1980: 131–132) identifies five important traits that characterize the ‘political economy’ of knowledge in post-industrial era – where ‘knowledge’ means the ‘will to truth’, as already explained. ‘Truth’ is centred on the form of scientific discourse and the institutions which produce it; it is subject to constant economic and political incitement (the demand for truth, as much for economic production as for political

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Theoretical power); it is the object, under diverse forms, of immense diffusion and the consumption (circulating through the apparatuses of education and information whose extent is relatively broad in the social body, not withstanding certain strict limitations); it is produced and transmitted under the control, dominant if not exclusive, of a few great political and economic apparatuses (university, army, writing, media); lastly, it is the issue of a whole political debate and social confrontation (‘ideological’ struggles).

This passage outlines the new status of knowledge as contested discourse in a political arena, where interest groups collide over its articulation. The commercial significance of knowledge redefines its nature and the production processes, while at the same time the question of ‘legitimization’ and ‘governance’ becomes more and more crucial, since ‘ethics’ and ‘metaphysics’ do not provide a satisfying framework for reasoning when they have to compete with materialistic economic and political interests. From this point on, we should expect certain changes that this new discourse triggers in regulating economic and political relationships among the actors in this network: among countries, social groups and organizations, as well as intraorganizationally, as the employers and employees acquire new identities. The professionalization of science together with the new role research institutions are called in to play in the new game connect tightly the production of knowledge with the production of commercial goods, and the competitive advantage of organizations that embrace this move is currently probably the ‘hottest’ topic of debate and research for both academia and R&D companies that now acquire a commercial identity. The rhetoric of ‘commercial knowledge’ As Drucker puts it in the first page of his book Post-Capitalist Society (1993: 17) in celebration of the new era ‘[k]nowledge has always been a private good. Almost overnight it became a public good.’ This statement ties nicely with the grand narrative of ‘knowledge to the people’ and constructs the ideal of a responsible, emancipated and informed individual, who knows – knows what right and what wrong is. It is ironic how a discourse on knowledge and emancipation disciplines people. As I discussed, historically, knowledge has always been highly accredited in western societies. The economic expansion and the political interests of these societies have given people free access to higher educational institutions, regardless of their social and economic background. Nowadays, more and more people have the opportunity to study sciences. This opportunity, combined with the grand narrative of the emancipatory power of knowledge (Lyotard, 1984), drove more people to choose a career of intellectual over manual labour – i.e. they chose occupations that traditionally enjoy high prestige and approval by the wider society. Besides, an educated workforce is more receptive to technological changes and the discourse of progress and wealth, since the members are educated with the same values that shape the future direction of the economy. As an

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effect of the dominant narrative, the citizens of the post-industrial society have reached a higher educational level, which grants them the valuable and highly respected cognitive skills and specialized knowledge that constitute the key resources of the post-industrial organization. As the ‘hegemony of computers’ expands, the story of knowledge is started being built incrementally on the concept of information. Technological evolution has played a catalytic role in forming the new society. The birth and expansion of the World Wide Web has given access to uncountable stocks of information spread around the world and about the world, and facilitated the communication among individuals across the globe. This easy access to sources of information, but also the information and communication systems that are built, led to the mass production of data and to even more easily accessible information. Some theorists have doubted whether this mass production and availability of information can support individuals in making sense of the world (e.g. Weick, 1985), a comment that reflected early the contemporary practitioners’ everyday experience. Information establishes its key role in the new society, but it would not have happened alone; the development of this social transformation can be traced in the discourse of new disciplines (Informatics, Decision-Support Science, Communication Science, etc.). Human communication is important and the new technological devices bring people together allowing them to communicate any time and in any form. The traditional images of ‘talk’, ‘write’ and ‘message’ and the semiotics have undergone radical transformation. Old practices (letters, phone-calls, face-to-face communication) are being abandoned in the name of ‘technologies’, which are promoted as ‘time efficient’ and ‘economical’ (here, traces of the discourse on ‘capitalist rationality’ as described above are evident). Information is available everywhere and most of the times for free. Information becomes people’s prerogative: they can know, they can be aware of facts and evidence, and they can make informed choices. The discourse on the responsible citizen of the world, active member of a society or simply a mature consumer – the last category is more interesting, in the first place, for the business world – has been of great interest for Marketing Science. The transformation of the naïve consumer to the informed and experienced customer – ‘customer’ is another key concept in describing today’s economic relations and business direction – has guided the firms to coming up with more sophisticated products, or more sophisticated ways to sell products. Distinct knowledge, hard to imitate knowledge allegedly returns a competitive advantage to organizations – on this point, Management Science takes over, and studies innovation and knowledge management techniques (Sveiby, 1997; Boisot, 1998). The pursuit of new knowledge becomes a discourse that engages and disciplines not only people but organizations as well. Drucker (1993) successfully reminds us that money knows no fatherland – nor does information. The state failed in drawing boundaries and controlling business activities, capitalism crossed the national boundaries and the firms expanded the operations across the globe. Markets – both product and labour

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markets – are open to the global firms who reap knowledge and expertise from developed countries and cheap labour from poor countries, in the name of wealth and profits for all. The rhetoric wants globalization to be a win-win situation, where firms provide rich markets with quality products, which are manufactured in developing countries, and poor people have the opportunity to win at least the basics to survive. Some argue that in these ‘sweatshops’ one encounters the exploitation of labour the same as in Marx’s era, i.e. that post-capitalism has exported its working class beyond the national boundaries, whereas others prefer the view that there is no unskilled labour class any longer in global postcapitalism, as the labour force now is educated – the ‘knowledge worker’. Globalization would not have been actualized without the changes that took place in the economic and political stage, or without the possibility of freely floating information and communication. The need for communication and coordination of actions and operations around the globe is on the top of the Organization and Information Studies agenda. The impact of globalization is not evident only in the organizations’ environment, but also in the organizational structure and the work organization. Contemporary firms are not located physically in one place, neither necessarily within the boundaries of one premise. Furthermore, there is no need for the ‘knowledge worker’ to be physically present in an office. Since the operations of the business have crossed the national boundaries and have expanded in the global markets, the ‘knowledge workers’ need be ‘virtually’ present, to follow and participate in many operations – sometimes simultaneously – in different parts of the world, as members of ‘virtual groups’. Information and communication systems are developed to support and to enable these needs. Hence, a new ‘flat’ organizational structure, the ‘boundaryless’ or ‘virtual’ organization is actualized and seems to give the knowledge worker a great degree of flexibility and freedom; hierarchical relationships are more informal and the line manager – who might even be in another country – does not necessarily follow all the moves of the subordinates (Drucker, 1993).

A new discursive and social order: the new production of knowledge All these technological, demographical and economic changes have transformed the nature of knowledge, which is worshipped by society and the business world; knowledge has gained a great commercial significance. It is now the ‘raw material’ for competitive products, and an output as well, a commodity in itself with great commercial value. Indeed it has become the object of trade between organizations (e.g. consultancies and R&D laboratories) and the object of exchange in the labour market (knowledge workers sell their cognitive abilities and knowledge). Knowledge is a valuable commodity that can be traded – accessed, transferred and stored – in other words, it can or at least should be controlled as all other resources, on the grounds of ‘economic rationality’ and ‘performativity’. The technological evolution supports this rhetoric; the ongoing research and development of a more sophisticated software and database for

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supporting the sharing and storing of knowledge is based on and recursively reinforces the image of knowledge as ‘object’ that can be codified in a computer language (Lyotard, 1984). This new discursive order, which defines knowledge as a valuable object, has consequently transformed the structure and the processes of its production, sharing and consumption. The new discursive order is supported by a new institutional infrastructure and technologies, which allow the intensification of research; the more organizations are disciplined by the discourse of commercial knowledge, the more they realize the pressures for generating new knowledge. Consequently, the role of knowledge production institutions, whereas traditionally has been undertaken by universities and the state, now has started being shared with private research laboratories. Big corporations, realizing the great economic benefits commercial knowledge can return, are getting actively involved in the knowledge production, by founding and funding research centres and corporate universities, and by creating alliances with academia and other research institutions (Gibbons et al., 1994; Morgan et al., 2004; Whitley, 2006). Discourse effects on structures Research structures Gibbons et al. (1994) in their book the New Production of Knowledge have identified and examined in sufficient detail a number of changes that this new mode of knowledge production bears for science, research and education. Now, almost 15 years later, this book has proven to be one of the most influential books in studying the new organization of research, as it pointed early to some of the areas that would undergo substantial transformation. Gibbons et al. suggest that the commercialization of knowledge transforms the structure and processes of knowledge production from Mode A to Mode B, implying that the latter has been shaped from the disciplinary matrix of the former and will exist alongside it. ‘Mode A’ describes the traditional approach, which has drawn a sharp line between fundamental and applied research. This has created an operational distinction between the theoretical (scientific) core and the applications of it from disciplines such as engineering or management sciences. ‘Mode B’ is fundamentally transdisciplinary; it is characterized by a constant flow back and forth between fundamental and applied, between science and technology, between research and society. Hayek (1945) very early noticed, talking in ‘rational’ and ‘economic’ terms about the use of knowledge in society: ‘it is a problem of utilization of knowledge not given to its totality’ (p. 520), indicating by this to the socially distributed character of knowledge, which starts now being addressed. The proliferation of sites that undertake research outside disciplinary structures and institutions, which are recognized now as competent actors in the research network, opens up many possibilities for interconnections and interactions. The pursuit of commercial knowledge is a language game that displaces research from the disciplinary ‘Ivory Tower’ and from being the

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privilege of an ‘elitist’ class, and grounds it in society. However, it would be naïve to expect that now there is no privileged class and anyone can benefit equally from the game. The fact that academic researchers’ status transforms can only mean that the power structures have changed and another group – the corporate world, as I explain below – struggles for the privilege of the governance of truth. Communication Transdisciplinary research depends heavily on the density of communication; communication between actors from different interest groups and paradigms, which will lead to further knowledge growth and social distribution, i.e. between scientists and society, between scientific practitioners and ultimately between social and natural world. Gibbons et al. (1994) envisioned cooperation across the different actors working on a common theoretical understanding and accompanied by a mutual interpenetration of disciplinary epistemologies. The transdisciplinary character of the produced knowledge turns it highly contextualized, strongly oriented and driven by a problem-solving model of research; it consists of a continuous linking and relinking of clusters of knowledge configurations, which are brought together temporarily in a specific context application. Communication attracts particular attention in this new language game and becomes a new, contested by many disciplines, buzzword; I say contested because it stimulated much research and solutions on how it can be supported (Hinds and Kiesler, 1995; Boland and Tenkasi, 1995; Tenkasi and Boland, 1996), together with a turn towards discussing the significance of narrative knowledge for organizations. Knowledge legitimization The change in the mode of knowledge production, which translates into the disclosure of the boundaries of the research communities, has inevitably influenced the way new knowledge is evaluated and legitimized. The production of commercial knowledge has become a larger process that integrates the stages of discovery, application and use, and in which many interest groups participate. Hence, the traditional criteria of correspondence to truth applied strictly by the scientific community and the approval of the proposed ‘statement’ by the peer colleagues, who are equal in terms of training and competences, cannot apply. The new mode of knowledge production shifts the criteria that were applied so far, in order to reflect the interests of ‘all’ the stakeholders – society, industry, knowledge communities. The criteria now have to reflect the economic value of the produced knowledge, and its applied use in the society. The economic and political interests that are now explicit in the commercial nature of knowledge call for thorough control and assessment of the economic value of the ‘product’ throughout the process of knowledge creation – from the stage of the research proposal to the ‘end product’, i.e. the ‘innovation’ that will be marketed.

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The research and teaching language game There is an evident change in the language of the research game, as now the ‘economic’ language becomes dominant and the one that everyone has to be able to speak. Scientists so far were accused of speaking an incomprehensible to the outsiders jargon that made their work difficult and inaccessible to the nonexperts. Now, they have to translate their ideas in a ‘clear’ and ‘precise’ language and explain the benefits of their proposals ‘in numbers’, in order to secure the necessary funding from the relevant bodies or customers. Financial jargon has been established as the natural language of science, and it is expected that all members of the scientific community should be competent enough to speak it. The question of legitimization of knowledge becomes explicitly political. The question of who legitimizes knowledge and what legitimizes this decision is central, as mode B lacks the appropriate structure, and hence provides an unsettled site of contestation (Gibbons et al., 1994; Jones, 2000). The changes in the research language game would not leave unaffected the teaching language game either; the massification of education together with the commercialization of knowledge have led to the development of new disciplines, the transformation of the nature of relationship between teacher and learner and have imposed new rules. The sovereignty of science and arts dissolves, as new disciplines such as engineering sciences, information science, management studies and increasingly environmental sciences, attract the interest of young students, who are motivated by the commercial value of these studies. Education acquires a dominant professional character and emphasizes the continuous training throughout professional life. Consequently, an increasing proportion of the practitioners nowadays have an understanding of the academic ‘form of life’ from personal experience, and this somehow demystifies the academic Ivory Tower and transforms the relationship between researchers and practitioners in the new mode of professional alliances that is being shaped. Higher education starts losing its high status as it becomes accessible to a broader range of people, reaching from upper, to middle and working class. However, postgraduate studies retain their elitist nature, as they are addressed to a specific ‘market’: whereas higher education becomes the prerogative (in theory) of everyone, postgraduate studies are a commodity for those that can pay the (not negligible) fees. This turns the relationship between learner and teacher to one of customer–supplier; the student pays the fees and expects ‘knowledge’ (or at least a certificate for it) in return (Prichard, 2000). Furthermore, the nature of the teaching language game changes: I discussed above how teaching serves the research game by creating equals. However, in the new order where knowledge has a high commercial exchange value, few students are willing to stay in the research community, when they can ‘sell’ early and at good price their knowledge to the corporate world. Universities cannot compete in salaries with the private sector, hence they are bound to accept and train more people than they traditionally did. The commercialization of knowledge could not but affect the structure of the knowledge industry as well;

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universities are seen as cost centres, and they compete for securing money from the government, research councils and increasingly the private sector. This is translated to commercial research programmes with specific problem solving character, and raises questions about the legitimization of knowledge, as universities increasingly have to adapt in the new order by abandoning most of moral and cultural claims transcending the accumulation of intellectual and professional expertise (Gibbons et al., 1994). Discourse effects on subjects The intellectual and research community The scientist traditionally was perceived as the intellectual, who occupied his2 time with questions of ‘truth and justice for all’. As Foucault (1980) describes him: a ‘universal intellectual’, who, through his moral, theoretical and political choices, was entitled to theorize about the world, by representing without partaking in it. He was representing the universal consciousness, the free subject, and he was counter-posed to the ‘specific intellectual’, or rather the ‘intellectually competent’ worker, in the service of the state or the capital. The institutionalization of research after the Second World War and the dependence of academia on the state have transformed the ‘free subject’ to a ‘specific intellectual’, who works in a specific sector. The intellectual was brought probably closer to the conditions of the world about which he was theorizing. Still, scientific communities were elitist circles with established rules of operation and rituals of initiation, and enjoyed a high status in society. The new order of knowledge production has shaken the status and the values of the research community, which now enlarges and includes researchers and partners from the corporate world. The ‘specific intellectual’ becomes a ‘knowledge worker’ with a specific area to research and a specific programme to work on. A good ‘knowledge worker’ is one that adapts and learns fast the new language and rules of knowledge production and is capable to raise funds from research councils and corporations. Gibbons et al. (1994) argue that this does not mean that research has lost its elitist character, but rather that the community has expanded the boundaries; however, as I discussed above, the fact that more people today outside the scientific communities have an understanding of the rules of the research game, the economic dependence of the research institutes upon the corporate world and the formation of research programmes by big corporations, together with a change of the scientific ethos, do not support this view. Quite the opposite, alliances between corporations and academia are being received with suspicion by the public that refuses to accept without questioning the economic motives of research findings produced via these structures. Scientific discourse is still tightly connected with truth, however its governance is increasingly being displaced from the scientific community to the big corporations; the new discursive order requires the collaboration of the two for sustaining itself at this stage.

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The state In this newly construed network of power relations, the role of the state cannot be overlooked, for many expect it to control the development for the public interest, whereas others already celebrate, maybe prematurely, its impotence to interfere in the game. Thinking about the role of the state in this power game is not simple, for the state is not one supra-power. Foucault (1982) explains the idea of ‘pastoral power’, which is developed in the Christian world. Pastoral power promises salvation and preaches sacrifice of the self for the public good and for each individual separately. On the basis of this odd duality – securing the public interest and the interest of each individual separately and simultaneously with the same mechanisms – the state was developed as an institution of pastoral power that promises ‘salvation’ – health, wealth, education, security – in this life, and the agents of the pastoral power are multiple – police, education system, health system. Whence, it is not difficult to understand first the influence of the state upon the public, and second to conceive the scientific disciplines as agents of its pastoral power. In the new discourse, knowledge as commodity is defined as the primary resource for wealth and a major stake for competition over its control. Going against the rules of the game as they have been developed so far, to impose control over the transactions of knowledge transfer would violate the principle of the ‘communication transparency’ (Lyotard, 1984), which constitutes indispensable assumption of the new discourse – the soundness of which is debatable, as I argue next. Consequently, the state – and its agents – does not stay out of this game, but rather it tries to enter actively, for it identifies its economic and political interests with the control of commercial knowledge and the process of its production, even if this means new forms of collaboration with the corporate world. The fact that the state encourages universities to seek funding from the private sector is explained as a strategic action of reinforcing the collaborative link between the two. The knowledge-based firm Finally, the discourse on knowledge has created a new subject, the ‘knowledge intensive firm’ (KIF), and has prescribed a new set of rules and practices that regulate its behaviour. The term ‘knowledge intensive firm’ was coined by Starbuck (1992) and signifies ‘[o]rganizations whose competitive advantage is lodged more critically in forms of knowledge than in forms of capital and labour’ (Jacques, 2000: 203). Starbuck (1992) describes in detail the characteristics of these firms, and hence the newly construed subject of ‘knowledge discourse’ is distinguished from firms that are not knowledge intensive, because they do not fulfil the criteria. Hence, the rules and practices that are being developed are addressed to a clearly defined subject, and firms that are not ‘knowledge intensive’ are excluded from these practices and the promised benefits. This taxonomy through the many distinctions it makes, draws a very clear line between information and knowledge: it argues that knowledge is a stock of

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expertise and not flow of information; it is strictly esoteric and not widely shared; however it acknowledges that it does not necessarily lie on individuals, but also on the firm’s capital, routines and cultures. Following the discourse for cost-efficiency and ‘flexible’ structure, which allegedly enables organizations to adapt in the fast moving global environment, many knowledge intensive firms have undergone major restructuring in the last years; R&D is an expensive activity and in general the first to stop when organizations proceed to cost-cuttings. In the 1990s many firms, in attempting to be more ‘commercial’ and ‘cost-efficient’, have shut down their research departments. On the other hand, besides the high costs of developing the increasingly sophisticated products that the markets expect, organizations realize that knowledge is socially distributed, and no firm is able and can afford to have all the knowledge that the development of new technologies requires. Firms, by identifying themselves as knowledge intensive and realizing the benefits of investing in knowledge for gaining a competitive advantage, seek the knowledge and expertise they need to develop innovations in collaborations with other firms, government laboratories and university research centres. Gibbons et al. (1994) suggest that one reason for the high cost of developing new knowledge in-house is that firms are unsure about the particular knowledge they need in order to generate a technology – and hence it would take long to develop it – and second that even if they identify it, it might be difficult to get access to it – it might have been developed already and be protected as ‘Intellectual Property’, etc. The need for accessing knowledge and expertise in short time and reconfiguring it in novel ways is such that new specialized firms (R&D consultancies) have emerged, of which the function is precisely to mediate and facilitate this process. Alliances among knowledge actors are increasing. Notably, the rhetoric of the strategic alliances wants collaboration to be associated with a healthy competition among organizations (Gibbons et al., 1994) – despite how paradoxical this may sound. The competitive advantage for a knowledge intensive firm can only be secured by making strategic choices in developing a network of collaboration. Strategic alliances are associated with the expansion of the learning network of the firm, with reducing research costs and developing distinct knowledge and expertise – and some limitations, such as free-rides, unpredictable partner behaviour, reduced revenues, etc. However, the benefits for the firm from collaborating with universities, government laboratories and other knowledge intensive firms are identified with the survival and growth of the organization (Oliver, 2001).

Discussion So far, I presented the rhetoric of the commercialization of knowledge and the effects the new discursive formation had on the social structure. However, some theorists doubt that the world is as rosy as the new discourse suggests: a world with free floating information and knowledge for everybody, where people become more and more educated, technologies more and more sophisticated,

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and firms more and more socially responsible; in other words a world where knowledge reigns and forms the social and economic structure. On the contrary, many theorists have pointed out the commonalities between the knowledgebased society and the industrial societies, and the inequalities that are reproduced in the new order – inequalities that stem from the discourse itself and the practices it develops, and affect not only groups within the same organization, but relationships between organizations and institutions, and between countries as well. Alvesson (1993) reminds us that ‘objective’ changes do not stand in a one-to-one relationship to words, concepts and proposed images; furthermore it is not self-evident that we actually need and why we need these concepts and technologies that the new discourse suggests. It is then crucial to question the implications of the discourse on commercial knowledge. The rhetoric of the commercial value of knowledge represents a world of justice, where everybody can have access to knowledge – which is now the determinant factor of economic success. Furthermore, it represents a world where every individual is responsible for supporting the free sharing of knowledge, in order to be able to reap the fruits it promises (Blair, 1998). However, it is questionable whether everybody and all countries can have their slice from this valuable resource – which, in reality, requires a distinct infrastructure of technological devices, and skills and education; in other words an expensive infrastructure, which is more commonly encountered in the developed world. The question is who can have access and will control the governance of knowledge in the new society. Thinking globally – as the globalized times prescribe – a concern has been expressed that such an intensive investment in the knowledge production in the developed countries will result in the widening of the gap between them and the developing world (Lyotard, 1984; Jessop, 2000). The discourse on knowledge has brought forth many new occupations – such as management consultants, information technologists, computer engineers, etc. – which share the same title of ‘knowledge workers’ with traditional scientific professions, such as physics, chemists, biologists, etc. The distinction between professionals and non-professionals had been drawn based on strictly defined criteria (such as systematic, scientific-based theory, long formal education, an ethical code, etc.), and had yielded an elitist character to professions that enjoyed high respect and status. Now, the distinction between professions and occupations becomes vague, since these criteria do not apply strictly any more, and all these new and old professions fall under the same label of ‘knowledge work’ (Alvesson, 1993). The power relations between groups are being renegotiated and redefined in the new knowledge discourse, and the power of ‘speaking the truth’ is now being ‘shared’ among ‘knowledge workers’ – scientists, computer experts and consultants. I have already discussed how the criteria of ‘truth’ have already changed, as each paradigm suggests its own; however, there is a tendency that they all meet under the grand discourse of performativity and progress. As I pointed out, the question of legitimization of truth and its power effects becomes more important than ever.

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The new discourse pays attention and promotes a very restricted and ‘focused’ notion of knowledge: it represents it as an ‘object’ that can be transferred, stored and measured, in other words, an object that can be controlled for the – economic – benefit of the organization. This discourse is being supported by newly created disciplines that have developed the techniques and technologies to achieve the desired control. ‘Continuous Learning’, ‘Knowledge Sharing’ and ‘Innovation’ become top imperatives in the corporate agenda, and ‘gurus’ in the related fields develop the appropriate solutions – courses, software, techniques – to support organizations in meeting the newly defined needs. These practices aim to discipline, first, organizations as to how they perceive their identity and what the ‘right’ thing to do is – and if the solution does not work, an ‘expert’ will be called in to find what the organization is doing ‘wrong’ in the pursuit of knowledge – and, second, the ‘knowledge workers’ in each organization, who now have to ‘know’, ‘learn’ and ‘share’ their knowledge and ideas. The power of the new discursive formations aims to control both minds and bodies of the ‘knowledge workers’ (Prichard, 2000) – in other words, it aims to achieve what had always been on the top of the Tayloristic agenda (cf. de Vos et al., 2002). Critical theorists suggest that there are issues of subjectivity and control as they are now taking shape by the new discursive formations and its technologies that need to be addressed (Prichard et al., 2000). Furthermore, these technologies are based on the notions of ‘trust’ and ‘communicative transparency’; fundamentally, the whole discourse on the commercialization of knowledge assumes a free and unhindered exchange of information and knowledge, which can only be achieved through ‘knowledge networks’ (alliances) of communication (Adler, 2001; Panteli and Sockalingam, 2002). The rhetoric of knowledge wants everybody – initially within the boundaries of these alliances, and later on, as the alliances multiply, it becomes a generalized phenomenon – to share knowledge for the higher ideal of economic and social wealth. It is questionable, however, why in an economy where knowledge is the key resource someone would share valuable knowledge. Knowledge means economic and political power, and this idealistic view of harmony and collaboration that the knowledge discourse promotes has overlooked this variable when conceptualizing its assumptions. Admittedly artfully, the new discourse has succeeded in re-articulating its elements and promoting concepts that traditionally have been considered opposite and contradictory; through re-articulation the new knowledge discourse aims to neutralize frictions created from previous discourses, demonstrating a coherent and logical new order. Hence, notions such as trust and conflict, collaboration and competition (Gibbons et al., 1994; Panteli and Sockalingam, 2002), which so far were considered inconciliable, all gain a positive functional place in the new formations, and not only co-exist, but one becomes the presupposition of the other – the functional counterpart – and they work harmonically towards the objectives of the new knowledge order.

3

Knowledge and innovation in organizations

Knowledge is fiercely argued to be very important for the sustainability of any business. What is striking though, is that knowledge and innovation have been approached theoretically, and treated in practice as two separated phenomena. Only recently theorists began to argue that the two phenomena have their roots in similar processes, and that the two bodies of literature have much to share to broaden our understanding. In this chapter, I track these common elements between the two literatures, and discuss the discourses on the value of knowledge for the ‘knowledge organization’. I then examine the technologies that are subsequently developed within these discourses and promise to ‘support’ those organizations that wish to get actively engaged in creating or ‘discovering’ and sharing precious knowledge. I review in more detail different approaches to innovation and conclude with the view that innovation discourse is essentially political, since at its core lies knowledge. My main argument is that the existing mainstream approaches, which suggest the technical or cultural management of innovation, neglect the power struggles enacted in the organization, struggles that result from the stakeholders’ personal and group interests from defining what ‘innovation’ is, what is accepted as ‘good’ and what is rejected; hence innovation analysis should address issues of power. I conclude with an evaluation of the knowledge management discourse, which I conceptualize as a hard scientific formation, and a short discussion about the role of managers as political actors who have an interest in complying with the knowledge management discourse.

Knowledge in organizations Organizations have always tried to make the most out of the intellectual resources and skills they possess. The need to manage these intangible assets is not new, neither the simple ‘statement’ that the competitive advantage of a firm lies on these skills and expertise, as many popular theorists assert (Drucker, 1993; Boisot, 1998). However, ‘Knowledge Organization’, ‘Knowledge Management’ and ‘Innovation’ are the latest buzzwords of organizational theorists and practitioners. One might wonder then, what has driven suddenly the organizational world to start talking about the significance of knowledge in

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organizations. Cynics prefer to see it as another passing ‘fad’, another way for consultancies, IT companies and managers to ‘wrap’ and sell old practices and tools under new names. In other words, they prefer to see it as a surface change that hides nothing new underneath. Others (Hull, 2000) claim that the development of academic programmes, the increasing volume of research on these topics and the emergence of research centres that study these phenomena, indicate that it is not a merely passing fad, but a transformative move that reflects trends in the structure of society. New technologies, such as new pieces of software, new organizational structures (boundaryless and flexible organizations), as well as the new notion of ‘knowledge worker’, have been deployed around the new discourse of knowledge, and their impact underscores the significance of the new formations. We could argue then, that the realization of the need to support knowledge is indeed as old as the firms, but the intensity of the evolvement of these phenomena justifies the distinct name (Knowledge and Innovation Management) and the money invested in research to understand them and in technologies to support it. All these structural transformations reflect the momentum the discourse on the significance of knowledge for business sustainability has gained. ‘Knowledge’ is widely acknowledged both by academics and practitioners as the new source of wealth for organizations, the intellectual capital that increases economic value, as well as future prosperity in an ever-changing environment (Sveiby, 1997; Boisot, 1998). Initially research adopted a very specific view of knowledge – i.e. codified knowledge, which can be stored and shared as object. The majority of studies focused on knowledge in knowledge intensive firms (Starbuck, 1992), where knowledge work and expertise were investigated. This approach neglected the ability and need of other organizations to create, store and diffuse knowledge within their groups of practice (Brown and Duguid, 2001). The constrains of this formation breaks Orr’s (1990) ethnographic work on Xerox technicians, which showed paradigmatically that knowledge is a vital question for all businesses, and they can all benefit when paying attention to any type of knowledge they may have, and to the various ways communities use to share it. What is important to note here is that organizations, living the pressures to be competitive as the knowledge discourse prescribes, jumped into this game unreflectively, by adopting the latest knowledge management tools and practices, without taking the time to think of their specific knowledge needs. Nowadays we experience the opposite phenomenon compared to how it started: knowledge comes to mean almost everything and all companies like to see themselves as knowledge intensive. It is then worth having a closer look to this field. When we talk about knowledge phenomena in organizations, we are referring to three main processes: knowledge creation, sharing and storing. Knowledge storing is concerned with the codification of knowledge, and has been dominated by technological solutions. Knowledge sharing (or most commonly, learning) steps in two fields: whilst it is being supported by ICT, the role of people in sharing knowledge is now being widely acknowledged. Knowledge creation

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looks at the process of knowledge generation and innovation. What is striking is that even though the fields of knowledge and innovation management are essentially studying similar phenomena (i.e. knowledge processes), the two bodies of literature have only recently started communicating, recognizing, at least, that the insights of the other may be useful (Plessis, 2007; Chatzkel, 2007). Here, I explore concepts of knowledge sharing and creation in organizations, since they are directly related with innovation management. The field of knowledge management In order to be in a position to understand the field of knowledge management, it is important to understand ‘who says what’, and what the implications are. The phenomenon of knowledge in organization has led to the emergence of conceptual and empirical approaches that seek to meet the need to control it – to ‘manage’ it. Sørensen and Kakihara (2001) distinguish four main discourses that shape the thinking and practices of knowledge management. The discourses are distinct in terms of the views they adopt on knowledge and they are described as: (a) knowledge as object, (b) knowledge as process, (c) knowledge as relationship and (d) knowledge as interpretation. The authors argue that, in spite of the epistemological differences, the four discourses have led to common organizational practices. The first discourse treats knowledge as object, i.e. an entity that exists independently and in humans’ mind-embrained knowledge, that can be easily managed. From this perspective, knowledge is a representation of a ‘real’, pregiven world, the outcome of humans’ cognitive ability to process information. Knowledge is another ‘asset’ – such as money, land and labour that each organization possesses – objectified and transferable within and among organizations (Boisot, 1998; Sveiby, 1997). The aim of knowledge management is to ‘discover’ and ‘transfer’ this knowledge to storing databases. The discourse of ‘objectified’ knowledge is an offspring of the established positivist discourse that dominates management studies and has shaped the thinking and the related research. This paradigm has been, until recently, the dominant one in the field of knowledge management and has informed a very ‘rigid’ and de-contextualized image of knowledge, which led the practitioners to see knowledge management as an ‘improved’ version of technology management. This rational–cognitivist view reflects the managerial assumptions – which are based on ‘rationality’ – about the nature of the organizations and the tasks they are expected to accomplish. However, empirical work conducted from different perspectives (Zuboff, 1988; Weick, 1988) has shown the inadequacy of ‘rationality’ in analysing interaction between humans and machinery, as well as human communication and improvization processes. In response to this positivist view, other discourses have emerged that tried to open up the concept of knowledge in organizations, adopting wider approaches that tried to include different images of knowledge and knowing (Blackler, 1995) in understanding the phenomenon. The second discourse on knowledge is based on a socially

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constructed view of the world (Tsoukas, 2001; Boland and Tenkasi, 1995; Blackler, 1993). From this perspective, the world as we ‘live’ in it is an organized abstraction of a ‘brute’ reality of sense experience (Chia, 1997). ‘Reality’ is constructed through the process of ascribing meaning to phenomena and these meanings are attributed according to the system of codification – i.e. language – that has structured the thinking of each community. The discourse on knowledge as interpretation focuses on the humans’ mutual interpretative acts, which are shaped by, and simultaneously constitute, knowledge within a community. This discourse recognizes that knowledge depends on the ‘point of view’ of individuals and the interpretative actions and linguistic behaviour of the members of each community (Tsoukas, 1996). ‘Knowledge as interpretation’ raised awareness of the importance of communication, and the role of language and the varieties of ways in which people talk; these are seen as vehicles of knowledge and catalysts in the process of knowing. The discourse on knowledge as process is based on the ontology of ‘becoming’ (Bergson, 1913) and has been mainly framed in the field of organizational learning (Senge et al., 1999). From this perspective, the world is not static but rather in continuous transformation. Seeing the world as ‘outcome’ and unchangeable facilitates its conceptualization, which relies on static categories that the language provides; however it only allows the understanding of the phenomena as ‘snapshots’ of an ever-changing ‘reality’ (Chia, 1997). The discourse of process views knowledge as a complex of processes that humans apply to make sense of the world and reality (Weick, 1995). From this respect, knowing – rather than knowledge – is part of humans’ actions and interactions (Cook and Brown, 1999). ‘Knowing’ bridges the beliefs individuals have with the ‘truth’ of the external world viewed as a whole. This discourse has started moving the focus of the debate about knowledge management from the technologies to the centrality of humans in these processes, and has become the most influential discourse among those who want to avoid the static, cause–effect view of knowledge as ‘object’, which, it is argued, cannot capture the complexity of knowledge phenomena. The last discourse conceives knowledge as relationship. According to this view, knowledge is always relational to the surrounding world; knowledge is a result of human mental acts, be it individual, group or social acts, and those acts depend on the socio-cultural surrounding. These human mental and linguistic acts continuously shape the world of experience and can induce new contextual drifts to the world (Berger and Luckmann, 1966). This discourse is similar to the interpretative one, however it emphasizes the context and network of relations that allow the creation of knowledge. From this respect, knowledge is an ‘interconnected web of relationships’, in which human interpretative acts ceaselessly shape and maintain intentionally and unintentionally the relational setting of the web and the contextual disposition of social reality. Knowledge is always perceived as relational to a web of other ‘knowledges’. In knowledge management, this discourse has drawn attention to the web in which people and organizations are related to and ‘do the knowing’ with. Issues of intranet, internet and organi-

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zational structures are central to these approaches to knowledge in organizations; for them the question of knowledge is not deployed around what knowledge an organization has, but what the set of relationships is that the organization is connected with. This discourse has started recently gaining force, since it aspires to answer questions regarding knowledge phenomena – notably, knowledge sharing and innovation – in a globalized world (Richtnér and Rognes, 2008; Mohannak, 2007). Images of knowledge and organizations By expanding Collins’ (1993) classification of images of knowledge (i.e. embrained, embodied, encultured, embedded), Blackler (1995) identifies four types of organizations, and links them with these. •

•

•

•

Knowledge-routinized organizations, which are dependent on knowledge embedded in technologies, rules and procedures; they are typically capital, technology or labour intensive, they rely on a hierarchical division of labour and control, and they have low skill requirements (e.g. ‘machine bureaucracy’, such as traditional factory). Key issues: organizational competencies, corporate strategies, development of computer integrated work systems. Communication-intensive organizations, which emphasize encultured knowledge and collective understanding; in these organizations communication and collaboration are key processes, empowerment is achieved through integration, and expertise is pervasive (e.g. ‘ad hocracy’ and ‘innovation mediated production’). Key issues: ‘knowledge creation’, dialogue, sense-making processes, development of computer supported cooperative work (CSCW) systems. Expert-dependent organizations, which emphasize the embodied competences of key members; in these organizations the performance of specialist experts is crucial, status and power are derived from professional reputation and training and qualifications are central (e.g. ‘professional bureaucracy’ such as hospitals). Key issues: nature and development of individual competencies. Symbolic-analyst-dependent organizations, which emphasize the embrained skills of key members; these organizations engage with entrepreneurial problem solving, status and power are derived from creative achievements and symbolic manipulation is a key skill (e.g. ‘knowledge intensive firms’, such as software consultancies). Key issues: developing systems analysts, organization of knowledge intensive firms, information support and expert systems designs.

Figure 3.1 illustrates the relationship between individual/community and the kind of problems they are predominantly expected to solve. Blackler argued that the interest of organizations increasingly move towards learning new ways of

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Emphasis on collective endeavour

Knowledge-routinized organizations (embedded)

Communication-intensive organizations (encultured)

Emphasis on key individuals’ contributions

Expert-dependent organizations (embodied)

Symbolic-analystdependent organizations (embrained)

Focus on familiar problems

Focus on unfamiliar problems

Figure 3.1 Organizations and types of knowledge (source: Blackler, 1995).

dealing with the unfamiliar (be it at the individual, or the community level), because in this space organizations have the opportunity to innovate, or even enact a new reality (Daft and Weick, 1984).1 By expanding the notion of knowledge, more paradigms started participating in the debate, and this has led to a re-evaluation of what type of ‘knowledge’ returns a competitive advantage to organizations and how. The argument is that the competitive advantage lies in a difficult to imitate type of knowledge, and this cannot be its explicit form – i.e. information. Thus, great importance starts being given to the tacit dimension and the role of communities and communication processes. These new concepts in the discourse of knowledge in postindustrial societies, are expected not only to deliver hard to imitate knowledge, but also strategically to lead organizations to live with or absorb environmental uncertainties (Blackler, 2000; Weick, 1985). Here, I suggest, lies a misunderstanding observed in practice: by opening up the concept of knowledge, more organizations can see some interest in the suggested practices. Yet, even though all companies should learn ways to deal with the uncertain, not all companies need to be constantly radically innovative. Hence for most companies their interest should move from new knowledge to new ways of knowing and acting. From knowledge to knowing Nonaka’s model (Nonaka, 1994; Nonaka and Takeuchi, 1995) has proved probably the most influential model in shaping academics’ and practitioners’ understanding of knowledge creation in organizations. Nonaka was concerned with the management of the processes of innovation; his model incorporates elements of various discourses on knowledge management, i.e. the ongoing character, the recognition of the importance of communication and the technological solutions. Knowledge creation is represented as a dialogue between the tacit and the explicit knowledge that individuals in an organization possess; this knowledge is transferred from the individual to the group level, and then to the organizational while individuals and groups or ‘communities of interaction’ span within the

Knowledge and innovation in organizations Tacit

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Explicit to

Tacit from Explicit

Socialization

Externalization

Internalization

Combination

Figure 3.2 Model of organizational knowledge creation (source: Nonaka, 1994).

organization. This interaction among organizational members challenges existing knowledge and fosters the creation of new. The model presents four modes of knowledge creation. a

b

c

d

From tacit knowledge to tacit, called socialization. It refers to the creation of tacit knowledge through shared experience, during the everyday interaction of individuals, even without the use of language (by imitation, learning by doing, on the job training, etc.). From explicit knowledge to explicit, called combination. This mode considers the role of social processes, as individuals exchange information during meetings, conversation, etc. From tacit knowledge to explicit, called externalization. In this type of conversion of knowledge Nonaka recognized the crucial role of the metaphors and analogies during the communicative interaction. From explicit knowledge to tacit, called internalization. Internalization is described as the process that resembles the traditional notion of ‘learning’.

Nonaka maintained that all four practices exist in dynamic interaction in ‘knowledge creating’ companies. Communication is important for sharing experience and creating knowledge. The view holds that knowledge management is feasible via managing the communication process among individuals. Knowledge creation and sharing are represented as an upward spiral process built on the interaction between individuals’ tacit and explicit knowledge, which tends to get bigger as more individuals participate in it. This approach appears to be the most influential model of knowledge creation in organization. The simplicity of the linearity it deploys to explain knowledge creation and sharing has led to the flourishing of mechanistic approaches proposed by consultancies and IT companies, of which the discourse and technologies shape the image of knowledge management and the actual practices in organizations. Apart from the radical and very significant suggestion to conceive knowledge as an ongoing process, Nonaka insisted that knowledge is an entity – hence it can be captured and managed – which, despite its social character, is formed in individuals’ minds, conceptually distinct from the material technologies around

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which organizations are structured, as well as distinct from the process of learning (Blackler, 1995). Furthermore, this approach and the related technological practices it supports ignore the complex nature of knowledge, which affects the sharing process for two reasons (Turati, 1999): first, people know more than they can tell (Polanyi, 1967) and second, it is difficult to recognize what one knows, unless one makes it explicit through language or actions. The complexity of the nature of knowledge springs out of the assumption that all knowledge is, partially, tacit and depends on contextual elements. Moreover, this position bears as an epistemological cornerstone the distinction between tacit and explicit knowledge. Tsoukas (1996) following Polanyi insists that since tacit and explicit are complementary dimensions of knowledge, and hence mutually constituted, they should not be viewed as two different types of knowledge. Explicit knowledge is always grounded in tacit knowledge and thus they should be considered as inseparably related. A third limitation of the model is the assumption that people are willing to share openly their knowledge for the benefit of the organization. But in a society where knowledge turns to be the core resource for the well-being of the organization, knowledge and expertise equal power more than ever. Informal structures within organizations are reformed based on the power held by the ‘knowledge workers’ (Foucault, 1980). The current debate on knowledge reinforces and legitimizes these power relations. Hence, it is difficult to see how people will accept unconditionally to share the most precious resource they hold (Prichard et al., 2000). Bridging the epistemologies of knowledge and knowing Despite the breadth of different images of knowledge these approaches adopt, which admittedly embrace its complex character, the findings are still compartmentalized and static, for the analysis does not address the interrelationships between them.2 Blackler (1993: 864) summarizes the work done on understanding knowledge in organizations from different perspectives; knowledge has been described as: socially constructed (Berger and Luckmann, 1966), often tacit (Polanyi, 1967), a function of the play of other meanings (Derrida, 1978), enacted (Weick, 1979), distributed (Hutchins, 1983), situated (Suchman, 1987), material, as well as mental and social (Latour, 1987), resilient, but provisional and developing (Unger, 1987), public and rhetorical (Vattimo, 1988), and acquired through participation within communities of practice (Lave and Wenger, 1991). All these definitions have a common ground, namely they suggest an expansion of the dominant rational–cognitive understanding of knowledge, by emphasizing the complexity of tacit skills and practice, as well as the significance of social processes, cultural categories and language in ‘creating’ knowledge. The narrow understanding of scientific–abstract knowledge expands and breaks the conventional distinction between people and technologies (Blackler, 1995), and the narrative and tacit dimension of knowledge is gaining attention, together with the contextual factors (structures, culture), which support knowledge

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processes (Detlor et al., 2006). Still, what we need is a unifying view to explain knowledge and knowing, since evidence show they are interwoven phenomena. Cook and Brown (1999) provide a useful account for developing a unifying theory of organizational knowledge, which suggests the epistemological bridging of ‘knowledge’ and ‘knowing’. Their thesis does not consider ‘knowing’ to be more appropriate than ‘knowledge’ to describe the creation of knowledge, but rather, following the steps of Polanyi, who views the tacit and explicit dimensions of knowledge inseparable, they consider the two concepts as complementary. Cook and Brown suggest that knowledge is a tool of knowing, whereas knowing is an aspect of our interaction with the social and physical world and that the interplay between them can generate new knowledge and new ways of knowing, which is essential for innovation in organizations. Cook and Brown maintain the four dimensions of knowledge – tacit and explicit knowledge created and possessed at an individual or group level. However, they examine knowledge both as possession and as practice. The notion of knowledge as possession derives from conventional approaches that view knowledge (what is known) as ‘object’, as something that the individuals possess. Cook and Brown call this approach epistemology of possession. In this epistemology, explicit knowledge is favoured to tacit, and individual human mind to the group. Following the Cartesian tradition, western culture tends to consider that all knowledge and learning lie in individuals’ heads. This position neglects the ability of groups and thus organizations to learn, and the knowledge that is embodied in humans and embedded in organizational practices and structures. By presenting the limitations of the traditional way of thinking about knowledge, Cook and Brown do not suggest that the group should be favoured in preference to the individual, nor tacit knowledge in preference to explicit. Rather they suggest the epistemology of practice in order to give new insights into understanding better the process of creating and acquiring knowledge. The epistemology of practice refers to the process of knowing. The typologies of knowledge cannot capture and describe the distinct knowledge that lies on the basis of an act – of a practice, e.g. the act of riding a bike does an epistemic work on its own. The argument lies on the assertion that each human group has not only its own set body of knowledge but also distinct ways of knowing. Practice implies not only doing, i.e. a behaviour, but rather a behaviour imbued with meanings. Practice is thus an action informed by meanings drawn from a particular group context. Two elements are distinct in Cook and Brown’s notion of knowing: first, the concept of productive inquiry that gives the motive to start the process. It is called ‘inquiry’, implying that the action has the sense of a query, like a problem or a question; it is called ‘productive’ because its aim is to find a solution or an answer. The second element is the interaction with the social and physical world. We act within this world and our actions either give shape in the physical world or affect the social. Hence, knowing, since it is about our actions, lies on this interaction. While knowledge is about possession, i.e. what we have in our

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heads about these worlds, knowing is about relation, i.e. the interaction between the knower and the world. By bridging the two epistemologies, Cook and Brown add a dynamic aspect to understanding the relationship between knowledge and knowing. By identifying the concept of knowing in all actions of individuals and groups, knowing brings into play the four forms of knowledge, and knowledge becomes the tool in the interaction with the world, giving it shape and meaning. In the organizational world it suggests a different perspective in assessing the role of what is known (both as knowledge and knowing) in an organization’s ability to learn, to maintain quality, to develop competencies, to innovate, etc. Knowledge is not the product but an input of the organization’s activities to produce goods and services. These activities require from the organization to be innovative, and this is translated into paying attention not only to what the organization possesses but also to how it practises it.

Knowledge phenomena: learning, knowledge, innovation ‘Learning’ and ‘knowledge’ are two processes, which, even though closely connected, the literature traditionally has tended to treat them as separate phenomena, and were addressed through different epistemologies aiming to answer different questions. By paying attention to both ‘knowledge’ and ‘knowing’, as Cook and Brown suggest, the two phenomena (learning and knowledge) find a unified base to theorize knowledge phenomena (learning, sharing and innovating) in organizations. Daft and Weick (1984) see the process of interpretation as fundamental to knowledge processes. They suggest that conventional approaches treat learning as a de-contextualized process, which separates knowledge from its environment and practice. If knowledge is abstracted from practice, then it cannot be well understood, engendered (through learning) and enhanced (through innovation). The model they suggest conceives the environment as containing a great degree of uncertainty, and hence, the organizational members must search for information and interpret it in order to make sense and proceed with decisions and actions. In that process, each organization develops its own distinct ways of knowing the environment. From this perspective, organizational learning can be seen as the mechanism to acquire knowledge from the environment. The process of interpretation can be thought of as a process of giving meanings to data that the organization scans, and of developing the conceptual schemes of the organization. This is a threefold process consisting of the scanning stage, when the organization scans information from the environment, the interpretation stage, when the organization makes sense of it, and the learning stage, when action is taken. Organizational learning can also be thought of as a process of enacting the environment, wherein the organization operates. According to the interpretations given, the organization constructs a way of ‘seeing’ and understanding the world, constructs a perspective from within it interprets and interacts with the

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world, which is shared among the members. Daft and Weick argue that these interpretations may shape the environment more than the environment shapes the interpretations. They suggest a model of organizational interpretation modes, where they identify four different types of organizations, according to the degree of intrusiveness and the assumptions they hold about the environment. Along with this model, the organization behaves according to the distinct ways it interprets the world. The model is based on two key dimensions: (a) the managers’ beliefs about the analysability of the external environment and (b) the degree to which the organization intrudes into the environment in order to understand it. The first assumption in the first dimension is that the managers believe that there exists a right answer – a correct interpretation – before they start thinking about a problem. They tend to interpret current information according to their previous experiences. Consequently, there will be a homogeneity in their actions, which will be undermined when the environment turns to be subjective, difficult to penetrate and unanalysable. The ‘organizational intrusiveness’ is referring to the extent to which an organization actively searches the environment for information and answers, and is engaged in ‘trial and error’ acts by allocating more resources in exploring the environment. A possible explanation for this behaviour is that these organizations perceive the environment as hostile and threatening and allocate more resources in the interpretation processes. The model presents four types of organizations, classified according to the previous types of behaviour: •

•

the conditioned viewing, which perceives the environment as analysable, believing that the answer is out there and accepting passively the information given from the external environment; the discovering, which perceives the environment as analysable, but is committed to active search for the right answer;

Unanalysable

Assumptions about the environment Analysable

Undirected viewing Constrained interpretations. Non-routine, informal data. Hunch, rumour, chance, opportunities

Enacting Experimentation, testing, coercion, invent environment. Learn by doing.

Conditioned viewing Interprets within traditional boundaries. Passive detection. Routine formal data.

Discovering Formal search. Questioning, surveys, data gathering. Active detection.

Passive

Active Organizational intrusiveness

Figure 3.3 Model of organizational interpretation modes (source: Daft and Weick, 1984).

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•

the undirected viewing, which perceives the environment as unanalysable, but is not engaged in a structured processes of interpretation; the enacting, which perceives the environment as unanalysable and is engaged actively in processes of interpretation, ignoring precedent, rules and traditional expectations; this organization gathers information by trying out behaviours and seeing what happens. This is the most interesting type of organization, since it imposes its interpretations on to the environment and shapes it more than it lets itself be shaped by this. For this distinct ability they have to shape the environment, these organizations are identified with innovative organizations, which are in a position to suggest and enact radical ideas.

•

From a similar perspective, Lave and Wenger (1991) argue that learning in an organization, conceived as the transmission and acquisition of knowledge, is situated in the everyday interaction and communication of the individuals. This position detaches learning from the constraints of training programmes and classrooms and identifies it in all actions that take place in an organization as potential resources of learning. It recognizes the active aspects of learning as process, while individuals negotiate meanings of words and situations as they interact. In other words, it sees learning as embedded in discursive patterns. From this perspective, learning is not the transmission of knowledge from one head to another, but rather lies in the process of participation between them. Thus, instead of asking what cognitive processes and conceptual structures are involved in it, the question should be what kind of social engagement provides the context for learning to occur. For Lave and Wenger, understanding and learning are defined by the context of action: the agent, the activity and the world. This approach emphasizes the role of discourse in this process, as it is not seen as the means to talk about the world, but rather as a way of acting within it. People constitute their identities and a representation of a world – a perspective of seeing the world – as they interact and communicate. What one knows is associated with whom one does the knowing with – thus learning is dependent heavily on the identity of the community. Learning is not a fragmented phenomenon but a relational one, as it is also dependent on the current engagement and dilemmas of the specific situation. The model of learning they suggest with the concept of legitimate peripheral participation (LPP) provides a framework of understanding learning as socially constructed process. From this perspective, to learn means to become an ‘insider’ and learners do not receive or construct abstract knowledge, but rather they learn to function in a community, to become a practitioner. Furthermore, the LPP model identifies the learners with the workers, recognizing by this the learning process as part of the everyday life of a ‘community of practice’. Brown and Duguid (1991) bridge the sense-making process with learning and innovation. Their analysis is based on three exceptional works: Orr’s ethnographic work with Xerox’s reps, Lave and Wenger’s model of learning as legitimate and peripheral participation (LPP) and Daft and Weick’s model of

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organizational interpretation modes. Brown and Duguid claim that canonical practices, well-defined processes and training programmes blind the organization and impede innovation. By following strictly determined ways of acting and thus thinking and behaving, the organization constrains the non-canonical, actual practices that are a source of learning and innovation. Drawing from Daft and Weick’s work, they point out that, like story-telling, enacting is a process of interpretative sense making and controlled change. The process involves an organization re-imagining its environment and re-perceiving itself in it. This process can be a source of learning and innovation that would return a competitive advantage to the organization. Orr’s (1990) ethnographic study at Xerox is a classic work that features the ‘war stories’ that the maintenance engineers told each other. From this work, the different functions that discourse – in this case stories – serves emerge: • •

•

an informational function, preserving and circulating essential news about particular problems; an educational function, as the story-sharing teaches the technicians about particular faults on the machines and helps them to develop diagnostic and trouble-shooting skills; the technicians establish their identity within the community of Xerox technicians; the newcomers, by participating in the story-telling process, establish their identity as professionals and contribute to the collective wisdom of the group.

Boland and Tenkasi (1995) acknowledge the importance of communication in the process of knowledge sharing within communities of knowing, by offering two models of perspective making and perspective taking (the process of communication), the conduit model and the language games model, suggesting that they have a complementary function. The conduit model portrays communication as a message sending and receiving process through a transmission channel. ‘Language games’ is a model based on Wittgenstein’s notion of the role of language in forms of life. This model considers conversations and activities as language games, in which people create the meanings of words and forms of speech and continuously evolve ways of talking and acting together. Building on Bruner’s work, Boland and Tenkasi recognize two modes of cognition: the information processing (or paradigmatic) mode and the narrative mode. The paradigmatic mode emphasizes the rational analysis of data in a mental problem and the deductive process of the argument construction. Beyond this conscious process of sense making, humans narrativize almost continuously their experience, as they recognize unusual or unexpected events and construct stories to make sense out of them.3 This narrative capability is a cognitive process through which humans construct and represent the cultural world and a sense of self. Boland and Tenkasi suggest that the conduit model of communication and the paradigmatic mode of cognition are valuable in designing communication systems, whereas the notion of language games and

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the narrative mode give insights into the creation and sharing of knowledge within a community. Perspective making and perspective taking throw light on to the socially constructed nature of the organizational knowledge. Weick (1995) argues that whereas sense making occurs in an individual level, perspective making occurs in a group level and is a social process. By perspective making is meant the ‘knowing’ process, the way according to which the community interprets the world and constructs new knowledge, whereas perspective taking is the process of sharing the perspective with new members and the way according to which knowledge passes among individuals. In organizations where knowledge is considered to be a key resource, perspective taking is considered a process through which knowledge is appreciated and utilized. The organizational knowledge base emerges from the exchange, evaluation and integration of knowledge among its members; knowledge emerges from their interaction and not from their isolated behaviour. Drawing from a Kuhnian approach, which conceives knowledge as articulated and validated within the boundaries of a paradigm, organizational knowledge is created, defined and accepted as such by the particular perspective of each distinct community of knowing. The contribution of Boland and Tenkasi’s work is that having recognized the importance of the conduit model of communication in organizations, they argue that language games are equally important. The problem of knowledge integration in an organization is not only a problem of simply combining, sharing or making data commonly available. It is also a problem of making the perspective of a community visible and accessible to others. On this point lies the importance of studying the discursive interactions among individuals. Communication and communities in the knowing processes The importance of communication within communities of knowing is acknowledged widely by theorists and practitioners (Lave and Wenger, 1991; Boland and Tenkasi, 1995; Snowden, 1998). However, the main tendency, springing from the mechanistic approach, is to treat communication as a three-stage process: the transmitter encodes the message, transmits it through the selected channel of communication and the receiver decodes it. The technological devices that aim to enable communication among people and groups are based on this linear model – the conduit model as explained by Boland and Tenkasi (1995), who also suggested that attention should be drawn to ‘language games’, for it is precisely the encultured knowledge that communication and information systems cannot capture. Understanding and learning are defined by the context of action: the agent, the activity and the world. Discourse in this process is not the means to talk about the world, but rather a way of acting within it. People constitute their identities and a representation of a world – a perspective of seeing the world – as they interact and communicate. What one knows is associated to whom one ‘does the knowing with’ – thus learning is dependent heavily on the identity of

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the community. From this perspective, to learn means to become an ‘insider’ and learners do not receive or construct abstract knowledge, but rather they learn to function in a community, to become a practitioner. The identity of the community is not constituted merely by the common aim towards which the members are working, but fundamentally by the history, the established processes under which it works and its culture. Being an insider means participating in the knowing processes. These processes are founded on the trust that the community identity aspires to the members (Park, 2006; Usoro et al., 2007). However, trust is a psychological state, not behaviour (O’Donnell et al., 2000), and it is questionable whether it can be imposed on the individuals; it rather develops through time as individuals gain their identity as insiders. Yet, its importance for knowledge exchange is beyond doubt. Communities and e-communities that are built to accomplish a certain task and then dissolve, ‘communities’ that lack history and steady members, also lack a steady identity. Members may exchange information, but a great part of knowledge the members carry remains tacit. What I question here is not the significance of trust, but whether it is realistic to expect it forcefully within temporary professional relationships. ‘Knowing’ and further research Blackler (1995), drawing on work done from the community perspective, i.e. work that emphasizes ‘knowledge’ as collective, situated and developed through people’s construction of shared experiences and through their perceptions of their activities, suggests ‘activity theory’ as an insightful approach in analysing knowing processes in organizations. ‘Activity theory’, developed by Engestrom (1987), takes as a unit of analysis the socially distributed activity system, and analyses the complex relations between agents, the community of which they are members and the conceptions they have of their activities. These relations are mediated by other factors, i.e. language and technologies used by the people in the system, implicit and explicit rules that link them to their broader communities and the role of system and division of labour adopted by the community. Engestrom’s analysis suggests that incoherencies and contradictions are inherent in any system, and they are potential agents of change; organizations are not stable and rational, as conventional approaches suggest, but rather ‘experienced’ as such, partly because of the common imagery of the organization as ‘rational machinery’, and partly because of people’s ability to learn to work together, for this gives a sense of stability. Adopting an activity theory perspective, Blackler (1995) suggests an analysis of knowledge as active process, as ‘knowing’, and distinguishes the following aspects, which need further research. •

Knowing as mediated is reflected into the dynamics of activity systems and the ways they change; research in this area needs to study how structural and technological changes transform the contexts of action – and make the system larger and more complex.

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•

Knowing as situated emphasizes the significance of people’s interpretations of the contexts within which they act, and the key role of ‘communities of practice’ in the acquisition and development of skills. However, little is known about the ways in which people’s understanding of their activities is changing as a result of the developing complexity of the contexts within which people are working Knowing as provisional emphasizes the idea that knowing is temporary and constantly developing, as inevitable tensions emerging within the systems of knowing and doing; these consequent changes may or may not be planned, and may or may not be understood by people. Blackler suggests that from alerting people about the tensions – that otherwise could be ignored or tolerated – a process of dialogue, experimentation or collective learning may be enacted. Knowing as pragmatic reflects the fundamental assumption of activity theory that action is driven by the conception people have of the object of their activities; further research is needed precisely on how the conception people hold of their activities change as systems become more complex and expand, what the consequence of these changes are for the individuals and how the probably inefficient traditional ways of organizing can be supported by developing communal narratives. Knowing as contested praxis reflects the structures of power and emerging conflicts between groups, as the discourse on ‘knowledge’ transforms the social order and forms new roles and identities; this area – the power/knowledge theme – is less addressed from current research in activity systems.

•

•

•

From knowledge to innovation After the Second World War, robust technological progress and economic growth drove economists to study the relationship between investments in science and technology, and economic growth. However this approach was insufficient to answer how technological progress affects exactly the economic system, because it could not answer why some firms were performing better than others; to answer that, there needed to study the internal characteristics of the innovation process, and how it is related to individuals, management and the wider socio-economic environment. Hence, new approaches placed emphasis on the firm and in particular on the related managerial activities. Progressively, innovation management is seen as the core of the knowledge firm’s strategy (Trott, 1998; Tidd et al., 2001; Bessant and Tidd, 2007). What is striking in this debate is the lack of communication between knowledge and innovation theorists, as if the two are distinct phenomena. Indeed, innovation theorists only recently started using concepts of the knowledge literature – finally realizing that innovation is about knowledge generation and sharing. However, what is meant by innovation, is blurred. Fonseca (2002) summarizing the work done in the field, distinguishes the following views: a key feature of certain organizations – called ‘innovativeness’; an economic process of

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applying and spreading scientific advances – ‘technology-push’ innovation; a marketing process addressing unspecified needs – ‘market-pull’ innovation; a strategic dimension of competition in high technology industries; a routine function of the organizations; a cause of economic development through cumulative (self-reinforcing) complex interactions; a determinant of industrial structures and barriers to entrance. The field of studying innovation is indeed multidisciplined (economics, finance, organizational behaviour, etc.), studied by many different epistemic traditions (Slappendel, 1996),4 and hence characterized by high inconsistency5 in terms of assumptions and findings. At least some agreement appears at the element of novelty that innovation supposedly has – or a ‘perceived’ novelty, as some theorists suggest (Zaltman et al., 1973; Van de Ven and Andrew, 1986; Van de Ven et al., 1988). Regardless of the definition and the theme each approach adopts, the key drive of the mainstream research so far relates to how manageable the innovation process is. On the other hand, alternative approaches doubt precisely that this key assumption is a valid starting point for studying innovation processes; in other words, they doubt whether the question of how to control and manage innovation is suitable for understanding the phenomenon. Here, I discuss two dominant conventional approaches to innovation management at the organizational level, i.e. innovation management as a rational planning activity, and as a cultural issue, which I believe embrace the aforementioned approaches to analysing innovation in organizations. Then I examine two alternative approaches, which I believe, offer a bridge between the knowledge and innovation literatures; these approaches conceive innovation as social construction of meanings, and as a political game (Fonseca, 2002; Frost and Egri, 1991). Conventional approaches to innovation management By reviewing key articles of popular managerial press (e.g. McKinsey Quarterly, Harvard Business Review), one observes that the debate tends to deploy around some core questions and themes. Innovation is either an administrative question or a technical problem, a social or a political matter; the story of innovation is always constructed via success stories of single individuals – bold entrepreneurs or mad inventors – that dare to persist and go against the stream. It seems that stories with a central hero, who works against the tide and succeeds, are easier to spread and become popular – they are easier to remember in terms of plot – compared to stories with many persons acting and not drawing a clear line whether a person is ‘good’ or ‘bad’, ‘successful’ or ‘opportunist’, and hence a ‘moral conclusion’ cannot be drawn. However, innovation is never one man’s ideas; ideas are socially constructed and redefined over a long period of time. These success stories might be easier to remember, but they tell a ‘one-sided’ story about how innovation emerges. The size of the organization is an issue, as well: small size firms and limited resources are supposed to boost innovation, as they make people bold with experimenting – the loss is not that big in case of failure – and there are not

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many hierarchical levels involved that might kill the new idea. Big companies are successful innovators as well, as long as they apply flexible structures and processes of networks that support these features that characterize small companies (Brown et al., 2002; Quinn, 1985). The role of technology is highly debatable too, as to whether it can secure a competitive advantage; technology deterministic views bring many examples of companies that have invested in pioneering technologies and conquered the market (McFarlan and Nolan, 2003); technology, they believe, will improve the flexibility of collaborative networks, since companies can communicate more information using internet technologies, and this will loosen up tightly coupled processes. Opponents counterpose that technologies, nowadays, have become available and affordable to everyone, and they doubt how they can be the core of distinct knowledge (Carr, 2003); for them, fostering and capturing distinct knowledge is not a technology project. A main shortcoming of the dominant discourses is that they label innovation successful only when profit is being made after the new product is launched in the market. If the innovation will not return value to the firm, then it has not been successful – it is probably considered a lesson to learn. In other words, the base to understand or the criteria applied for evaluating the innovative process are economic and drawn from the discourse of ‘economic rationality’. Consequently, the dominant understanding of innovation is limited to developments that return profit. This dominant discourse leaves out of the ‘innovation language game’ – and hence common understanding – first, ideas that were traditionally researched in the scientific language game, i.e. long-term and uncertain regarding the specific results and their commercial chances, which nevertheless are the ones that generate hard to imitate knowledge and products and, second, smaller ideas, which might not generate revenue, but still they are developed through and are part of the organizational everyday life, and their existence is crucial in sustaining or transforming the current organizational order. Innovation as rational planning We could distinguish two main streams in theorizing innovation (Bessant and Tidd, 2007; Fonseca, 2002): the first conceives innovation as a rational planning process, whereas the second conceives it as a social and political issue. The first strand, as developed from neoclassic and evolutionary economics, holds that innovation is a prime strategic goal of organizations to be realized through particular organizational functions. Influential authors of this discourse (Drucker, 1985; Tidd et al., 2001), suggest that innovation is an entrepreneurship function, essential for the survival of small and bigger organizations. The objective of innovation activities is the development of new products, which result from conscious and purposeful search. The environment is recognized as turbulent, fast changing and unpredictable; hence, the role and activities of R&D departments are closely associated with departments of which the role is to scan the market for needs and new product opportunities. The rational planning of

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innovation process suggests models that tend to split the process in controllable and measurable distinct stages, which involve the evaluation of ideas, the matching of an idea to the market conditions, the elaboration and the development of the idea into material reality, the technical tests and validation of trials, and final stage is the launching of the product. At the end of each stage, the idea is evaluated against the market and the profits, that it is expected to return in defined (predominantly short-term) time, and the compatibility of the idea with the strategic route of the organization. All these matters are supposed to be arranged and designed in advance, and incorporated in a business plan. Fonseca (2002) notices that defining sequential models of the innovation process in this way displays systems thinking, and calls for cybernetics systems to use in the control of innovation process. Innovation is conceived as unfolding what has been enfolded in the design of the system from within it emerges. The difficulty with this approach is that it excludes any possibility of novelty, since the cause of innovation formation is the system itself. Moving from the macro level of the market to the micro intraorganizational level, this approach appeals to the rational, autonomous individual, who chooses the innovation. Here, for Fonseca, it lies the paradox of this approach in that by proposing that autonomous individuals choose innovation, in effect putting intention into the system, but also parts of the system, which unfolds what has been put into it: an individual is said to be free to choose but also subject to the operation of the system. (p. 20) This approach does not address the paradox, but tries to downplay it by suggesting a ‘both . . . and’ explanation; furthermore, neither formative nor rationalist teleology have provided a satisfactorily account on how innovation emerges, other than attribute it to the individual’s rational choice. Innovation as culture The second discourse on innovation that emerged in the literature and influences organizational practices, has a different starting point. Having accepted that the rational planning account suggested by economists is insufficient to explain innovation processes, for it can only study correlations between investments in R&D and profits, this discourse adopts an idiosyncratic agency approach in studying innovation, and is deployed around the significance of scientific knowledge for innovating – and hence related theories and practices allocate a distinct and central role to research institutes and R&D laboratories. For example, Gibbons and Johnston (1974) mentioned four types of benefits that might flow from scientific research: benefits of trained manpower, cultural benefits, the direct benefits of applied research where the application of the research is known and the benefits resulting from the subsequent application of fundamental ideas discovered through curiosity-oriented research.

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The discourse has developed from the human relations school and emphasizes the significance of values and culture in making innovation blossom. The analysis of innovation from this perspective takes into account how cultural variables, biased decision-making strategies and managerial procedures mediate the processes of creating and sharing knowledge within and across institutions. This approach attributes a central role to the management of an innovative culture, and hence to the charismatic leaders that will design and manage this culture of shared beliefs and values, from within which innovative ideas will emerge. Kanter (1988) describes in a nutshell the views of this approach on innovation; she suggests that innovation – whether technological, administrative, processes or systems – has the following characteristics: •

•

•

•

the innovation process is uncertain; the source of innovation or the occurrence of opportunity to innovate, as well as the outcome may be unpredictable, and hence its forecast difficult; the innovation process is knowledge intensive; the innovation process generates new knowledge intensively relying on individual human intelligence and creativity, and involving ‘interactive learning’ (Quinn, 1985); the innovation process is controversial; innovations always involve competition with alternative course of action – or even poses a threat to vested interests; the innovation process crosses boundaries; an innovation process is rarely contained solely within one unit, as organizations interact with the environment and form networks of collaboration. It is claimed that the best ideas are interdisciplinary or interfunctional in origin.

This description defines innovation as uncertain, fragile, political and imperialistic, and suggests that it should flourish where conditions allow flexibility, quick action and intensive care, coalition formation and connectedness. In other words, it determines not only the features of innovation – and the way theorists and practitioners should think about it – but goes further to suggesting adequate structure, culture and possible actions. As a response to the rationalist planning approach, ‘innovation as culture’ acknowledges the ambiguity and uncertainty of the process, and hence the impossibility to try and control the process itself, for at its heart it is political and dependent on its social context. Research from this perspective brings evidence of innovations that were either silenced because the inventor had not the appropriate network to support it, or successful precisely because the idea was supported by the ‘right’ person in the ‘right’ position. Kanter (1988) goes on to describe the four stages of the innovation process, as identified through empirical studies, which again are much different from the models of the rational approach: (a) idea generation and activation, where individuals such as ‘entrepreneurs’ and ‘innovators’ are seen as driving forces; (b) coalition building and acquisition of power, which is essential to move ideas into reality; (c) idea realization and innovation production, where ideas are

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turned into a model; and (d) transfer or diffusion of the spreading model, which is actually the commercialization stage of innovation. These stages again emphasize the unpredictability of innovation, the centrality of the innovation heroes (individuals) in the process, as well as the clash between creativity and control in attempts to design the process rationally. Even though this approach rejects the possibility of controlling directly the innovation process, it supports the view that innovation can be influenced, shaped and supported indirectly by designing and controlling the ‘right’ environment, which will ultimately lead to the desired performance and outcomes. In other words, this view does not suspend the drive to control innovation, but by acknowledging the political aspect of social life, it suggests an indirect way to achieve it. However, the approach bears the limitations that the literature on culture management has identified, i.e. whether there is one corporate culture, and whether culture can be managed (Smircich, 1983; Meek, 1988); in addition as Brown and Duguid (2001) note, it makes no sense to talk about a shared culture that supports the innovation process, as the organization is open and people interact with individuals and other organizations beyond the boundaries of their own. Furthermore, the question of power from this perspective is addressed as merely a means of negotiation, not as the force that creates new order and rules. Consequently, many aspects of power relations in organizations are left unanswered. For Fonseca (2002), both discourses conceive the innovation process (from origin, formation, cause and evolution of ideas) in terms of constructs outside the ordinary experience of interaction between people in local situations, and imply that the emergence of novelty is an extraordinary experience, connected with very particular instances or factors that cause it. Both mainstream approaches conceive innovation process as a ‘both . . . and . . .’ scheme. So, innovation is the outcome both of: •

the mind of the autonomous individual, who is understood either as a rational, calculating scientist that is planning the ‘discovery’ of the innovations that exist outside the system; or understood as an intuitive, political and heroic entrepreneur that fights against conformity. Both approaches focus on the individual and the existence of already defined innovations awaiting to be discovered.

And •

a system understood either as a self-regulating control system, according to the rational school, or as cultural, vision-driven system, according to the entrepreneurial school.

‘Both . . . and . . .’ means that innovation is understood in terms both of the autonomous individual that designs the system and the system/organization in which the individual is part (Bessant and Tidd, 2007; Slappendel, 1996).

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Either conceived as a ‘rational’ scientific process, or a ‘soft’ intuitive human process, both approaches give a linear, cause and effect explanation to creativity and innovation, which fails to capture its complex nature, and creates the belief and objective that innovation can be managed, if all factors (individuals and contexts) are controlled. The paradox that both approaches recognize and try to overcome is that, in the race of gaining the competitive advantage, the orderly and predictable decisions, on which the business rests, rely on and have to support the unpredictable process of innovation (Drucker, 1985). Belief in the rational ‘choice’ creates a second paradox, since it describes a situation where all organizations – having the same information – are seeking the same innovations. Organizations are seen as designs of individuals, and individuals are at the same time parts of the organization, hence their actions are controlled by the organization, and at the same time outside of it, hence they can rationally design and control the system. From this respect, innovation is described as a rational process, emerging via a designed model and evaluated by its outcomes. Knowledge in this process is treated as ‘object’ resulting from individuals’ cognitive abilities. Research and theories from these paradigms aim to control and manage the unpredictable character of innovation, whereas it is precisely the assumed rationality and power of management that should be questioned and investigated. Fonseca (2002) argues that firms in their attempts to create stability either by technologies or new structures, etc., they create more and more complexity, and suggests complexity theory to understand the situated, non-linear, dialectic interaction among people that generates novelty – to a similar conclusion came Blackler (1995) when he was reviewing the wider field of knowledge management, and suggested for this purpose activity theory. Alternative approaches to innovation management ‘We have moved from an economy based on the transformation of energy and matter to an economy of knowledge creation’ (Fonseca, 2002: 6). The traditional mechanistic concepts that measure and calculate the natural world, are proved insufficient to study complex relationships, human experiences and cultural issues, which are the substance of knowledge. The process of knowledge creation and sharing needs new approaches and methodologies, which would give up the illusion of rationality and control and study the emergence and consequences of knowledge phenomena as part of the life-world. In response to this call, I distinguish two approaches: the first suggests the study of innovation as the creation of new meanings, in a continuous process and naturally, as people try to make sense of the environment, to communicate and to take actions; the second suggests the analysis of innovation as a game of power and politics. This second approach, combined with ideas from activity theory and a Foucauldian concept of knowledge/power forms the analytical framework of this research.

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Innovation as the social construction of meanings Fonseca (2002) conceives the process of innovation as creation of new meanings; innovation from this respect has already emerged via people’s discursive interactions in social institutions, which is a stage prior to the rational models of innovation management. Then what these models provide is a common basis for conversations, when people talk about innovation processes; however, the models themselves do not bring order and controllability, as they are expected to. Organizations are in continuous flux and transformation; stability is created temporarily as temporarily some meanings are agreed and accepted over others – but this stability is illusive, since meanings continuously change via discursive interactions. According to this view, innovation is not the final product, but an ongoing process where meanings are created every single moment and that makes the organization dynamic and innovative. The evaluation in this case would be the successful response of the organization to the environmental challenges. Fonseca sets out to explain how innovation emerges, emphasizing the conversational nature of innovation; through everyday discursive interaction, misunderstandings and frustration stirs the settled order of an organization. As mentioned, an organization is not a ‘tool’ that individuals design and use, but rather a system of patterns that emerge through interaction and they become ‘habits’. In other words, organizations are temporary patterns that people have adopted as ‘good enough’. The members of the community perceive these patterns as things that have always existed, and they are represented in their verbal interaction. As people interact verbally, miscommunication and persistence in making sense and in overcoming the uncertainty and the subsequent anxiety will create new meanings – these new meanings will be actualized as innovations. What makes people insist on talking, despite the misunderstandings and the frustration, is precisely the willingness to make sense, the curiosity to understand each other and the trust in each other and their relationship. Fonseca stresses the dialectic nature of innovation, beyond inspired visions and rational plans of individuals, and systems of control and cultural systems. Issues of language and power are inherent in this ‘organized system’; language represents the accepted order, thus a shift in language would mean a shift in the organization. Power relations are balanced in the settled system; the emergence of new meaning (and subsequently a new pattern of talk) will disturb the power relations that have legitimated the existing order. Fonseca concludes that the emergence of new meaning cannot be located at a point in time or space; it can neither be attributed to one particular person – despite the stories that the organization will create around the contribution of one ‘heroic’ person (organization and in general modern cultures like to mythologize individuals, and take examples from their deeds). Ideas do not occur as a direct result from the purposeful search over a perceived problem (innovation is not a problem-solving activity); ideas do not result from sequential processes laid out in advance by the legitimate control systems of the organization, nor

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presented themselves as already stabilized meanings, but rather they are acquired incrementally meaning through conversations. From this perspective, innovation is the actualization of new meaning, as the latter emerges through the conversations that result from understanding, but also from misunderstandings. Fonseca holds that finally through misunderstandings a new meaning emerges, and the new meaning will become innovation; whence, innovation, the creation and materialization of ideas is not an individual and political process, but rather a social process that sets up in all instances of human discursive interaction. Addressing the question of innovation as construction of meanings reflects the latest development of the related debate on the nature of knowledge and social phenomena, as it is presented in the beginning of the chapter, and offers indeed insights into the nature of innovation, for it focuses on and questions the nature of innovation – not on management neither on the culture, as the previously presented approaches do. However, all the approaches so far assume and intentionally aim to create consensus among people in organizations; the greatest part of the debate about knowledge phenomena has invested great hopes in the trust between people and between people and organizations. The question of power is addressed as a variable that can be manipulated, in other words, it takes a very limited definition of what power and politics are, and how they impact on the emergence of new knowledge and innovation processes. Innovation as power game It is a common criticism that conventional approaches apply quantifiable measures to assess the utility of an innovation. These approaches identify variables for the generation of numerous contingency models of innovation; however they have been criticized for their conceptual and methodological limitations, since quantifiable measures neglect the dynamic aspects of innovation, which are better studied by conceptualizing it as a process shaped by the interaction between humans and the world. I argued in Chapter 2 that the creation of knowledge is not a moral superior activity, but what is accepted as knowledge is socially constructed; furthermore, who decides what knowledge is and what is not is a key question in theorizing knowledge. These two aspects of knowledge creation suggest that innovation process should be studied not only in technical terms, but essentially as political process, for this analysis would highlight aspects of innovation process that have been neglected so far. Frost and Egri (1991) suggest a framework to analyse innovation as political process, where the establishment or not (acceptance or rejection) of a product or social/administrative practice is the outcome of a power game, and not of its value in terms of utility or profitability etc. – criteria that are formed within the current dominant discursive order and agreed as the basis for evaluating ideas. The authors provide numerous examples of cases where a superior in utility idea was lost because it did not have the necessary network to support it. In analysing these cases, they combine in the analytic framework of power in organizations the literature of organizational change, since innovation is about bringing in

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something new, and most of the times discarding the old, in other words, innovation is always associated with changing the order of things – innovation process is a contested process of change. Ultimately, what is understood by ‘innovation’ is the result of a complex interplay of power and politics at many levels – individual, intraorganizational, interorganizational and societal. For Frost and Egri, power is not simply the ability of someone to manipulate and control the behaviour and actions of others, but they employ a wider notion, according to which power forms the surface and the deep structure of the organizational life. At the surface level, power and politics shape the everyday life, the contests and struggles for collaborations; here, power manifests itself in attempts of individuals and groups to exploit the rules and take control of the current order for their own benefit, and in the expenses of another group. At the deepstructure level, power operates in subtle and hard to detect ways; it springs from already contested and agreed order, which now is accepted as natural and neutral. This ‘deep-structure’ power shapes and influences – but not necessarily determines – the choices and actions individuals take. This position recognizes a degree of freedom to an autonomous individual, who can act freely at the surface level and challenge the established order and ultimately the deep structure. In other words, there is an interactive relationship between surface and deep structure, and political action. Following this argument, organizational politics involve opportunities (current and embedded) to act, orientation (will and skill) and intention (goals). Hence, the role of human agents as surface actors and as intermediaries between the deep and surface structures impacts on the innovation process. The proposed analytical framework here, i.e. viewing innovation as political game and analysing issues of power and order, can be addressed not only to examine and question the actions of the organizations, but to the constructed dominant view of what innovation is – the technical view that links tightly innovation and progress, which creates the image that innovation and change are always good. The political analysis of knowledge creation addresses the question of what is defined as ‘good’ and what is rejected as ‘bad’, who decides and who benefits from these decisions, what supports and what stops change, and what the implications of innovation are; this analysis addresses the technical, social, political and ethical aspects of individual, organizational, and social action. Furthermore, this framework can give enriched insights into these issues, if combined with a discourse analytical approach; such an analytical framework would conceptualize power relations through the lenses of discursive formations. From this perspective, the discourse of innovation is examined as ‘hard’ scientific formation that expands its influence in taking control over social and natural world; a classic example of the field is the ‘green’ discourse on technology and innovation, an area that has attracted great research interest (Frost and Egri, 1991; Steward and Conway, 1998; Asimakou and Joshi, 2003), since it provides the arena where multiple compatible and conflicting discourses meet and shape actions with severe social and environmental consequences.

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Discussion Evaluating the knowledge management discourse All these discursive and structural transformations have impacted on the kind of knowledge that is sought and valued from the society and the business world; knowledge has acquired a great commercial importance, it is construed as the basis of competitive products, but also a commodity in itself, as it becomes the object of trade among organizations (e.g. the consultancies and the R&D departments ‘sell’ knowledge) and also the object of exchange in the labour market (knowledge workers sell their cognitive abilities and knowledge). Knowledge is seen increasingly as ‘object’ that can be traded – assessed, transferred and stored. The technological evolution supports this narrative; the ongoing research and development of more sophisticated software and databases for supporting the sharing and storing of knowledge is based on and recursively reinforces the image of knowledge as ‘object’ that can be codified in a computer language (Lyotard, 1984). The standardized practices that this discourse has created, such as databases, innovation mechanisms, learning practices, are intended to capture and control commercial knowledge. The practices that have been developed to support the organizational needs for knowledge management have been framed within the dominant ‘rationalistic’ discourse of technological progress, which has been proved inadequate to study the nature of knowledge and to address issues of its social and political dimensions. Empirical findings from academic and consultancy research report the failure of knowledge management in practice. KPMG’s (2000) report on knowledge management showed early that the actual implementation of knowledge management practices had been problematic. Companies, even though they recognize the importance of such practices and dedicate considerable resources in the implementation of related systems and practices, face difficulties in integrating the systems into day-to-day working routines. KPMG reports as possible causes the failure of organizations to communicate ‘right’ the use and the benefits from the implemented system, the lack of training and the lack of time spent over the use of the system. Essentially, the report implicitly indicates that even though the dominant model incorporates elements of the four discourses, the dominant discourse on knowledge management is performance driven. The existing different approaches offer alternative epistemological views to knowledge, but there appears the necessity for a unified understanding of the phenomenon at micro but also macro level – i.e. the necessity to address the interdependences between agency, structures, institutions/organizations and society (Hull, 2000). Most research work on knowledge phenomena in organizations responds to the challenge, which, briefly, states that the existing knowledge cannot be known in its totality by a single mind, but is dispersed in individuals, routines and activities, and distributed, in the sense that is inherently indeterminate: nobody knows in advance what knowledge is or need to be, hence firms face radical uncertainty

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(Tsoukas, 1996; Hayek, 1945). The decrease of this uncertainty becomes the objective of mainstream approaches, which are still preoccupied with the development of best practices prescriptively, and neglect the necessity to think of the emergent consequences of these practices on the work design and society. De Vos et al. (2002) analyse the dominant views on ‘knowledge management’, and argue that ‘knowledge management’ and the Tayloristic model of theorizing organizations are based on similar assumptions: (a) organizations as reified and without conflict, (b) depend on transparency, (c) recourse to codification – they instrumentalize their projects, (d) both set managerial goals, which involve the reduction of uncertainties, and this, in turn, influences the power relations in a given organization. They conclude that there are issues of conflict and resistance that are left aside in theorizing the knowledge management phenomenon, which are highlighted once it is viewed as a transformation of the Tayloristic mode of organizing. In specific, the rhetoric and assumptions of knowledge management have been subjected to critical scrutinization; ‘knowledge management’ within a performance discourse is promoting an ideal world where knowledge will flow unimpeded, and to this end advocates the significance of trust between people and between organizations. Adler (2001) goes as far as to identify a new kind of trust – ‘reflective’ trust – which will be the base of collaborations, in the knowledge economy.6 Having acknowledged the political nature of knowledge and the relation between knowledge and power, it is difficult to see how people would accept sharing freely their highly valued knowledge, and how trust will develop. In addition, by recognizing the political and social dimension of knowledge, alternative research has questioned the new order that knowledge discourse has formed and the power relations deployed around the new formation. In the ideal world of free knowledge for all, it is questioned who controls the processes of knowledge creation and who benefits from the new knowledge. The role of experts – academics, consultants, knowledge workers – in forming these processes, as well as the power that they might gain in a knowledge economy needs be further studied. The role of technologies that this discourse constructs, has been criticized regarding the social implications they bear, as critical theorists argue that they are not as innocent as the rhetoric of technological progress suggests. The technologies that are developed and put in place, such as accounting of Intellectual Capital, Intellectual Property regulations, Innovation Mechanisms and knowledge databases, etc., aim apparently to standardize these practices and develop consensus and homogeneous behaviour. Essentially however they aim precisely to control knowledge via controlling its sites: bodies and minds, structures and culture (Yakhlef and Salzer-Morling, 2000). It is a question of further research regarding the degree that this ‘body and mind’ control succeeds, together with issues of conflict and resistance.

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Managers and knowledge discourses McKinley (2001) suggests that the debate surrounding knowledge management is dominated by ‘uncritical prescription and critical abstraction’; ‘knowledge management’, seen as technologies and practices, has not yet become a power/knowledge regime comparable in scope or depth to Taylorism. However, he continues, it cannot be dismissed as a passing fad, for it highlights structural tendencies in controlling employee knowledge and creativity. To avoid the technological determinism that an interpretation of a Foucauldian approach in analysing the power/knowledge relations and the technological regimes that form bodies and souls, it is necessary to study the permanence of the new structures and practices within the organizations, as well as the impact they have on individuals; hence it is necessary to examine cases of conflict and resistance against the discourse of ‘knowledge management’.7 The question that arises, then, is why managers follow the knowledge management ‘hype’. This question has been examined from the ‘fashion-setters’ perspective; most of the research done in this area assumes that managers are passive followers of the experts’ – be it ‘gurus’, consultants, academics, etc. – discourse. It would be worth, however, questioning the other side of the phenomenon, i.e. the role of managers in the development of this ‘hype’. I have argued that the popular knowledge management discourse has been deployed around the dominant ‘hard’ scientific discourse of management studies; this discourse has constructed the ‘reality’ of an organizational world, where firms are ‘rational’ organizations that strive towards ‘excellence’, ‘progress’ and ‘improved performance’. The role of managers in organizations describes them as the ‘rational’ agents that adopt ‘scientific’ designed procedures for sense making and decision making in order to achieve the organizational strategic objectives. Successful and innovative organization is one that continuously scans the environment searching for information, in attempting to take control over the former. Following this mode of thinking, knowledge management propagates rational, well-thought decisions, based on ‘proven’ best practices. However, this image of the organizational world has been criticized for it assumes an ordered environment that can be measured and understood by ‘rational’ means. In other words, it downplays the inherent ambiguity of sense making in a turbulent and fast changing environment, and the complexity of the decision-making processes. Organizations do not stand alone as independent entities in the world; they are units of a wider system, and their actions and decisions are affected by the actions and reactions of other institutions, organizations and social phenomena at the macro level (competitors, globalization, law system, sources of information and knowledge, academia, etc.), as well as at the micro level, by perceptions, conflicts, etc. within the organization. Consequently, their actions are formed to a great degree by external – i.e. social tendencies – and internal factors – i.e. the organizational dynamics. From this perspective, ‘rationality’ is a construct; one of the ways in which organizations try to make sense, bring

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stability and move forward in an ambiguous and unstable ‘reality’. Accepting ‘rationality’ not as truth but as discursive construct that shapes frames of logic, subjects and actions, and furthermore accepting that there are multiple actors and discourses that contest each other, indicates that the reason why managers follow the suggested new practices is not simply because these are ‘rational’ and guarantee improved performance, but rather that there are issues of personal interests for each actor involved. However, explanations as to why managers follow the hype so far has allocated them a passive role; these accounts give a deterministic explanation to management knowledge, and assume that managers simply and passively follow what the fashion-setters (management gurus, popular press) suggest (Scarbrough and Swan, 2001). From this respect, accounts of ‘fashion management’ focus mostly on the diffusion process and on the actions of suppliers (i.e. fashion setters) in the development and communication of new concepts. Here emerges the paradox, since this approach is incompatible with the view that managers and organizations are ‘rational’ actors – and not ‘rationality’ followers: if managers (as representatives of the organizations) actively and consciously seek information and knowledge from the environment in order to take decisions and proceed to actions, why then do they follow dominant trends, with no guarantee for their effectiveness? Abrahamson (1996) highlights that it is a cultural phenomenon shaped by the norms of rationality and progress. As argued above, western culture and the business world are based on these two values; however, normative influences alone are not sufficient to explain the trend, hence he goes on to examine a number of socio-psychological factors (such as frustration, boredom and striving for novelty, and striving for status differentiation) and techno-economic forces (such as economic, political, organizational) that impact on forming the phenomenon. Techno-economic forces indicate that the robust techno-economic progress forms a demand for more sophisticated technologies and practices in order to respond to the newly formed needs and accommodate new technological possibilities. It is also suggested that macro-economic fluctuations impact on the need for different and more sophisticated tools and practices, in terms of either technologies and investments in capital – in times of economic ebbs – or personnel practices – in times of economic contraction. Consequently, all these forces open gaps between organizations’ actual and desired performance. Psychological explanations suggest that the phenomenon is dominant because it fulfils a need developed in a collectivity of managers; managers seek these ‘fashions’ in order to fulfil their need for individuality and novelty, on the one hand, and conformity and traditionalism, on the other. Another stream of explanations suggests that in times of despair and frustration across individuals in a collectivity, constraints and coherence in terms of behaviour are loosened up and individuals seek to reveal their sources of frustration even via unrealistic hopes. Traditional managerial roles have been defined by the dominant managerial discourse as ‘rational’; stakeholders expect from managers to act in ‘rational’

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ways, in order to improve the organizational efficiency and achieve strategic roles. In order for a manager to be perceived as innovative and progressive – as the managerial role prescribes – one has to follow the trends that promise business excellence. This however implies that managers seek knowledge not because they aim at the optimum decision, but because they intend to construct and maintain the image of a successful and efficient manager. To be an ‘efficient manager’ depends not only on the application of formal and accredited knowledge, but also on personal and social wisdom of which informal knowledge plays a part. Hence, the essence of the managerial actions belongs to the realm of politics and tactics, where managers gain consent through socially legitimated courses of action, rather than self-fulfilling, instrumental economic rationality (Mazza and Alvarez, 2000). This leads managers to seek guidelines for actions in the social structure, which provides different types of knowledge (both formal and informal) and legitimacy to their actions. The assumption that managers simply follow the prescription of the communities in which they participate (be it ‘experts’, stakeholders, managerial communities) tells a one-sided story about the emergence of these fashions, and ultimately about managers’ expectations from them. Watson (1994) takes a more subject-oriented perspective and argues that ‘flavours of the month’ play a role in the double-control problem faced by all managers; the problem of managing their personal identities, careers and understandings, while at the same time contributing to the overall control of the organization in which they are managers; hence, there arises the paradoxical phenomenon, managers being critical of the ‘fads’ and still follow them. The paradox can only be explained once we suspend the assumed managers’ ‘rationality’ and acknowledge that managers have to pursue the strategic objectives of the organization, but at the same time they are individuals with their own system of values and interests, which are often incompatible with the organization’s; yet, both drives are reflected in the choices they make. This view opens up the possibility to understand managers as political actors, who need to balance social pressures and their own interests. Jackson (1996), in exploring the impact of ‘management gurus’ upon managers, bases his analysis on Gergen’s conception of ‘saturated self’. He suggests that as the ‘technologies of social saturation’ – such as automobiles, telephone, electronic mail, popular magazines, television, etc. – develop and expand, people are exposed to much information, opinions, values and life styles that would not be possible before; in other words the networks, in which each individual participates, expand and become more complex, and consequently people – and in this case managers – become more and more aware of the multiple possibilities of what they could be and how they could act. Managers increasingly realize the relativistic and local value of their system of beliefs and values that guided their actions so far, and start reconsidering the core belief of ‘one right way’ of doing things. Consequently, they search out answers and alternative ways of actions in formal and informal sources of knowledge. The political view on managerial role approaches the phenomenon as process, in which ‘suppliers’, ‘consumers’ and society are actively engaged;

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hence, the reconfiguration of the very concepts that are implemented is suggested (Scarbrough and Swan, 2001). According to this view, managers do not simply absorb accidentally encountered information, but rather they actively search it in the literature, periodicals, mass media and their interaction with experts in the field and ‘tailor’ the suggested practices to match the specific organizational needs in a way that serves their own career and personal interests. In this political race, as mentioned, managers rely both on formal and informal knowledge; as I have discussed, networks between firms, experts and academia expand, as managers feel they need to expand the sources of valuable information and knowledge. Alvarez and Mazza (2002) present empirical evidence about managers’ expectations from this active search for knowledge (e.g. to get help with professional practices, gain academic knowledge, etc.), and observe that managers more and more tie themselves with professional groups and construct an image of themselves as members of a profession. On the other hand, these newly set links between managers, consultants and academia unavoidably transform the way each group perceives its identity and its role in the network, and the influence it has on shaping others.

Part II

Empirical

4

Commercialization and knowledge production Hydro-Carbon Solutions

In this chapter, I discuss the case of a technology knowledge-based company, Hydro-Carbon Solutions UK, its relation with the parent company Oil Co. and its trajectory through the commercialization discourse; in specific I examine how the latter has impacted on their understanding of innovation, and the subsequent related actions they undertook to support the need for new knowledge, like the commercial discourse prescribes. The research studied the discourses in two Business Groups of Oil Products, which I call Technology Group A and B, and fell under the new Hydro-Carbon Solutions umbrella. Technology Group A concentrated on the development of new fuels, whereas Technology Group B operated in the area of lubrication. The chapter analyses the formal commercial discourse that Oil Co., i.e. the parent company, constructed, and the consequences this discourse had for the Business Groups on the way they perceived their identity and activities, and on their culture. My argument here is that the articulation of knowledge within a commercial discourse brings changes in the research language game, which ultimately affect the knowledge production structures. The question that I pose here is what kind of knowledge can actually be produced within a commercial discourse, and what its value is. The discussion focuses on the strategies of the formal discourse employed to naturalize the new order and neutralize its effects, and on competing groups that struggle to keep or gain power in the new, unsettled commercial order.

The era of commercialization Oil Co. was a multinational oil and energy company. It employed more than 100,000 people and was active in more than 130 countries in the world. Until 1998, Oil Co. Research UK had been its Research and Development (R&D) Laboratories; they conducted research and supplied Oil Co. with innovations and product technology. In 1998, Oil Co. went through a radical change in strategy that led to major restructuring of the operating companies and affected the focus, the object of activity and ultimately the identity of Thornton Research Laboratories – the UK Oil Co. laboratories site – which was now renamed ‘Innovation Park’, in order to signal the commercial turn. In effect, Oil Co.

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instead of entering a merger and shutting down the research laboratories, as most of its competitors did at that time, decided to support them and created technical consultancies, which could now sell their services to Oil Co. and nonOil Co. customers; hence Hydro-Carbon Solutions was born. In other words, Hydro-Carbon Solutions, where this piece of research was conducted, was the commercialized R&D labs of the Oil Co., and its purpose was R&D and technical services. The change was definitely radical, but not sudden; the talk about the necessity to go commercial, as well as about other minor changes to support it, had already emerged much earlier, preparing the – structural and emotional – ground for the radical transformation. The reason for this change is explained with reference to the powerful trends of globalization, which set knowledge as a key resource, and the pressures the latter created in the external environment, both the market and the competitors. However, the official documents, which communicated the objectives and the process of change, made no reference to competitors’ actions; the reason and route of change was constructed around the needs and demands of the ‘customer’: the customer became the new driving force of all Oil Co. decisions and actions from that point onwards. In the Newsletter of Oil Products – Research and Technical Services, which was first edited in August 1996, the need and the objectives for this change were clearly stated by the Head of R&D in Thornton Labs (October 1996, no. 2) as: When we see the continuing pace of change in Chemicals, when we read of the proposed [. . .] merger, we can be sure that the pace of change will not lessen. We can be sure that whatever organizational form we have today, it will have to change and evolve to meet customer needs in the future. We can be sure that however we worked in the past, it will need to be different in the future as our customers change. (emphasis added) ‘Change’ in this quote is represented as inevitable and driven by external forces – i.e. the changes in the customer profiles: customer is being placed at the heart of the changes and this reality is being presented as the only way to lead the company to the future. The current organizational form and work practices are being abolished without precise description (whatever . . . however) and reason as inappropriate. Nothing of what Oil Co. had been doing so far was good enough to serve the Customer. ‘Customer’ becomes the key word behind Oil Co. changes: it is encountered in all justifications and explanations for the transformations. For example, in the Newsletter (December 1996) the necessity for change is constructed as a response to customers’ feedback: According to its customers, RTS [Research and Technical Services] has considerable more potential than is currently being used. The average ‘satis-

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factory’ score awarded to RTS by the Operating Companies, could easily be turned into ‘excellent’. There are no doubts about the quality of RTS work, which many customers rate as good, compared to other suppliers. What must be changed is the way in which RTS cooperates with its customers. They want RTS to develop closer contacts, intimate involvement, appreciation of financial and economic implications, understanding of local conditions and sharing of responsibility in implementing integral solutions. This excerpt ascertains that the distance from point = ‘good’, which was achieved by the RTS doubtless quality of work, to point = ‘excellent’ could only be reached by bringing RTS closer to the customer; the customer-focus language introduces the key words and establishes the rules of the new commercial game: closer contacts, financial and economic implications, local conditions, sharing responsibility for the implementation of solutions. The commercial language signalled a change in the established power relations in the research side of the business, where the customer now would indicate the nature of the research that should be conducted, and hence the Operating Units started acquiring a significant position in the new organization, for they laid in the interface with the customer. The ‘financial and economic implications’ of each project becomes a considerable variable for funding research, the ‘local conditions’ open up new possibilities for business in a global environment – as the globalized times and, whence, Oil Co.’s commercial route prescribed – and the ‘sharing of responsibility’ suggests a new work design and teamwork concept. The ‘vision’ is captured in an Oil Products Manager’s words: Oil Co. Research should become a ‘one-stop centre for fit-for-purpose solutions’. The value of RTS was not, at least explicitly, doubted; however, the aims of Oil Co. are clear here, to keep the knowledge resources they had, and make them work for the market rather than for the scientific ideal of knowledge. The, at that time, CMD Chairman’s view on innovation was clear (the Newsletter, October 1996): What must be achieved, however, is for the period between what RTS does and putting it into practice to be made as short as possible. Endless polishing can delay the process. Just pass them on what you’ve done and tell them to try it out. This statement sets clear short-term objectives for innovation, and at the same time it implies the dissatisfaction of the ‘slow pace’ of research so far, which does not support the new ‘aggressive’ and market-oriented focus that the business decided to adopt. The Chairman continues: I want to dispel from people’s minds the idea that we can manage without technology and that we haven’t got any funds to spare for innovation. That’s a fairy tale! But here too we have to count the pennies and make sure we get value for money.

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The statement also addresses the reactions of scientists at that time, i.e. their concern that in the new organization there was no place for technological research and innovation. The consequences of the short-term objectives for the organization and research are explored later; at this point, the statement begs the questions (a) why a rich company like Oil Co. had to ‘count the pennies’ in regards to innovation, especially when the research structures until that time had served them satisfactorily and (b) what the implications of this tight financial control over innovation would be. The rationality of cost-efficiency is not sufficient to explain this argument, which had indeed unexpected consequences. The Head of R&D at Thornton Labs continues: We have a choice. We can look back with regret. Or we can look forward for opportunities and seize as many as we possibly can. We will do this by seeking out and building on success in solving our customers’ problems with the most appropriate technologies we can deliver – and in a competitive world that’s often the best. ‘Change’ is articulated within the same web of relations with ‘progress’ and ‘prosperity’; hence, resistance is rendered pointless and unacceptable. The offered choice was not really a choice, but a rhetorical device used to describe any resistance to the forthcoming change as futile and ‘pathetic’, and to encourage employees to embrace change as positive, and as the only accepted attitude that would turn the organization successful in a competitive world. It also establishes a clear and direct link between solving customer’s problems and organizational success – hence the strategic framework, from within which the expected technologies and innovations should be developed, was set: ‘problem solving for customers’. The analysis here points out a war language, employed together with a number of rhetorical devices, as strategy for invading the established scientific order, and changing it. It becomes explicit in the formal talk, that Oil Co. entered the commercial game determined to make commercial and profitable use of all the ‘knowledge assets’ that existed across the organization; from this radical strategic turn, the most valuable asset, its experts could not remain unaffected. The turn translated into a reconceptualization of the customer needs, which opened up opportunities for growth and development for the new Hydro-Carbon Solutions, and the search for a new commercial role and identity for the technical experts, who until then had been peacefully conducting ‘interesting’ instead of ‘marketable’, technological, instead of commercial, research. So, for Oil Co. it was a question of re-inventing itself and the business, in order to stay competitive – and ultimately to aim to take the lead in the energy market. In October 2002, a senior scientist from Technology Group A, with 16 years of work experience on site, reflects back to the time of transformations, and in his talk the formal arguments and rationale for this commercial move emerge still vivid:

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and since about six years ago . . . I’ve never actually heard us being described as a research organization the past six years, we’re being described much more as a technical support organization . . . there was a big change within the oil industry in general, ehmm, whereby there were a lot of mergers, . . . ehmm . . . now, when all those mergers occurred they were always getting rid of the laboratories, . . . now, Oil Co. was different from most other oil companies, because we didn’t enter a merger and yet we still have this fairly expensive laboratory, so we took this alternative route, which is we amalgamated all our technical areas, where that be for product laboratory here or our refinery and manufacturing people in the Hague, and we put them under the title ‘Hydro-Carbon Solutions’ and as I said instead of getting rid of jobs in the technical area, what we said was that those technical people can sell services to non-Oil Co. companies . . . so in order to keep our own R&D efforts well funded and have a reasonably large pool of technical people, we could, if you like, subsidize that route, being allowed to sell technology to non-Oil Co. areas. (emphasis added) It is interesting to hear how the scientists embraced the need for this commercial change, because instead of losing their jobs, as it happened in other oil laboratories, they had the opportunity to keep working in the prestigious and expensive site. However, what they could not accept was why ‘commerciality’ brought the end of technological innovation: why they were not a research organization any longer, but a technical support consultancy. Against all expectations that the discourse on commercial knowledge might have raised, knowledge, expertise and innovation were not treated as precious resources, and did not acquire a high status in the commercial order. And here is the beginning of my investigation in discourses: could it be that the commercial discourse supports innovation only in talk and not in practice? And if this is the case, then what are the implications for our understanding of innovation and knowledge?

The current structure Oil Co. was a group of numerous companies, which operated in 140 countries and territories around the world, and mainly engaged in the following activities: exploration and production, gas and power, oil products, chemicals, renewables and other activities. Hydro-Carbon Solutions provided Oil Co. and non-Oil Co. customers with research & development and technical services, and consisted of six main business portfolios; the Business Groups engaged with technical and recently with commercial aspects of the business activities. Both Technology Groups A and B fell under the ‘Oil Markets and Technology Resources’: Technology Group A worked in the area of fuels and Group B in the area of lubrication. However, the exact structure of Hydro-Carbon Solutions was a mystery for all employees and visitors, since it kept on transforming; new alliances, which were taking

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advantage of the globalized nature of activities, allowed the space for experimentation, whilst they attributed distinct identities to the Business Groups. In the year I spent on site, the organizational chart changed at least three times. Hydro-Carbon Solutions was determined to try out all possible combinations and business concepts before it settled with the most flexible and profit-making structure. Hydro-Carbon Solutions’ activity changed into ‘research and development’ in the broadly defined ‘energy area’, instead of ‘oil-based products’, and they actively started seeking business opportunities, which would keep themselves and the parental Oil Co. competitive in the future not necessarily as an oil company, but, having broadly defined the area of activities, in the energy market. From this radical change into Oil Co.’s identity and business interests, we should expect that the support of innovative ideas and research would be on top of the business agenda; and indeed, innovation was recognized as the driving force into the future, or at least so emerged in the formal documents and talks. However, some senior scientists expressed some reservations regarding the nature of innovation that was supported in the new order. The powerful commercialization discourse for making use and profit from all assets, combined with the ‘market driven’ vision, changed the relationship between parental Oil Co. and Hydro-Carbon Solutions: instead of the Technical Groups serving exclusively the parental Oil Co. Petroleum Company, now the rhetoric placed the focus on the customer, who might or might not be Oil Co. Each Business Group became now responsible for its financial achievements, and they were drawing their own policies and strategies, since now parental Oil Co. funded their activities only on a customer-based relationship. This transformation changed the rules of the game: it made the Business Groups reconsider their identity and position towards Oil Co. Now the Business Groups had to go out and actively expand their businesses (which now included products and services) in order to satisfy customers in a competitive environment. Without having the secure funding from the parental company, being commercial became for the Business Groups a question of survival. A Knowledge Creation Manager in Hydro-Carbon Solutions comments for the Newsletter in March 2000: I quite agree with his [Hydro-Carbon Solutions President at that time] comment that you have to close down your Business Group if it’s not performing well. We now have about 40 BGs [Business Groups], which is really quite a lot. A process of natural selection would be healthy. When you sow seeds in your garden, you have to pull out plants that aren’t thriving to make room for the ones that are. To a certain extent the same applies to us. The competition between the Groups is introduced here wrapped in a metaphor borrowed from the natural world; following on the analogue, its legitimization is gained by appeal to the laws of natural evolution – which are well accepted as

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the ultimate truth, and hence are unquestioned outside the scientific community. The strongest would survive and take the space of the weaker one – one of course could question why the laws of the natural world should hold for humans, as well. Nonetheless, this resulted in a radical change to the nature of relations between the Business Groups that used to work together, and the rules of knowledge sharing – since now knowledge became ‘the object of trade’, and hence could not be freely available. In 2001, in a further step to optimize the benefits of a flexible and customerfocused structure, Hydro-Carbon Solutions was redesigned in ‘Market Sector structure & associated Business Network’. The new structure was promoted as best practice, because it created a ‘wider technical, commercial and business support community in Hydro-Carbon Solutions’. The Vice-President of Marketing Development and General Manager of the Innovation Park, at that time, identified the objective of the change in turning Hydro-Carbon Solutions to playing as ‘one big orchestra, instead of separate bands’, the Vice-President of Marketing and Sales stated ‘the name of the game is focus, focus, focus’ and the Vice-President of Engineering and Process Technology framed the new rationale ‘the question is no longer: why are you going to do this, but how does it fit in the Strategic Marketing Framework [SMF]’. It is clear that the arguments of ‘autonomy’, ‘independence’, on which the rationale for Hydro-Carbon Solutions had been constructed, had created individual(istic) technical consultancies, which were striving for business survival. Nevertheless, two years later a Technology Manager from the Technology Group B, with 32 years in Oil Co., commented ‘Hydro-Carbon Solutions is an enigma, doesn’t really exist, almost everything we do is for the Group [Oil Co.], and that’s how it should be.’ The SMF still had not managed to break down the (actual or experienced) dependence of the Business Groups upon the parental company. Concisely, the new model was based on forming Sector Business Teams, which would represent all business units that played a major role in that particular Market Sector. Consequently, the dependence of the business groups’ decisions and actions upon the market increased and, given the new customerfocus culture, it allocated a central role to the Market Sector. The power relations were changing, whilst the rhetoric that wanted the Business Groups ‘autonomous’ to take decisions for their business activities and their survival soon lost its gloss; under the new structure the business groups got even tighter controlled, not by the customer, but by the Market Sector that gathered all relevant information. We could suspect now that this change, which implied a transformation in the established power relations, would not go uncontested by the business groups. Technology Group A in transition Technology Group A consisted of 114 employees in four locations across the globe; approximately 70 worked at the Innovation Park, UK, where the main Research and Development (R&D) work was conducted, whereas the rest of the

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sites were operating as customer centres. Technology Group A quickly adapted and followed admittedly successfully the changes that the turn towards the commercialization of knowledge imposed. ‘Successfully’, in this case, is defined by the rules of the new commercial game: Technology Group A entered actively in the market and secured customers, projects and resources that guaranteed its survival in the short run. In times when memories of the downsizing that followed the commercial turn and restructuring were still fresh, and when further downsizing was about to be announced, Technology Group A felt very confident for its position in the Oil Co. picture. Furthermore, the financial and business success was such that Group A acted as exemplar or rather benchmark for the rest of the groups at the Innovation Park, who tended to compare their practices with it. It is interesting to note here, that during the fieldwork, the staff of Technology Group A never compared their activities and practices with other groups at the Innovation Park, but with Business Groups across the globe; this implies how they were proud of their culture and business achievements, which distinguished them now from their exThornton colleagues. Technology Group A seemed to have early learnt the rules of the commercial game and actually used them efficiently for its economic benefit. In its discourse commercialization was constructed as a question, not of ‘progress’ or, in a milder language, sustainability, but of ‘survival’. In this new world of words, the Business Group had to go out and get customers, or it would vanish. With this aggressive and menacing representation of reality, the only option for the people of Technology Group A was to embrace and believe in this change. there’s been a change in the past four years, towards, eh, as we became more commercial, we moved from working only for traditionally Oil Co. customers and the emphasis changed on third parties utilities and the realization that it’s been that to survive we have to grow our own different revenue streams. (emphasis added, young scientist with four years in Hydro-Carbon) Five years after the transformation, and the people of Group A had no doubts about the importance of the change; effectively, commercialization was constructed as the only way to go, and it was accepted by the staff as such. The following senior scientist with 31 years at the company reflects back on the reactions of people at the time of change; his talk explains the concerns about the new task that scientists had now to undertake and especially his frustration for turning from a scientist, in its traditional sense, to salesman: I:

I think actually that there was a great will to respond to it positively, when you hear about a big change like that, people could . . . be antagonistic to change, but in general it was not an antagonistic change to that . . . change of culture, there was a number of people – I suppose I was on of those – who were slightly more sceptical of the new direction, it was a new commercial

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direction, as I explained to you, we used to do things just for Oil Co. and then we have to think of how we can sell things to anybody we know. R: And why were you sceptical about it? What didn’t you like? I: Why didn’t I like it? Because that was not what I was trained for, it was not what I was used to do, and I suppose I am getting too old to change . . . yeah, but most people responded better than I did. Technology Group B in transition Technology Group B consisted, at the time of the fieldwork, of 230 employees in five locations: the majority worked at the Innovation Park (80 people) and USA (100). Technology Groups A and B shared much of the recent history, and the structural and cultural changes that followed the commercialization turn. However there were some differences as well, as to the way the two groups responded to the call of commerciality, which stemmed from their particular understanding of the new order and the way they perceived themselves and the possibilities to act in it. Similarly to Group A, the employees did not doubt in principle the need to be commercial; being commercial was understood as a route to job security, since the business would not be dependent on the needs for innovation of a single customer. Commercialization was largely accepted as the rational and ‘intelligent’ way of surviving in a fast moving environment, which would allow the organization to make full use of its intellectual assets. The acceptance of the new commercial rationale for running the business is evident in the talk of the following Technology Manager with 32 years in Oil Co.: I think people, people saw, I certainly saw it was the right way to go initially . . . because at that time when you move into products and product divisions you take the stance that you are viewed by assigning how much time you spend on a particular project, that’s fine, if I’m assigned 100 per cent of my time on a specific project you might as well pay someone with far less qualifications than what I have, because then you are dictating what they should do; I mean you should only ever dictate 80 per cent of a true scientist’s time because then that leaves 20 per cent to think, and that’s really what you are paid to do, it’s to think . . . that’s only my own personal view, and I’m sure it’s completely out of the standard modern management literature. Nevertheless, the reality here was that the people who were in charge to drive the new organization to new business challenges were not as effective as in Technology Group A. A ‘cynical’ senior scientist with 20 years in Oil Co. comments: one of the disappointment for me, there was a mixed reaction to that initiative, some people here said that it was a good idea, it obviously makes

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This interviewee, throughout the interview, expressed serious reservations as to the consequences the commercialization turn had for the Business Group and the new status of research and science in the new order. Commercialization opened up opportunities for new research and businesses, however an historical coincidence, i.e. in this particular time some of the people in key positions lacked the essential entrepreneurial skills, stopped the business drive. As a result of a less aggressive activity, when compared with Technology Group A regarding the ‘going out and get customers’ imperative, Group B was still going through a time of radical transition in terms of organizational structure (i.e. the creation of Global Lubricants) and jobs (the threat of downsizing was very real), which increased the budget pressures and the levels of anxiety. A member of the team that was set up to bring about the structural change identified the reasons for the restructuring with the low business performance of the Technology Group: ‘old defined strategy, poor execution, not enough customer focus, not enough emphasis on operation excellence and structural cost reduction, so it is a rather sick business’. The objectives of the restructuring were to give the business the essential for any commercial organization customer focus and a dynamic business direction, which the Technology Group so far had failed to reach under the current structure.

Consequences of the commercialization discourse As expected, the force of the commercialization discourse and the consequent structural changes could not but affect the structure, culture and identity of the Business Units, as well as the employees’ identity. Even though the groups experienced some of the transformations in a similar way, however, the routes of development for each group were different. New activity: ‘research and development and technical services’ well, that’s [i.e. the name of their activities] ‘research and development and technical services’ well, we do, we do ‘Development and Technical Services’ we don’t do research; research is when you investigate something for the purpose because it might be interesting; development is when you are doing something because it is interesting, or you hope to get a product out of it; technical services is to maintain the quality of the product, so, clearly . . .

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we are not going to be too fussy, we don’t quite do research, it is a very much less payment out of it than it used to be. (emphasis added) A senior scientist with 31 years in Oil Co. gave above a clear description of the nature of the current activities they were undertaking. Research is bitterly recognized as an expensive activity that does not match with the commercial direction – an expensive activity that does not immediately return the money from the investment. The new Business Groups were not parts of a Research Centre, in the form that Oil Co. Research UK used to be. The turn towards commercialization changed the nature of the activities from long-term research programmes to short-term development projects with clear commercial objectives, as the formal commercialization discourse directed them. The fundamental difference, as perceived by the senior scientist, was that ‘Development clearly focuses on developing a better product rather than on understanding the theory that supports it.’ In other words, development, as the main activity of the new Business Groups, was in agreement and served the purposes of the commercial turn Oil Co. was taking. Beyond the first reaction that ‘old people don’t like changes’, we should pay attention to the objection the scientist raised: it is true that senior scientists were not entirely happy with the commercial turn, but not only because they did not want or they could not change. Senior scientists had accepted the necessity for commercialization and the benefits of it. Their objections, however, were concentrated around the notion of ‘research’ and the impact of commercialization upon it, and upon their role as scientists. The main concern of the older scientists was that they could not see where research fitted in the new commercial direction – unless ‘research’ was re-articulated within the new web of relations, which imposed the commercialization discourse. New object of activity Technology Group A: ‘Specific fuels instead of a Mars bar’ A change in consumers’ profile and the perception of their own needs turned fuels to a commodity: you get at the stage where people are going to the Oil Co. petrol station to buy a Mars bar and say ‘I will fill it while I am there’, rather than ‘I am going to fill my car and I will buy a Mars bar while I am there. This means that Technology Group A had to reconceptualize what their main object of activity was – because ‘you don’t make money out of commodities’. The new object of activity for the group had to be ‘special fuels’ instead of ‘cheap fuels’; hence they chose to use their expertise to differentiate substantially from other competitors’ products. The members of Technology Group A

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commonly agreed that ‘specific knowledge’ rather than ‘fuels’ was their main commercial product, and also their key resource. This had clearly an impact on people’s understanding of the nature of knowledge, but also on the practices built around to support its creation, and also to protect it from leaking outside the company’s boundaries. The development of specific fuels needed the use of scientific expertise and knowledge: the rhetoric gave scientists the grounds to ‘remind’ the commercial organization about the value of research skills in the new order, and to use further the arguments for claiming their ‘right’ to longerterm research, which so far had been excluded from the intensive commercialization and formal discourse. Technology Group B: ‘Lubrication instead of lubricants’ On the other hand, Technology Group B had a different story to tell. A technologist with 17 years in Oil Co. comments: well, I think with lubricants they may be trying to move away from the traditional business of supplying products, supplying oil and grease to people, and looking more into supplying services, sort of the marketing phrase we have is selling LUBRICATION, not lubricants, in other words . . . helping a customer problems solve, perhaps using lubricants that can improve the efficiency of what somebody is doing. Technology Group B was changing the way it perceived its object of activity too, and this made them reconsider the nature of their business and how to expand into other areas; defining the object of activity as ‘lubrication’ signalled the importance of intellectual capital in the new order and the operations are oriented towards services rather than research, as it had been the case so far. From this respect, the discourses of both Technology Groups were similar, and both constructed to serve the commercial turn and the customerfocus orientation. However, together with the new ‘marketing’ driven view of their activities, the old view that articulated the object of activity as the formulation of lubricants was still active and dominant; this old view constructed the nature of the business as a specification-driven activity, of which the customer is not the end user (the car driver), as it is largely the case for fuel products, but the engine manufacturers, who set the specifications and the characteristics of the new lubricants, in order to be compatible with the requirements of the new engines. From this perspective, and in spite of the large number of products available (approximately 5,000 varieties of lubricants as opposed to three to four main fuels), which would lead one to think that the object of activity itself allows infinite product innovation, the possibilities for innovations were limited by the dependence of the product upon the customer: simply, a lubricant is useless without the appropriate engine. The following excerpt comes from the interview with the Innovation Manager:

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what we do mainly here is to come up with the recipes of the lubricants, because lubricants business is a specification-driven business, the people who make the engines will decide what performance lubricants should have and they . . . they tell us to make sure that lubricants pass a series of tests for them to approve it, so a company like Ford for example, there will be a number of tests they will say lubricants have to pass in order for them to approve one of our oils, and all the major car and track manufacturers have these specifications that lubricant has to meet, but because their engine are always changing, their specifications change quite frequently, probably every two or three years, so for many of our oils we have to keep updating the recipe to meet the specifications, which is quite a different situation to fuels. It is interesting to compare these two last excerpts: on the one hand the technologist lines up with the commercial discourse and the business opportunities that it opens, on the other hand the Innovation Manager provides an account of a mature business, and constrained by the external environment business, where possibilities for innovating and expanding in new areas are limited by the same nature of the activities. A possible explanation for these conflicting views would be that the Innovation Manager had not ‘seen’ the possibilities that the ‘new’ object of activity offered yet, and the account he provided drew from the way the business was driven so far. I would suggest then, that what we observe here is a clash of discourses, from where scientists could choose their arguments each time, without being clear yet what the dominant perspective was, and hence what the legitimated way of seeing things and acting were. New identity and the argument of autonomy All the structural and cultural changes could not but affect the identity of the new Business Groups, which now gained an independent and distinct identity, cut-off from the overshadowing and paternalistic identity of Oil Co.: well, we’ve gone from a research and development organization, we only had one customer, that was Oil Co., and it did us all work, and basically at cost, in the past five years we transformed ourselves in a fully commercial organization, where Oil Co. now is still an important customer, but it is not our only customer, so we, [Technology Group A] gets of a third of its revenue, from, a bit more than that, yeah, maybe 40 per cent of its revenue from Oil Co., sorry from Oil Co.’s fuels global business, but the rest of its revenue comes from other Oil Co. customers and other non-Oil Co. customers, so we have a completely different customer base, and we are a much more commercial org . . . we are a commercial organization, and, we . . . I think we now have an organization, which is based globally, so we have resources here in the UK, in Hamburg, resources in Singapore, resources in Houston . . . so again, that’s . . . we’ve gone from a UK based

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Hydro-Carbon Solutions was not Oil Co.’s research laboratory any more; its business units had their own customers and offered a variety of products and technical services. Oil Co. remained the main customer and hence kept to a great degree its power on determining the activities and shaping the perception of the needs of the Business Group. Hydro-Carbon Solutions does the most of its work for Oil Co., so a lot of the things that Oil Co. needs, we need therefore in order to help, but there are some things that we need, which we do not intend to do for Oil Co., and therefore we need more knowledge for that sort of things, on the business of understanding outside customers’ knowledge and that sort of things and developing technologies which are outside the periphery of interest of Oil Co., even though I would say we are not terribly successful in doing that. The senior scientist from Technology Group A here, implied the change in this relationship of dependence, and the problems with living independently, as the Business Groups now had to undertake new commercial functions. Some older scientists with critical views were more precise in terms of the degree of freedom that they could now enjoy; independence and autonomy are scrutinized here and rejected as fads: I know I am not independent [laughs], because if, if larger Oil Co. says to my management that we should do something then my management says even if it believes it is wrong, it comes down to the Group as Oil Co. views, how can you be independent. (technology manager in Technology Group B) However, a new value emerged – a value that had not been a feature of the relationship with the parental company before; and this is ‘trust’ built in professional relationships: ehmm, certainly more responsible, I don’t know about more autonomous, because we still have to work with people in the centre, and there is still a lot of . . . we must tell the same story that people are telling in London and we do make visits joint together or we work in teams together with the people in London, but we are certainly trusted more to either set up meetings directly with customers and ourselves or people attend these meetings and be equal partners with the people in London. And later the same scientist from Technology Group A described this relationship of ‘control’ rather than ‘independence’ as:

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because we have a problem here with the fact that [Hydro-Carbon] Solutions wants to become almost truly independent and sell its technical consultancy to people other than Oil Co., but it hasn’t been given the right framework to do that, it is still, although we would like to be fully commercial, Oil Co. controls us and says ‘oh, no, you can’t have these customers and you can’t have these customers, you can’t sell these products’ and it’s like the business can’t really operate like that. Nevertheless, the changes in the relationship with the parental company gave the Business Groups a degree of independence, and the possibility for each of those to create a micro-world within Oil Co. cosmos, with its own values and beliefs, and with a distinct identity and culture, of which they take pride. The parental company was now almost unanimously described by the interviewees as ‘old fashioned’, ‘conservative’, ‘slow in decision making’, ‘risk-averse’ and certainly ‘non-innovative’, and generally was used as scapegoat for most types of problems the Business Groups faced; the Oil Co. culture was contrasted with the new identity and culture that the new Business Groups developed, which was claimed to be informal, friendly and ‘innovative’, and of which the greatest asset was ‘people, people make the Oil Co. Group what it is’. New commercial culture Traditionally, Oil Co. Research UK had been staffed by scientists of high academic calibre, recruited for their scientific qualifications, mostly from the universities of Oxbridge; the site was called ‘Cambridge of the North’. It used to have a very strong academic culture, sometimes described as ‘cliquey’ or even snobbish from the ‘outsiders’ – e.g. engineers, lab technicians, administration staff, etc. Hence, Thornton Labs had the reputation of an ‘Ivory Tower’ or as some other interviewees described, it used to work as a university, conducting ‘blue-sky research’, i.e. research without necessarily direct commercial interest and profit return in the short run, for the sake of developing new theories and ‘see where they fit in the picture’. The senior scientist from Technology Group A with 23 years at Oil Co., in the following quote again demonstrates the differences between concepts of ‘research’ in the old days and in the new organizational order. It is important to note that this scientist again did not doubt the significance and necessity for the commercial turn, but the nature of the research, since research in the older days is not suspended as useless and irrelevant, only that its applications were not evident immediately. when I first started here, we used to do a lot . . . what you could call, well it is long-term, well it is long-term research, research that you couldn’t necessarily see an application for it, at least immediate . . ., I mean it is much more academic type of approach, we used to ask questions with scientific interest like WHY this happens, we don’t ask that question now, we usually

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Clearly, those people who were excluded back then from the privilege of doing scientific research, and the benefits that this returned, had different views on the culture back then, and the new commercial culture; an engineer with one-and-ahalf years in Technology Group A comments: I think currently it is changing very much, and I think that the original Oil Co. culture was very much, here in Thornton, was very much . . . a very secluded culture, it was a research organization here and people felt very separated from the rest of the world, and they felt very much that they were doing these projects that were for their own good and their own interest pretty much, but there was very little view of the world around of what the research project was actually aiming at, what would be done with it, how we would ever make money out of it, we were just given a budget, we were a cost centre, and we would get on with it, we would finish as much of the budget as possible because if you wouldn’t, then next year you would get less, but this is really changing in the past five years in becoming a commercial organization, where now we need to prove our existence, we actually need to go out and find customers for our projects, for our knowledge, for our products, and, that has meant also that the whole attitude here on site has to change, and significantly is changing, people see a lot more now, that it is not . . . just the project or the product that it is important, but it is also important to have a customer for it and making it useful. (emphasis added) This scientific ethos of the community, characterized by curiosity and analytic thinking, however essential in all types of research, could not fully support the turn towards commercialization, which necessitated new values and a new mode of thinking. Technical skills, teamwork and the informal/collaborative culture were still essential parts of the new culture, but the commercial turn needed to change the priorities and the focus of the activities; in other words, it commenced a new ‘language game’: new words were introduced and gained importance in the everyday talk, whereas others were used to make clear the distinction between past times and now. Where ‘science’ had been the end of research, now was replaced by ‘customer’ and ‘delivery-time scheme’. The traditional way of doing research had been characterized as ‘blue-sky research’ and it did not seem to fit in the new culture, which was driven by the new values of ‘profit’ and ‘cost-efficiency’. A Resource Manager of the Technology Group A, with 12 years in Oil Co. comments on the current culture: the culture is one I think of . . . commitment to delivery, and there is a good, in my opinion, good team working culture, so people try to be cooperative

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and help each other, ehmm, . . . I think there is a culture of delivery results, results matter and we have a quite good culture in terms of having processes and procedures ehhh, so we try to manage things, rather than doing things chaotically, so planning . . . planning is a very important activity and . . . I would like to think of it as well as quite an open and honest culture, so that the . . . I certainly feel that the managers don’t dictate to the staff what it has to be done, where they’re there to try to coach and advise and facilitate, rather than instruct . . . ehm, I think as well . . . certainly my staff are very good at telling me what I am doing wrong, which is a good thing . . . that is locally within the Business Group, I think the culture is . . . I think this is a fair description of the culture, I think we also have a quite good record now of being innovative, in the way we are doing things, I wouldn’t say that we are brilliant, but we certainly have improved over the last few years. (emphasis added) And he adds: I guess I didn’t mention customers, we are very customer focused in our culture . . . and . . . so . . . the work we do . . . we try and get very clear in our minds what the customer requirements are . . . and we . . . we deliver against them, so you know, in that sense we, probably having the customer focus is, I would like to think, is very important for the whole organization, it is certainly important within [Technology Group A] . . . so we, as well as getting customer requirements clear and deliver to those, we spend a lot of time, once we finish a piece of work, going back to the customer, saying ‘well, were you satisfied with that work, how can we ever improve what we did for you’ all this sort of things. (emphasis added) This quote, even though it could be contested by many members of the Technology Group, as to the meaning of this cultural image that it promotes, it clearly draws from the commercial discourse that drives the Business Groups actions: the Resource Manager was conscious and clear about the new directions the organization had to drive to, and he promoted this image when asked by the ‘intruder’. The excerpt is loaded with the new values that recently emerged and changed the way things were done: ‘teamwork’, ‘delivery results’, ‘planning’, ‘innovation’, ‘flat, non-hierarchical relationships’ and ‘continuous improvement’ were the new key-words that shaped the dominant frame of logic. A contested area, i.e. ‘manage instead of doing things chaotically’, was criticized by engineers as a remainder of the old scientific culture, and by scientists as a borrowed value of the oldfashioned Oil Co. culture, and in both cases it was identified with an obstruction to ‘progress’, as articulated within the commercial discourse. What is striking is that, in the discourse of the Resource Manager (and in common with the rest of the management team) there were no cues of values from the previous scientific culture; it seems, then, that the new management of the Business Group was very

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clear as to what the commercial identity meant and what they tried to achieve. The role of innovation was mentioned, indicating that it found its position in the managerial talk, and hence, in some sense, in Technology Group A life. The following young scientist and team leader with seven years in Oil Co. explains further the consequences of commercialization upon research and the significance of innovation in the commercial culture. Innovation is described as the part of the past that the Business Group should have kept, and which the commercialization turn vanished – to realize only recently again its importance and to make a conscious turn to support it. Furthermore, some negative aspects of commercialization are mentioned, as they affected everyday life: the intensive pace of ‘going commercial’ also meant a nearly obsession with ‘justifying’ – ‘justifying what we do, justifying what we spend’ – and ‘ranking’. Everything was measured – expenses, activities and people – and translated into numbers – the commercial language. However, this was considered normal in the new order, and its negative implications were neutralized by the rationale of commerciality – for the new Business Groups, this is how commercial organizations act. and from the minute I joined over three to four years after that all these [structures of fundamental research] have vanished, and we have started to look back to that, the innovation side of what we do is starting to take us back to developing new ideas, but for a while we have been very focused on delivering and it’s the ‘going commercial’, it’s the ‘justifying what we do, justifying what we spend’, you know everything we do has a customer now, and we have to get them to score what we do and they rank us, we get customer satisfaction feedback, we’re very much a service provider now, as opposed to this kind of ‘Ivory Tower’ research institute. (emphasis added) New work design and ‘teamwork’ At the Innovation Park, the work had always been organized as ‘teamwork’; good research is in principle a team-based activity. Scientists used to work in one or two projects, and each project employed up to 15 people (scientists and lab technicians); a senior scientist was responsible for up to five technicians, and there was one manager responsible for the whole project. By the nature of the work, scientists and lab technicians had to interact personally and face-to-face on a daily basis, since they were working in the same physical space, and their work was closely interdependent. Even though the culture had always been informal, the hierarchical relationships were clearly structured, as prescribed by the rules of the scientific language game. Technology Group A At Technology Group A, this work design had been described as highly individualized (‘individual silos’) and a new form was introduced in order to reinforce

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teamwork and the benefits from it. A Resource Manager, with 24 years in Oil Co. explains below the perceived ‘problem’ of the traditional ‘teamwork’: in the past there was a lot more, eh, of what was called ‘individual silos’, silos of one or two or three people that worked on a narrow area and they only worked on these areas, we, we made a deliberate policy, about four years ago to break the wall of these individual silos . . . we also eh changed from, effectively everybody had their own projects, we changed into a small number of project leaders managing very big projects, which meant that people work on lots of different things, rather than always just working on one area, so it was a deliberate transition to increase flexibility . . . and to get involved with awkward people [laughs], well I don’t know. (emphasis added) The rationale finds legitimization in the commercial discourse, where the value of ‘flexibility’ drives the actions. The problem is not that the previous way of working did not qualify as ‘teamwork’, but rather that ‘that’ teamwork was not flexible and cost-efficient. To achieve the optimum use of the knowledge and skills in relation to time, the Technology Group was structured in a rather flexible form, following a matrix structure. The work was organized in project teams that run simultaneously; each project employed a number of scientists and technicians, and was coordinated by the project leader. Each employee was involved in two to three projects at the same time and one could be project leader in one project and team member in another. This implies that the roles of superior/subordinate were not fixed and did not bear any power outside the project. In addition, given that not all the staff were located at the Innovation Park – there were also sites at Hamburg, Singapore and Houston – the members of a project did not necessarily meet in person to complete the tasks; the work was designed in loosely dependent parts, which allowed each member to complete their part in predetermined time, without being constrained by the other members’ work completion. The employees’ skills and knowledge were organized in skill pools, from where they were retrieved according to the needs of each project. However, older scientists were not convinced by the rhetoric of the rearticulated ‘teamwork’. A senior scientist with 16 years in Oil Co. comments: well, the management here always tell us that we work much better in teams now, but I am not sure if I believe that, because I’ve always worked in a team, since 15 years ago, the structure of the team has probably changed a lot ehmm. And he continues, by expressing his concerns drawing from a scientific discourse about commitment to ‘research’ rather than commitment to ‘customer deliverables’:

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Further restructuring and stretching of the concept of ‘teamwork’ resulted in restructuring what a team included. As explained above, the Business Groups were now structured around the Market Sector, and they were supposed to work together on identifying and satisfying customer needs; at the same time the Market Sector acquired increasingly more authority and power from being at the interface with customers. There started emerging a competing relationship, where the two groups struggled over ultimately controlling the business. As the Innovation Manager commented, ‘before the Business Groups did their own business; now they are not Business Groups, they are Delivery Groups [laughs]’. The new structure and the concept of teamwork had some inherent flows, as they assumed the consensus of all parts to run the business, disregarding their own group interests. Whatever the case might be, ‘commitment’ and ‘teamwork’ are two key concepts of the new order, and hence are worth further reflection.1 Technology Group B For Technology Group B things were slightly different; the business was organized in two main divisions, the industrial and the automotive lubricants. Each division was supervised by a resource manager, and was split in further product areas (industrial, hydraulics, greases, etc.), in which a technology manager was responsible for the technological side and innovation needs of the area, and was working closely with the marketing people in London. Whereas in Technology Group A, a senior scientist was in charge of a specific project and could be involved in many different projects, in Technology Group B the structure was more rigid and hierarchical. The teams were in principle ‘fixed’ and staffed with five to six members – hence a person worked only for the Hydraulic team or the Grease team, etc – however, scientists could be called in to participate in joined projects with different business units of Hydro-Carbon Solutions. Here, the old practice of ‘teamwork’ was encountered – the one that was criticized as working in ‘individual silos’. People still used to interact with their close colleagues and maybe with their peers over lunch. Nevertheless, again there was a difference between the teamwork in the group now and back in Thornton days: the projects had become highly specialized, customer oriented and needed to be delivered in tight deadlines. Consequently, employees did not feel like they had the time to spare on discussing theories and exchanging views in abstraction. Since everybody worked in short time limits, the relationships between colleagues transformed into ‘customer-based’ relationships:

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so the opportunity for cooperative type of activities is limited in a sense, in other words, if you want help for something is difficult to find somebody that has the right skill or has the time to spare or . . . there are barriers to overcome in order to get the help you might wish for, so you tend to do much more yourself . . . the move towards Electronic Information Systems has tended to make things worse in some sense, now everybody has to do everything themselves. Some of the barriers this scientist refers to could be overcome when provided an activity number: people were willing to help as long as they could justify the time spent on ‘helping’ others. However, a strongly expressed concern was the fragmentation of activities after the commercialization turn, which resulted in the creation of individual entities. An engineer with ten years in Oil Co. explains: nowadays it appears to be much more a collection of people who rent the space on the site, so, it was Thornton Research Centre and is now changed to [Innovation Park], that says it all actually, so the degree of collaboration between the entities on this site, ehm, is not as great as it could be, it appears to be less than what it was, but actually my perception is that a lot of changes on the site may never be any better than it is now, certainly [Technology Groups A, B, C] tend to exist within their own worlds, and they tend not to, at a working level, to exchange information, that they could do, there is certainly more space for exchanging information that we, that is, that we actually use at the moment. Each Business Group had constructed its own micro-world in the Innovation Park; the urge for business survival in the new commercial game, which imposed new rules based on ‘time delivery’ and ‘performance measurables’, changed the formal and informal relationships between the ex-colleagues of Thornton. It was certainly my feeling as an outsider that there was no interaction between the two Business Groups I was studying, and furthermore, I could notice an almost competitive relationship, where the successful Technology Group A was hiding their ‘recipe of success’ from other groups, by not disclosing information beyond the boundaries of their group. Information is believed to be power especially in a commercial organization, thus this has created rigid barriers across the groups and changed the principle of free-floating knowledge, which is the keystone of the scientific language game. On the other hand, Technology Group B that needed this information due to its difficult business position at that time, felt excluded by their successful colleagues, who now were running a different business. In a few words, relationships between Business Groups were reduced to formal ‘customer-based’ relationships directed by the needs of projects and justified by activity numbers.

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Changes in the innovation park population and ‘knowledge management’ A restructuring of the knowledge base At this point of transition from the old ‘academic’ to the new ‘commercial’ culture many of the senior scientists decided to leave the company, refusing to comply and follow the rules of the commercial order. [laugh] Are there many people like you here? Ehm . . . that depends what you mean like me, is that a common view? R: I mean sceptical like you. I: Yes . . . it’s largely an age thing I think, the older people are a lot more sceptical. R: So are there many people of your generation here? I: No, because you see five years ago, almost all the people, very large number of the older people left early, they took an early retirement . . . so I guess we have . . . normal age retirement is 60 and I guess that in our department we have two people that are 55, I think, and we probably have two around 50 and that’s about it, so we don’t have many old people. R: And I guess you chose to stay here because you were enjoying. I: Yes . . . but that doesn’t stop me from being cynical. R: I:

This scientist, who had 31 years on site, could afford to be cynical and resist in his way to the commercial discourse, because he happened to be a world expert in his field. Nevertheless, the attention attracts the argument ‘old people are sceptical’, ‘old people don’t like changes’. The argument seems to have arisen and be used widely during the time of transformations: ‘going commercial’ was tightly linked to progress and business sustainability, and the necessity for this change was supported by the formal discourse as the only way to go, i.e. as the natural route to follow. Resistance was constructed in the formal discourse as a fruitless and pointless behaviour that would impede the promising – economic – progress. As expected then, the senior scientists’ objections were anticipated and criticized before they arose; the argument ‘too old to change’ had been widely used to explain the senior scientists’ cynical attitude. In fact, it was expected that the older scientists would resist, because the new order would mainly affect the way they were working so far, and most importantly, their status and power. Their attitude thus, is not fully captured by the psychological explanation of ‘too old to change’, but better explained when a political standpoint is adopted. However, the commercial discourse managed to neutralize their criticisms, by turning them ‘graphic figures’ of the site, and hence presenting no threat for the new order any longer. Actually, they had become a part of it, acquiring a functional place, since any democratic move needs those, who would criticize it; scientists were welcome to stay or leave if they did not like it. From one side the replacement of older staff with young people facilitated the

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process of change. Since the new scientists had not memories and experiences of the previous scientific culture, they could adopt the new discourse and adapt in the organizational order easily; ultimately a ‘smoother’ and more coherent, and thus controllable, workforce was built. However, old scientists left taking with them scientific skills, experience and knowledge. A young scientist and laboratory team leader comments: this is a big worry for me [laughs], because I don’t think we are, and it is really unfortunate, because they have developed the knowledge for over 20 years, how do you pass that on in one year, you just can’t, and to be fair, all of us the young graduates, we all learn as much as we can from the people, who have the experience, but because we are in this fast moving culture and there is a lot of pressure on us, there is a timeline we have to deliver to our customers all the time, there isn’t really the time to do this background reading to get the knowledge; . . . but at the same time if I have a question if I go and ask any of the experienced scientists they will always, always help, and I think we’ve moved to a culture that we work a lot like that, so, I’m not gonna develop the knowledge in the next ten minutes, but I know who to go and ask; the worry then is, like you say, if these people retire, what it actually happens, and I guess we just have to beg them to come back as the consultants do if we need them to . . . but I mean the knowledge is slowly dripping down, it is not that it will be the end of the world, but there are some things like, a lot of people have spent their time getting this experience. (emphasis added) In this excerpt, the commercial culture is represented as an obstruction to knowledge creation and sharing: the fast pace of changing and the new values of ‘delivery’ and ‘customer focus’ did not allow for substantial learning and training, at least as the latter occur in the ‘scientific game’. However, two new solutions were identified: the first was to ask the old scientists, who had left, to come back as consultants; this means that they would do only research, and would not have to ‘go out and find customers’. The second is a striking observation I made during my fieldwork: people avoided to hear, know or remember anything beyond what they needed to fulfil their current tasks; in case they needed an extra piece of information, then they knew whom to ask. People were increasingly relying on codified and stored knowledge in external structures, rather than being interesting to internalize all the valuable knowledge for future use or for personal development. However, the young scientist was very confident for the knowledge that Oil Co. still had, and the way things were progressing, as she concluded that ‘it is not the end of the world’. Here, she continues: I mean the other problem is that we have a much fast turnaround of young graduates, so a lot of people come in, spend a few years with the [Technology Group A], but now Hydro-Carbon Solutions offers attractive opportunities

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Oil Co. was committed to supporting the continuous development of the staff, and indeed provided a great variety of training classes whenever there was a request. It also offered an ‘open-resource’ career development scheme, by which the staff could pursue their own career objectives and apply for any job within Oil Co., where they thought it would be more suitable for them. Consequently, dripping of knowledge was not only due to senior scientists leaving the company, but also to young recruiters leaving their technical positions for other more prestigious ones, which promised better career opportunities and rewards. This means that sales and marketing roles were acquiring greater importance – and power – in the new global organization, where scientific expertise was not appreciated as much as it used to be in the past. The technologies of knowledge management This leak of knowledge signalled the necessity for documenting and filing all knowledge and information; new archival processes and databases were put in place, and the scientific staff were now expected to write detailed reports, store them in electronic databases and share them at least with colleagues from the same skill pool across Hydro-Carbon Solutions. This last practice replaced the face-to-face sharing of knowledge among the colleagues in the older days. A bureaucratic culture with heavy administrative work and many forms to fill in emerged, in order to keep control over and coordinate all the activities and knowledge spread around and across the Oil Co. world; the administration staff started acquiring more importance and power, as they were gaining a central role in the new order. This bureaucratic aspect of the commercialization in a global environment was not particularly well accepted by the scientific staff: the girls from the administration unit complained about the attitude of some older, cynical scientists towards them, and the latter believed that ‘the Group is now run by the admin. girls’. For the scientists these new procedures were rather time consuming and unnecessary, since they were sure that in reality nobody really checked their content, and they hardly made use of the stored information. These knowledge technologies then, were perceived solely as tools of controlling and enacting the new commercial order, rather than tools to support substantially the new activities. New skills Oil Co. always believed in recruiting individuals with a variety of knowledge and skills. However, it had always faced the problem of recruiting new employees with high scientific competences, due to shortage in the labour market. In this acknowledged problem, i.e. to attract people with the required

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technical knowledge, the multiplicity of skills that were considered necessary to support the new commercial culture was now added. This means that over the necessary scientific rigour, analytic thinking and intellectual capacity, now communication and presentation abilities, and managerial skills gained importance. ahm, god . . . well, research skills are where you . . . research skills have to be where you inquire, always sceptical about or even inquiring about how something works, why something is, whether it is true or not, whether you can prove that it is true or not and how it fits in into the general picture, that’s what research is; now, when you talk about development skills, you don’t need to know all of that, you just need to know what it is that you can do to achieve the . . . the important skill is to make sure you achieve the goals that you set yourself; so development is much more goal oriented than research is; research is not the same that . . . you are trying to do something in research, but the only thing that matters in development is getting to the end whereas in research you can learn a lot of things while you are going along the way. (emphasis added, senior scientist, 31 years at Technology Group A) Here, research is constructed as in principle a sceptical and ever-critical activity, and effectively, these are the essential scientific skills – here ‘science’ is defined within a positivist discourse, which is not surprising given the speaker’s ‘hard’ scientific identity. The activity of development is described as one that does not necessitate scientific skills – as defined above – since importance is given on the ability to deliver, to reach your goals. ‘Development skills’ are constructed as belonging to a different language game, the modern, commercial discourse, where individuals are target oriented and driven by the goals they set themselves. Ultimately, ‘learning’ for this scientist is actualized only in the research language game. it is probably, I am sure it has changed the way that we recruit and interview people . . . as I said 15 years ago we would have recruited someone perhaps directly from a PhD or a post-doc, we might have not been over-concerned about how well he would interact with the customer . . . I get the impression now that people’s presentation skills, presenting their research or their technical know-how is much better, but I think . . . it is a bit harsh for me to judge that, because that’s something it happens in the society in general, when you look at the youngsters coming from schools and they are much better in presenting than when I came from school . . . so we are probably looking . . . we’ve always looked for a mix of skills, but I think some of the emphasis has probably changed, now. (emphasis added) This scientist elaborates further the skills that gain importance in a new commercial order; presentation skills are highly valued in the business world and the

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new recruits are valued for their abilities to present and promote their work – and themselves. the training is generally on the job, certainly in terms of science spending in UP you tend to get along and you learn very quickly; clearly they are giving us a number of more targeted courses in terms of marketing and commercial awareness. The final excerpt illustrates the priorities of Hydro-Carbon Solutions in terms of the expected skills: as far as the ongoing development of scientific skills and training was concerned, this relied upon the individuals to decide what they needed, find the courses and participate; however, regarding marketing and commercial awareness, the training was already decided by the management, and the scientists had to follow it. The knowledge worker The new commercial order changed not only the skills, but also the tasks that the employees had to perform; the senior scientist in the following excerpt describes these changes: urgh . . . the marketing people in London, when this was a research lab, they were not real marketing people, they were technical marketing people, they had a big technical component to their job, we had, what I think a very ridiculous situation is that, they didn’t trust the technical people to go out to meet the customers or to make visits, and what you would have found is that the people on site were writing briefing documents and papers, they would pass them on to people in London, who then perhaps re-edit them and then the people in London would make the visits . . . the change here that’s happened now, is that the people on site now are trusted [laugh], the people in London have much less of a technical role, they are doing real marketing now, rather than technical marketing and as a consequence a lot of the visits to customers and the report, we write the report and it goes straight to the customer, it is not re-editing by anyone else in London, so there’s been a certain amount of streamlining, ’cause I think there was a lot of duplication of efforts, the people in London doing the same jobs as the people in [the Innovation Park], so I certainly with my job I travel much more than I would have done six years ago. From one side, this change enriched scientists’ jobs, and as mentioned before, the scientists felt ‘trusted’ by their ‘partners’ in other parts of Oil Co. to do their jobs. ‘Trusting’ relationships are important for the new Oil Co. identity, where the umbilical cord with the parental company was cut; the new structure had a flatter and informal hierarchy – let us not forget that rigid, hierarchical structures have been criticized by academia for being inflexible and costly. Control was

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not exercised any longer directly via the line manager, since the new flexible structure was built on ‘equal’ relationships of partnership and teamwork, and employed a new discourse to replace the rigid mechanism of direct control by the subtle mechanism of control via ‘coordination’ within the team and via ‘trust’. Furthermore, the scientists acquired an ‘expanded’ identity, which admittedly not all of them enjoyed and appreciated. A young scientist from Technology Group A, with four years on site comments: I think it [the commercial turn] put more pressure on people . . . pressure to deliver within fairly short time, ehh, and perhaps as well . . . eh, we have to try and cross every resource rather than being traditional scientists I think now we have to become salesmen and I think that put some pressure and we have to do more of the things that we wouldn’t have done in the past. (emphasis added) And a senior scientist from Technology Group B, with 20 years in Oil Co.: I would also say there was a loss of morale, because some of my colleagues say ‘I am paid a senior’s salary just for doing a clerical job’ I receive a task from London, they look in the next generation of leading oils, I pick up the phone and I talk to Lube-Resolve, I know something about the base oils we have, I give Lube to resolve the job, they do the job, [laugh] I approve the job, where is my role as a scientist, as a formulator? I state that very crudely, but I think that’s the attitude some people have here. (emphasis added) The commercial turn did not affect only the structure and identity of the Business Group, but of its employees as well; the scientists, who were recruited before the commercial turn for their high scientific skills and competencies, now found themselves having to perform tasks, which were incompatible with their scientific identity. I have to stress, that ‘this clash of identities’ was experienced only by the scientists who started working in the place before the commercialization: as I discussed above, Hydro-Carbon Solutions changed the emphasis given on the young recruits’ profile, and credit was now given to people with good commercial (i.e. communication and presentation) skills. On the other side, lab technicians, who so far had been ‘restricted’ to performing testings for the scientists, saw now the opportunity to undertake extended responsibilities, as they get more involved in activities beyond the laboratories and even they got to manage small projects – whereas in the past, managing projects had been a scientists’ prerogative. when I first started on the site I was very much like a laboratory technician, now I have my own small projects, if you like, to manage in my own right, and generally the people, my colleagues find that we do less actual lab work and more managing projects, reporting and so on, things have changed in

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Hydro-Carbon Solutions stretched the concept of ‘knowledge worker’, to include not only scientists but lab technicians, as well. Consequently, the firm’s ‘knowledge capital’ increased, since more people were now included in the definition of the ‘expert’, and also more people were utilized in the short-term projects, which were now the object of the new activities. Furthermore, under their new identity the empowered lab technicians saw the opportunity to participate more actively in the Group’s activities, claiming that they had accumulated the necessary knowledge and experience throughout the years; here, lab technicians were offering a convenient alternative, by intentionally referring to the knowledge and experience that the Business Groups were afraid of losing, when the old scientists left the company. The assistant scientist from Technology Group A, with 18 years in Oil Co., constructed in her story a different version of the workplace than the one presented so far, wherein assistants’ voices were still oppressed. In her version, knowledge equals to experience – not necessarily associated with scientific skills. The concept of knowledge expands to include not only scientific knowledge, but all experiences from the past, together with the important commercial knowledge that was now valued. because I don’t think they use people to their full potential; they don’t realize that in the past many of us have worked in projects, like 10–15 years ago, I know, I can quote examples, I know Jeff can quote examples of work we’ve done in the last 15–20 years which are now almost, the wheel turned and are being done again, and we are involved in projects very similar to them, and we are not being fully utilized, we are not given the opportunity to . . . have an input to say well hang on we did that before and that didn’t work and it’s not . . . everybody thinks it’s new and it is not . . . we’ve been . . . a lot of us have been here a lot of time and they should use us a bit more. (emphasis added)

Discussion So far I discussed the nature of the commercial turn and the expectations of Oil Co.’s decision to transform its R&D laboratories into ‘fully commercial’ Technical Consultancies. These have been represented in the formal Oil Co. discourse, as found in the newsletters published at that time. The Oil Co. commercial discourse invaded the scientific site, and changed radically not only the way it was managed, but also the culture, rules and identity of the place. Oil Co.’s commercial turn followed the rationale and steps of a commercial knowledge-based organization, i.e. they realized the commercial value of the knowledge and expertise they had, and went on to exploit it commercially, by

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supporting this turn with flexible structure, teamwork, autonomy and equal relationships built on trust, i.e. the technologies that the academic literature prescribes. The commercial turn caused radical changes on site, which still had not settled six years later, when I conducted the fieldwork. Consequently, it changed the power relations, which were already established in the existing scientific order, and left room for negotiations and struggles of power over the new valuable resources in the commercial order. The question that emerges is what is accepted as a valuable resource now? In the previous order, it was clear that the site was driven by scientific values, hence knowledge, expertise and research had a central role and status. However, in a commercial culture, even though it is supposed to be built around the notion of knowledge, core values appear to be predominantly the values of a commercial rather than scientific environment. The new commercial structure, with the intensive customer focus empowered the Market Sector, which operated in the interface with the customer, for now the Market Sector was increasingly deciding on the direction of the business. This domination emerged subtly in practice, whereas in theory it was still hidden behind the concepts of ‘teamwork’, ‘collaboration’ and ‘partnership’, which were deployed around and supported the commercial discourse. It is worth noting here that ‘teamwork’, ‘collaboration’, etc. are values accepted and supported highly in the previous scientific order; in other words, the new discourse expanded its web of relations by using well-accepted values of the previous discourse. However, by linking ‘teamwork’ and ‘collaboration’ with ‘flexibility’ and ‘autonomy’ the traditional values change their meaning, and hence their effects. Nevertheless, by usurping ‘values’ of the scientific rhetoric the commercialization discourse neutralized the force of the changes. In specific, through the review of formal documents certain discursive strategies emerged, employed to support the changes and minimize resistance: the commercial turn was constructed as the only way to go, and resistance was illogical – at least beyond commercial rationality – and futile. The changes that it caused were accepted as the natural order, because ‘the organization is commercial now’, and this is how things are in commercial organizations. Furthermore, being convinced for the importance of commerciality, nobody really doubted its implications, which were accepted and soon neutralized. On the other hand, fundamental concepts of the scientific game, which characterized the previous order, i.e. ‘research’, ‘scientist’ and ‘knowledge’ had undergone a re-articulation, whereas they still enjoyed central attention in the commercial order. Knowledge has been recognized by both academia and practitioners as the vital resource, which should be protected and supported. First, by turning knowledge to a commercial object its nature changes: whereas ‘narrative’ and ‘scientific’ knowledge increase through sharing, commercial knowledge decreases, and hence has to be protected and carefully used. ‘Knowledge’ sharing was encouraged within the boundaries of each Business Group, but being commercial – as opposed to a ‘university site’ as it used to be – conferences were not a place for Oil Co. scientists to share their knowledge any longer,

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but where they made commercial contacts. Furthermore, the production of ‘commercial’ knowledge needs different skills – since scientific skills are not sufficient. Commercial skills included ‘presentation’ and ‘communication’ skills, in other words, skills that could secure customers and funding for the Business Unit. Research changed nature and objectives. Now, by ‘research’ is meant shortterm projects with clear commercial applications and business profits. Senior scientists insisted on drawing a line between ‘research’, as articulated in a scientific game, and ‘development’, which is what was meant by ‘research’ now. However, this distinction served only the senior scientists; the commercial language simply distinguished between long-term and short-term research, and furthermore long-term research was not welcome unconditionally any more. Finally, the role of the scientist was transformed as well, to the scientists’ frustration, as they had enjoyed so far the benefit of doing well-paid research of an academic nature. Scientists now had a range of administrative tasks, when at the same time they had to develop their commercial skills – and ‘go out and find customers’. At the same time, laboratory technicians now acquired the ‘privilege’ of managing small projects. This means that in the commercial order, where commercial replaces scientific knowledge, ‘knowledge worker’ is not the scientist, for the skills and training it requires are different from the ones the scientific game requires, and furthermore the kind of ‘knowledge’ they use or produce is of a different nature. ‘Knowledge worker’ is a broader concept, based on different skills, knowledge and training – now work experience is much valued with or without scientific training – and the outcome of the ‘research’ is not assessed and approved by a specific scientific community, in terms of its scientific contribution – the knowledge worker does not belong in a specific scientific community – but by the business, in terms of the profit made. The question of governance of the production of ‘commercial’ knowledge at the organizational level is tackled in Chapter 7; however, its significance for the society is crucial and its implications deserve further research. It is true that the ‘secluded scientific culture’ of Thornton cracked by the commercial turn, and gave more people the possibility to participate in activities that in the past had been a scientists’ privilege: it gave more people the possibility to use their knowledge and experiences, and reach higher pay rates. Together with the flatter and flexible structure they implemented, it could be argued that commercialization led to a more open and democratized site, where the scientific elite lost its status and privileges, and more people could allegedly equally enjoy the fruits of hard work. Democratization is indeed one side of the story, where now the voices of the weaker groups are heard by the managers. On the other hand, the aim was not democratization, but exploitation of all types of knowledge resources and competences under Hydro-Carbon Solutions’ umbrella, in order to increase their knowledge capital and profits. All employees were invited to participate in training programmes, and contribute their ideas to the Group, because the Group needed them for survival – as the formal discourse prescribes.

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Nevertheless, despite the discursive strategies and practices employed for this transformation, furthermore, despite the positive consequences that might have resulted, inevitably such a big change would not have gone through uncontested. The scientists felt early the changes in the rules of the game, and most of them decided not to comply by leaving the site – and take with them precious scientific knowledge, which at that time might not have felt like a big loss, but now the Business Groups reconsidered. Those who remained, enjoyed the privilege of criticizing and not participating in a process that did not match with their scientific identity. Others applied more political ways for regaining the power loss they suffered after the radical commercialization: the Business Groups soon realized the significance of scientific knowledge, and scientists used the need for research in order to regain their status.

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The construction of ‘commercial innovation’

In this chapter, I explore the formal organization discourse on innovation, and the relationship between ‘commerciality’ and ‘innovation’. I examine closer the structure of the most popular ‘innovation machine’, i.e. Eureka, an innovation mechanism that reflects clearly the discourse ‘innovation as rational planning’, the assumptions and expectations from it, and from the scientific population, who are supposed to engage with it. Ultimately, I look at the language used, which ties together innovation with ‘business profits’ and its implications. The formal – i.e. the organizational – view on innovation is presented, via the talk of the Research and Innovation Group, which was in charge to promote innovation at the Oil Products Business, and their explanation of the problems encountered in managing innovation. I take this to be the ‘formal’ view on innovation, since, like the innovation managers stressed during the interviews, the top level avoided expressing an opinion, and delegated the full responsibility of innovation to this group. The analysis addresses issues of politics and power related to innovation, not merely as negotiating variables, as mainstream analysis of innovation suggests, but as a force of creating the dominant understanding of what innovation is, what is not and what the necessary actions are, in order to comply with the new and naturalized articulation of innovation. Ultimately, the questions I pose are, how innovation is articulated within the commercial discourse, what struggles are enacted for its control and what the consequences are for the organization.

The revival of innovation A resource manager in Technology Group A (with 24 years in Oil Co.) comments: I guess historically there was more, an emphasis on knowledge creation, because we used to have, eh, proportions of budgets set aside to do blue-sky types of research knowledge, we then moved more to a, eh, product development, product application, and it’s only recently that we started to look again at . . . new knowledge generation.

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The intensive pace of becoming commercial, the new language it introduced – a language of ‘customer focus’, ‘cost efficiency’, ‘time delivery’, etc., which derived from an economic discourse – together with the clear distinction between the past and new times, resulted in the end of long-term scientific projects, which were judged inadequate and inappropriate for the commercial order. The projects became short term, and the funding for ‘blue-sky’ research with unspecified utility stopped. At the same time, the Business Groups were concentrating on learning to operate within the boundaries of the new acquired identity, in other words to work as Business Units, and thus new knowledge and innovation were bracketed off, and for a while were considered a ‘thing’ of the past. The following rich account of a technology manager in Technology Group B gives insights into the ‘hard managerial rationality’ and the way it affected progressively the process of new knowledge generation: We cut innovation from the bottom of R&D budget every year, because what you would do is put forward all the ideas that you had and then they would rank them, their use in the business, of course you would get a business analyst or a financial accountant say, well we can’t support this business case because it’s, it’s, it’s woolly . . . so it’s a diffused idea, we don’t know how much it’s worth, we probably won’t do it, so we cut innovation off the bottom of R&D budgeting, and we did that successfully from ’90 . . . probably from ’98 onward, that we cut innovation off the bottom, and that was the problem, the people that actually decided how to spend the money, they were all short-term business people, there was nobody with a, should we say, helicopter overview of what the business might need. However, the intensive focus on the ‘time and delivery’ language and the subsequent short-term research projects had not contributed much in the body of Oil Co. knowledge, and the business groups realized that they had already used the ideas they had and they needed to ‘restock the shelves with ideas’. At that time, the knowledge discourse had already gained significant momentum in the new ‘knowledge-based’ society; the creation of new knowledge and innovation became important not only for Oil Co. and its competitors, but also for their customers, who also needed new ideas to remain competitive. This turn towards supporting innovation would not have been successful without the appropriate discourse that had created a new understanding of what the business was and what the employees were expected to do. The following quote comes from a scientist of the Technology Group B, with six years in Oil Co., and it is a classic example of how discourses operate in this sense; here the employee analyses the formal organizational talk: The Oil Products Business about six years ago, when I joined Oil Co. was always described as a mature business, that’s the word that was always used: ‘a mature business’. R: The oil business? I:

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The oil business is a mature business, and to some extent that was the rationalization before, like three years ago, we moved to doing short-term projects, ‘why is there any point in doing long-term projects in a mature business?, everybody knows what everybody knows, and there are no new things to find out’ was part of the logic, well in the intervening three years things changed dramatically, probably we all realized we didn’t know what we needed to know, that it was not a very mature business and there are loads of things to find out. (emphasis added)

Oil Co. has traditionally been a ‘knowledge-based’ company, given the number and the qualifications of its experts; however, it was not perceived as particularly innovative. Blue-sky research had been conducted without specific expectations for immediately producing products and satisfying customer needs. The oil business in general was described as a mature business, with limited needs and possibilities for new products, and many oil companies saw no reason to keep their R&D departments. However, the revival of the knowledge discourse together with changes in the external environment, e.g. the green discourse, technological advances in alternative energies, etc., opened up opportunities for the viability of the business in the future; these opportunities were not conceivable through the lenses of ‘the mature oil company’ identity. Therefore, it made business sense for Oil Co. to seize the opportunities of the knowledge discourse and become an innovative company. I think there is also a recognition that, if we just do technical services we only provide what we already know, we don’t provide new products or new knowledge, then it will come a time when we will have nothing more to give, and then we will have to invest both for Hydro-Carbon Solutions and for Oil Co. in general in . . . having a careful look in our intellectual property . . . and I think the key aspiration is that whatever the way that transportation develops that Oil Co. will be in a position, both in terms of the patents it has and the expertise and knowledge to be there beforehand . . . and, you can see that things are changing, a lot of our activities now is on bio-fuels . . . and the challenge of sustainability . . . it is a challenge on the way we do business, and I guess it susses out to know that we are the people who will be required to meet that challenge on the behalf of Oil Co. (senior scientist from Technology Group A) Clearly, Oil Co. did not want to consider itself an oil company any longer, but an energy company; this change in perspective encouraged its employees to use their scientific knowledge and expand into the broader area of energy. Hence, scientific knowledge, long-term projects together with the discourse on knowledge regained attention. Whereas so far the commercial discourse had indicted research for being an ‘unsuccessful’ activity of the past and stopped its funding, now research became again ‘the flavour of the month’; however the conditions

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for its conduct were up for negotiations, since no part (scientists, Market Sector, Oil Co. Group) were willing to give up the struggle for its control. The realization of the significance of innovation and a conscious turn to support it started approximately three years before my fieldwork. A number of funnels and funding started appearing at all levels and units at Oil Co. and Hydro-Carbon Solutions, aiming to support new ideas and generate innovations. Each funnel was designed to support different types of ideas, and thus it offered a different articulation of ‘innovation’, and of what ‘valuable ideas’ were. Various funnels appeared, with the intention to support short- or long-term, commercial or technical, groundbreaking or simple ideas. Consistent with the new commercial culture and practices, idea proposals submitted to any innovation funnel had to present a business case, i.e. the researcher had to provide a clear estimation, explanation and justification of the required funding, the application of the idea, the timeline and the expected profits for the business. Nevertheless, these innovation mechanisms were working independently and in fragmentation, and so it rested upon each scientist to reach for them and suggest a research idea; if the idea was rejected by one funnel, then the scientist had to start the process again from the beginning, by identifying a more appropriate funnel revising the business case to reflect the specific interest of the funnel, and proceeding with the presentation of the proposal, etc. Each group conceived innovation in a different way, according to the distinct identity, the object of its activity, the needs and objectives it pursued; we can suspect already that the fragmentation of the funnels, the different understandings of innovation and the politics behind the promotion of innovative ideas, would create a terrain for competing discourses and actions within HydroCarbon Solutions. The consequences of this richness of co-existing articulations of innovation and subsequent practices is presented in the next chapter; here I shall discuss the formal innovation discourse.

Research and Innovation Group: Eureka [S]o most people think Innovation is Technology, but one of the things we have persistently tried to impress on people over time is that innovation is not about technology per se, innovation is about exploiting opportunities for change. (Eureka Manager) Amongst the many mechanisms that emerged to support innovation, the most important, at least for the scientists at the Innovation Park, was ‘Eureka’, which was managed by the Research and Innovation Group, a team of five members: one in Houston, two at the Innovation Park and two in Amsterdam. Eureka was a higher-level innovation machine; it was first implemented in the Exploration and Production Business to support innovation and essentially long-term projects, and then a similar mechanism was introduced in the Oil Products Business.

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Eureka was an innovation funnel: it appeared as a website linked to a database, where scientists could log on, have a look at other ideas and submit their own. The Eureka team reviewed the ideas, and if one was assessed as worth exploring, then the person who submitted it had to prepare a business case and make a short presentation in front of the Innovation Panel, which consisted of senior managers of Hydro-Carbon Solutions and people from the business. If the Panel was convinced about the value of the idea for the business, then an initial amount of money was granted to start the scouting stage of the project; the progress of the project was assessed at the end of each stage and, if the results until that stage were satisfactory and could still demonstrate significant financial returns to the business, then more funding was granted, and the project passed on through the ‘gate’ to the next stage. The assumptions of the ‘rational planning’ discourse on innovation are evident in the approach taken here; the process tried to control the uncertainty of the environment, by maximizing the control over the process of developing innovations from the early stage of ideas generation until the launching of the innovation in the market, and by putting the scientists and the business to work together. The literature identifies this model of innovation mostly with short-term projects, for the simple reason that it is difficult to plan in thorough financial and technical details a project that would last more than five years. However, Eureka was a process that aimed to support long-term projects; the stretching of the model to long-term innovation was not perceived as shortcoming by the Eureka team but as strength – it is the ‘Eureka method’. Below, a member of the team suggests a strengthening of the model based on a rational problem-solving view of innovation, where the market sector would expose problems, and the scientists would seek solutions: we are in the process of, what we’re trying to do is to give people shots about what we are trying to do . . . and set specific challenges to meet; because I think that unless you feel passion about innovation . . . there’s a saying about necessity being the mother of invention, you need to expose people to problems and then let them find how to work out, how they might be solved from their knowledge and skills and competences, what I know of might be useful to solving this problem, and that’s what we are trying to do. A member of the Research and Innovation Group at the Innovation Park with 20 years in Oil Co. gives the following account about the need that Eureka intended to fulfil: the backlash of that . . . the pendulum, sorry, swung completely and then people thought, well, what about our longer term, what about our longer term, effectively, where are we going to be in the future, and how are we going to nurture ideas, which then will take longer to come through and longer to develop; and that’s when you swung back to having a Eurekastyle process; so it all started in EP [Exploration and Production], the EP

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slashed its R&D budgets and got rid of huge trunches of long-term research, and when they got rid of it . . . they sack a lot of people, and when they got rid of them, then they realized that actually those people were providing a function, and at the end . . . the problem was not that you had those people, the problem was that you didn’t tie them properly into the business, they were not properly integrated into the business; and it’s always been that problem that R&D has historically let the business down . . . in some areas, but the business has let R&D down, by not saying what it wants; so what emerged, the consensus that emerged from that rather painful process is that what you need is an R&D process which ties the business in with the innovators, with the research innovators, and that’s what the Eureka process is supposed to enable, it’s supposed to be a mechanism for enabling you to do risky, non-core, long-term things, BUT keeping the business properly engaged. (emphasis added) The account gives insights into the relationship between the business and the R&D department: the end of innovation made the business people realize that scientists were not ‘mad’ researchers, who were wasting the business money for science. On the contrary, they were actually providing a function; therefore, they could play a vital role in the new commercial organization, as long as they amended the relationship between the two parts, which so far had been proved dysfunctional. The problem is that innovation, at least as scientists understood it, and commercialization did not seem to work together; however, the business (the ‘people’ as neutrally and all inclusively was described by the interviewee) saw an opportunity for profits from their knowledge resources, and attempted to bring commercialization and innovation together. The ‘solution’ was presented as ‘consensus’ between the business and innovators, and part of it was a process, which tied the two together; according to this solution, now scientists had to innovate strictly according to what the business needed – the problem then would become for the business to realize what they needed. Before I explain how this becomes, in theory at least, feasible with the Eureka framework, it is important to note the harmonic representation of the solution as ‘consensus’: ‘consensus’ remained a chimera throughout my fieldwork, since the scientists were never convinced to embrace fully this articulation of innovation, and thus the suggested actions. A fuels scientist with eight years in Oil Co. confides: I think the danger is that we’re being conditioned to think of innovation just as a business thing, but there are a lot of kinds; SAFE innovation that you are allowed to be creative, to think about ways where they can have a big impact on the bottom-line, and those are, if you like, good ideas that have a low risk capacity; coming up with technical ideas . . . I don’t know if that’s happening here . . . that’s where the guilty pleasure of innovation is. (emphasis added)

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The excerpt demonstrates how experienced scientists refused to accept the business-oriented definition of innovation, which fundamentally expected low risk and safe innovation with applied results. ‘Real’ innovation is described as a ‘guilty pleasure’, which emphasizes that it was a ‘forbidden’ activity in the new commercial order – an activity that many scientists were missing. This account also calls into play another variable, which characterized the nature of innovation in Oil Co.: pursued innovation had to be ‘safe’ and low risk; the riskaverted commercial culture that was built excluded in practice blue-sky and uncertain regarding results innovation. Nonetheless, the Eureka approach chose to overlook this fundamental feature of innovation, i.e. uncertainty. Eureka was an initiative of the CMDs of Oil Co. for supporting long-term, non-core ideas that did not fit in any other innovation channel. CMDs saw an opportunity to invest in long-term projects that would turn the business competitive and viable in the future, probably by exploiting non-core ideas – i.e. ideas that were not relevant at the present to the businesses – by giving business focus to the scientists’ technological ideas. A member of the Research and Innovation Group explains: the role of Eureka is to find and nurture and support in their early stages ideas, which don’t comfortably fit into the existing businesses; so what you could say is that there are two types of innovation: it’s in the box and out of the box, it’s core and non-core; so we are looking for those non-core ideas, which would otherwise be difficult to support, that’s essentially our role, but because it’s sometimes difficult to distinguish core from non-core, it might be almost non-core, there is actually a grey shading between the black of the core and the white of the non-core, so people come to us with ideas which are clearly core, and we might even support them at early stages, but they wouldn’t come through our mechanism for significant funding, we are likely to support them at an early stage. (emphasis added) And further on he elaborates the difference between core and non-core projects: core is ‘delivering value in short term at low risk’, and there are other issues, which are involved around that, such as: is it part of our brand, does it deliver on our brand, is it product or service which is what Oil Co. does, but we’ll take this for start; so we say non-core is delivering value at any time scale at high risks, in an area which is not currently part of the core proposition of the business. (emphasis added) For the interviewee it was very clear that there are strictly two types of innovation: core and non-core. All ideas fall somewhere between the edges of this continuum, and the funnel was ready and open to support any idea that would expand outside Oil Co.’s current business. From the way he represents Eureka,

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one is led to believe that there can be no valuable idea remained unexploited or at least untried: his account promotes a process that seeks ‘non-core and highrisk ideas’, which means ‘not relevant at the current businesses, but which may open business opportunities in the future’. The first objection is that this definition of innovation distinguishes ideas strictly by reference to the business immediate or longer-term relevance – technical ideas, which still match the definition of non-core and high risk, are excluded. The advantage of the Eureka method, as perceived by the team, was precisely the requirement of a business case, which should support the research proposal. A member of the Research and Innovation Group explains the requirements and benefits: what will be the size of the prizes, how it fits into the business, what’s its place in the value-chain; if you’re clear about that up-front, then you have a much stronger case, and it also obliges you to engage with the business, right from the beginning in order to determine how you are going to make use of, before you do any of the toys for the boys sort of stuff. However, this created a considerable degree of dissatisfaction among the scientists, who did not feel comfortable with the tight financial planning and control imposed by the process that progressively achieved to neutralize subtly the call for high-risk ideas. how can they ask you to give a very rigid time scale at the beginning, about where you will be in four years time, how much time it will take, how much money it will cost you, which kind of involvement you’ll take on board as you go on, etc. etc., and that’s what they want you to do, at the early stage they want you to present Net Present Values for five, six, seven years, and that is very hard for the programme, and that puts off many colleagues, ‘hang on, I am a mechanical engineer’, or ‘I am a chemist’, or whatever, ‘I am a lab technician’, or . . . ‘I have a pretty good knowledge of the job I am supposed to do, but I am not very strong in finance’, that’s some of the complaints I’ve heard. It was very clear to all, that the process would not support any technical or other longer-term ideas, unless the scientist could demonstrate clearly how and when they would deliver value to the business. The excerpt above scrutinizes and argues against the logic behind the main advantage of the Eureka method, and overall of the commercial discourse: the process tried to tie together the business with innovation in a single discourse, however in practice it encountered great resistance both by scientists who did not accept the suggested articulation of innovation and its tight financial control, and by the business people, who had no interest nor understanding in the ‘scientific’ articulation of it. A member of the Eureka team discusses the problem of the gap between long-term and short-term projects from a business perspective and suggests solutions:

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The problem was constructed, not simply as a lack of communication between the business and scientists, but fundamentally as an incompatibility of drivers, interests and objectives between the groups that were called in to participate. However, the suggested solution did not address this political issue, but treated ideas and experience as distinct entities that could be managed independently of the individuals that generated them and would actually work on them. Another consequence of the all open and embracing discourse deployed around the concept of Eureka was that it led many scientists to see in this process an opportunity to do some ‘interesting’ – or non-core – research, like they used to before the commercial turn – in other words to pursue long-term technical ideas. However, this led to a generation of ideas that were more ‘noncore and high-risk’ than Eureka was prepared to support. A member of the Eureka Team with 21 years at Oil Co. talks about this problem, which was created by a ‘misunderstanding’ of what a ‘relevant’ non-core idea would be for Oil Co. business: the numbers are OK . . . there is a reasonably good number of ideas coming in, but again a lot of them are completely irrelevant, and lots of them just keep on coming back at the time, and a lot of them are quite small. And later: for example, a very large percentage of ideas coming in are for bits and pieces of hardware, things you attach on cars, or screen-washing devices, and that sort of things, there is no way that we will implement those as part of the Oil Co. Business . . . and we shouldn’t waste our time even thinking about these things [laughs], if it was a different business, and it is a good idea and exciting, then we would take it forward. Not surprisingly, the scientists, who saw their ideas being rejected over and over, even though they were ‘non-core and high-risk’, became frustrated by the undefined and unrefined expectations of the process, which was now perceived as ‘a bit of a lottery: you put in a proposal, keep your fingers crossed, and hope you will have the OK to go ahead’. Still, Eureka was not abandoned, but a new

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image emerged among its users: it started being treated as an available pot of money that could sustain some jobs in the Business Group for a while. The issue remained that the Eureka money was an attractive pot for the Business Groups, which now under the new commercial identity had to find means to survive and prove their value to the Group. Hence, a struggle for the Business Groups started over getting funding, or in some cases as the following excerpts imply, a struggle over getting control of the available funds. The Eureka manager introduces this concern: ehm, Eureka always sits – it’s always seen to sit peripheral to the main business, there is a tendency for businesses to think they could do it themselves and . . . at some levels of the organization, people would rather see the money, which Eureka has, which Technology Vision has, they would rather see it absorbed by the business. And also: now, the reason why we are here, is because if you allow all the R&D funding to go through the businesses, through the global hydro-carbon business or whoever, then there is a tendency for it to get driven to the short term, so we are here to provide an alternative to short-term time zone; now, short term does not necessarily means, it means core, everything is driven to the core, because of the short-term objectives, so we are here to provide an alternative to that. (emphasis added) The commercial turn was pushing the businesses to prove constantly their value and improving their financial performance, and consequently core-projects became their main priority. The business wanted to fund innovative ideas for change, but it is difficult for one to see how this individualistic, survival-oriented approach to run the businesses would let innovation penetrate into the Business Groups, unless the older scientists saw some interest in it – and as I said, temporarily the mechanism was fed with ideas by certain scientists, who wanted to do research projects like in the old days. Furthermore, this struggle addresses clearly the issue of governance of the innovative process – which is related to the question of governance of knowledge: in other words who decides the criteria of what is a good and what is a bad idea, and who knows what it is to be decided. In other words, the Business Groups doubted the adequacy of the Innovation Panel to decide what a good idea is and tried to get control of the resources. I said in the beginning that Eureka was a ‘solution’ to conciliate the business interests with the research staff capabilities – a combination that was impossible in the previous order, where scientists were left to pursue their own research projects without being controlled. The findings so far demonstrated that there were more group interests, to be served by the ‘innovation game’, beyond the

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roughly defined ‘business’ and ‘scientists’ camps; groups, which had not been included in designing the ‘solution’ to the problem, now contested the rules of the innovation game. Nevertheless, in the story of this Eureka manager, the ‘business’ was pictured as engaged and supportive to the innovation move, and the problem of the innovation not working properly at Hydro-Carbon Solutions was simply identified with different objectives and mentalities: er, people don’t like . . . people that do long-term R&D don’t like working with the business, and people in the business don’t like working with people who do long-term R&D, because they have other objectives; now, our role is to force them to do that, some like that, some people don’t, but those people they like our system, our system goes down well, urgh, but the overall process is not always perceived as positively as it should, because it requires people to work with the business and requires the business to work with the originators. This account recognizes the politics behind innovation, as different groups have different objectives to serve, however it does not give sufficient insights into the nature of the problem, i.e. the creation of an innovation concept and process that would involve both the business and the scientists. The other member from the Innovation Group I interviewed had serious reservations about the feasibility of this, and below he represents a ‘reality’ where the Research and Innovation Group solely had the responsibility to make innovation work at Hydro-Carbon Solutions, without the active involvement of the top managers at any stage: At the very top – this is a problem, but I am not sure we can solve this problem, probably it’s just the way we run the organization – at the top the senior people, the MDs, for example, say – they have said on the record – that we don’t generate ideas, what we do is accept or reject ideas, and they are recorded saying that all strategy is communism [laughs], now . . . that’s what they decided, now unfortunately that’s cascading down to the level of OP and the OP executive committee for Oil Products essentially says the same thing, ‘we don’t really understand the whole term, we think it is important, please tell us what you do’, it’s a complete eradication of senior management responsibility, so how do you then match up the ideas to the business, it’s really, really hard, we have a process going on at the moment, the technology strategy exercise, where we’re trying to get the business to . . . respond, so we’re doing it by making suggestions, it’s easier buying into suggestions rather than . . . and they don’t, I mean they are horribly, horribly short-term thinking. R: In the Business Units or Oil Co.? I: At all levels within the business, i.e. outside Hydro-Carbon Solutions, even within Hydro-Carbon Solutions, that’s the response, everyone is very, very short-term thinking, and limited . . . ‘X’, one of the OP executive committee members, said that they only think that the long-term innovation is safe in I:

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the business, because it’s sort of very enormous, so they don’t have very many people in the business for long-term mandates, basically the longterm mandate stays with OG – that’s Hydro-Carbon Solutions; but that is good in a sense that someone is responsible for it, but bad in the sense that we still have this barrier between the implementing businesses and the people who generate the ideas. (emphasis added) This account reveals the ‘rhetoric and reality’ of innovation in a commercial organization; aligning with the knowledge discourse that was gaining momentum, Oil Co. was convinced that innovation should be supported but, as the interviewee describes it, the management avoided any responsibility. Innovation was good to be supported as long as someone else was dealing with it, because people had already schedules that were too busy. I encountered the same attitude in other interviews with other managers and scientists, too: it is interesting how this ‘eradication of responsibility’ had crossed the boundaries of the management group and imbued staff at all levels. The management of Oil Co. was described as extremely short-term thinking, and this was represented as a barrier to long-term, strategic innovation, even when the responsibility for it had passed on to another Unit. Eureka was an attempt to cross this barrier and make the business and the inventors communicate, but it is difficult to see so far how a mere mechanism, which was perceived by the staff either as an opportunity for blue-sky research or as a pot of money to support their jobs, and by the management as their fulfilment of their duties towards innovation, could bring the conciliation between the two parties.

Conclusion The story so far narrated the revival of innovation at Oil Co.; the turn towards commercialization kept the Business Groups busy with getting used to their new identity, and with learning the rules of the commercial game until innovation faded away. The emergence of the knowledge discourse reminded Oil Co. that its business was fundamentally a ‘knowledge-based firm’, i.e. they needed new knowledge in order to stay in the business: knowledge was their key resource and their output. Innovation returned at Oil Co., however, this time the scientific culture was not the dominant any longer: it had been increasingly replaced with a commercial way of thinking and acting. I argued here that this turn towards innovation was a necessary move for Oil Co., since the oil business had reached a dead end; the dominant perception was that the oil industry is a mature industry, hence there was not much to offer in terms of new ideas. Furthermore, increasingly external pressures, which attacked the oil business as a whole, due to its environmental impact, and the demand for alternative sources of energy made Oil Co. realize that unless they re-invented their identity soon, they would be out of the picture. The question for Oil Co. was not to find the knowledge resources – they already had a pool of world experts working for them; the question was rather

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how to develop and agree on a strategy for innovation, and then implement it. In other words, how they could coordinate their actions – and interests. The problem, as presented by both managers and scientists, was that ‘real’ innovation, i.e. research ideas that would allow Oil Co. to transform its identity and object of activity, is a long-term, expensive and uncertain process, whereas the business way of thinking was risk-averted and focused on the short term, which is easily measured and assessed in economic terms. Eureka was developed in the principles of the ‘innovation as rational planning’ discourse, which, in order to control the financial risks, asserts the evaluation of an idea in terms of its financial benefits, in a defined timeline. Ultimately, what the Eureka managers attempted to do was to merge the commercial ‘rationality’ of the business with the scientists’ creativity in one discourse and one process. The problem between the two was constructed as one of ‘miscommunication’ and ‘different mindsets’, and Eureka was promoted as the solution for overcoming the cultural hurdles, by forcing both sides to participate and collaborate for the good of innovation and the sustainability of the business. Through my analysis I suggested that viewing the problem as ‘miscommunication’ and ‘different mindsets’ is a dangerous redundancy; the root of the problem is that scientists and the business people operate within two different discourses, they perceive the world differently, and hence act upon different assumptions and beliefs. The scientists were trained to have a technological understanding of research and innovation, whereas, the business people preferred not to have an understanding at all – and passed the responsibility down to the next level. This problem did not only perpetuate the incommensurability between the two worlds, but also did not effectively allow the development of a strategy for innovation, which all levels would abide. Nonetheless, the conceptual framework of Eureka exhibited another important shortcoming: the method set out to bring together the business people and the scientists and forced them to work together but in practice, the evaluation criteria required the translation of the technical ideas into an economic language, which was the language that the business people talked, and most importantly they would ultimately decide in which idea to invest. It is clear that the scientific interests and understanding of the ideas generators were not represented in the decision-making process, since they were expected to ‘justify’ their ideas on a rigid financial ground, which excludes the scientific value of the idea. On the other hand, the people, who were in charge of making decisions, were coming from a different language game; still their role was to assess technical ideas. The question that arises from the dissatisfaction of scientists and of the people who managed the innovation process was clearly the political issue of ‘who decides what a good idea is, and who knows what a good idea is’. In other words, who is the most appropriate actor to say what innovation should be in a commercial environment. In the current process and under these rules, it is not difficult to see how ‘innovation’ turns into ‘business-as-usual’. In sum, the story so far has pointed towards two main issues that predominantly concern the people in charge of long-term innovation at Hydro-Carbon

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Solutions; the first question that sharply arises is the political question of ‘who decides what is a good idea, who sets the criteria and who or what legitimizes this decision’; in other words, whose interests will innovation ultimately serve? The account so far emphasizes the significance of governance of the knowledge processes – which seems that it is not only a philosophical and sociological concern, but also Oil Co.’s reality, and one of the main concerns of the Research and Innovation Group. The second issue that follows from the first is the question of responsibility for innovation: how the definition of and the criteria for innovation can be set by a group of people (management) that tries to avoid the responsibility for it. The paradox begs the question: what this avoidance of responsibility means for innovation, and if and how ultimately the short-term commercial objectives can be served by the same process that supports longterm ideas. A member of the Eureka team comments on the support of Innovation by the management: ‘in its heart, everyone believes in innovation, and everyone does . . . but believing in something and making it happen are two different things; . . . and why Eureka is supported, it’s sort of . . . it looks sexy I suppose’.

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The politics of innovation Technology Group A

In this chapter, I examine the ‘ideas machine’, an innovation mechanism developed by Technology Group A to support its own need for innovation and future sustainability. I show how this system, which reflected the principles of the ‘innovation as culture’ approach, met obstacles in engaging the scientists population, and how politics at many levels, were enacted and hindered the process. I claim that the all-embracing and open rhetoric of this approach, borrows values of a democratization discourse; however, what it is actually trying to do, is to break down the scientific elite, and make full use of knowledge resources, which do not need be highly scientific for the wide purposes of a commercial organization. I argue that the discourse on innovation gave the opportunity to some groups and individuals to use it for their own benefit, turning it into a ‘controlled’ area, for the career benefit strictly of those who were willing to participate. At the same time it failed to engage the scientists, who refused to embrace this articulation of innovation. By discussing the different understandings of innovation, I elucidate further the nature and politics of innovation in a commercial order, where time was a precious and limited resource, and where the management was happy that ‘innovation is someone else’s responsibility’ – an attitude that seemed to share the top levels of Oil Co., as well.

Technology Group A and the ideas machine because if you don’t innovate you die . . . urgh, let’s put it this way, if we don’t innovate, if we don’t come up with new fuels, the business will go to commodity-fuels, if they go to commodity-fuels, they don’t need us; the only reason why they need us is because we can come up with new fuels. The innovation manager at Technology Group A stated clearly the importance of creating new knowledge and innovation for the Business Group; he sharply described innovation as a question of survival. To tell the story from the beginning, Technology Group A, first probably among the Business Groups at the Innovation Park felt that the turn towards commercialization had created a noninnovative, delivery-focused culture that did not allow space or time for generating or, to be more accurate, progressing new ideas. The Business Group saw the

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ideas they had ‘in stock’ – since the times they were doing research as an R&D department – decreasing substantially, and felt that there was ‘a piece of experience they were losing’ in the new commercial order; hence the management decided to support the Business Group and its customers with new knowledge. Soon, they realized that what was missing was an innovation system, which would support with processes and tools all the stages of innovation, from the ideas generation to the intellectual property protection, and most importantly the commercialization of the final product. One of the resource managers states clearly the importance of linking innovation with the market, in a pure rational language of profits: Well . . . ultimately it’s about how providing technological solutions that their customers will buy, obviously, and again innovation is really about taking ideas – preferably from a customer or a market and developing these ideas into products and services that you can sell that to the customer and make money from it. R: Are these objectives met?. I: Eh . . . I think increasingly so, yeah, I think the key thing is that we are not just . . . coming up with technology-based ideas with no location to the marketplace, you need to have this addition to the marketplace, to . . . understand what the customer need is, if there is no customer need, then you stop the innovation, there is no point in doing it, cause you can’t . . . commercialize it. I:

The conceptual framework [B]ut you have to be very clear about what innovation is, to me innovation covers the whole spectrum of things, it is business processes, it is working processes and it is also ideas generation for revenues, so I think you have a really big spectrum and I think what you need to be quite careful in your project [my research], is to make sure that that’s covered, because just because you don’t have lots of big ideas that generate lots of revenue, it doesn’t mean that you don’t have innovation, you know, if you can start off by finding ways to make the life easier you are still being innovative, to me it is a big spectrum, to me that’s essential, a quite big spectrum; so yes, to ideas and big projects that work really well, but also the underground should work well as well. (emphasis added) Technology Group A followed the innovation as culture approach, which acknowledges the uncertain character and uncontrollability of innovation, and the system in place aimed to create the ‘right’ environment, from within the ‘right’ innovation eventually would emerge. It is impressive the extent that this frame of logic had penetrated the thinking, the talk and subsequent actions of the staff, especially those who were actively involved in the initial move to support

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innovation; the system they implemented reflected precisely the assumptions and principles of this approach. In contrast to most approaches that try to support innovation mechanically by introducing a new tool or technique, and ‘forcing’ or simply ‘expecting’ the employees to use it (e.g. the Eureka method, explained in the previous chapter), the Technology Group A attempted to trigger a cultural change; they made clear that innovation should not be part of the routine, of the tasks that had to be accomplished, and they aimed to develop a culture, wherein innovation would be what people naturally did; in other words, innovation would be the way of living. The following senior scientist had participated in the first team, which was set up to be responsible for the revival of innovation in the Business Group, and explains the rationale behind it. I think it had been a general discussion that what was needed was not how to make people innovative, you know ‘it is your job to come up with new ideas, so get on and do it’, but the idea was that we would try and change the culture, so everybody saw that there was a need to innovate within their own job/ The desired innovative culture aimed to change both the new delivery-focused culture that made people think only of the short-term objectives of their work, but at the same time it intended to avoid the older scientific culture, where a group of people were responsible for innovation and the rest of the staff was dealing with the everyday mundane work, because that culture could act as a hurdle in the new concept of innovation – innovation as an embracing culture – that they were trying to build. The senior scientist explains further the issue: ‘in a sense it implies . . . it suggests that there is only a group of people that can do innovation and the rest of people who work here can’t do research and shouldn’t do innovation, or it’s not their job.’ The new innovative culture aimed to crack not only the short-term, delivery-focused commercial culture, but also the scientific elitist culture of Thornton. The previous account presented the question of innovation as an issue of democratization of the workplace; nobody should be excluded from the innovation game, because they were all equally competent to come up with small ideas, which could eventually grow bigger. Beyond the rhetoric of democratization, this open and all-encompassing view of innovation had another more practical objective. A member of the initial innovation move comments: the whole point with innovation is that you’ve got a funnel, where you have, at the front of the funnel you have to generate lots of ideas, because at the end of the funnel you will only ever have a few that you can actually commercialize, and, and we felt that we didn’t have a big enough effort in terms of generating new ideas. The more ideas were gathered in the beginning of the funnel, the more chances there were to come up with a marketable idea at the end. Ultimately, the

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message that they were trying to impress on people was that innovation should not be a responsibility of a certain group, but a way of working for the whole of the Business Group. ‘Innovation would be evident at all levels (i.e. business, administrative, operational, etc), and not constrained only at the advancement of technical knowledge’. The envisioned system was aspired to grow organically and expand beyond the boundaries of Technology Group A, to involve other Business Units, Market Units, and customers, where via communicative interactions more ideas would emerge. The conceptual framework matched the prescriptions of the relevant literature on this point as well. However in practice the Business Group kept the system strictly within its boundaries; ideas worth commercializing were far too precious to share with other Business Groups, with which they had now a competitive relationship, since only the most ‘valuable’ would stay in the Oil Co. picture. So, even though in principle the innovation system anticipated communicative interactions with other actors in the network, the benefits of these interactions were reaped strictly by Technology Group A, since it had the appropriate mechanism to progress them. Technology Group A was creating a new secluded culture, where the dominant value was not scientific knowledge, but business performance: the new innovation game was open for everybody within the Technology Group, because everybody could and should participate in improving the performance of the Business Group. However, it excluded all non-members of the group, and hence the valuable ‘knowledge’ of how to succeed as a commercial Business Unit stayed safe within the organizational boundaries. The system The innovation system at Technology Group A evolved through time and experimentation. Fundamentally, it was a combination of techniques for ideas generation (Ideas Chats, funding for inspirational conferences, etc.) based on the assumption of the social and communicative nature of innovation, and a funnel, which appeared as a website, i.e. the Ideas Machine, for collecting and progressing ideas to the appropriate route, whether this involved immediate action internally by the Business Group, or forwarding them to an external innovation funnel (mostly to Eureka) or, if the idea was more relevant to another business unit, communicating it accordingly. As mentioned, the system intended to support small, incremental changes that had the potential to grow big; the people who looked after the system persistently broadcasted that there were no ‘good’ or ‘bad’ ideas, only ‘small’ and ‘big’ – and any small idea could eventually grow big. The treat for ‘taking the time’ to submit an idea – regardless of the nature of the idea – was a voucher for a coffee and a muffin, and seasonal prize draw! Technology Group A tried, this way, to emphasize that there was no difference between ideas and all ideas were equally good and welcome. Nevertheless, the most significant part of the system was not the ‘Ideas Machine’, of which the Innovation People were taking pride, but the people behind the stage, who supported it. The initiative was started by the management

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and the drive of few scientists, who believed in the importance of innovating – and researching again. However, this first wave had not gone very far, because no one had the time to drive it – no one was willing to take this ‘responsibility’. Then, the position of the Innovation Manager was created and he, in his turn, put together an Innovation Team, of which the main task was to run Ideas Chats and assist people with issues around innovation funding, channels, etc. Innovation needed an hero – as the literature prescribes – someone to believe in the importance of innovation, with a vision, and with understanding of the political backstage of innovation, the rules, the key-actors and the innovation channels at Oil Co. – let us not forget that the ultimate objective of innovation was to get money from Oil Co. to fund the research projects – and, finally, one who would be determined to go against the current and defend the higher ideal of innovation. This role found its ideal performer – I will call him ‘Z’; Z was a scientist with a ‘charismatic personality’, as he was described by the supporters of the innovation initiative at the Technology Group, to the extent that one would believe ‘Innovation = Z’. Here Z is presented through the words of another key member of the innovation move: obviously you need the right person, because there are other people that do innovation on site, but they are not the same as ‘Z’ [I laugh], you’ll know what I mean when you meet him; and it was important, because you often meet . . . you’ll see some other people of the team and every each of us is a bit . . . [makes a gesture and we laugh], right? you know what I mean . . . that’s what you find, and you say how I can get along with these . . . and then you actually meet people . . . and I think when you meet people that have or haven’t put ideas in the ideas machine, you might find it explicitly, that’s the most interesting thing to me . . . it is a personality thing, I mean you can have an idea and you can have the machine, but if you don’t have a driver personality, you can just sit there and nobody will do anything about it. (emphasis added) Some interesting issues emerge in this extract: the success of the innovation initiative is treated as a ‘fact’. As a ‘fact’ is also treated the main success factor, i.e. the personality of first the Innovation Manager, and then the rest of the Team. Innovation is presented not as a socially constructed process, but an individual’s characteristic – ‘a personality thing’. This view is at odds with the wider and all-embracing view of innovation the group was promoting, i.e. that everybody is capable of innovating. Here we encounter a first instance of politics in innovation management: it is true that Technology Group A had a very good record of innovations, for which they had secured funding from various innovation channels, and for which they took pride. As Z underscored during our interview: yeah, there have been trivial ideas, nothing very big, but, you’ve just missed [the Eureka manager], he showed me a graph of the idea into the Oil Prod-

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ucts Eureka, and he said ‘oh, we can tell whether you are pulled off from innovation, because the graph of ideas drops off dramatically’, so all the ideas in the Business comes from Technology Group A. Securing funding for ideas was a key criterion for the success of the innovation initiative for the Business Units. Taking innovation as core value (and that was the assumption on the basis of which the interviews were conducted, i.e. we all agreed that innovation was ‘good’ and should be supported), then the people that had proofs for their innovativeness, either by putting ideas in the Ideas Machine or by getting a project into Eureka, were taking up the role of the ‘good guy’, of the person who was doing the ‘right thing’. This created a new ‘subgroup’ in the organization, the ‘innovation supporters’, who were different from the rest, as the previous excerpt described, because they were innovative, they had this gift of personality. Their personality made Technology Group A distinct among the rest of the Business Groups at the Innovation Park and successful in terms of innovations and financial performance. In simple words, the new innovation game had opened up opportunities for emerging ‘stars’ in the Oil Co. sky. Being determined to trigger a cultural change – a rebel move against both the serious delivery-focused and the previous scientific culture – the Innovation Team took the approach that innovation practices should act against hierarchy: they should not be imposed from above (i.e. by the management) and be formalized and bureaucratized, but rather be promoted by colleagues as a ‘fun’ activity, so that it would grow organically with the participation of all the staff. In the words of an Innovation Team key member: when you’ve been here 18 years – as long as I have – you get a lot of things that are forced on you by management on Safety, Quality . . . you have to do these things, but they become . . . hmmm [both laugh, she makes a gesture of being fed up] – I can’t describe that in words – another initiative, and we didn’t want innovation to be like that, we wanted people to think it’s not that management imposed it; so let’s make it fun, that’s the whole thing. (emphasis added) The commercial turn had created a stressed culture: people were taking their new roles very seriously and were trying to learn and perform according to the new rules. The commercial order had brought with it a great deal of paperwork and procedures that made people frustrated. The innovation initiative should emerge as an innovation in itself, it should be different and make a statement on its own right; it should be a step out of the everyday boring things, and hence attract the interest of people. The Team used humour, and their enthusiasm and confidence for the value of what they were doing in all occasions: from the initial presentation of the system to the Business Group (where little trolls were used to exemplify the idea of innovation system) to the posters in the corridors and the website of the Ideas Machine. The objective was to make innovation

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approachable to everybody, and especially young people, who were closer to the Innovation Team members circle, embraced indeed the move. I don’t know if you’ve seen some of the posters, they always make you smile and you think, well, you know, someone has put a bit of time and effort into just thinking about that, so other than the usual boring old posters, you got these little cartoons, have you seen the one sitting on the toilet, thinking? However, some senior scientists did not appreciate this approach, which they felt it was ‘silly really’ or at least trivial. The following excerpt is part of an interview with a senior scientist, who had been throughout the interview very enthusiastic with the issue of innovation and research at the Innovation Park; until we turned the discussion to the Ideas Machine, on which he obviously did not want to comment. Senior scientists could not see the ‘fun’ aspect of innovation, which for them was a much more serious question, and they refused to embrace the specific mechanism. R: Have you seen the Ideas Machine I: Urgh, yes. R: Where they use humour? I: Yes. R: And the Little People? I: Yes. R: It is a fun website. I: Yes. R: What do you think about this? I: Well, it so be, I would be pleased

website?

if it encouraged people to have ideas, [low

voice] but it does not really. It is important to stress, that their objection was not addressed against the all inclusive principle of ‘innovation at all levels’ (i.e. administration, operational, business, technical, etc.), nor the cultural change, but precisely against the trivialization of the concept through the way it was promoted, the ‘razzmatazz’ about the innovation initiative at the Technology Group. Severe reservations were also expressed as to who controlled the mechanism, and for whose benefit, implying, this way, the publicity and the power some people gained from the new innovation game. Nevertheless, the Innovation People repeatedly said that the innovation move was very successful within the Technology Group. It is worth mentioning, here, a minor criticism regarding the materialization of the conceptual framework into process: even though by introducing these tools and techniques they aimed to a cultural change, the criteria to assess the success of the innovation initiative were not the number of people participating in the practices, or the quality of ideas generated, or a change in attitude towards innovation or anything else, but

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purely the funding secured from Oil Co. for the ideas that started in the Ideas Machine and were forwarded to other mechanisms, e.g. Eureka. A key member of the innovation initiative in the beginning of our interview expressed her queries regarding the Ideas Machine, while she was explaining the wider attitude of the Business Group towards, if not innovation, at least the system: I think the way you structured it [my research proposal] is very good, and I think the actions at the end are very good, because I think this will throw out some of the anomalies we found; because in some of the discussions we had, is that people use the Machine and then they use it lots of times; to get people to use it is very difficult; we know that all those people have ideas, but why they don’t like it? do they think it is very trivial, do they just think that . . . or they don’t want to end up with more work . . . I don’t know what it is, but I think it’s interesting to ask people who HAVE contributed and then those who haven’t, I think would be quite interesting; because if the stimulus is reward, then we have to figure what rewards, if it’s not reward, then what is it that bothers them; another thing as well is that, I am an assistant, apart of Rob who is our Innovation Manager none of the managers or senior personnel have put in any ideas, so none of the Resource Managers, and none of the . . . Business Group Manager or any of those has put any ideas in . . . and I think that’s unusual in itself; I think they should be included in your group of people that haven’t put ideas in, not just on the job ground. (emphasis added) This account captures many issues that emerged during my fieldwork. First, the shared assumption among the people, who were involved in innovation, was that ‘people have ideas’. The creativity and the capability of people to have ideas were never an issue: people have ideas – small or bigger ones – naturally as they are involved in various projects. The problem was that these ideas were never gathered in one place, and most of the times remained in a piece of paper, or in people’s heads, who never took the time to forward them to the appropriate person or channel – ‘people aren’t short of coming up with ideas, they just don’t have the time to implement, to do anything about them’. The implemented system was set up to promote the attitude that ‘it is good to have ideas, and it is good to do some little research regarding those’ rather than purely to stimulate ideas to people. However, whereas all agreed that innovation is ‘good’ and the system is ‘good’ too, the management and senior scientists did not seem actively involved in it, and were leaving the initiative entirely to the assistants, students and administration staff. This was frustrating and against the initial expectations, because even though the rhetoric of innovation at the Technology Group emphasized the cultural change, fundamentally they pursued ideas worth commercializing. This effect was unexpected for the Innovation People, who found it ‘unusual in itself’. Hence, the question that arises is how people perceived the Ideas Machine and, more importantly, the concept of innovation.

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Voices from staff and management Interestingly, the rhetoric of cultural change, which had driven the ideal of innovation, in trying to make it part of the ‘natural order’ of the Technology Group, soon faded out. At the time of the fieldwork only those, who had participated in the initial innovation move a couple of years ago, still remembered it. The commercial discourse had overshadowed the principles of innovation, and consequently, the newly recruited young scientists could now only see the financial benefits from the implemented innovation system. For them, innovation in a commercial environment made perfect business sense, and they could perceive no inherent contradictions in the attempts to support it. The following prestudent, who used to work with the Technology Group for about one year, explains the attempt to support innovation at the Group in the rational language of profits. It is interesting how he constructs the answer as a win–win situation, by making direct reference to the individuals’ personal interests in and gains from participating in the game. what do they expect; business opportunities basically, I believe that the innovation tools are there to sound out that there are new ways, new avenues and basically new ways of bringing in revenue . . . I mean, I suppose a part of it would be to help the employees, if you have employees thinking outside of the box sort to speak, thinking in different areas on their own, it’s gonna broaden their own expertise as well, they’re gonna be involved in more diverse projects, they’re gonna think more . . . so it’s gonna help the employees as well. (emphasis added) The innovation system at the Technology Group was simply a local funnel to collect all ideas, filter the interesting ones and promote them to the appropriate channel, from which they would secure money; surprisingly, this view was shared among the new members of the Innovation Team as well, who during our interviews made no reference to the vision of cultural change. However, this is not to say that the innovation system had faded out; some people had embraced it, used it and praised its significance for the Business Group. Especially the significance of the Ideas Machine was promoted as its key tool. Among its most widely cited advantages were its locality, and the easiness of using the website, which facilitated the deposit of little ideas. The allembracing rhetoric was successful in involving in the innovation game the groups that were excluded so far. The following lab technician, who used to use the Ideas Machine extensively, and he had actually seen some of his ideas turned into small projects, comments: it’s great for me that I have little ideas in my head that they may be utter nonsense for now but they might have some use later on or whatever, I’ve got somewhere that I can type it all in and then forget about it for a while, it

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is not annoying anymore, because I’ve registered it and someone else can pick up on it if he wants to, it’s a way to offload it, does that make sense? Or as a pre-student involved in the management of the innovation system comments: I’ve never thought that my ideas are also important, so I think it helped me to express my own ideas more articulated and also to have a bit more confidence to myself, but I can’t speak about the rest of the Business Group. The open and all-inclusive discourse on innovation resulted in attracting the attention and the ideas of those groups who had been excluded from the research game before, and indeed at an increase – at least in the beginning – in the number of submitted ideas, of which the fluctuation followed the announcement of seasonal prizes. The following Innovation Team member comments on the quality of ideas in the Machine. Having lots of ‘crap’ ideas was considered natural and necessary to get a brilliant idea; the process of ideas generation via the Machine was still believed to be one where many little and irrelevant ideas could be combined and one brilliant would come out. However, the reality of the Machine was somehow different, since nobody (neither user nor Innovation Team member) really took the time to read through and get inspiration from all these ideas. It emerges that the problem of quality of ideas is common, when an all-embracing rhetoric is employed to popularize the funnel: oh, you can’t expect anything from people, I think the wonderful thing is that you are not constrained and you can put there basically a bit of rubbish and nothing happens, nobody laughs and ‘OK, well, listen, we shouldn’t consider it further, but well, it is a valid thinking’, and let’s face it . . . a lot of ideas put in the ideas machine is rubbish . . . but some are brilliant, and this is the whole idea of the thing; it’s like a brainstorming thing: for any single good brainstorming session unit, you’ve talked A LOT of crap; so the same thing, of course this is a lot of work for the people working in the ideas machine, but it is the only way. (emphasis added, Innovation Team member) The scientists’ voices More revealing and complex responses regarding innovation and the Ideas Machine came from the experienced scientists, whose views varied. As I mentioned, not all scientists embraced the innovation system at its present form; however, there were a few, who saw some positive aspects of it, regardless of whether they used it or not! The following scientist, who had a good record of innovative ideas into Eureka, interprets the existence of the Ideas Machine as a symbol of the innovation turn against the delivery-focused culture:

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The account reveals a few more interesting things: first, innovation and research were believed to be a scientist’s task, instead of anyone’s job, which had been nearly forbidden in the commercial order; for him, the ideas machine signalled the importance to do research, as they used to in the old days. Second, it introduces the time dimension of the new order as a hurdle to innovation. The new commercial organization required people to account for each hour of their working time; this new practice, together with the reality of having to learn and perform new tasks, which were fundamentally different from their training as scientists, and the short-term objectives of the main research they were undertaking now, made them feel the pressures of the new work order, and stopped thinking or being willing to pursue ‘innovative’ projects. The following scientist shared this view, i.e. he assumed that research and innovation were a scientist’s task, but he disagreed that the ‘symbolic aspect’ of the system was sufficient to drive innovation. He went on to suggest a formal structure for incorporating time for innovation into a scientist’s work time. As logical as this suggestion may sound – and this view was shared among many scientists – it remained an idea in the Ideas Machine: what was essentially suggested was to give back the scientists the exclusivity for doing research. However, the suggestion clashed with the new open and democratized environment that the commercial order was creating, and the ground where the innovation system was built, i.e. an open innovation game for everybody, because it would create a knowledge elite among the staff. Furthermore, this suggestion clashed with the rationale of commercialization, which aimed to use every single resource, and predominantly knowledge resources, to serve the commercial and short-term objectives. Clearly, then, even though a balance between the two cultures was proposed (commercial and innovative) by dividing the time and creating a dual working structure, this could have not been accepted at that stage of intensive commercialization.

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I mean, I have to say I am a bit of a cynic about it, because I believe that unless you physically have the time to put into that innovation . . . I think, I myself don’t have time to put through any innovation ideas . . . I suggested that if scientists [interruption from a colleague] I was saying that I was a cynic and . . . my view is that for the project leaders or some of the scientists there is a limit to how much of their time they can spend on innovation and I have an Ideas Chat, for as part of the Ideas Machine I think about three months ago and I made the suggestion that each scientist should perhaps be resourced to only do a 90 per cent of Oil Co. work and thus have 10 per cent free and they . . . in other words allocate quite a large chunk of a scientist’s time in order to do innovation, because just by having someone called ‘Innovation Manager’ and having an Ideas Machine, I don’t think we necessarily drive Innovation forward, but this is my view and if the management hear me speaking like this I’ll be in trouble [laughs]. (emphasis added) Time in relation to innovation and research was experienced in many different ways. The following young scientist acknowledges the time pressures as an obstacle to getting involved in innovation; however, he is happy not to have the burden of the ownership of ideas: so if I’ve put an idea in the Innovation Funnel, I’ve got to find the time to work on it, write the proposal and do the documents on it, and likewise with N’s money [other innovation funds], you know, if I say I want to do this, I take ownership of it, whereas with the Ideas Machine, you put an idea in, and it is in someone else’s area all together, so you just sit back and have your free cup of coffee. And further on he elaborates on the time pressures, as he experienced it: the big problem I think we have is time pressures on our resources, as I say everything has changed the past two years and we have become more commercial, people now have less time urgh, I find myself occupied eight hours or even ten hours per day, therefore I guess there are things that are more critical to my learning and personal development, as I said I am taking on aviation this year, therefore my course this year will be focused on aviation courses and they are very specific on what I am trying to do on a day-to-day basis; I am trying to find the time to say OK I’ll take another week off to go on a fuel conference it will be nice, but it will be one more week out of the office and when I’ll come back I will try to catch up with the work at the best, so . . . it’s difficult . . . it is more about prioritizing I think, that’s the problem we have with innovation, it’d be nice to do rather than a real part of your day-to-day job, perhaps. (emphasis added)

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The argument ‘no time’ was probably the most popular justification for not engaging with the innovation initiatives, even when the interviewees were acknowledging the significance of innovation for the survival of the Business Group as a commercial organization. The question is not whether people really had less time now, or they experienced the new order as time constraining and controlling. The argument ‘no time’, which was used predominantly by young scientists, was treated as a valid and accepted reason in the new commercial reality. The previous account talked about ‘prioritizing’ and ‘personal development’: by turning the R&D labs into a commercial organization, with so many career opportunities for its employees especially in market-related positions, the scientists were taking charge of their own professional development. Given these conditions, if innovation did not fit in their career plans, it would be difficult indeed to see why one would engage valuable time with it, instead of going on with their daily work. The following senior scientist suggests another dimension of why people were avoiding getting involved in innovative projects. He introduces the ‘risk-avoidance’ variable, which was used as a key argument against Oil Co. as well, when its attitude towards innovation was discussed. It appears that the current commercial and stressed culture had a low tolerance towards unfruitful experiments and wasted resources, which is against the nature of the desired innovation: But in fact, the management now do see it . . . have seen as their role to encourage people to be innovative, so if people are innovative and has actually led to something, it is difficult for the management to say ‘but you haven’t met your other targets’, but of course the majority of innovative ideas don’t want to do that, so people take the less risky . . . you see it is very risky thing to do that, to spend time on something that might not happen, whereas they fail to do the things that would happen if they were taking the time on them . . . it is a matter of how much risk individuals are prepared to take. R: Should or shouldn’t people take risk nowadays? I: Well, different individuals are prepared to risk different amounts, and this depends on where they are in their career as well, actually . . . if you are early in your career you don’t necessarily want to take risks, that can make you be seen as an unproductive person, and then your career would not develop, and you get in my age where it doesn’t really matter. (emphasis added) I:

However, the previous argument has a reverse side as well: the revival of innovation opened up career opportunities for some people, who were happy to engage in the innovation game, and used it for their future career development – and hence created the arena to play the politics of innovation. Innovation discourse created champions in the field, who knew the rules of the innovation game and they were interested in playing and winning. In other words, they perceived the turn towards innovation as compatible with their personal interests as

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researchers and employees at Oil Co. These people were the ones, whose ideas were promoted in other innovation funnels and they were getting funding for conducting the projects. In contrast with the literature on innovation, which identifies certain personal characteristics as features of innovative personalities, the investigation had not encountered this kind of distinct individuals, but only experienced scientists, who were interested in working in innovative projects and, by taking advantage of the rhetoric of innovation, set first the rules of the game, which now they almost exclusively were playing. This certainly created some dissatisfaction among their experienced research colleagues, who, in their turn, refused to participate in the local innovation game. The following two excerpts come from two senior scientists, who more or less categorically distinguished innovation from the innovation game enacted at Technology Group A, and they explained the possibility of following other routes for progressing their innovative ideas. However, I should stress here that these were senior scientists who had been working at the Innovation Park for many years, hence they knew the existing structures and processes, and also the politics behind; they knew how to move between these structures and promote existing ideas on their own – in their cases they felt confident for the quality of their ideas and their career development was not in question. because I’ve been putting ideas in other places, the mainstream work I do is on innovative ideas for things, so all the ideas that I get in that, which are connected with those things I put into my mainstream work, I’ve put other ideas into Eureka, which is the higher level, and as I said some of them are quite successful, and others of the ideas have gone directly into the kind of work we do here, into the programmes that are going on; I haven’t found it necessary to put it through that formal structure. (emphasis added) I . . . perhaps had a concern with some things going into the ideas machine didn’t have any depth, and we all . . . we all on our jobs in some way or another innovate, but we don’t actually recognize this as innovation, and you know, some guy might be working very hard on a research project and be really doing a lot of very impressing innovation, but he doesn’t sell himself to the management team or I don’t know and says ‘this is innovation’, he just says ‘well, this is part of my job’ and he just does it, and another guy might not be working so hard, he might be coming up with a very simple, not very clever idea, and he might say ‘this is innovation’ and then just sell it. (emphasis added) The last scientist explicitly referred to the momentum the innovation discourse had gained within Oil Co., and the way people were taking advantage of it, in order to promote themselves. The account implied that ‘innovation’ had turned into a ‘buzzword’, i.e. an empty signifier (a vaguely defined and all-inclusive

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concept), which gave various groups, but also individuals, the opportunity to manipulate it according to their interests. Beyond these power games enacted at the deep structure of the organization, the same scientist referred to politics at the surface level, by expressing his concerns regarding the (lack of) evaluation criteria, and the way the ideas were assessed: I think . . . I have a slight worry about how those ideas are assessed, because . . . what’s happened with some ideas, some of the ideas . . . the person assessing them thought that ‘oh, they are in my . . . in X’s area’, and so he sent these six titles from the web and said ‘X, you should be looking at these’ and I said, I just sent back an e-mail saying ‘no’, so from that point of view, if all those 300 hundred ideas are just . . . not being pushed forward the right way, perhaps I would have a worry about it, well of course some of the ideas have been pushed forward from the Ideas Machine . . . but . . . I certainly, I’ve probably submitted 12 ideas into it . . . in the first quarter of this year, and I haven’t submitted any for the past six months. R: Why? I: I guess I don’t have the time. (emphasis added) I:

This account emphasizes the problem of ideas being lost after entering the Ideas Machine, simply because there was no ‘strategic framework’, as one of the resource managers pointed out, to assess and push the ideas forward. At that time, the ideas relied upon the Innovation Manager’s judgment and the experts’ interest in spending some time and helping the process. It also indicates another problem that the Innovation Team had to face soon after: the Ideas Machine started to resemble a black hole, where ideas were gathered but not much was coming out – or rather only certain individuals’ ideas were coming out; little by little the newness of the Machine started losing its gloss. In the excerpt above the scientist used the well-known argument ‘I don’t have the time’ to point out his frustration from the way the process had developed – ‘no time’ was a justification widely accepted and unquestionable, for it drew legitimization from the new ‘commercial reality’ and shared experience. The management’s voice The attitude of the management towards innovation had been interpreted variously: some interviewees claimed that managers had always been supportive, whereas others said that they were indifferent. To do justice to the managers of the Business Group, the turn towards innovation started from them: they had first realized that the Technology Group had become too delivery focused and the ideas coming from the R&D programmes were not sufficient to sustain the (Oil Co.) Business, and hence their business in the future. Innovation was recognized in the scorecards of the Business Group as a legitimate activity, on which time and money should be invested. At the same time, a Resource Manager initi-

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ated the first workshop on Innovation – where the principles of the innovation model were agreed. Later on, the position of the Innovation Manager was created, and the system was implemented. Innovation time, i.e. time spent on thinking about ideas and conducting short experiments and research projects, was now recognized as an activity that could be included in the Personal Performance Contract, where employees set their targets for the year, and at the end of the year their performance was assessed against this. In other words, the management had acknowledged innovation as an important activity that had to be supported, and where they should invest time and money. On the other hand, the conceptual framework of the system prescribed that the management should be supportive, but not actively involved in pushing innovation practices down to people. The innovation system was suggested, rather than imposed, by colleagues, rather than management, and intended to grow organically as a cultural change. In other words, the management was in principle excluded from the ‘management’ of the innovation move. However, when the expected cultural change did not seem to happen, the staff expressed their expectations for the management to get actively involved in it: it turned out that apart from the Innovation Manager, (who was exceptionally resourceful in coming up with a great number of good ideas and feeding them into the Ideas Machine and from there to Eureka) no others from the managerial team seemed to partake actively in innovation. The management, from its side, was happy that innovation found a champion and a structure to support it, and they kept on getting on with their own tasks and targets, like the rest of the staff at the Business Group did. The following comment, coming from a Resource Manager, shows how managers were no different from the rest of the staff regarding their attitudes towards innovation; in other words, ‘innovation is good as long as someone else is dealing with it’: I am more than happy if somebody else . . . I’ve put one [idea] on ‘scientists are us’ and somebody else is doing it, and I am delighted that they are doing it, because I wouldn’t, I wouldn’t have the energy to carry it forward. Nevertheless, the management’s role in supporting the innovation move was not as passive as the previous accounts presented it; the management felt the need for innovation and supported it by providing processes and funds. The issue was that, at a higher level, the strategy of Hydro-Carbon Solutions was still driven by the dominant commercial rationale of cost-efficiency, which had severe consequences on innovation, because it created a different understanding about the move. This commercial rationality cascaded down and impacted on the innovation processes of the Technology Group. The following account gives the continuation of the story of innovation, as the Innovation Manager narrated it during our last interview; the account taps on some serious issues that impact on the development and success of innovation processes: IM:

What happened next, eh, I was called off . . . out of innovation to do commercial work, and only this last week I’ve come back . . . so for nine or ten

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months nothing happened; and on top of that we were told not to do . . . actually not to get more money . . . funding, because we were revenue rich and resource short, so nothing has happened . . . AT ALL. R: Alright, let me understand this . . . [he is getting himself a cup of coffee]. IM: So we were so successful the first half of the year. R: For all the ideas you had. IM: Yes, we got so much money, that we absorbed all the extra resource that were available in the Business Group, and then there was no extra resource available, and so they said ‘stop going after more money’ and then they said ‘go and work for getting this commercial customer’, which I spent nine months doing, and just heard today that we got it, so great. R: Congratulations. IM: thank you, so now I am back on my old job, and I’ve been told yesterday that we need more innovation money, so I should start everything again. R: So . . . [laugh confused]. IM: That’s the Oil Co. way [laughs]. R: Alright, it seems that the Oil Co. way thinks that innovation is a button that now I push and people are innovative. IM: [interrupts] That you push on and off. (emphasis added) The Innovation Manager pointed out some of the controversies in understanding innovation and acting upon it; first, the cultural change that Technology Group A attempted to bring did not go further than a change in the everyday talk; people recognized that innovation was important, but it had failed to become a part of everybody’s job – like the rhetoric was promoting. Innovation became the Innovation Manager’s game, which he certainly enjoyed playing, even on his own; while he was away, things had stopped, and now that he was back, he would start things over again. The view of ‘innovation as culture’ clashes with the commercial rationale, which drove the decisions and actions of both HydroCarbon Solutions and Oil Co. I have explained elsewhere how the move HydroCarbon Solutions to become independent, i.e. to have other customers beyond Oil Co., met practical difficulties, which were greatly due to the objects of activity of each Business Group, i.e. fuels, lubricants etc. As a result, Oil Co. could not but remain the main customer of Hydro-Carbon Solutions, and the sponsor of R&D activities. It needs to be stressed that this commercial rationality conceives innovation in pure economic terms and suggests a very mechanistic way of managing the process. Ultimately, innovation processes were perceived as a machine that the management could switch on and off, according to their current needs. Even if Technology Group A was heading towards a cultural change, at the end it would be Oil Co. rationality that would overtake, as more influential – for organizations do not exist in a vacuum, and their culture is shaped through interactions with other organizations in the network. From this story, it appears that there was an incompatibility among understandings of innovation: the management of the Business Group perceived innovation processes as a mechanism

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for getting money in the group in the short term. This understanding is quite at odds with the rhetoric of the business future sustainability. The following excerpt, coming from a senior scientist, illustrates these issues: I suppose it is a bit complicated, he [the Innovation Manager] could probably get . . . even if the people are overworked, he could probably get people to run the Ideas Machine and start putting up applications in to get this money, but at the same time M. [the Business Group Manager] has imposed another set of rules, again imposed by the higher people to say ‘you must run your department cost-effectively and we are not going to allow you to recruit more people’, so there is a disconnect, there is not a proper strategy for linking innovation . . . well if you think that an important component, it’s absolutely not the only component, but I would say an important component of innovation is the Eureka programme, that’s not particularly well integrated into the site: if the site is told ‘it’s all under threat and we must keep numbers down’, so the policy is not well thought through, if you say yes, we have all this money and CMDs say they will give you the money and R. [a Eureka manager] says ‘they can have as much money as they like’, there’s no point in having all that money, if at the same time the same . . . there’s always this perception I have from Oil Co. and a lot of other companies think that research is a . . . the cost on their bottom line, rather than it’s actually bringing money in, because it produces costs and – you know more about this than myself, through being in a Business School – but there are different ways of drawing up a company’s accounts, you can put the research on one line and make it look like a terrible cost that you have to try and reduce, and you can write it on another line and actually say that it has actually a value. (emphasis added) There are certain similarities between the two accounts, as they both point out the same issues, i.e. the cost-efficiency rationale coming from Oil Co. and the discontinuity between commercial order and innovation. Both accounts indicate the problem of resourcing the projects: the economic rationality allowed some money for innovative ideas, but in order to turn these ideas into projects scientists are needed. However, the principle of cost-efficiency prescribes to run the business with the least people possible; hence, no new recruitment could easily occur – whilst, people were fully utilized in the current short term projects, from which the business used to make money in the short term. Ideas might be suggested to overcome these specific problems each time, however, the problem at its core was simply that innovation, even though recognized as important, had not become yet a priority. More importantly, the rationale of cost-efficiency that imbued managerial thinking, personal interests and decisions cannot support the long-term and high-risk projects that were expected. The Innovation Manager gives a political explanation of the dominant short-term thinking of Oil Co. people, by describing managers as political actors who follow the dominant

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secured cost-efficiency rationality prescribed by their roles: ‘and the people in the business are on two to three years contracts, they don’t want something that will pay back in five years, they want it here.’

Conclusion Technology Group A early realized the benefits from investing in innovation – benefits that were expressed in terms of the business current prosperity and future survival. The implemented innovation system was based on the assumptions of the ‘innovation as culture’ approach, i.e. that innovation is uncontrollable and can only be influenced by providing the ‘right’ environment. The formal discourse proclaimed that innovation exists in small everyday things, and did not distinguish between ‘good’ and ‘bad’ ideas, but only between ‘small’ and ‘big’, hence it invited everybody to participate in the game with any kind of ideas. The rhetoric envisioned a cultural change, against the secluded and elitist scientific culture, which fostered blue-sky research, and also against the commercial delivery-focused culture, which focused only on product development. The rhetoric pictured an open culture, which would enable everybody (from students and administration staff to lab technicians, managers and scientists), to contribute longer-term, innovative research ideas in the innovation process – in other words, ideas that would secure the sustainability of the business in the future, the kind of ideas that were missing at that stage. I argued that innovation was wrapped in a veil of a democratization rhetoric, since it proclaimed the right to innovate for everybody; behind the rhetoric, what the management intended to achieve was to make full use of all knowledge resources, not only strictly the scientific qualifications, such as narrative knowledge and other skills or experiences. I also claimed that the role of management was very important in constructing the innovation move; however, they again were trapped in the commercial rationale, and could not actively spend time in ‘spreading the word’ of innovation. I suggested that the ‘eradication of responsibility’ for innovation was shared across the management at all levels of Hydro-Carbon Solutions and Oil Co., which indicates a dominant and accepted way of thinking and acting. The management was very happy that innovation had found itself a volunteer – the innovation hero – so that they could continue with their managerial ‘commercial’ tasks. The Innovation Manager, who took the responsibility to drive innovation at the Business Group, had a clear vision of what they should be doing, and had successfully achieved to secure funding for research projects, building the image of the most innovative Business Group at the Innovation Park. Beyond the ‘rationalistic’ understanding of innovation management here, which assesses how many ideas have been produced and how much money secured, the innovation move had a political aspect as well, which is evident in the transformation of power relations and personal or group interests. As knowledge and innovation discourses were gaining momentum, the innovation game opened up opportunities for differentiation at the individual and group level. The

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Innovation Manager became the only authorized person to decide over what is ‘innovation’ and what is not; being the Innovation Manager of the Business Group, and at the interface regarding innovation of Hydro-Carbon Solutions with Oil Co., he had the legitimated authority to ‘judge’ what innovation is according to the needs of their sponsors. This led to the emergence of ‘innovation stars’, i.e. people, who were acknowledged to be creative, and given that the parental company was still considered non-innovative and short-term thinking, their innovative achievements were wrapped in an epic veil – which could also be used in the Personal Performance Contract as proof of their distinct abilities. The prestigious innovation language game, once established as the only right way to innovate, and as a rebel move against the new dominant commercial culture, excluded those who did not participate in the processes that the Innovation Manager controlled; the innovation game became his ‘controlled area’, and those who did not support his system were left out. Resistance emerged from certain senior scientists, who, knowing the structures of innovation, took the responsibility for pushing their ideas to the appropriate route bypassing the controlled area of the Innovation Manager. The rest of the group members were happy that innovation found its Hero – hence it was someone else’s responsibility – and they continued with delivering on time their commercial tasks, with which they identified their personal career development. Nevertheless, the Innovation Manager did achieve to create a dynamic image regarding the innovative performance of the group, and this image created a new secluded culture: innovation discourse and practices created a local symbolic order, which unified all the members of the group, whilst distinguished them from the rest of the Business Groups, which were not so successful in these terms. The Ideas Machine tried to show both the business and the scientists that it was good to do long-term research and that there were benefits for both sides from innovation. The concept aimed to trigger a cultural change: it propagated the significance of small incremental changes even in mundane things, which could potentially lead to groundbreaking innovative projects. The system was compatible with the commercial environment, as it showed consideration for the time pressures of employees, and asked only for small ideas. At the same time it was taking away the burden of ownership of ideas from the generators, by giving them the choice either to continue with their commercial projects or to pursue their ideas. However, the Ideas Machine failed to engage the senior scientists, for their definition of innovation was more austere, since it was driving from the scientific language game, and furthermore, they felt the loss of power with the suggested discourse. What is more, the cultural change remained a utopia since it did not have an impact on the rigid properties of the commercial structure. Quite the opposite, the commercial culture, by changing the concept of time on site from long to short term, gave the employees the legitimated excuse ‘no time’ for not participating in the innovation processes. Cultural change is grounded on the implicit assumption that the ‘change leader’ has overall control over the environment they set out to change, and these laboratory environments are hardly found in the

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social world. Organizations and groups are parts of wider social networks and influenced by external uncontrollable factors and internal forces. To put it simply, the sensible innovation discourse and its practices were not enough to convince people to join in, at a moment when everybody was engaged in the overwhelming commercial game, and furthermore, when new recruits increasingly stopped believing in the value of scientific research for a commercial organization.

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Innovation management in a commercial environment Technology Group B

In this chapter, I present the attempts of Technology Group B to comply with the prescriptions of the innovation discourse. Technology Group B, which operated in the lubrication business, borrowed the Ideas Machine from Group A; however, their culture, expectations, understandings and interests were very different from the first group, hence they ended up developing a different innovation system. Nevertheless, this group too struggled to engage the scientists in the innovation game, even though here the politics at the individual and group level were not so upfront. The question that emerges from the examination of empirical material is how to support innovation in a commercial environment, since the two are based on fundamentally different and opposing assumptions.

The Ideas Machine and Eureka The innovation story at Technology Group B started one-and-a-half years after Group A. From one side the success of Technology Group A in terms of innovation, and at the same time the Eureka team, who were trying to get people involved in the process, made Group B consider the benefits from the innovation game: an Innovation Manager was appointed, and he, in his turn, tried with the help of the Eureka people and the Innovation Manager from Technology Group A, to spark an interest among the staff. First, a day off was organized, where the most creative scientists were invited; the purpose of the day was to generate ideas, which were inserted later in Technology Group B’s Ideas Machine. Technology Group A had already been recognized as the most innovative Business Unit in Hydro-Carbon Solutions, having to display a considerable number of projects funded by higher-level innovation funnels; that was translated into considerable amounts of money brought into the Business Group. The success was attributed to the Ideas Machine, which was considered the key tool of their innovation system. Hence, Technology Group B – and later on other Business Groups – saw the financial benefits from having a local structure to support innovative ideas, and so borrowed the Ideas Machine. In the beginning, the Innovation Manager proposed the two Business Groups to have a shared database, since by exchanging viewpoints more ideas for projects would be stimulated. The Innovation Manager describes:

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The people who drove innovation at Technology Group A had seen in it an opportunity to create a distinct culture that would lead them to business success in a highly competitive commercial environment. Innovation was perceived to be the competitive advantage of the Business Group, and logically it follows that the Innovation Manager would not like to share the business success with others. Hence, Technology Group B took the Ideas Machine and adapted it to their specific needs and understanding of innovation. In effect, during the fieldwork, this Business Group was facing some financial problems, which made the announcement of further downsizing an actual threat; later on further restructuring was announced, and took place in January 2004. There was much hope invested in this change, that it would strengthen the commercial direction and the market position of the lubrication business. The Innovation Manager expresses here his anticipation that this would give focus to the research processes of the business, bringing innovation closer to their customer needs, when at the same time the control would pass from the Operating Units to the business. [T]he [new organization] is going to run as a separate business and the decision on what is selling and what is not selling and things like that will be made centrally rather than through the operating units, but that’s going to have quite a big impact on research and development as well, because if the whole business is changing, the way we work with them, we’ll work close to the business, is also changing, so we are going through a sort of transition phase at the moment and it’s [the new organization], is supposed to be up and running by January 1st 2004, but it is going to be quite a big change. (emphasis added) Meanwhile, the funds for innovation appeared to be a good source for revitalizing financially the group. The senior managers realized this opportunity, and started pushing the staff to participate in the processes with ideas. The Innovation Manager describes the innovation turn at Technology Group B in purely economic terms, beyond the language of culture change and creativity, which was driving Group A: and the reason why Group B set up an Innovation Manager’s job was that there were announcements of sources of income for innovative projects, so

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things like Eureka and Investments R&D they didn’t use to exist until two or three years ago, but now they exist, it’s like an extra source of money for us. (emphasis added) The conceptual framework [B]asically the system is the same, basically the main difference really is that . . . we don’t encourage people to put in ideas on improvements within the department, in their Ideas Pipeline there are many ideas about how the department can run more efficiently; and we have a separate quality improvement process within our Technology Group, so we try to restrict our Ideas Pipeline on technical ideas for lubricants. (emphasis added) The Innovation Manager explained above the conceptual framework of the system; he described it as being the same with the one at Technology Group A, because they both had an Ideas Machine and a position of Innovation Manager to support it. The innovation system consisted of a single tool, i.e. the database (or a funnel), where ideas were collected and from there would be forwarded to other higher-level funnels. The cultural change that the Technology Group A tried to trigger by introducing the Ideas Machine was not part of his understanding of innovation – it seems that, when Group A passed on the Ideas Machine software, they did not attach the discourse from within its symbolic use for cultural change would emerge. Instead of the all-embracing rhetoric of Group A, which invited all types of ideas into the Machine, Group B restricted the Ideas Machine to technical ideas, excluding this way the staff whose jobs were not directly related to research. In other words, the cracking of the scientific elite was not an issue for this group. In contrast, their Ideas Machine was open for everybody from Hydro-Carbon Solutions to browse in the ideas, which reflects that, as opposed to Group A, they had not entered competitively into the innovation game; they saw themselves as part of the Hydro-Carbon Solutions scientific community rather than as an independent Business Group, and they would like still to consider their ex-colleagues as co-researchers, instead of business partners. In other words, even though the commercial order had changed the rules of research to an undisclosed activity, the people at Technology Group B had not given up their understanding of research formed by the scientific discourse. Nonetheless, there was another substantial difference between the two Groups; Group A had set aside a part of their budget to support small ideas and experiments, whereas Group B’s efforts for innovation aimed purely to secure external funding. In other words, its management saw the importance of supporting innovation purely as a way to bring money in, without being willing to invest a part of their resources in the process; furthermore, in contrast with Group A, innovation time was not formally recognized in the scorecards as a legitimated activity:

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Empirical we are supporting it, the main reason we try to support it is to get more money in, we are not in the same position as Technology Group A, because they have their own money within the Business Group, which they can support innovation, we don’t have that here. (Innovation Manager)

Consequently, the use of the Ideas Machine was reduced to a tool for collecting ideas, and could only provide support for the ideas generation stage, and then connected ideas with the appropriate funnel – predominantly Eureka. The mechanistic rationale of the innovation system here was stripped away of any strategic objectives that various approaches to innovation assert; the Machine worked as a database for collecting ideas and producing proposals, and the reason for adopting it was to ensure that little ideas, the kind that scientists naturally have, were not getting lost, since ‘even a small idea can trigger a bigger project’. [B]ut they’re always gonna be some ideas that sort of . . . sit in the Ideas Machine . . . and they don’t . . . actually get followed up on, but it is important to keep them there because some read that idea and that might trigger another idea. I think it is quite important not to throw away the ideas, in the past we didn’t have such an Ideas Machine, so people had some good ideas, and the ideas got lost when the people left or the ideas got stuck in the reports which was archived . . . when we set this Ideas Machine up. (Innovation Manager) The system The system consisted of the Innovation Manager, without any Innovation Team or assistant, but with focal points, who were responsible to promote innovation in other sites of the Technology Group. The Ideas Machine looked slightly different to its visitors: the comic element was missing from the website (there were no Little People characters on the web pages), no funny posters, or vouchers for coffee and prize draws, like there were in Group A. Below, the Innovation Manager justifies his choice to avoid the ‘fun’ element – or, for others, the trivialization – of the Machine: when I looked in the Ideas Machine it seemed that some people put lots of ideas in to get lots of free cups of coffee, so you see the ideas that we seek for getting revenue in, we . . . none of these ideas would be suitable, so we decided not to encourage those ideas. The system relied more on the Innovation Manager’s activities, who was trying to motivate people to send ideas in the Machine, either by talking with them personally or by sending them e-mails with updates regarding the latest innovation achievements. However, the problem of engaging people in the use of the

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innovation tool was equally difficult as it was in Technology Group A. The Innovation Manager addresses this issue, and suggests some sort of prizes to motivate people to participate. Oddly enough, the ‘time-pressures’ issue was absent from his talk throughout the interview. I think I am inclined to implement a sort of prize system, now it does say you may win a prize, but I haven’t sorted it out yet, but as I said, the fact that most of our staff is not here, I felt it was not appropriate to offer them free cups of coffee, I thought it wouldn’t do it . . . so that bit . . . I think we will start getting more ideas coming in once we offer them prizes. In practice, the Innovation Manager tried to engage people in contributing ideas in the Machine. Once an idea was submitted, then he would meet and discuss it with the generator, and together they would put together a proposal and send it to the appropriate funnel. The ideas were not forwarded to other ‘experts’ for reviewing it and maybe materializing it; the question of ownership of ideas had not been an issue here, at least at that stage, since the assumption was that the people who were submitting ideas were personally interested in working on them. The old value of scientific curiosity was still the main drive for the ‘knowledge workers’ to bracket off their commercial tasks for a while and undertake research. [B]ut the other reason that people would put ideas in is that, if they have a good idea for a project and for example goes through to Eureka, they would perhaps work on that project, so if they think they have a good idea a really good and it looks convincing, we put it to Eureka and then can actually work on their project and have a saying on what they do, and a few people have realized, there is a few people who have put pots of ideas in, but there is still quite a few people who haven’t been really involved, so they probably need a kind of a push. The Innovation Manager had ascribed to himself the role of Innovation Assistant instead of Innovation Hero, and most people recognized that he was really supportive in guiding them through putting together a proposal, and in doing an ‘advertising job’. Nevertheless, the process was not free from ‘surface politics’. Even though in principle anyone could put an idea directly to a funnel, the practice had introduced some restrictions; in order to reassure that the proposal would be successful, a committee would meet to discuss whether the proposal should be pushed forward or not. A scientist with seven months at Technology Group B, who was actively involved in the innovation game and had been working close to the Innovation Manager comments: I:

I think they are a constant group of people . . . one of them are from Marketing, one of them I think he is . . . I am not sure what he is right now, but he has a fuels background, and one of the problems is that he doesn’t often

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understand the ideas from lubricants, therefore he throws them back, he can’t understand the idea, he can’t see why this could be useful, and [the Innovation Manager] keeps on telling . . . tells me to push them back in, to look at them again, think of them in more detail, write a better description, and he can probably advise me on the best way to write a description. R: Is in this discussion, whether the idea will be pushed forward or not, is the person that has the idea participating? I: I don’t think so, it is completely . . . not an anonymous group, but it’s a group that meets behind the doors and, two of them are commercial, which I think it is fair enough, they say to understand the idea, but I think it is a bit like politics on the way, so that depends on who is supporting you, you can put down, say the marketing person, if you can put down the name of one of the people that works for him, for example the grease product manager, if you can say that the grease product manager supports this idea, then you will have no problem to get passed the marketing person, because it’s one of his people who says it’s a good idea, so it is a bit like lobbying and politics, if you want to get something passed you have to go and talk with the right person and get him to support you and then at the end you will have your idea through . . . so in a sense it’s already become corrupted [laughs]. (emphasis added) Trust between partners and alliances is a shared assumption among discourses on knowledge generation; however, here trust emerges as an illusive ideal, since when groups from different language games and interests need to collaborate, naturally, communication breaks down and mistrust arises. The question is not whether politics had really been an issue in judging the value of an idea, but the shared suspicion both towards all panels at all levels who evaluated the ideas, as to their adequacy and knowledge to take the decision, and towards the transparency of the process. The evidence from Technology Group B indicates that there was no system that in itself could manage innovation, only the activities of the Innovation Manager who, responding to the pressures from the top management for taking advantage of the available funding for innovation, tried to involve the scientists. The Ideas Machine was reduced to a database for recording ideas, of little use and value; the account below highlights the centrality of Eureka as the main innovation system. The Innovation Manager asserts this view and places the Ideas Machine at the periphery of the system – the Innovation Manager argues for the need to link mechanically the two pipelines; however, he did not explain why the scientists should report all the ideas for proposals to the Innovation Manager, and what the real value of keeping a record of all the ideas be, other than adding to the paperwork. [T]he thing with the Eureka ideas database is that it is not linked to the Ideas Machine neither of Technology Group A nor B, so it is possible someone to put an idea into Eureka without putting it in the Ideas Machine,

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so I try to keep an eye in both databases to see . . . I try to copy the ideas from Eureka and put it in the Ideas Machine, because we try to keep a log off of all the ideas, so this is sort of manual intervention, it’s not automated [laughs], it’s a bit of disconnect, because suddenly anyone can decide to put an idea in Eureka without telling anybody . . . even though they are not supposed to do so, sort of ‘let me know before you put anything in Eureka’, they can still do it independently. (emphasis added) I next discuss the scientists’ and technologists’ views regarding the system and regarding innovation. However, before we condemn the ‘system’ here as unsuccessful, due to the lack of an Innovation Hero and appropriate ‘culture’, or of a ‘rational process’, I need to stress that, Technology Group B was considered to be the second most innovative Unit of Hydro-Carbon Solutions, with a good record of projects in Eureka. This observation suggests that the force of the innovation discourse is more powerful in constructing a convincing reality, rather than the actual tools and processes that are promoted by the main approaches to innovation management. The scientists’ voices Due to the strictly technical nature of the expected ideas at Technology Group B, the investigation here explored only the scientists’ and technologists’ (i.e. the people, who would use the system) viewpoints. Compared to Group A, where most of the interviewees were relying on the Innovation Manager to sort out the innovation needs of the Business Group, here the interviewees were feeling strongly about innovation, and they had strong personal views about what innovation would be and how it should be supported. These views most of the times were addressed as criticism to the current innovation system and the broader Oil Co. structure and culture. Partly because of the politics and mistrust on the way the ideas were assessed ‘behind closed doors’, partly because of the Innovation Manager’s low profile, the ideas machine did not achieve to attract much attention from the staff, who most of them had not heard about it. Even those, who were in close contact with the Innovation Manager and were aware of the existence of the Machine, tended to consider it a trivial tool in managing innovation, when there were more important issues lacking. Most of the interviewees argued for the pressing need of a clear conceptual framework, which would set the objectives of a coordinated effort, and would address substantial issues that might impede the innovation process. The following senior scientist was insisting on this point throughout the interview. Ultimately, similarly to another senior scientist from Group A, he distanced himself from the Ideas Machine, which he considered ‘silly’ – even without the comic characters! [I]t is possibly worth to have it as a component, but I think we really ought as a company to do more strategic thinking, saying: ‘what are the problems

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This account made reference to the dominant view among the research staff as to the innovation model they should follow now that they operated as a commercial organization, i.e. ‘expose people to problems systematically and let them find solutions’. Obviously, this model was quite at odds with the one implied by the Ideas Machine, which supported small ideas and advocated the ‘anything goes and something good might come out of it’, and about which quite a few scientists from both Business Groups had expressed serious reservations. The following excerpt, coming from an engineer with ten years at Oil Co., exhibits elements of the particular culture of Technology Group B: we are taking those things serious once they’re planned, so money process for Oil Co. sponsorship, money process for working together with non-Oil Co. customers, those things are taken very serious by everybody, but for the moment the innovation side of things is somewhat frivolous almost, in that, it is not formal, it is an informal system, it’s a website you put ideas in when you have them, which is great, I’m not saying, because to innovate you probably need to capture the creative ideas, not constrain them, but I think what this might have done is actually it might have said, ‘actually this is not quite important, it is not a part of the formal planning, and you don’t need actually to do that, this is an option, it doesn’t go to your profile, because it is not formalized’, so what is missing, I think, the technology teams, within themselves to, because this is how we are structured, in technology teams essentially, to be thinking about what is the future and how do we get support for R&D. (emphasis added) And below, a young researcher with six years at Oil Co. provides a scientific understanding of innovation, which fundamentally clashes with the allembracing rhetoric of ‘little ideas’. Thus, it is no surprise that the scientists of both Business Groups did not accept cordially the Ideas Machine. OK . . . well my perception of innovation is that we submit something radically different, and we submit a project that can go from the start to the end;

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well people’s area of expertise is clearly lubrication, where I work, so I would expect to be around lubrication, but if you propose a small change to me, that makes one of our projects slightly better, then to me that’s not innovation. Innovation is if we can do something completely different, and actually change a whole product family, change the way lubricant is perceived, change the way our customers the way customers use lubricants ... or change the manufacturing process, that is you know, the biggest, totally different ideas. Most of the scientists stressed the lack of the conceptual framework, since they did not feel that the support from the Innovation Manager was enough to revive innovation. Through their accounts they emphasized the need for formal guidance and structure, since so far innovation was relying on each scientist’s understanding and willingness to work on innovative projects, and on the technology managers’ personal interest and support: we’ve never discussed it between different teams, so I think because we have never discussed it, each one tends to bring their own. It’s never discussed as a Department ‘what is Innovation, what are we going to do about it, how much time we are going to spend on it, what is the procedure’, I mean Eureka as such has been mentioned and promoted etc. but I don’t think that within the Technology Group there is a shared vision. It is true that most of the interviewees suggested their own definition of innovation; the issue that they were addressing was fundamentally how innovation could be supported in a commercial environment. The views differed widely, and arguments were ranging from supporting the need for fundamental research, because it would be the way of building the core knowledge for product development, to bracketing off fundamental and long-term research as expensive and time consuming in a commercial environment, and networking instead with universities, which could provide in low cost the essential knowledge. Nevertheless, there was common agreement that innovation is not a product development, because this relies on short-term projects and focuses on products and specific needs. Innovation should emerge as an idea out of the box, and this would require long-term research, and with uncertain results. The following technologist, with 17 years in Oil Co., gives an account of various types of innovation, included the business’ understanding of it, which was product focused; he acknowledges the uncertain and uncontrollable character of innovation, and he construes science as essentially a creative activity. This last issue, i.e. that science is fundamentally creative and returns value in terms of innovation, prevailed in scientists’ talk, who had always tried in every occasion, and now through the innovation revival, to prove the value of their scientific work to the business. R:

Yes, but before we talk about Eureka, let me understand what innovation is for you . . . because while you were talking about innovation you mentioned that it takes more than three years to show.

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To show returns on what you are doing urgh, I think innovation can be a number of things, it could be coming up with some improved process, improved technique, an improved product, that’s probably what the Business see as innovation. I think it can also come through better understanding of the science and the technology, I think sometimes innovation comes through serendipity, you look at something and then somebody else can say well, that could be used for the benefit elsewhere in the organization. I think innovation is creative and I think that’s often forgotten, a lot of science is routine and so on, but I do think that science is also a creative subject, built in thinking what you are doing, sort of while doing the work, and also when you write it up, you present it, you explain it, I think that’s creative as well, and certainly they are aspects that are coming in Innovation. (emphasis added)

The Eureka process Technology Group B concentrated on putting proposals in the Eureka funnel, which they considered the main funnel to support innovative projects, since its rhetoric and objectives matched with their own understanding of innovation; I remind that Eureka set out to support long-term and high-risk research. However, the rhetoric did not meet the practice, and the actual process of selecting projects had let many scientists down, when they started realizing that what was defined as ‘high-risk’ projects by the Eureka team, was not exactly what the scientists perceived real ‘innovation’ to be. A scientist, who had only recently joined the Group, but already had experience in managing innovation processes from his previous job, comments: I thought the Eureka would be for that, but a lot of the Eureka ideas are fairly normal, they don’t seem particularly radical at all, so I have the impression now, within this group anyway, within the company, Eureka is really a way of getting funding for the more long-term ideas, which Oil Co. don’t want particularly to fund themselves, the Oil Co. Business I mean, the sales related business, so I have to alter my impression of Eureka [laughs]. The main advantages of the Eureka method, i.e. the requirement of presenting a detailed business case, and the close control and assessment of the project in each stage through the funnel, had not been received as logical by the scientists who were called in to participate, and who now identified severe conceptual flaws in the process. The following technology manager gives a sharp account of the controversies in the process, and reveals the politics in terms of conflicting interests and incommensurability between the groups involved in the assessment of innovative projects. The account highlights a common concern among the scientists, i.e. that innovation was only supported in talk and not in practice, because the practicalities of the new process in reality created more problems to the commercial organization. It emerges that the rhetoric of innovation had not

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achieved yet to change the traditional view that innovation was a cost that had to be controlled and eliminated. [The Innovation Manager] tries to encourage people to have brainstorming meetings, add things in the pipeline that might be interesting and then he works them up to the business cases, because that’s the first down side with an idea: you have to make a business case, you have to go out and find, you see, before you even start it, before you EVEN START you have to have a business case . . . isn’t it just a sad way to do anything? I mean you can’t even have an inkling of an idea, you don’t even know whether it’s going to work or not, because it has to have a business case, and then it is reviewed by the people in the business, . . . and what’s more they are people in the supply chain of the product, and people in the supply chain are just transactors, they have no interest in anything innovative whatsoever, imagine that innovation just adds to their problems, because at the end of the day innovation means usually single solution, point solution, and they have to go and negotiate a price with somebody for a single point solution. They would pretty much like to have a commodity so they can play people off against each other, because they’re so bloody thick that they can’t see how to handle a single point of negotiation . . . supply chain . . . they are from Oil Co. from all around, from the operational units . . . these are the cost-cutters, innovation they say is expensive, even when [we talk together]. R: [laugh] And they say it at the same time that they try to support innovation. PS: Even now, yes, this is what’s wrong, yes, but it’s they way they are trying, they pay lip service to innovation, they support it by saying you have to have a business case, that’s not innovation, this is commercial business, that’s exploitation, not innovation. (emphasis added) PS:

Nevertheless, Eureka was strongly associated with the innovation turn, and slowly found its place in the everyday talk, even as a joke at this early stage, at least for those who had an interest in innovation, or whose work was on an innovation project. The following engineer was brought into Technology Group B from Oil Co. Operational Units one year ago, in order to give a commercial flair into the Business Group. Given his commercial background, it is no surprise that the advantages he saw from innovation were translated purely in shortterm survival via funding opportunities. In his account, another hurdle to innovation is identified, i.e. the time–delivery culture and the workload that takes priority over innovation in a commercial environment: no, no . . . well we talk about it over lunch, if someone of us has a new idea, we say ‘oh, put in Eureka, that’s a good idea, put it in Eureka’, but priority is working on the programmes, we have deliverables. Eureka is an innovation programme that takes lots of your time. If people are tied up with time because they have to deliver their product developments or reports or

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Innovation and commercialization So far, the dominant understanding among scientists described innovation as uncontrollable, uncertain, highly risky and one that necessitates a long-term horizon to actualize. Even though in talk, commercialization set out to support innovative projects, it turned out that the very nature of the commercial environment clashed with the nature of innovation and reduced it to a rigid articulation of ‘exploitable innovation’, which emerged from the researcher’s free time and personal interest. The following passages elucidate the contradiction that was encountered in applying the theory of innovation management in practice, as voiced by the ‘users’ of the system, i.e. the researchers. I think it is a challenge for organizations. I think with the commercialization you have to have control, you have to have control on budgets, deliverables, eh, if you work for a customer you obviously don’t want to over-deliver what you said, you don’t want to under-deliver, you want to get it just about right and so on, and of course in that sort of controlled environment especially in a cost-conscious as we are now, it’s very difficult to happen it is very difficult to have the space to people to innovate and be creative. (technologist with 17 years in Oil Co., emphasis added) The account constructs ‘control’ over ‘budgets’ and ‘deliverables’ as the natural order in a commercial organization. Interestingly, however, it makes a distinction between ‘controlled’ and ‘cost-conscious’ environment, leaving some room for doubts as to whether all these new financial control mechanisms and processes were the only way to manage. The following passage coming from the interview with an engineer in the post of customer focal point of the Business Group, who had spent ten years at Oil Co., gives further insights into the nature of control that was being developed; he describes softer ways of assessing the activities of the Business Group instead of the ‘hard core’ and financially rational measurables of commercialization, which resulted in the suffocation of innovation: so I think that bit was always there, but the measurables were much more in terms of whether the customer was satisfied than in terms of how we had

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made a margin calculated in particular financial system that we have today and we made a margin on that activity, or have we, we planned to spend a certain amount of money, and we actually spent less, or more of what we planned to spend, so people spend a lot more time now focusing on, and I call it financially possibly sensitive measurables rather than real planning. They are related to money, that is, we measure the activities, we put immense effort measuring the activities, so we have measures of efforts, we express that in terms of money and we spend a lot of time nowadays on perhaps we are making the margins or not of that activity, possibly more time than it’s healthy, someone could argue, we might have lost this balance between technology and commercial side. (emphasis added) Similar to Technology Group A, the research staff in Group B felt overloaded by the bureaucratic procedures and control processes that were considered extreme, sometimes unnecessary, and definitely time consuming. Furthermore, the ‘time delivery’ scheme, which made the Business Groups take pride in their customerfocused services, was presented as the greatest enemy of innovation time. The following passage, from the interview with a young scientist with six years in Group B, presents the rationale of commercialization and the clash with innovation as a cultural issue: there’s a penalty for delivering late, that’s why it’s called ‘time and delivery’, so you’ve got to get it on time, when you said that you’d do it, and you’ve actually got to deliver it. You can’t say ‘I haven’t quite finished’ it is not acceptable, so that’s a constraint, so, yeah, the penalty of not meeting it, is you get less funding for that project, or in principle the project is stopped . . . so, so, I mean, that’s good, it’s a rigorous practice, why not? It is fair the people to know when it is going to finish, it is fair you’re asked about the chances of success and I think it is a natural result of that, that your sponsor, anyone’s to sponsor, and he wants to pin down those ten things to work, doesn’t he? That’s the normal business, but you have to ask, if people work in that mindset in the majority of time, are they likely to propose terribly innovative projects? It seems unlikely to me, yeah? That’s a cultural thing. (emphasis added) ‘Time’ was a great concern in the new commercial order. From one side the scientists were used to work on long-term projects with flexible deadlines and without strictly defined deliverables, whereas now commercialization changed not only the time horizon of work from long to short term, but also devised a system to measure time and translate it into cost; each activity had a special number, by which the staff had to account for the time spent on it. As the following interviewee points out ‘there are no time-free activity numbers’, which means that there was no number for justifying the time spent in thinking about an idea. Once Eureka approved the idea, then an activity number was

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given; however, the time spent in translating the idea into a proposal could not be justified, and thus had to be in the scientist’s own free time and will. Nevertheless, this illuminates the rhetoric of ‘little ideas and anything goes’ that the Ideas Machine propagated, and the Innovation Managers’ interest in this system – which unfortunately conflicted with the scientists’ understanding of innovation: there are no time-free activity numbers. You can’t just call a time and write an activity number, you have to give an explanation . . . so that’s probably the biggest block for innovation, the time to sit and think about; now, the time to sit and think about is dictated by where you are writing your time. (scientist with six years in Oil Co., emphasis added) Together with the short-term working horizon that commerciality had created, which translated into short-term projects and thinking, and clashed with the long-term nature of innovation, its second feature, i.e. high-risk, was constrained by low-tolerance of failure, in other words risk-aversion, and was justified as a way to protect the financial investment. [O]ur research and development is done on the assumption that you will achieve at least 80 per cent, and that’s a hot concept, because . . . it is a new concept as well. It didn’t use to be like that, but you could have your research in 50–50 failure rate, if you are really doing research. My experience from the university research is half of the things shouldn’t work, here it’s 80 per cent should work and 20 per cent shouldn’t work, tough, yeah, so you probably in terms of like daily, with the majority of the projects people are working on, there has to be a fair chance of succeeding, so is it innovative? No, so it might lead on to the question of what you’re saying, what are the systemic problems with innovation on this site, if you are expecting, if people have history or expecting the projects to be 80 per cent successful, how likely is that a true innovative project is going to be 80 per cent successful, so we have a management culture imposed that says you’ll do things that are 80 cent successful because that allows us to build the customer. (emphasis added) Most of the interviewees involved in innovation from all levels and positions – scientists, managers and even the Eureka team – acknowledged in their interviews the short-term and risk-averted culture of the corporation. Another problem, where all these views met, was the problem of resourcing the projects, since ‘nobody here is employed with any slack in their time’. The following scientist comments on this issue, which ultimately questions whether commercial work and innovation can be undertaken at the same time by the same pool of people, i.e. whether innovation and commercial work can be supported in a single structure. The question of resourcing was a simplification of the core

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problem of managing innovation, which translates into: (a) managing the pool of ideas in the website; (b) managing the scientific time and (c) managing the sponsors’ interests. [I]t will probably take dedicated people whose jobs will be to take projects from start to finish, there is a man-power factor, yeah? So if something illuminative comes up, I am interested to see how these people will staff that project, yes, basically, it has to do . . . it’s my experience really, recruiting someone here is a fairly difficult task. There is quite a lot in the recruiting process, and typically you take a PhD scientist, and even then for a PhD scientist, it takes three years to really understand the lubricants business should we say, or the chemistry of lubrication, so a person is probably useful after the third year. So how do you manage to have a pool of people that you can actually get to work on projects, unless you have a continuous improvement project, and at the moment we are probably on the stage of having major projects, so we haven’t yet got that pool of people. I don’t know . . . we are talking about a technical project that needs someone with the knowledge of the subject to do, and I don’t think these people are available on time; so the real challenge with innovation is how to manage the skill pool you need. These people don’t have to be innovative themselves, but they need to be able to carry on a project. (emphasis added) Even though the issue of resourcing projects was acknowledged by scientists, the Business Groups’ management and innovation managers, a key member of Eureka expressed a more cynical view; he didn’t believe that ‘time’, ‘resourcing’, and ‘rewards’ were the most significant hurdles for not having good ideas, and instead implied that scientists were simply not particularly creative – a view which reflected the business’ ‘older’ view regarding the R&D department: we can manage it [the project] yeah, we do, I do that in [the other innovation funnel]. It is not a particularly detailed engagement, but there is some engagement, and we can suggest that they should work with other groups, yes, of course; but as I said, that’s not been a problem so far. The resourcing issue has been a problem, and the project idea, the project ideas have been a particular problem, I think that it is fair to say, if you get good ideas we could support them and the reason for that it isn’t that there are lots and lots good ideas out there but people don’t have the time to work on them, it’s because they don’t have good ideas, it’s the other way round; if you have an idea and you want to do it, we can get you the money, we can provide the money, even if we spend all the budgets. If it is a very good idea we can provide the money, if you need millions, essentially there is no constraints, Oil Co. is a rich company. If you need resources to develop good ideas, you can get them; when people say ‘I’m not putting ideas in, because I am not being rewarded’, that is not in my experience true; I think people don’t put

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The question of rewards had been addressed by the Innovation Managers, but it was not a common concern among scientists, who still felt that their work and skills were not appreciated enough by the business, despite the vivid innovation talk. The following technologist highlights precisely this shared feeling among researchers, who were driven by scientific curiosity and interest in simply doing research: I think for a while when commercialization started it got neglected, for obvious reasons . . . people were focusing on different things, but I think it is back with a higher profile now, and people are encouraged to do it . . . I think it needs more encouragement in terms of if people are innovative it should be recognized, not necessarily financially, not like a prize for the best ideas, but in the culture. I think we have to work on that, because I think that’s where most of the people get the buzz from, you know doing good scientific and technical work and that being recognized. I think that’s as important as the financial remuneration, I think it is not valued enough in the organization. (emphasis added) In Chapter 4, I argued that the commercial turn had changed the necessary skills sought from the newly recruited staff, by giving emphasis to social competences over scientific qualifications; this had as a consequence caused the erosion of ‘scientific ethos’, and according to some senior scientists, had also an impact on the ability and the willingness of people to be creative and interested in trying out new and uncertain research ideas. Much of these arguments appealed for legitimization to the discourse around the Innovation Hero, where innovation becomes the higher task of certain exceptional individuals, who are not like ‘the rest’. Yet, there was indeed a change in the recruitment criteria, and the new culture and structure had limited the eagerness of people to take ‘risky’ initiatives; to put simply, as a senior scientist noted, commercialization had created a ‘civil service culture’. The following technology manager points out a serious issue for innovation, i.e. the avoidance of responsibility, which the innovation funnels set out to address by disengaging the idea generators from the responsibility to undertake the project: R:

I:

At least, if you don’t get any kind of rewards, money or something, because of your idea, do people look more prestigious, is it good for their status in the Innovation Park if they have a good idea? No.

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So what is really important, who is considered to be a good employee here, if not a creative one? I: A good employee is probably someone who just says ‘yes’, who follows the management lines and works seven days a week. R: Yeah? I: I would say so, it is very little about what you return, or what you bring to the job or what you do . . . we have a culture of . . . eh, mainstream that tells it all, that’s it, we run into a culture where we don’t want to account for responsibility, only ‘yes-men’, which is not very good for innovation. (emphasis added) R:

Politics and the innovation game In contrast to Technology Group A where innovation had stopped due to the absence of its Hero, the end of my fieldwork found Group B going through more transformations that influenced their innovation processes. The Business Group continued its efforts to get projects funded by Eureka; however, some ‘inexplicable’ rejections of ideas had frustrated the few scientists who had believed in the innovation move, and invested their time in developing proposals. Whatever the reasons for rejecting the ideas might have been, the fact remains that people had worked on these proposals in their own free time and will to do research, and it was no surprise the degree of the dissatisfaction that ‘unreasonable’ rejections had caused. The following passage comes from an engineer brought in recently from an Operation Unit, in order to give a ‘commercial touch’ to innovative ideas; nonetheless, even him, he found it difficult to understand what kind of innovation was expected by Hydro-Carbon Solutions. The difference between ‘us and them’, the ‘business and the scientists’ is clear here as well, and furthermore the scientific conviction that their definition of innovation is the ‘right’ one: maybe you’ll get a different answer if you talk to someone from the management, but in our team I think it’s the contrary, we are very frustrated by the fact that a biodegradable, our best environmental, one of our environmental friendly products didn’t make it to Eureka. OK we have the energy efficiency funded, so unless . . . our environmentally friendly product sits in the back, absolutely against the philosophy of innovation, and we spent a hell of a lot of time trying to get into it, because it could work, so the frustration as a result of that I think justifies that we have left behind innovation. If we come up with an idea now, I think we would be very, very reluctant to propose it to Eureka, even more to customer organization who don’t know about innovation, awful in terms of innovation, so . . . and probably I will not have any idea for the next year, when all the deliverables will start to pop up, which is a shame really, but I will see what happens. (emphasis added)

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It would be easy to say that if one idea did not fit in the definition of innovation of one funnel, then it could be forwarded to another more appropriate one; however, definitions, regardless of how clearly expressed, are made out of words that are interpreted each time they are uttered, depending on the actors’ particular interests and understandings. In practice, ideas may be killed because they fit in more than one funnel, and ultimately none, since no group sees some immediate benefit from funding it. It does not come as a revelation the fact that the openness of Eureka rhetoric and the extreme willingness to fund interesting projects at any stage meets its limits in practice; the same interviewee explained: well, it was not really innovative they [Eureka] said, it had to be funded, they said, it had to be funded by the marketing group responsible for these fluids, and the marketing group said ‘no, this is about environment, it’s about hard science, we are not going to fund that’; but the marketing group in the new organization will be the ONLY group responsible for funding. So you see where I am coming from, and I don’t blame marketing. They consider and they are judged upon their internal investment and the margins they make their products. If I were them I wouldn’t fund an out of the box idea. That’s common sense, and that’s gonna be the case next year, but that was not the reason, according to Eureka it was not so much to do with innovation as such, it was a product development, but the people who were supposed to fund the product development, they said that ‘it has nothing to do with our core business, as such, we like your idea, but present it to us once it’s finished, but until that time, try to get your money from somewhere else’. The passage made reference to the forthcoming commercial transformation. In Chapter 5, I discussed the intentions of some Business Groups to take control over the money of Eureka, which is meant for high-risk projects, and invest it in product development, where they could see their business financial interests. Now, with the new organizational structure, the Business Group would take overall control of all innovation programmes and decide what would be worth funding, and where to allocate its resources, according to their understanding of innovation needs. This would have the following consequences on innovation: first, Eureka would be disconnected from the new organization, hence non-core projects would be excluded; and second, the projects would be assessed purely on the basis of a rigid economic language and approved by the commercial line manager, whose aim was clearly product development. [T]he way I see it is that because now in 2004 the commercial manager will be responsible for the budget. Again it comes down to an investment, to pay-back times, etc. so even in the very beginning of an idea you have to start to defend, or perhaps to justify or explain the benefits from this and in the beginning, you know, it is the most weird, we have to invest an amount of money, before we even know if we will get there in the end. So I see it as

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a major change, it’s no longer ‘XY’, who has to decide or to justify a specific programme, it’s gonna be a commercial line manager. (emphasis added) The question that arises is not whether it is right or wrong for the Business Groups to decide by themselves where to invest money and time, and whether this is good or bad for innovation. Given the recent history of commercialization in the corporation, the loss of innovations and the realization of the significance to invest in longer-term uncertain projects, the question rather becomes why the pendulum went back and more intensive commercialization was decided. It is clear that the struggle over controlling financial resources takes priority over any other rationality, and the evidence so far indicates that the rhetoric of innovation cannot compete with this rationality, and thus, in practice remains a cost to be eliminated and the first activity to stop, as it has been the case so far.

Conclusion In this chapter I presented the implementation of the Ideas Machine in Technology Group B, and the attempts of this group to comply with the prescriptions and reap the benefits of the discourse on innovation. The Innovation Manager of Technology Group B borrowed the Ideas Machine – stripped away the ‘cultural change’ rhetoric – and adapted it to his understanding of how an innovation system should be, which recursively constructed his role as Innovation Manager. Being less political or ambitious regarding his career development via innovation, he acquired the role of the Innovation Assistant, who would be there to advise the ideas generators about how to promote successfully their ideas in the appropriate innovation funnel. The Ideas Machine lost its role as a symbol of the new innovative era, and was reduced to an electronic log of ideas. The scientists recognized Eureka as the main innovation funnel for the Business Group, because that funnel was created in principle to develop the kind of projects that matched with the scientists’ understanding of ‘real’ innovation, i.e. uncertain, with high-risk and developed in a long time horizon – the kind of innovation that had stopped together with the R&D function of the site, during the commercialization process. Eureka was developed on the principles of the ‘innovation as rational planning’ approach, which, in order to control the financial risks, asserts the evaluation of an idea in terms of its financial benefits, in a defined timeline. There emerged the incompatibility between the two: the presented evidence indicated that the technologies of commercial rationality, i.e. the rules and procedures, which were developed to control a commercial environment, are not adequate to support long-term and risky innovation. Commerciality sets out to create a controlled environment with clearly defined and therefore short-term objectives, which are translated into numbers, the language that all ‘rational’ managers should speak. This rationality creates an environment, where short-term thinking and actions predominate, and plans for immediate profits are always preferred

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and promoted at the expense of the uncertain longer ones. In this environment, long-term and risky innovation cannot thrive, for its nature is fundamentally different. Innovation did not encounter difficulties only because of the properties of the commerciality, but also because of people’s experiences and understandings of the requirements of commercialization. Structures and rules can be bent, and exist as rigid entities only when people perceive them as such; in other words, people (both managers and staff) understood commercialization as a stressful and tightly controlled process, where short-term commercial deliverables should always take priority over longer-term projects. They went on to enact this reality, without seeing, at least at that early stage while the rules of the commercial game were being discovered, the alternative worlds. As one of the Eureka members commented ‘yeah, you change reference indicators, you change organizational structure, what is not changing is the world . . . the world people invented . . . the shared.’ Nevertheless, both the Ideas Machine and Eureka tried to change this invented world; they tried to show both the business and scientists that it is good to do long-term research and that there were benefits for both sides from innovation. Eureka was developed on a scientific articulation of innovation, hence senior researchers with an interest in science saw in it the opportunity to work on some interesting projects again. However, like the Ideas Machine, Eureka failed, too, to provide a good enough motive for people to engage into the innovation game, other than the individuals’ scientific interest. The ‘rationally planned’ process of Eureka was enacted once the generator submitted an idea, and did not address the issue of rewards – neither financial nor moral. It did not include in the process design the earlier stage of incentivizing that is especially significant in a financially driven environment, which is characterized by an increasingly individualized workforce and where the ‘scientific ethos’ and values do not provide a system of reference for the majority of employees any longer. Nevertheless, this should not lead one to think that innovation cannot exist in a commercial environment, only that there are issues that are not addressed either with the cultural or with the rational planning model. The difficulties that the management of long-term and uncertain innovation in a commercial environment encountered, were rooted indeed in the incommensurability of their assumptions, and at a first glance it may suggest that the commercial and innovative processes cannot run in parallel. Essentially, it appears there is a need for a dual structure, which would split the time and tasks of scientists into innovative and commercial, and hence, innovation would find its place independently from the commercial business, but still in a commercial environment.

8

Conclusion The commercial condition of knowledge

In the empirical chapters, I discussed the transformation of Oil Co. traditional R&D laboratories into a commercial environment and the implications that this move had on the site and employees’ identities, but more importantly on people’s understanding of innovation. I presented evidence of changes in the power relations that were being redefined in the new organizational order, where the commercialization discourse and values overrode the previously dominant scientific language game, resulting in a ‘commercial innovation’ discourse. In this chapter, I elaborate further the findings of the empirical chapters, in the light of the theoretical framework of power and innovation, and their significance for organizations and for innovation. In particular, I discuss further the suggestion that commercialism changed basic concepts of the traditional scientific language game, i.e. knowledge, research and scientist; I explore in more detail the new innovation language game, and discuss the implications it has on our understanding of knowledge and innovation, and the actions it shapes.

The rise of commercialization In Chapter 2 I discussed the nature of knowledge, and the conditions and processes that attributed knowledge a commercial value in post-industrial societies. There, I have claimed that the wedding of scientific knowledge with an economic discourse, and the naturalization of the authority of managers to decide on the elements that are wedded to the expanded economic discourse have attributed all elements (included scientific progress), an economic character. It is important to underscore this point: the economic discourse meets its limits when embracing progress – for this move it needs elements of the scientific discourse, which traditionally has been identified with progress – hence it rearticulates its elements to include values of science in its web of relations. The two, as I noted then, intermesh in a powerful discourse, where scientific progress equals strictly economic progress – leaving abstract and cultural knowledge beyond the common understanding. In the empirical chapters we actually observe this wedding – i.e. the dislocation of economic discourse and re-articulation of scientific elements – at the organizational level this time, and in specific, while it invades a traditionally

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scientific site. The data in Chapter 4 presented the dislocation of an economic discourse, i.e. its failure to sustain the business of a technology-based company, and the necessity to embrace innovation. I remind here, that until the mid 1990s oil companies had considered R&D an expensive and redundant activity with no strategic importance, and most of them had shut down their laboratories or at least cut-down the funds for research activities. Nonetheless, the revival of innovation discourse, which attributed knowledge a strategic importance for business growth, has turned the R&D labs (and by this I refer to the knowledge pool and skills) into a precious asset that could be further exploited commercially. The revival of innovation has opened up new commercial opportunities for oil companies, as much in terms of customers, as in terms of re-inventing their identity from an (unpopular) Oil Company with no sustainable future, to a much promising Energy Company, with many opportunities for growth. Table

Table 8.1 The sovereignty of economic rationale Scientific discursive order

Commercial discursive order

Relation with the parent company

No autonomy; lose control

Take decisions that the business approve; feel ‘trusted’ by the business

Activity of Technology Groups

Research and development

Research and development and technical services

Innovation

Technology-driven

Market-driven

Identity of business

Oil company

Energy company

Identity of research site

R&D labs; research organization

Global-based consultancy; technical support organization

Structure and work design

Clear hierarchy; work is interdependent; members share the same physical space

Blurred hierarchy; virtual teams; independent individual work; customer-based relationships; ‘flexibility’; accountability for time

Core skills

Scientific rigour; analytic thinking; intellectual capacity

Communication and presentation abilities; managerial skills; ability to deliver on time

The knowledge worker

Scientists

Extended intellectual assets: scientists; lab technicians; managers

Time horizon

Long term

Short term

Means

Loosely defined programmes

Control: measures and deliverables

Results

New knowledge; discontinuous innovations

Cost control; growth

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8.1 presents a number of changes, as identified during my fieldwork at HydroCarbon Solutions. The invasion of commercialism into the scientific site becomes possible via the re-articulation of its web of relations, and a number of structural and cultural changes. The latest management trends advocate the importance of flexibility, teamwork, trust, collaboration and even conflict (Gibbons et al., 1994; Oliver, 2001; Adler, 2001), which supposedly would support organizational knowledge and innovation. Here we observe that the scientific order is structure-wise defined by a rigid organizational hierarchy, where relations among staff, departments and units are relations of high interdependency. This well-structured environment allows the scientists to cope with the uncertainty that characterizes long-term scientific projects. However, this environment in a business language is translated into a lack of measurable processes and immediate results. Probably, the most problematic concept of the scientific order for commerciality is the concept of time, which is perceived as a loosely defined long-term horizon, and thus reinforces the impossibility of controlling, measuring and ultimately delivering to customers. Clearly, the scientific discursive order is imbued with the values of knowledge, which set the ground for radical technological innovation; however, these practices hold ‘uncertainty’ as a core assumption. In contrast, the commerciality discourse lacks any substantial reference to core scientific elements, at least to those which directly collide with ‘control’ and ‘cost-efficiency’. Interestingly, commerciality, due to its focus on control and measurable results is being perceived as a ‘fair’ and ‘safe’ environment – despite its war language! A number of discursive and actual strategies have been employed to this end, i.e. to merge the two discourses in one ‘commercial innovation’ discourse, which would engage both the business and scientists, and naturalize the commercial order. Table 8.2 picks out these invading strategies, as well as the strategies of resistance that were employed as response, since such radical changes would not go through uncontested. Discursive strategies for change The ‘invasion’ of commercialism could not have been actualized, but by appeal to a set of discursive weapons for ‘conquering’ the research site. Consistent with the business language of war games,1 the formal organization discourse represents the turn to commercialization as a question of survival, and as the only viable option. The change is represented as imposed upon the business by a highly competitive external environment, leaving no other option, nor room for discussions and negotiations, since as stated, the business follows the demands of the external environment. This discursive strategy, i.e. the construction of commercialization as the only logical way, is supported by a set of rhetorical devices, which identify change with progress, and hence no new member of the organization would like to be stigmatized as conservative and slow-moving; people that do not take quick decisions nor adapt fast in changes cannot support

Sustainability = survival

Change = progress and prosperity

War language

Rhetorical devices to naturalize change

‘no time’

Not participate in the new innovation language game

Commercial career opportunities for scientists

‘I guess I am too old to change’

Use arguments of the new commercial order Cynically accept attack Old scientists leave the site

‘too old to change’

Preemptive attack to resistance

‘I am not sure this is teamwork’

‘we also saw it was the only way to go’

‘this is silly really’ ‘it is somehow corrupted already’

Examples

Question contested concepts; defend older articulations

Acknowledge necessity for commerciality

Reveal politics

Mockery of new articulations and practices Appeal to scientific authority

Strategies of resistance

Replace old scientists with new staff

Teamwork, collaboration, partnership

Use of values of the scientific discourse

‘A process of natural selection would be healthy’

Examples

Strategies of commercialization

Table 8.2 Strategies of invasion and resistance

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a dynamic organization in a fast-moving and unpredictable commercial environment. Hence, ‘commercialization is the only way to go’. This language move has been successful, since no scientist doubted the necessity for change. What is surprising though, is the logical contradiction, in that the use of a war language, which is in principle loaded with uncertainty, achieves to link commerciality with job security! Innovation starts acquiring a place in this commercial discourse; however it does not escape the war language: ‘either you innovate or you die’; innovation again, similarly to commercialization is represented as the only way to go, and as a question of survival. Hence, the new discursive hybrid of ‘commercial innovation’ starts developing, which allegedly places innovation at the centre of practices. Furthermore, the new commercial discourse re-articulates its web of relations, by including a set of values and practices dominant in the scientific order, e.g. ‘teamwork’, ‘collaboration’. However, their significance now changes; as discussed, ‘teamwork’ now means involvement in more and bigger projects, where the face-to-face interaction and the degree of dependence of the various parts of the work is reduced, as opposed to the highly interdependent and interpersonal nature of work in the scientific culture. Nevertheless, by including ‘elements’ of the scientific discourse, commercialization discourse neutralized the force of changes. Finally, in any war game, strategists should be able to anticipate the enemies’ moves; here, the response of those who would not eagerly comply with the changes, has been predicted and attacked. Change is constructed as synonymous to progress and prosperity; those who fail to see benefits of this are conservative and ‘too old to change’. Much popular literature on change management has contributed to naturalize the rationality of this argument, since the fear of change and the age factor have widely been identified with the most common hurdles to change management, offering this way a ‘convenient truth’. Certainly age and fear of change may be factors of resistance; however, this view denies the intellectual capacity of actors to judge for themselves the benefits of a change, and decide on their personal interests. In other words it ignores the political dimension of change. New structure and practices Apart from the discursive strategies employed to support the new commercial ‘reality’, a number of structural changes were initiated as part of the same transformational move. The commercial discourse has drawn the attention to key managerial concepts of control (i.e. measuring, filing and justifying activities) and flexibility, which are indeed very powerful. Their domination has triggered a series of changes, such as the redesigning of teamwork, which had unanticipated consequences upon collaboration and knowledge sharing; collegial relationships have now turned into customer relationships, and knowledge sharing is progressively dominated by electronic filing. These effects actually mean that knowledge processes are losing their discursive dimension; hence knowledge is limited to only what can be codified and measured.

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In a research structure, work relationships are formally defined and most often represented as a rigid hierarchy; interpersonal interactions are formed on the basis of whether one is an ‘equal’ (a scientist), or an ‘outsider’ (assistant, administrative staff, etc.). As expected, the scientists’ community lies in the middle and enjoys a high status; relationships among ‘equals’ can be informal, and based on collaboration. Other groups are determined by reference to the relations with the scientific group, and hence their position in the structure and their status is strictly determined. On the other hand, commerciality pursues the ideal of a flat and hence more flexible structure (the two are always wedded together). However, the flexible structure combined with the ‘globalized activities’ and the need for control does not necessarily create intensive face-to-face interactions. My fieldwork suggests that the pursuit of control can instead create a thorough bureaucratic mechanism for reporting, justifying and storing information, which contradicts flexibility. The consequences – for the scientists’ dissatisfaction – are: (a) the increasing paperwork, which becomes a part of the scientist’s daily tasks, (b) the empowerment of the administration unit, since administration becomes a key activity and (c) the weakening of the personal interactions for routine tasks, as most of the communication now takes place via formal procedures and e-mails. The weakening of personal interactions, together with the transformation of teamwork design, eliminates the opportunities for developing informal relations within and across the business units, and corrupts the essence of collaboration and, ultimately, knowledge creation and sharing. Commerciality adopts two more practices, which act as strategies of dominating the site, and have similar negative consequences for the knowledge base of a research site: (a) the exit of old scientists and (b) new career opportunities opened to all the staff members. The first one was a strategic move, intended to minimize the resistance of the old scientists, who were feeling the loss of their privileges in the new order; scientists who did not want to comply with the new commercial direction had the opportunity to get an early retirement and leave the site. Those who stay, tacitly agree to play along the commercial game. The second practice is not intentional; however, it results in the corrosion of the scientific population. All members of the corporation can pursue their own career objectives, and apply for jobs that they found interesting, even in different fields. Young scientists, after experiencing the loss of their scientific status, have the opportunity to apply for more prestigious positions in marketing and sales. However, this practice affects the knowledge base, and makes very hard the planning of skill needs, as much as the investment in training new recruits. Time The rationale of commerciality imposes its own concept of time in the new order: in a research site, projects are developed slowly and deadlines are hardly a factor to be seriously concerned; research is by nature highly uncertain and unpredictable regarding results, hence projects roll from one year to the next, without this affecting the relationship between scientists and sponsors. The

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funding for the projects is secured regardless of the research outcomes, and scientists can decide upon the time they need to spend on a project, without having to justify this decision to the business. The new commercial environment brings a radical change in that respect. Time is not an inexhaustible resource any more, neither a necessary dimension for a piece of research to show results. Time does not work on scientists’ side any longer and does not unfold together with the development of projects; on the opposite, time counts-down for the research staff, who now have to compete against it to meet the deliverables and the deadlines imposed by their customers, who expect the results of the projects in a defined time. The time perspective changes from long to short term and time is split in short periods, which can be more easily controlled and managed.2 Time becomes a valuable resource closely associated with the costs and profits of each Business Group – a resource that cannot be wasted and against which all activities are measured being given the relevant ‘activity number’. The consequence of this change in time perspective for the organization is that it creates a ‘stressed’ culture, where increasingly people are willing to do only what is directly relevant to their projects or at most what they can justify with an activity number. This affects the professional interactions and knowledge-sharing between scientists, who now are eagerly assisting colleagues only when they can justify their time spent on it, turning in this way professional relationships to ‘customerbased’ relationships. This change has more severe implications for innovation, since the short-term time perception on site leads to treating with suspicion ideas and projects that require a longer time horizon. Strategies of resistance No change, especially such a radical change, which affects the order of a site, would occur uncontested. While the commercial innovation discourse was invading the research site, the scientists felt that they were losing their status and privileges they had (in particular, the most important privilege, i.e. to do bluesky research), and hence fought back. However, it needs be clear that not all scientists joined the ‘resistance’: some were too afraid to react, some identified their career ambitions with the current development. Some – especially senior scientists, which were considered world experts in their fields – felt that their careers were already well established, hence they could resist changes. A range of discursive and actual strategies is employed to this end. First, the necessity of commercialization is not doubted: it is clear that struggles will not take place in the field of commerciality, since here scientists would soon be left short of arguments; their intention is not to tell the business how to manage a commercial organization, but how to manage innovation, because this is the scientists’ field. Innovation is a concept overdetermined by scientists, lab assistants and managers, who all from their side put fiercely forward a different meaning of it. Consequently, it soon becomes a contested by many discourses concept, i.e. an empty signifier that means at the same time too many things, but nothing

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specific. In other words ‘innovation’ provides the arena where various interest groups would collide in order to determine what it really means, and hence the appropriate actions they should undertake to support it. Scientists set out to impose their own understanding, because this would determine the actual direction a ‘research-based commercial organization’ should take. The discursive strategies they use include a range of direct attacks to the new articulations and practices: mockery and jokes, which play a symbolic unifying role for scientists, and also more constructively questioning of the new articulations and practices, by exposing their inadequacy and shortcomings. Scientists appeal to their expertise and authority in the research language game for legitimizing their direct discursive attacks. However, the most unexpected and admittedly efficient strategy is the use of arguments, which derive from the commercial discourse, and in practice they collide with the pursuit of new ideas and innovation. The argument ‘no time’ has been discussed in Chapter 6, where I showed how scientists abstained from the new innovation language game, by just doing their everyday job! Finally, a last strategy employed by old scientists is their complete negation of the new commercial order, exhibited through leaving the site. Despite the gaining momentum of innovation discourse, the fact that leading world experts have left the organization or snub the new innovation language game did not seem to concern seriously the Business Groups. ‘Innovation’ was at the time of my fieldwork still a blurred concept and a contested by different interest groups discourse, hence the significance of this loss had not been realized and assessed yet.

The pragmatics of commercial knowledge In Chapter 4, I presented the transformation in the scientific language game, as put forward by the commercialization process. I claimed that innovation has become an empty signifier, i.e. a vaguely defined element, which means nothing in particular. The commercial discourse attempted to unify all staff members of the research site around this nodal point, and to achieve their support; innovation has been historically accepted in such a site, hence, commerciality should fairly easily dominate, once included innovation in its web of relations. Nevertheless, once innovation is being articulated in a commercial web of relations, then its meaning changes, as well as the practices it supports and the identities of those involved in the research activities. Table 8.3 presents the main changes that occur in the scientific language game, when knowledge is being articulated within a commercial discourse. In Chapter 2, I discussed the transformations that the commercialization of knowledge produces upon structures, processes and subjects. I claimed that by turning knowledge into a commodity, i.e. an object that can be traded, its nature changes, as well as the infrastructures that support its production and legitimization (Gibbons et al., 1994; Lyotard, 1984). Table 8.3 elucidates further the arguments raised back then, by throwing light into the specific changes that occur in the nature of knowledge once it turns into a commercial object.

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Table 8.3 Re-articulation of the research language game Scientific research language game

Commercial research language game

Knowledge

Ideal; increases through sharing

Commodity; loses its value through sharing

Innovation

Long term, technological

Short-term applications; simple little ideas

Research

An open and collaborative activity

An undisclosed and controlled activity

R&D activities

Research aiming to new knowledge

Development aiming to application of what is already known

Time

Inexhaustible resource; long time horizon

Scarce resource; tightly controlled and measured

Scientist

Researcher

Project manager; sales person

Research skills

Scientific rigour; analytic thinking

Communication and presentation skills

In the scientific language game, knowledge is an ideal, the end of research activities. A peculiar feature of knowledge articulated within the scientific language game is that it is a valuable resource that increases through use and sharing – this is in itself exceptional for an object, i.e. a material resource. Based on this key feature, a number of practices have been developed (publications, conferences, ICT tools, etc.), which would ensure the unimpeded knowledge sharing. The significance of communication and collaboration found well their place within this discourse. However, once knowledge becomes a commercial object, i.e. an object with a price and a buyer, then its value decreases through sharing – hence it needs be protected. To this end, corporations adopt an aggressive attitude towards the protection of innovations, which is reflected on the ‘intellectual property’ policies they implement. More importantly, the rules of knowledge sharing are changing; whereas in a scientific site knowledge is freely shared among research groups and with the wider scientific community, commercial knowledge is being constrained within the boundaries of each research group, and by the requirements of each customer. There emerges the paradox, where the knowledge generator does not own and cannot use this knowledge further, since knowledge is a commercial object that has been bought by a customer. Knowledge sharing is strongly encouraged and to some extent required by the corporation; however, due to the increasing importance of ‘time’, which turns into a valuable resource, face-to-face knowledge sharing is regulated by ‘activity numbers’, which turn the existing collegial relationships to customer-based relationships. Knowledge management technologies come to replace face-to-face communication with electronic filing

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and distribution of reports. The practice of electronic reports, which are selectively distributed, gradually comes to replace the production of scientific papers. For a commercial research site – as opposed to a ‘university site’ – conferences are not the place where scientists share their knowledge any longer, but the ‘marketplace’, where they make commercial contacts. In the commercial language game R&D activities change nature and objectives. In a scientific research site, research aims to the production of new knowledge, and innovation means long-term and technological programmes; in other words, the weight is on research and the science behind it. Research is conducted with unspecified ends and uncertain business applications. Scientists enjoy the privilege to engage in research of an academic nature, without tight control from the business. However, the loose connection between research of this type and business interests had been criticized for the small number of commercial innovations that it produces, and hence this research structure had to change. In a commercial site the weight is on development3 rather than research; development does not mean applied research, since the element of new knowledge is minimized and replaced with the application of what is already known. Innovation in this context means short-term applications, and simple little ideas, of which the production costs and market value can be measured. The consequence of this transformation is that the pace of knowledge production, together with the number of radical innovations (the kind of innovation that would give the competitive advantage to the organization) decreases. Long-term research does not comfortably fit in the new research structure, and even though its necessity is acknowledged, its problematic nature in terms of controlling and measuring deliverables creates a grey zone, into which business people do not want to go. This grey zone of innovation starts attracting the attention of various groups, which see the opportunity for group and personal gains from controlling it. The scientist’s role is transformed in the commercial order, to the scientists’ frustration. In the scientific research language game, scientists enjoy the privilege of conducting blue-sky research without being subject to tight control from the business side. Innovation has been articulated within a language game that the business people did not understand and hence could not control. In Chapter 2, I discussed the question of the research community losing its elitist status, and hence scientists turn into ‘knowledge workers’, once the boundaries of the research community are disclosed after collaborating with the business world, and the corporations increasingly decide upon the direction of research. Here I shall add that the scientists’ identity changes not only because scientists lose their autonomy to decide upon what valuable knowledge is, but also because the nature of research tasks changes as well. Since the research process does not aim to new knowledge, but to the application of what is already known, then a scientist does not need to do research any longer, but to apply what is known to new application; hence, a scientist becomes a project manager, with a range of administrative tasks, or sales people who ‘go out to find customers’ capitalizing on their scientific expertise. As expected, the production of commercial knowledge needs a set of different skills, since scientific rigour and analytic thinking

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add no value any longer. The commercial knowledge requires ‘presentation’ and ‘communication’ skills, i.e. skills that can secure new customers and funding from the business. At the same time, the boundaries of the ‘research’ community open up to include lab technicians as well; since the complexity of research projects in the commercial research language game decreases (as the aim of the activities is development rather than research), lab technicians now have the opportunity to run their own small projects. The disclosure of the boundaries can be interpreted as a move towards democratization; the secluded scientific community, which has the prerogative to decide upon knowledge breaks down, and more occupational groups, which in the past have been engaged in the periphery of research without having the academic qualifications to assert membership in the research community, now acquire the identity of knowledge worker. From this perspective, it could be argued that the commercial site is a democratized site, since elite groups break down, and more people have the opportunity to undertake better-rewarded activities. On the other hand, there is no evidence to suggest that democratization has been in the corporate agenda, but rather the increase of the knowledge resources and capital. Once the elite group of scientists gets eroded, then another group appears, which acquires its power; this group is not the lab technicians, but the market sector, which increasingly participates in the legitimization of knowledge. Finally, the transformation of the rules of the scientific language game, and in particular the expansion of its boundaries, to include those who have an understanding of science without having the academic qualifications, raises the question of legitimization of knowledge. I discussed in Chapter 2, how in the traditional scientific language game, the truth-value of a scientific statement is established by the agreement of the scientific community. Science has been a self-regulated language game, wherein those who produce knowledge are responsible for the legitimization of their claims, which actually occurs via the production of a second statement of the same order. However, in the commercial innovation language game, the truth-value is not the most important criterion for legitimizing knowledge, but rather the correspondence to the market needs, i.e. its commercial value. The scientists, who generate the idea, cannot establish the commercial value of knowledge; this is undertaken by the market sector, which operates in the interface with the customers. This means that the legitimization of commercial knowledge leaves the boundaries of the scientific community and appeals to an external mechanism of regulation. However, the market community is increasingly treated with mistrust by the wider society, in terms of the genuineness of the intentions and the practices they apply. The commercial value by no means represents the social value of knowledge, and the interests of the stakeholders.

Power and politics in innovation management I claimed in Chapter 4 that the grand discourse on knowledge has changed the route of commercialization for oil companies and their understanding of innovation and innovation needs. Societal pressures from customers, competitors,

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governments, NGOs, social groups and local communities for socially and environmentally responsible behaviour, together with the fact that oil is a scarce resource, point out the need for distinct innovative and sustainable solutions. The re-articulation of energy needs by various stakeholders led to a reconceptualization of the role oil companies – and in specific their R&D infrastructures – could play in this new discourse: they see the opportunity to transform from a twilight Oil Company with limited possibilities for innovation, to an innovative Energy Company, which needs groundbreaking research programmes to develop in the new field of operations. This identity transformation promises the sustainability of the company in the future, since opportunities for expanding in new business areas emerge. Innovation, not as short-term product development, determined within a rigid commercial discourse, but as long-term and uncertain research projects, regains attention and ‘energy’ companies set out to support it by devising a number of innovation funnels and funds. The acquisition of the new identity could have not been accomplished, had the discourse of commerciality not re-articulated innovation as a ‘strategic competence’ in its web of relations. This is the moment of ‘dislocation’, i.e. when ‘commerciality’ cannot domesticate ‘innovation’ as prescribed by stakeholders, and breaks down. At this moment, innovation becomes an empty signifier, i.e. a vague concept with no specific meaning, articulated by many discourses, and provides the arena for contestation by antagonistic groups. Chapter 6 demonstrated how scientists, business people, managers and lab technicians seize the opportunity to articulate what innovation means – and hence shape the relevant practices. Table 8.4 presents four discourses on innovation in a technology company, as identified during the fieldwork at Oil Co. In Chapter 3, I discussed the theoretical background of the first discourse on ‘innovation as rational planning’ (Drucker, 1985; Trott, 1998). There I claimed that it has been developed on the grounds of a pure economic rationale and from this perspective innovation is a cost that has to be controlled. The risk-averted nature of this rationale does not support long-term projects, and it is appropriate only for short projects, new product development and knowledge applications. The failure of the business discourse to meet the requirements for innovation as prescribed by the new company identity soon becomes evident: the business rationale can suggest managerial tools for integrating innovation in its strategy, such as innovation in scorecards, in Personal Performance Contracts, etc., and set up Innovation Panels, where members of the business and the market sector participate to assess the commercial potential of ideas. These tools and practices have a symbolic role in that they link innovation with the business, turning it visible as much to the staff, as to the external environment. In other words, they make a statement of the strategic importance of innovation, and attempt to create an order where research activities meet. Furthermore, they aim to the standardization of practices and, progressively of homogenization of behaviour, by achieving consensus over practices, which are perceived as part of the natural order. However, this discourse can provide no conceptual framework for it, and hence cannot drive research activities forward. Lastly, it results to the

A sense of democratization of workplace

All staff

Funds, conferences, database, Innovation Hero and Team, Innovation Chats

All-embracing; big and small ideas (instead of good and bad)

Cultural change

Innovativeness as a personality trait; innovation as an asset

Improved business performance

Small, technological, administrative, operational, etc. ideas

Innovation as culture

A secluded culture –’Ivory Tower’

Scientists

Funds, conferences, collaborations, publications

Curiosity oriented; Blue-sky research

Uncertainty; knowledge sharing between scientists

Innovation as a scientific community trait; innovation as an asset

Contribution to knowledge; groundbreaking innovations

Radical technological ideas

Scientific technological innovation

Note 1 Evidence for this discourse has been gathered through the examination of organizational documents, which exhibit the company’s arguments, and the interviewees’ counterarguments. Nonetheless, I stress the need for a more thorough understanding of the discourse by talking directly with the business people.

Collision of mindsets; lack of shared understanding

Eradication of managerial responsibility; lack of strategic framework

Unanticipated consequences

Innovation strategic framework; problem solving for customers

Business, market sector and scientists

Commercial innovation as competitive advantage

Rhetoric

Collaboration between business and scientists

Scientists

‘Safe’ risk

Key concepts

Innovation as measurable economic element; innovation as a cost

Responsibility

Innovation process as a thing to use when needed; innovation as a cost

Assumptions

New products

Funds, funnel, panel, business case, database, networks and alliances

Improved and/or new products

Objectives

Small technological ideas

Long-term commercial innovation

Practices and tools Funds, Innovation Management Groups, innovation in scorecards and in Personal Performance Contract

Commercializable ideas

Type

Innovation as rational planning1

Table 8.4 Competing discourses of innovation

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eradication of responsibility from the business side, where innovation is someone else’s job. In order to fill in the gap that the absence of the senior management involvement in the innovation processes creates, Innovation Management Groups are set up to monitor the system. I discussed above how the ‘commercial innovation’ emerges, when the business rationale fails to explain innovation phenomena and support actions. The ‘commercial technological innovation’ discourse is grounded too on the assumptions of ‘rational planning’, and attempts to wed commercialism and technological innovation in a single discourse; in other words it attempts to keep in-line with the managerialist/economic rationale, while supporting long-term technological projects. It is constructed in order to overcome the ‘perceived weaknesses’ of the short-term commercial innovation discourse, which fails to engage the scientists, by creating a shared discursive order. This discourse is intended to give research a strategic focus, and pursues the collaboration of the two sides (i.e. business/market and scientists), hence progressively they accept it as the natural order. Nonetheless, the risk-averted nature of the economic rationale is evident here as well, and, even though the objective is to support technological ideas, only ‘safe’ ideas that can demonstrate economic returns, can really be produced. This discourse achieves to break the short-term time horizon, but not the riskaversion attitude. Hence, the outcomes of this innovation process are small technological innovations, which can be measured and controlled throughout. As the relevant literature prescribes, the tools and practices aim to control the innovation process, by splitting it into measurable stages, which are assessed by a panel. It is worth questioning then the concept of ‘collaboration’ it uses, and the role of the two parties in it: from one side the scientists are supposed to suggest technological ideas, following the standards set by the business side, and on the other the business assesses these ideas for their economic (not their technological) value. In other words, the scientists have to learn and speak the economic language and translate their ideas into it, whereas the panel makes a decision on the grounds of how well they play the economic language game. This type of collaboration soon becomes an arena for contestation, since in principle it is asymmetrical: it expects the one side to adapt according to rules set by the other, especially in a language game, where traditionally science – not commercialism – has been the hegemonic discourse. The process is subject to criticism regarding its transparency, since the rules according to which ideas are evaluated are not ‘clear’ to the scientists, for they are developed within another language. Scientists have the right to choose not to participate in the process, since their interests are not represented in it. It is raised then the question of who should govern the process, since this group ultimately decides about the value of knowledge that is produced. The third discourse offers a very broad conceptualization of innovation, since it includes everything (small and big ideas, administrative, operational, technological, etc.). It develops on the rationale of ‘innovation as culture’ (Kanter, 1988; Quinn, 1985), which argues for an organic view of innovation manage-

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ment: innovative ideas will flourish, when the environment allows it. It assumes that innovation cannot be managed directly, like the innovation as rational planning assumes, but it can be supported by the ‘right’ stimulating environment. The tools and practices that are used aim to support the communication among individuals, and acknowledge the central role of narrative knowledge in the innovation process. The rhetoric insists that there are no right and wrong ideas, only big and small, and hence, innovation is everybody’s responsibility, and not only the scientists’. In other words, it opens up the concept of innovation, which has been articulated within a scientific discourse, and returns it to all the staff. The objective of this all-embracing discourse is not only to result in more competitive products, but foremost to enhance overall business performance, making each department contribute with ideas. The politics in this discourse are inherent, because individual competences are part of its core assumptions. It assumes that innovation depends on personality traits, and that innovation management needs a ‘hero’ to support the process. I should underscore that innovativeness here is not associated with the ability of people to generate ideas, but with their political skills, i.e. their ability to distinguish good ideas, and pull the strings to support their materialization. In other words, it anticipates a specific influential role for certain individuals, who are perceived as having the gift of innovativeness. As expected, these individuals enjoy a higher status in this order, which is not necessarily well perceived by those, who disagree with this view on innovation. However, this all-embracing discourse on innovation resulted in attributing a sense of ‘democratization’ in the workplace, since the hegemonic scientific discourse, which had determined the operations of a research site so far breaks down, and innovation becomes a task for all the staff. Finally, the last discourse on scientific technological innovation is built on the grounds of knowledge, and pursues groundbreaking innovations and expansion of the body of knowledge. Innovativeness here is associated with the intellectual abilities and analytical skills of each scientist, but also with the scientific community as well, since it recognizes that no one can generate ideas in a vacuum. Hence, collaboration and knowledge sharing is part of the order, and the tools and practices in place aim to encourage them. Nonetheless, collaboration and sharing of knowledge is encouraged only ‘among equals’, i.e. scientists who participate in this language game, and they are responsible by training for innovation. In other words, it creates a small academic world within the bigger corporate world; a small, secluded culture, which traditionally has been governed by values much different from the ones of the business, i.e. by scientific values. Science has been the hegemonic discourse in research sites, before the ‘invasion’ of commercialism. It had created an elite group, i.e. scientists with high academic qualifications, while it excluded those who did not qualify to participate in the research language game, and who were allocated support activities. When the powerful commercialism invades the research site, and it is powerful, because economic rationale is accepted as the adequate order to run a business

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(and expands into other parts of life), the hegemony of scientists is attacked. A pure scientific discourse cannot meet the requirements of the market, which are widely accepted as primary imperatives. Nonetheless, the commercial discourse fails to accommodate and explain technological phenomena and innovation. Hence, the commercial innovation emerges, as a response to this failure, i.e. a discourse that tries to merge the two, by keeping the economic rationale and usurping the rhetoric of science. The theory of social antagonisms argues that when a hegemonic discourse is dislocated, the excluded groups are unified around a ‘nodal point’, despite their political differences. The transformation of R&D laboratories into commercial organizations, essentially implies the collision of the two discourses: the scientific and the commercial. Innovation becomes a nodal point, and unifies all ‘excluded’ groups against the scientific hegemony. At the same time, during this collision many discourses emerge, which provide alternative conceptualizations of innovation in a commercial organization. The question that they all try to answer is ‘how to manage innovation’. Nonetheless, what they actually do, is that they provide the employees with sets of arguments and perspectives that they can use, until one becomes the hegemonic one. Meanwhile, employees can use arguments that derive legitimization from either discourse, in order to serve their own personal or group interests.

Commercial innovation: a powerful discourse? The discussion so far suggested that the scientific ethos of the research community, characterized by intellectual curiosity and analytical thinking, which traditionally guided science, does not comfortably fit in the commercial order, for the two are grounded on different values and construct contradicting rationalities. The emergence of the discourse on commercial innovation tried to wed the two into one unifying order; nonetheless it has not achieved yet to address all the challenges that this merger creates, and more importantly to explain satisfactorily all the events that are now observed. The technologies that the commercial rationale suggests, its rules and procedures, are based on the assumption of cost control and risk aversion, which are fundamentally in opposition with the longterm and uncertain character of technological innovation. In this environment, short-term and safe innovations will always be preferred over the radical and risky ideas. It would also be a mistake to think that this can be resolved by translating long-term programmes into the economic language, since the value of uncertain technological results cannot simply be pinned down with an economic value. Nonetheless, the evidence presented the scientists’ efforts to speak the economic language. This resulted in the attribution of a dual identity – a manager and a scientist – which also requires a different set of skills in order for one to perform well, i.e. a combination of scientific rigour and managerial abilities. This necessary duality is not perceived yet as a necessity, but as a choice. Those who can excel in science stay in research roles, where they have the opportunity

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to work on projects, whereas those who have the commercial and managerial skills move to other positions, which promise well-paid career development. Two critical questions emerge here: first, whether this mix of skills is serving in principle the purposes of innovation, and second, whether this is feasible in practice, and if yes how it can best be supported. I shall argue here against its necessity, on the grounds of the benefits expertise returns, as much for the individual, i.e. in terms of job satisfaction, as for the organization in terms of the quality of work that is being produced. The evidence suggests that this duality may result to a leak of knowledge, since more and more trained scientists pursue a commercial job, with better remunerations. Some may consider this practice a channel to transfer knowledge and create progressively a shared understanding and language. However, activity theory (Engestrom, 1987; Blackler, 1993, 1995) suggests that people’s understanding is developed by their object of activity. Hence, scientists in commercial positions will soon start to think and act like their new tasks prescribe. A second, and more severe duality is encountered in the organization of tasks: in a commercial environment, activities are organized with no slack in time, whereas time has to be accounted for, with reference to the activities where it is spent. On the other hand, innovation needs time, not only for the materialization of an idea, but even before that, for the generation of it. In other words, innovation needs a slack in time. The contradiction between the commercial and scientific environment is obvious. Innovation cannot thrive in a commercial environment, where time accountability and control dictates the prioritization of activities, and essentially the work design. In this environment, commercial activities, due to their short-term nature will always be a priority, and radical innovation will be a secondary activity, and will rely on scientists’ personal interests and free time. The inclusion of innovation in the Personal Performance Contract, and the innovation funds is not a sufficient incentive to engage scientists. The actualization of commercial innovation necessitates a work design, which would allow scientists the time to think about science. In other words, it appears the necessity for a double structure, which would split the time and tasks of scientists into innovative and commercial, and hence, innovation would find its place independently from the commercial business, but still in a commercial environment. Finally, I pointed out throughout the discussion of theories and practices of innovation management, the importance ‘commercial innovation’ attributes in the collaboration between the business and scientists. Essentially ‘collaboration’ in all stages of an innovation process aims to bring the scientists closer to the market needs, and establish a commercial value for the new ideas. I have explained how this model expects the scientists to learn the economic language – and not the other way round. The decision for the progression of the idea through the innovation funnel is left on an Innovation Panel, which is competent to assess the commercial value of an idea, without understanding the technological implications of it. The problem that this model presents us with, is that the legitimization of the value of an idea leaves the boundaries of the scientific

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community, as well as the decision of what kind of knowledge we need to produce. These decisions are taken up by the business side, and do not necessarily represent the social interests and needs – and certainly not the interests of science. From an organizational perspective, this model may lead to knowledge holes, when science in the field would have progressed enough, however, the corporate scientists did not have the opportunity to keep up-to-date and contribute in the process. It is essential, then, for the benefit of the organization, to open up the decision-making process and involve the scientists in it, in order to balance the commercial and technological interests of innovation management. In Chapter 2, I discussed the Mode B production of knowledge (Gibbons et al., 1994), which asserts the transdisciplinary character and collaborative nature that science acquires today. A network of multiple actors (universities, corporations, private and public R&D laboratories, the state, etc.) is partaking in the production of knowledge, which moves back and forth between fundamental and applied research. The purpose of these alliances is the optimum use of knowledge resources and research infrastructures, in order to serve the society. This model poses the question: who should be charged with the responsibility for the governance of truth, i.e. who is to decide what knowledge should be produced? An overview of the alliances that are created highlights the increasingly influential role corporations play in Mode B, because of the abundant funds they can contribute. However, my discussion of their role indicates that their empowerment may put at stake the epistemological status of knowledge and the social interests it serves. It becomes a pressing need, then, that after these changes in the scientific language game, we need to redefine the role of each participant organization, and establish an independent governance mechanism to secure the transparent and ethical conduct of science.

Appendix Sources of information

Documentary data In this study, I used the following sources of documentary data: • • • •

• •

Oil Co. and Hydro-Carbon Solutions’ websites in intranet and internet; the Company’s Newsletter; annual reports; e-mail communication (messages exchanged regarding the Ideas Machine, and also information regarding everyday life, events and important notices to the employees of the groups under study); presentations on the innovation system and the Ideas Machine (for internal purposes and for clients); previous research and reports on the Ideas Machine and on work-life balance.

The reports from previous research conducted by students were examined only in terms of the historical information they were providing; even though the reports were approved by Hydro-Carbon Solutions, the authors (who I met personally in both cases) insisted that the reports were representing their own viewpoints regarding the company, and by no means a formal position.

Participant observation While in the field, I had the opportunity to observe the following events: • • • • •

Technology Group A Group monthly meeting; Ideas Machine monthly review; ‘Innovation Workshop Presentation’ for clients; many hours of informal conversations with various employees over cups of coffees and lunches; many weeks spent with the secretaries of the Technology Group A and Technology Group B in the administration unit, where I was given a desk.

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Appendix

Semi-structured and unstructured interviews Throughout the year of data generation, I conducted in total 41 in-depth interviews from which 30 were semi-structured with individuals from three groups of Hydro-Carbon Solutions, i.e. 18 interviews from the Technology Group A, ten interviews from the Technology Group B and two from the Research and Innovation Group, who were actually the people that ran the higher innovation mechanism Eureka. The first four interviews conducted in Technology Group A were used as a pilot study to refine the interview schedule. In addition to the semi-structured interviews, I conducted 11 unstructured interviews: five interviews in the beginning of the data-generation stage with members of Technology Group A Group that I interviewed again later, and also with one individual from the Human Resources and one from the Information Storing Department. These interviews lasted about one hour each, and the purpose was to start developing an understanding of the mechanisms that support knowledge sharing and storing, the related policies and the wider Oil Co. culture. The last six interviews (four in Technology Group A and two in Technology Group B) were conducted at the final stage as follow-up, to update my information before I concluded officially the project. In sum, the representatives of the following groups, who were formally interviewed: • • • • • •

two members of the Research and Innovation Group; two Resource Managers (from Technology Group A) and the two Innovation Managers (from Technology Group A and Technology Group B); six current Innovation Team members (from Technology Group A); nine PhD scientists from Technology Group A and five from Technology Group B; others (engineers, scientists, lab technicians): five from Technology Group A and four from Technology Group B; two pre-students (one being Innovation Team member, both from Technology Group A).

Table A.1 Distribution of interviews

Semi-structured Pilot Unstructured Follow-up

Business Group A

Business Group B

Other

22

12 4

2 (Innovation Management Group)

3 4

2

2 (Human Resources and Information Storing Depts)

Notes

1 A story of studying technological innovation 1 Broadly speaking, hermeneutics assume a unified, transparent meaning of the whole, which imbues and transcends each of its parts, and which they try to reveal. Thus, by understanding the parts the researcher reaches an understanding of the whole; hence the text is seen as a ‘system’, i.e. a unified whole. However, these assumptions lead to a coherent and consensual view of the world, which cannot allow an understanding of ambiguous meanings and of conflicting and discontinuous interpretations. Furthermore, the same hermeneutics circle expresses harmony and wholeness, which consists by parts and understandings; the question that arises is what lies in the centre of the circle – is this ‘circle’ not constructed by the researcher’s understanding and, hence, does this not give a privileged standpoint to the researcher’s voice? 2 Methodologically, Foucault’s view on discourse involves the analysis of assumptions, scientific claims and categorizations, and modes of thinking and reasoning. Discourse itself operates like a framework of logic and reasoning. His work consists in two parts: the ‘archaeological’ and the ‘genealogical’, which complement each other; the archaeological studies are concerned with the study of discourse, as constitutive of society, in multiple dimensions: discourse constitutes objects of knowledge, social subjects and forms of ‘self’, social relationships and conceptual frameworks (Foucault, 1972). Furthermore, even though the focus of the study is on the micro level, discursive practices are not studied merely ‘locally’, at the institution level, but the analysis assumes interdependence between these discourses, as ‘texts’ draw upon and transform other contemporary and historically prior ‘texts’; in other words, Foucault recognizes the intertextual and interdiscursive character of discursive formations, and also the impact of non-discursive elements (e.g. appropriation, interests, desires, etc.) in this process (Fairclough, 1992). 3 The traditional approach to interviews assumes that the interviewee is a ‘vessel of knowledge’, and the interviewer can ‘extract’ the information that is needed, if the ‘right’ questions are asked in the ‘right’ way. This assumes the existence of objective information held by the ‘passive’ interviewee, and attributes the interviewer the responsibility and power to control the interview process. Hence, ‘right’ and objective information is acquired, if the interviewer manages to ask the ‘right’ questions in a neutral way. The interview process is seen as the ‘pipeline’ to transfer knowledge from the interviewee’s head to the interviewer (Holstein and Gubrium, 1997). However, the view neglects that interviewees are never passive subjects, but they actively interpret (and sometimes misinterpret) the questions and the situation, and hence the interview and the meanings are constructed in turns, based on what has been said so far. 4 The interviews were constructed around three themes: the nature of discourse on innovation, where various formulations of the concept were sought, as well as how these conceptions fit in people’s understanding of the Innovation System; the expectations and

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Notes

aspirations from the Innovation System was the second theme and it sought to reveal the specific needs for knowledge creation and sharing of each organization; and ultimately, it was sought how the Innovation System was actually used – what the applied practices associated with the innovation system were, in other words the actions taken. These themes were explored at three levels, trying to capture a macro but also a micro image of Innovation: the organizational level, where the formal position was being sought; the group level, where the focus closed up to the R&D department, expecting to reveal competing understandings of knowledge; and the individual level, where the respondent’s views were expressed, bracketing the social dynamics to the degree that I described previously. The aim was to come closer to the interviewee’s voice and listen to her/him not merely as a member of the organization nor the member of a particular group, but as the individual that carries experiences beyond the workplace, as well. The study explored the language in use in a particular context, i.e. knowledge-based organization, and hence the questions of the interview schedule were built in the lines of the ethnographic interview (Spradley, 1979; Marshall and Rossman, 1995). The interview schedule used descriptive questions, in order to grasp the particular language in use, structural questions, which revealed the basic units in that cultural knowledge and contrast questions, which provided the meanings of various terms in the particular ‘language’. 5 ‘Reflexive’ here signifies the critical and post-modern views on research, which acknowledge the limitations that subjectivity of research participants (both researcher and researched) and the context of research impose on the interpretation, and attempt to include some of these aspects on the process of interpreting (cf. Alvesson and Sköldberg, 2000). 2 The value of knowledge in post-industrial societies 1 It is important to note, however, that the agents of the effects of disciplinary power cannot be attributed to the middle class (for that would represent it as a new sovereign power), but have to be sought for each phenomenon under study in the immediate network of the power relations, before a generalization to broader economic and political interests is attempted. 2 Here, I am referring to the scientist as a male subject for two reasons: first, during these early days science was a male dominated field; and second, Foucault himself refers to the ‘universal intellectual’ as a male scientist. 3 Knowledge and innovation in organizations 1 Still, computer science plays a dominant role in supporting all organizations’ knowledge needs, imposing this way a particular understanding of what knowledge – one which pretty much resembles information – and hence knowledge management is. In Chapter 2, I comment on the influence of information technologies in shaping the dominant discourse on knowledge management and the related practices that have ultimately impacted upon organizational structures, activities, as well as upon the individual (knowledge worker) and society. 2 Sociology of science, post-modernism, as well as work done from ethnomethodological and symbolic interactionist perspectives have challenged the abstract, cognitive and de-contextualized view on knowledge and have suggested the close tie between knowledge and context – be it culture, structure, etc. 3 See also Weick, 1995. 4 Slappendel (1996) offers an epistemological conceptualization of the aforementioned approaches: (i) an individualist approach, which assumes that individuals are a cause of innovation – this approach connects innovation with entrepreneurship; (ii) a struc-

Notes

187

turalist approach, which assumes innovation is determined by structural characteristics; (iii) an interactive approach, which is the most recent take, and conceives innovation as an interplay between structures and individuals’ actions. This last one attempts to integrate elements of the two, in a dynamic conceptualization of the phenomena under study. 5 Wolfe (1994) suggests that the inconsistency arises because researchers study different things conceived under the same name, and in order to clarify the field, he suggests three main themes that current research investigates: (a) the diffusion of innovation, which studies the patterns of diffusion of innovation over time and/or space through a population of potential adopter organization; (b) the organizational innovativeness, which studies the determinants of innovativeness and (c) processes theory, which studies the processes of innovation within organizations. 6 See the responses of C. Heckser, C.U. Stephens and A. Kiesler in the same issue of Organization Science. 7 To do justice to theorists, who take a critical stance towards knowledge management, it should be noted that, as it is evident from the discussion so far, there is a difference between the grand discourse on knowledge, which reflects permanent structural changes in the society, and the discourse on ‘knowledge management’, which has shaped possibly temporary practices within organizations. ‘Knowledge management’ practices may be a ‘fad’, suggested by the ‘experts’ – consultants and academics – but they reflect tendencies of the structural transformations at the social level. 4 Commercialization and knowledge production: Hydro-Carbon Solutions 1 A good discussion on how trust, teamwork and collaboration are used as devices of control is found in McKinley and Starkey (1998) – see for example, chapters by McKinley and Taylor, by Deetz and by Findlay and Newton. 8 The commercial condition of knowledge 1 Many theorists (e.g. Johnson et al., 2007) have noticed that business language is notably dominated by a war terminology, e.g. strategy, tactics, etc., and represents the activity of ‘doing business’ as a war game, which consequently builds an aggressive way of seeing and acting. 2 For the changing concepts of time and their effects on the organization, see Hassard (ed.) (1990), especially the chapters by Thrift and by Nyland. 3 The fact that nowadays we talk more about research, when the concept of development vanishes, does not mean that we produce more knowledge than in the past. Rather it means that we do more development, which we call research, because it sounds prestigious.

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Index

Abrahamson, E. 73 activity theory 59–60 Adler, P. 71 alliances 42 Alvarez, J.L. 75 Alvesson, M. 12, 43 antagonisms 28 BGs see Business Groups Blackler, F. 49, 52, 59–60, 66 Boland, R.J. 57–8 Brown, J.S. 53–4, 56–7, 65 bureaucracy 102, 157, 170 Business Groups (BGs): background 6–7; commercial culture 93–6; identity of 84–5, 91–2; see also Technology Group A; Technology Group B capitalist societies 32–3 career opportunities 136–7 change: discursive strategies 167–9; resistance to 100; structural 169–70 Clegg, S. 27 codified knowledge 22, 46 cognitive knowledge 23, 31 Collins, H.M. 22, 49 combination: Nonaka’s model 51 commercial culture 93–6 commercial innovation 167, 169, 180–2 commercial knowledge 34–6, 37–8, 172–5 commercial technological innovation 177–8 commercialization: and Business Groups 163; impact on research 88–9; and innovation 156–61; of knowledge 36–7, 39–40, 42–3; rise of 165–72; and Technology Group A 86; and Technology Group B 87 communication 38, 58–60

communication-intensive organizations 49–50 communism 32 communities and communication 58–9 competitive advantage 50 computers hegemony of 33, 35 conduit model 57, 58 construction as aspect of language 4 contradiction as aspect of language 4 Cook, S.D.N. 53–4 core innovation 116–17 corporate universities 37 critical discourse analysis 5–6 cultural knowledge 22, 49 culture: innovation as 63–6, 177, 178–9 customers of Oil Co. 80–1 Daft, R. 54–6 De Vos, A. 44, 71 Deetz, S. 12, 29 democratization 108, 126, 142, 175, 179 discourse effects: on structures 37–40; on subjects 40–2 discourse theory 3–5 discourses: economic 165–6; and Foucault 29–30; of innovation 1–2 dislocation 6 documentary data 7 Drucker, P. 35 Duguid, P. 56–7, 65 economic discourse, scientific knowledge and 165–6 economic language 39–40 economic progress 33 education 39 Egri, C. 68–9 embedded knowledge 49 embodied knowledge 22, 49

Index 197 embrained knowledge 22, 49 encultured knowledge 22, 49 Engestrom, Y. 59 epistemology of possession 53 epistemology of practice 53 Eureka 110, 113–21, 122, 150–1, 154–6, 161–4 evaluation criteria 11–13 expert-dependent organizations 49–50 explicit knowledge 22, 52, 53 exploitable innovation 156 externalization: Nonaka’s model 51 Fairclough, N. 5 fashion management 73–4 folk stories: characteristics of 24 Fonseca, J. 60–1, 63, 65, 66, 67 Foucault, M. 3, 4, 11, 27–30, 33–4, 40, 41 French narrative on knowledge 31 Frost, P. 68–9 German narrative on knowledge 31 Gibbons, M. 37, 38, 40, 42, 63 globalization 35–6, 43, 80 Graham, P. 33 Hayek, F.A. 37 hermeneutics 185n1 higher education 39 Hodgson, D. 28 Howarth, D. 3 Hydro-Carbon Solutions: establishment 80; structure 83–8 Ideas Machine 124–35, 138, 143, 145–54 identity: of Business Groups 84–5, 91–2; of communities 59 images of knowledge 49 inequalities 43 information 35 information processing mode 57–8 innovation: commercial technological 178; as culture 63–6, 177, 178–9; definitions 60–1; managers and 138–42; as power game 68–9; as rational planning 62–3, 65–6, 176–8; revival of 110–13, 166–7; as social construction of meanings 66–8 innovation management 61–9, 175–80, 181–2 Innovation Managers 139–43, 145–51, 179 innovation process 64–5, 67 internalization: Nonaka’s model 51 interpretation, process of 54–6 interviews 8–9

Jackson, B.G. 74 Johnston, R. 63 Kakihara, M. 47 Kanter, R.M. 64 Keenoy, T. 4 KIFs see knowledge-intensive firms knowing: as contested praxis 60; knowledge and 53–4; as mediated 59; as pragmatic 60; as provisional 60; as situated 60 knowledge: definitions 52; as interpretation 47–8; and knowing 53–4; legitimacy of 23; legitimization of 38; nature of 21–30; new production 36–42, 182; as object 47, 53, 70, 172–3; in organizations 45–54; as process 48; as relationship 48–9; scientific 23, 173; structure of 22–3 Knowledge and Innovation Management 46 knowledge-based societies 21 knowledge creation 46–7, 50–1 knowledge discourse, evolution of 32–4 knowledge-intensive firms (KIFs) 41–2 knowledge management 45–6, 47–9, 102 knowledge management discourse: evaluation 70–1; and managers 72–5 knowledge management technologies 173–4 knowledge phenomena 46–7, 70–1 knowledge production 36–42, 182 knowledge-routinized organizations 49–50 knowledge sharing 46, 101–2, 169, 173–4, 179 knowledge storing 46 knowledge workers 43, 44, 104–6, 108, 174 KPMG report 70 Laclau, E. 6, 28 language-centred view: of discourse analysis 5 language games model 57–8 language of research game 39–40 Lave, J. 56 learning 54, 56 legitimacy: of knowledge 23–6 legitimate peripheral participation (LPP) 56 legitimization: of knowledge 38, 175 LPP see legitimate peripheral participation lubricants 90–1 Lyotard, J.-F. 23, 24–5, 33

198

Index

McKinley, A. 72 managers: and innovation 138–43, 145–51, 179; knowledge management discourse and 72–5 Marketing Science 35 Marxist concepts 3, 32 Mazza, C. 75 methodology 5–10 Mode A: knowledge production 37 Mode B: knowledge production 37–8, 182 Mouffe, C. 6, 28 narrative language 23–6 narrative mode 57–8 New Production of Knowledge 37 Nonaka, I. 50–1 Nonaka’s model 50–2 non-core innovation 116–17 normalization 29 Oil Co.: commercialization era 79–83; current structure 83–8 oil companies: identity transformation 84, 112, 121–2, 166, 176 organizational interpretation modes 55–6 organizational learning 54–6 organizations: knowledge in 45–54; and types of knowledge 49–50 Orr, J. 46, 57 paradigmatic mode 57 pastoral power 41 perspective making 58 perspective taking 58 Polanyi, M. 22 post-capitalist societies 32–4 post-industrial age and knowledge 30–6 post-modernism 11 Potter, J. 4 power 68–9, 175–80; pastoral 41 power games 137–8 power relations 26–8, 29–30, 43, 52, 107 practice as aspect of language 4 process of interpretation 54–6 productive inquiry 53 professionalism 43 qualitative research 10 quantitative research 10–11 rational–cognitivist view 47 rational planning: innovation as 62–3 rationality 72–3 recruitment 102–4, 159

reflexive research 10–13 research: commercialization 174–5; impact of commercialization 88–9; nature of 93–4, 108; qualitative 10; quantitative 10–11; reflexive 10–13 Research and Innovation Group 113–21 Research and Technical Services (RTS): Oil Co. 80–1 research centres 37 research design 6–9 research language game 39–40, 173 research structures 37–8 resistance 28, 170, 171–2 risk aversion 115–16, 122, 136, 158, 160, 178 Rooney, D. 33 RTS see Research and Technical Services scientific knowledge: and economic discourse 165–6; and narrative 23–6 scientific language game 24–6, 62, 99, 143, 175 scientific technological innovation 177, 179–80 scientists: and Ideas Machine 133–8; identity change 174–5; loss of 172; role of 108; traditional view of 40 skills requirement 102–4, 170 Sköldberg, K. 12 social practice 5 socialization: Nonaka’s model 51 Sørensen, C. 47 state, the: role of 41 Stavrakakis, Y. 3 strategies: of invasion and resistance 168; of resistance 171–2 structures: discourse effect on 37–40; of knowledge 22–3 symbolic-analyst-dependent organizations 49–50 tacit knowledge 22, 52, 53 teaching language game 39–40 teamwork 96–9, 169 technological progress 33, 70 technology and innovation 62 Technology Group A: background 6–7; Ideas Machine 124–35; management’s voice 138–42; scientists’ voices 132–8; special fuels 89–90; structure 83; in transition 85–7; work design 96–8 Technology Group B: background 6–7; commercialization 156–61; Eureka 150–1, 154–6, 161–4; Ideas Machine

Index 199 145–54; lubrication 90–1; structure 83; in transition 87–8; work design 98–9 Tenkasi, R.V. 57–8 time constraints 134–6, 157–8, 170–1, 181 trust 44, 59, 71, 150 truth 29–30, 33–4 Tsoukas, H. 52 universal intellectual 40 universities 39–40 ‘virtual’ organizations 36

war language games 82, 167, 169 Watson, T. 74 Weber, M. 3 Weick, K. 54–6, 58 Wenger, E. 56 Wetherell, M. 4 Wittgenstein, L. 3 work design 96–9 work relationships 170 Xerox 46; ethnographic study 57