Journal of Intellectual Capital
ISSN 1469-1930 Volume 5 Number 2 2004
IC at the crossroads: theory and research Guest Editors Bernard Marr and Jay Chatzkel
Access this journal online __________________________ 219 Editorial advisory board ___________________________ 220 Abstracts and keywords ___________________________ 221 GUEST EDITORIAL Intellectual capital at the crossroads: managing, measuring, and reporting of IC
Bernard Marr and Jay Chatzkel____________________________________
IC valuation and measurement: classifying the state of the art
Daniel Andriessen _______________________________________________
Mathematics and modern business management
S. Pike and G. Roos _____________________________________________
Measuring and intervening: how do we theorise intellectual capital management?
Jan Mouritsen __________________________________________________
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CONTENTS
CONTENTS continued
Shaken, not stirred: defining and connecting indicators for the measurement and valuation of intangibles
Karin Grasenick and Jonathan Low ________________________________
Using content analysis as a research method to inquire into intellectual capital reporting
J. Guthrie, R. Petty, K. Yongvanich and F. Ricceri _____________________
Theory and method on intellectual capital creation: addressing communicative action through relative methodics
David O'Donnell ________________________________________________
The dynamics of value creation: mapping your intellectual performance drivers
Bernard Marr, Giovanni Schiuma and Andy Neely ____________________
Managerial knowledge to organisational capability: new e-commerce businesses
Anjali Bakhru __________________________________________________
COMMENTARY Moving through the crossroads
Jay Chatzkel ____________________________________________________
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Call for papers ____________________________________ 340
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EDITORIAL ADVISORY BOARD Guy Ahonen Professor in Knowledge Management, Head of Department, Hanken Business School, Finland Sabin Azua Mendia Managing Director, BearingPoint, Spain Margareta Barchan Co-founder and Executive Board Member, Celemi, Sweden Derek Binney Chief Knowledge and Technology Officer, CSC Australia, Australia David H. Brett CEO and Founder, Knexa, Canada Annie Brooking Chief Executive Officer, Lux Inflecta, Iceland Wendi Bukowitz Product Development, Mellon, Human Resources and Investor Solutions, USA Leif Edvinsson Managing Director, Universal Networking Intellectual Capital AB, Sweden Luiz Antonio Joia Associate Professor, Brazilian School of Public and Business Administration, Getulio Vargas Foundation, Brazil Baruch Lev Philip Bardes Professor of Accounting and Finance, Stern School of Business, New York University, USA Bernard Marr Research Fellow at the Center for Business Performance, Cranfield School of Management, UK and Visiting Professor of Intellectual Capital, University of Basilicata, Italy
Jose MarõÂa Viedma Marti Professor of Business Administration, Polytechnic University of Catalonia, Spain and President of Intellectual Capital Management Systems (ICMS), Spain Jan Mouritsen Department of Operations Management, Copenhagen Business School, Denmark Sharon L. Oriel Director, Global Intellectual Capital Tech Center, The Dow Chemical Company, USA Richard Petty Lecturer, Faculty of Business and Economics, The University of Hong Kong, Hong Kong, China Kurt P. Ramin Commercial Director, International Accounting Standards Committee Foundation, UK GoÈran Roos Chairman, Intellectual Capital Services Ltd, UK Hubert Saint-Onge Principal, SAINTONGE/ALLIANCE Inc., Canada Patrick H. Sullivan Sr President, Intellectual Capital Management Group Inc., USA Karl-Erik Sveiby Professor, Swedish School of Economics and Business Administration, Helsinki, Finland
Intellectual capital at the crossroads: managing, measuring, and reporting of IC Bernard Marr and Jay Chatzkel Keywords Intellectual capital, Intangible assets, Performance measures, Performance management, Performance appraisal This introductory editorial to the special issue “IC at the crossroads – theory and research” explains the rationale and background to the studies. In addition it outlines reasons why the field of intellectual (IC) capital is at the crossroads. It seems that awareness of the importance of IC has been created. It is now the role of researchers as well as practitioners to move to the next level. This next level involves issues around taxonomies as well as research methodologies. In order to move on, precise definitions of concepts such as IC, better justifications of why organizations need to measure and manage IC, and increased clarity about terms such as measurement, assessment, or valuation are needed. In addition, more rigorous research methods are needed in order to test and validate existing theories in the field.
Based on a literature review this article presents a classification of motives and solutions and plots ten existing methods in a “why” by “how” matrix.
Abstracts and keywords
Mathematics and modern business management S. Pike and G. Roos Keywords Intellectual capital, Asset valuation, Measurement This paper recognises the move towards making the disclosure of data concerning intangible resources a requirement. It sets down requirements for intellectual capital measurement systems that can be safely used by companies in disclosures and which are transparent and easily used by others. The paper argues that if rigour and safety comparable with ordinary financial disclosures is to be attained then only the rigour of measurement theory applied to intangible resources will suffice. Some existing methodologies are evaluated against the axioms of measurement theory. None evaluated so far are compliant.
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IC valuation and measurement: classifying the state of the art Daniel Andriessen Keywords Intellectual capital, Intangible assets, Asset valuation, Measurement, Literature The intellectual capital (IC) community has entered a phase of consolidation. This article contributes to this consolidation process by clarifying existing motives (why) and proposed methods (how) for valuing or measuring IC. In general, the field of IC performance measurement has paid little attention to organizational diagnosis and the “why” question. It is often unclear what the organizational problem is the methods intent to solve. Many methods for the valuation or measurement of intellectual capital can be characterized as “solutions in search of a cause. Another area that requires clarification is the “how” question. There seems to be confusion about the distinction between valuation and measurement. The distinction is fundamental yet not recognized in the field.
Measuring and intervening: how do we theorise intellectual capital management? Jan Mouritsen Keywords Intellectual capital, Measurement, Management information, Asset valuation, Narratives Measurement of intellectual capital is important, but not only for descriptive purposes. It is important because it enables intervention. If intervention and measurement are coupled, then measurement is an input rather than an output, and then measurement is not to be evaluated on its reflection of reality but rather on its ability to help actors transform their reality. This is particularly true for intellectual capital, which is widely accepted as part of an agenda for transformation and growth – it is a strategic/political agenda. To arrive at this conclusion, the paper discusses relationships between measurement and intervention comparing conventional financial statements with intellectual capital statements.
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Shaken, not stirred: defining and connecting indicators for the measurement and valuation of intangibles Karin Grasenick and Jonathan Low Keywords Intangible assets, Measurement, Accounting valuations The necessity and importance of measuring intangibles has become increasingly accepted in the business, financial and academic communities as a means for a better understanding of the value creation processes in private, public and not-for-profit enterprises. Intangible indicators are seen as idiosyncratic, unique to each enterprise and not standardised. Interpretation, dissemination and further research suffer from the lack of definition and measurement standards. This paper examines guidelines and suggestions for measurement instruments and discusses their limits. A framework for classifying intangibles and indicators through the utilisation of evaluation experience is derived in order to support the movement towards global agreement on terms, definitions, standards and measures. Further research is discussed concerning quality standards for measurement systems.
Using content analysis as a research method to inquire into intellectual capital reporting J. Guthrie, R. Petty, K. Yongvanich and F. Ricceri Keywords Intellectual capital, Annual reports, Disclosure, Research methods, Stakeholders Increasingly, researchers in the field of intellectual capital (IC) need to be able to justify the specific research methods they use to collect the empirical data that they examine to support and test opinions regarding the merit of different approaches to managing and reporting IC. Of the various methods available to researchers seeking to understand intellectual capital reporting (ICR), content analysis is the most popular. The aim of this paper is to review the use of content analysis as a research method in understanding ICR and to offer some observations on the practical utility of the method. Further, the paper examines several research method issues
relating to the use of content analysis that have been discussed in the social environmental accounting literature, but not as yet in the IC literature, which we believe are relevant to investigations underway in the field of ICR. This paper reports on several developmental issues we have confronted when using content analysis to examine the voluntary disclosure of IC in annual reports by various organisations. The paper also suggests two theoretical foundations for further investigation into the voluntary disclosure of IC by organisations, and suggests why content analysis is well matched to both these theories as a means to collect empirical data to test research propositions.
Theory and method on intellectual capital creation: addressing communicative action through relative methodics David O’Donnell Keywords Intellectual capital, Research methods Intellectual capital is a diverse and multidisciplinary field where there is much scope for interdisciplinary research. Such interdisciplinarity demands that we first transcend boundaries between IC researchers and disciplines and then transcend any subsequently perceived ontological and/or methodological barriers. Moving from the particular to the general, this paper draws on the contours of the Habermasian communicative relation to present some theoretical insights on how intellectual capital is created linguistically in social space. The ontological and methodological implications of this particular approach to research lead to the general argument for adopting a “relative view” on both ontology and methodology in order to craft navigational routes into interdisciplinary social space in the IC field. Such an approach allows IC researchers to draw on extant, and seemingly incommensurable, methodologies and techniques from analytical positivism, systems theory and the hermeneutic tradition in a scientifically justifiable post-foundationalist manner.
The dynamics of value creation: mapping your intellectual performance drivers Bernard Marr, Giovanni Schiuma and Andy Neely Keywords Intangible assets, Intellectual capital, Balanced scorecard, Resources This paper highlights the importance of visual representations of strategic intent in order to understand how organizational resources – especially intangible assets and intellectual capital – are used to create value. Based on the literature the paper provides a taxonomy of organizational value drivers. Grounded in the resource-based view of the firm, which argues that organizational resources or assets are bundled together and interdependent, it then highlights shortcomings in the strategy map approach based on the balanced scorecard. The paper then introduces the value creation map that utilizes both direct and indirect dependencies to map value creation. It is suggested that this approach complements the strategy map approach by extending its view of value creation from direct to both direct and indirect dependencies. Subsequently, the paper presents a case study of how the value creation map was applied to understand the new product development process in a leading furniture manufacturing firm.
Managerial knowledge to organisational capability: new e-commerce businesses Anjali Bakhru Keywords Knowledge management, Electronic commerce, Intellectual capital, Business formation The knowledge and skills of individuals are widely considered to represent an important component of a firm’s intellectual capital. The value of individuals’ knowledge is also
recognised from a capability-based perspective. While routines and capabilities are considered to act as the interface for the knowledge of individuals, an important and related issue is to examine how and to what extent individuals’ knowledge acts as the source of knowledge for the creation of firm-based routines and capabilities. Four firms across two online sectors, online broking and ISPs, are selected for the empirical case study research. The findings highlight the importance of the role of prior organisational experience in the development of new routines and capabilities. It is shown that variations in the role of prior organisational experience across firms and sectors are better understood in respect of the architectural and component knowledge of which managerial knowledge consists.
Moving through the crossroads Jay Chatzkel Keywords Intellectual capital, Knowledge management, Innovation The field of intellectual capital is at a crossroads. To move through the crossroads and to the next stage both practitioners and academics must substantially demonstrate the relevance of intellectual capital as a working discipline useful to achieve strategic goals and to improve levels of performance. While the field has generated a growing body of knowledge and practice over the last two decades, there is a need for both a great leap in how value can be generated and captured using an intellectual capital perspective, as well as acknowledging that there are multiple ways of knowing and different models for intellectual capital exchange. Much of this new development will come from an expanded, continuing dialogue between practitioners and academics.
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GUEST EDITORIAL
Intellectual capital at the crossroads: managing, measuring, and reporting of IC Bernard Marr Centre for Business Performance, Cranfield School of Management, Bedford, UK, and
Jay Chatzkel Progressive Practices, Anthem, Arizona, USA Keywords Intellectual capital, Intangible assets, Performance measures, Performance management, Performance appraisal Abstract This introductory editorial to the special issue “IC at the crossroads: theory and research” explains the rationale and background to the studies. In addition it outlines reasons why the field of intellectual (IC) capital is at the crossroads. It seems that awareness of the importance of IC has been created. It is now the role of researchers as well as practitioners to move to the next level. This next level involves issues around taxonomies as well as research methodologies. In order to move on, precise definitions of concepts such as IC, better justifications of why organizations need to measure and manage IC, and increased clarity about terms such as measurement, assessment, or valuation are needed. In addition, more rigorous research methods are needed in order to test and validate existing theories in the field.
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1. Background The background to this special issue was the 2003 PMA Intellectual Capital Symposium, which was held at Cranfield School of Management, UK, between 31 September and 2 October 2003. The Performance Measurement Association (PMA) is a global network for those interested in the theory and practice of performance measurement and management (see www.performanceportal.org). The Intellectual Capital Group of the PMA was established in recognition of the growing interest and importance of measuring and managing intellectual capital (IC). The PMA IC Group is a global and multidisciplinary network of thought-leading academics and practitioners who jointly facilitate and participate in cross-disciplinary knowledge transfer in the area of measuring and managing IC and intangible assets. Its aim is to raise the awareness of knowledge assets as critical value drivers in today’s economy and actively engage in high-quality research and global knowledge transfer. Participants in this group come from a wide spectrum of disciplines including strategy, finance, accounting, economics, HR, IT, operations, etc. and engage in a broad range of research projects. The aims of the 2003 PMA IC Symposium were to provide a forum where leading researchers active in the field of IC performance measurement and management can present their work to their peers and have it discussed. This enabled a dialogue about the boundaries of the field of IC and the forward research agenda. The Symposium was an interactive event which saw presentations of papers in addition to knowledge cafes,
syndicate as well as group discussions. Papers were required to address the important issue of research and theory in IC measurement and management. It was seen that for a concept such as IC, which was initially driven by the business community, it is important to address themes such as the underlying theory in the field of IC measurement, management, and reporting. The following questions were posted to potential contributors to respond to: . What are underlying theories in the field of IC? . Is IC a research field in its own right? And if so, what are the implications for the departmentalized management field? . How do we address the theoretical discussion of IC measurement? . Is it possible to measure knowledge? And if so how do we define measurement in this context? . How can we address the tension between high quality research and practitioner relevance? . Are there any implications for research methodology? And should there be a stronger focus on quantitative research? . What is the role of epistemology and ontology in this field? . What are the research themes that need to be addressed in order to take the IC field to the next level? The symposium saw presentations of papers addressing the above issues with contributors from across the globe. Outlined below are some of the key issues that were discussed at the symposium. In the final section we will then introduce the various contributions to this special issue and how they address some of the issues raised. 2. Why is IC at the crossroads? In an introduction article to a special issue of the Journal Controlling, Baruch Lev (2003), notes that the extensive research work on intellectual assets over the past ten years has succeeded in creating awareness. He then suggests that this was the first phase of the “intangible movement” and that we have to move on and shift the focus of our future work. Neely et al. (2003) confirm this and argue that we have to move on from first generation thinking. We believe that many early special issues on the topic in different journals fulfilled the important function of raising awareness that IC and intangible assets are principal value drivers in organisations today. However, since awareness has been achieved below we highlight some issues that arose from the discussions at the symposium and are believed important if we are to reach the next phase or next generation of IC research. 2.1. Taxonomies Even though organizations and scholars recognize the important contribution of many individual assets such as brand, relationships, culture, and knowledge, they do not necessarily use the term IC. It seems that the concept of IC is not well understood and rarely clearly defined. In their introduction to the special issue on IC in the Accounting, Auditing, & Accountability Journal, Guthrie et al. (2001) state that the concept of IC is often not or only poorly defined. With participants of the PMA IC Symposium from
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diverse backgrounds this issue came up very quickly: What do we mean when we talk about IC? Many attempts have been made to classify IC and many experts in the field made it very clear that they do not believe that we need any more frameworks or classifications. However, what we need is a definition of what we mean by IC when we use the term in articles or at conferences. The cross-disciplinary nature of the field means that different people with diverse backgrounds talk about IC. It often feels as if they are using the same terms but carry completely different meanings. It could happen that when you talk to accountants they refer to intangibles as “non-financial fixed assets that do not have physical substance but are identifiable and controlled by the entity through custody and legal rights” as defined by the Accounting Standards Board. Such a stringent definition excludes many commonly accepted intangibles like customer satisfaction, knowledge and skills of employees, as they cannot be controlled by the firm in an “accounting” sense. If we then went to a HR manager she might refer to intangible assets as skills, knowledge, and attitude of employees. A marketing manager might argue that intangibles such as brand recognition and customer satisfaction are at the heart of business success, whereas the IT manager might view key intangibles as being software applications and network capabilities. We therefore believe that a good definition of concepts in any written work is critical for an improved communication in our field. One way out of this problem would be to avoid using the term IC or intangibles, which would force us to define what we mean by it. As a conclusion we extract the following issue: IC as a concept is often poorly defined, we therefore advise that researchers and practitioners clearly define the term at the outset whenever the term is used. There are few people who would doubt that IC is critical for most organizations. For that reason many scholars and managers suggest ways and tools to measure IC. Often justified with the old adage “if you cannot measure it, you cannot manage it”. However, before any attempt is made to measure aspects of IC it is critical to clearly understand the reason for measuring it. A systematic review of the literature allowed researchers to identify three main categories of reasons why firms measure their IC (Marr et al., 2003). These main reasons can be brought together under the following broad headings: (1) strategy; (2) influencing behaviour; and (3) external validation. In addition, measurement can be seen as an output reporting on past realities or as an input for future decision making. The different reasons will have implications on the way we measure performance and therefore different measurement tools or techniques are appropriate to use. It is therefore important that we make the reasons for measurement explicit in order to judge the right tools and techniques. Directly related to the above point is the next taxonomy issue: what do we mean when we use the term “measure”? Do we refer to it as “indicating” a performance tendency or do we use it from a scientific measurement point of view with all the rules and requirements of measurement theory? Do we try to express our measures in percentage? Or do we try to assign financial value to our IC? Others might argue that measurement can be achieved without putting a single number against components of IC and rather assess the performance in a short narrative. We would like to distinguish
between operational measurement and financial valuation (Marr et al., 2004). Operational measurement approaches are more concerned with understanding the value creation process. They tend to be more internally focused and are used to gain management insights that can help organisations to better run their organisation. From this perspective the word measure – is used as a verb rather than a noun – is concerned with the process of understanding how IC impacts performance. On the other hand, financial valuation approaches are concerned with putting a financial value on an organisation or its IC. These approaches tend to take an external view of the firm and are designed to help analysts or investors calculate financial value. We acknowledge that other scholars might view it the other way around, however, the issue to extract is: When we use words such as measure, value, or assess, it is important to explain what we mean by it. Do we use the terms in their strictest sense or are we using them as loose terms to indicate performance? 2.2. Research methods The issue of research methods was discussed and the question was: what are the appropriate research methods to further the field of IC measurement and management? There seemed to be some consensus that more empirical research is needed. Much of the work published in the field is of theoretical nature or tries to build theories. This is not surprising for a young and evolving research field. However, in order to move to the next level it is important to empirically test the theories put forward. Some fundamental questions were raised regarding research methodology. Theory testing research projects are classically performed using quantitative and large sample methodologies. It seems important that we produce some of those studies in the field of IC. However, a key question was raised with regard to whether such methods would allow us to really understand some of the idiosyncrasies of IC. It seems that empirical testing should not only be provided by classical large sample, cross-sectional research projects but be complemented by rich, longitudinal case studies that will allow us to understand the specific context which seems to be critical for the analysis of IC. Much of the case studies reported to date do not test theories put forward by other scholars, the issue raised her is: We need to shift our research efforts towards academically rigorously testing of theories. For this purpose we need both large samples as well as longitudinal in-depth case studies. The multi-disciplinary nature of the field poses various challenges. The first is that academics often research in silos. It is rare that scholars read or publish outside their disciplinary area – e.g. marketing scholars tend to read and publish in marketing journals, go to marketing conferences, and talk to marketing managers. There are two challenges for the IC field: first, to engage a wider audience outside our niche field and second to ensure that a cross-disciplinary view of IC is taken. The issue here is: We need to engage in multidisciplinary and cross-functional knowledge exchange 3. How this special issue addresses the issues raised? Below we will outline how the various papers selected for this special issue contribute to the issues raised above and help the field to move on. The paper by Daniel Andriessen addresses taxonomy issues by highlighting the differences between measurement and valuation. Andriessen also extracts the different reasons of why organizations want to measure or value IC. Andriessen then moves on
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to map existing models of measuring and valuing IC into different categories distinguishing the different intentions and purposes. Stephen Pike and Go¨ran Roos pick up on the issue of taxonomies. In their paper they discuss the compliance of IC measurement approaches with measurement theory. Linking into Andriessen’s paper it is therefore important to know when we need measurement and how to create a “measurement system” as opposed to a “valuation system”. Whereas Pike and Roos put forward the problems of measurement theory when applied to measuring IC, Jan Mouritsen argues in his paper that the measurement from a conventional reason is not so critical. Mouritsen makes a case that measurement of IC is more about the process of measuring than about a hard number. Overall measuring and reporting of IC allow actions to be performed at a distance. In Mouritsen’s view measurement of IC should be seen as an input rather than an output. In the next paper Karin Grasenick and Jonathan Low pick up the discussion created by Andriessen, Pike, Roos, and Mouritsen. Low and Grasenick’s paper is concerned with the valuation of externally reported measures. In their paper the authors look at IC measurement as an output and highlight the problems in comparing different types of valuation approaches. The paper by James Guthrie, Richard Petty, Kittya Yongvanich, and Federica Ricceri addresses the issue of research mythology. The ever-increasing discussion about external reporting of IC resulted in a growing number of research projects into how much of their IC firms already disclose. Many of those research projects utilize content analysis as the main method for their research. There is a growing need for researchers to justify their research method. The paper by Guthrie et al. discusses content analysis as a research method and builds some theoretical foundation for this method. David O’Donell joins Guthrie et al. in a discussion about research methods and methodology. O’Donell argues that IC researchers from different disciplinary, social theoretical, and methodological traditions can in fact communicate substantially with each other. A key task for researchers and practitioners is to find a means of communicating with, explaining our approaches to, and understanding each other. For that to happen it seems important to clarify the ontological viewpoint in any dialogue. It is difficult to mix and match tools and ideas developed from opposing philosophical viewpoints but, based on work by Arbnor and Bjerke, the author argues it is possible. Following the theoretical discussions the next two papers are empirical in nature. The paper by Bernard Marr, Giovanni Schiuma and Andy Neely addresses the dynamic nature of IC. In this paper the authors disentangle the link between IC and value creation. Marr, Schiuma and Neely take a resource-based view and argue that mapping approaches can significantly contribute to clarification and communication of how IC contributes to value generation. However, they also argue that simple causal maps such as the balanced scorecard’s strategy maps are not sufficient to reflect the dynamics of IC. The theoretical concept is then tested using an empirical longitudinal case study of how a leading furniture manufacturing firm applied the concept. Anjali Bakhru also addresses the link between IC and organizational performance. In her paper Bakhru argues that IC is at the roots of organizational capabilities. In order to test the relationship between individual knowledge and its impact on the creation of firm-based routines the authors use case studies from newly formed
e-businesses. The research presented highlights the importance of the role of prior organizational experience in the development of new routines and capabilities. The closing commentary by Jay Chatzkel discusses the nature of the crossroads that the field has come to and how the symposium contributed to mapping out some next steps in moving towards the next stage of the development of the field. This piece incorporates views of additional symposium participants, as well as, on significant perspective that need to have attention paid to them. The paper includes contributions form Leif Edvinsson, Ahmed Bounfour, and Richard Hall. References Guthrie, J., Petty, R. and Johanson, U. (2001), “Sunrise in the knowledge economy: managing, measuring and reporting intellectual capital”, Accounting, Auditing & Accountability Journal, Vol. 14 No. 4, pp. 365-84. Lev, B. (2003), “Intangibles at a crossroads”, Controlling, Vol. 15 No. 3/4, pp. 121-7. Marr, B., Gray, D. and Neely, A. (2003), “Why do firms measure their intellectual capital”, Journal of Intellectual Capital, Vol. 4 No. 4, pp. 441-64. Marr, B., Gray, D. and Schiuma, G. (2004), “Measuring intellectual capital – what, why, and how?”, in Bourne, M. (Ed.), Handbook of Performance Measurement, Gee, London. Neely, A., Marr, B., Roos, G., Pike, S. and Gupta, O. (2003), “Towards the third generation of performance measurement”, Controlling, Vol. 15 No. 3/4, pp. 129-36.
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IC valuation and measurement: classifying the state of the art Daniel Andriessen
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Inholland University of Professional Education, Amsterdam, The Netherlands Keywords Intellectual capital, Intangible assets, Asset valuation, Measurement, Literature Abstract The intellectual capital (IC) community has entered a phase of consolidation. This article contributes to this consolidation process by clarifying existing motives (why) and proposed methods (how) for valuing or measuring IC. In general, the field of IC performance measurement has paid little attention to organizational diagnosis and the “why” question. It is often unclear what the organizational problem is the methods intent to solve. Many methods for the valuation or measurement of Intellectual Capital can be characterized as “solutions in search of a cause”. Another area that requires clarification is the “how” question. There seems to be confusion about the distinction between valuation and measurement. The distinction is fundamental yet not recognized in the field. Based on a literature review this article presents a classification of motives and solutions and plots ten existing methods in a “why” by “how” matrix.
Introduction In the past ten years the intellectual capital (IC) community has produced an overwhelming amount of new methods for the valuation or measurement of intangibles. Andriessen (2004) identifies over 30 methods and analyses 25 of them. However, the IC community has now entered a phase of consolidation. Several authors have taken initial steps in this direction. Bontis (2001) complains that in the IC community many distinctions exist that are merely labeled differently. He suggests a standard definition and classification. Marr et al. (2003) analyze various motives for creating IC measurement methods and study empirical evidence for their effectiveness. Pike and Roos (2004) judge the rigor of these methods by assessing their compliance with measurement theory. The time has come for the IC community to prove that its concepts can help in providing better understandings of the way organizations operate. More evidence is needed that shows that IC methods can help improve organizational performance. This consolidation requires three steps: (1) clarification by classification of existing concepts, motives and proposed methods; (2) separation of the corn from the chaff by assessing the rigor and effectiveness of the proposed methods; and (3) standardization and further development of the most promising methods.
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This article contributes to the first step. Clarification is needed with respect to three basic questions (Andriessen, 2004): what, why and how? This article focuses on the “why” and the “how” question. “Why” questions the motives found among influential writers for valuing or measuring IC. “How” questions the approaches for valuing or measuring IC. The “what” question is about the use of terminology and IC-classification schemes. This is beyond the scope of this article.
IC research has evolved primarily from the desires of practitioners (Bontis, 2002). Many of the leading authors in the field are more practitioners then academics. The field is dominated by a relative small number of frequently quoted authors. Consolidation starts with analysing their work and clarifying their concepts, motives and methods. Analysis of the “why” of various methods shows that these methods are based on a wide variety of problem-definitions. These definitions are sometimes made explicit but often remain implicit. Many methods can be characterized as “solutions in search of a cause”. It is often unclear what the organizational problem is that the methods intend to solve. In general, the field of IC measurement has paid little attention to organizational diagnosis. Generic methods have been proposed as a cure for all diseases. The “how” can also be problematic. Available methods use a broad array of approaches under various headings like valuation, financial valuation, measurement and assessment. However, there is a clear and distinct difference between valuation and measurement. This distinction is not yet recognized in the field and the concepts are being confused. For example, lack of insight into the value of IC is often used as a motive for creating IC reports, for example by Edvinsson and Malone (1997) and Roos et al. (1997). Yet, the methods these authors propose do not value intangibles; they merely measure it. Based on a systematic and critical review of the most influential writers in the field of IC measurement and valuation, this article contributes to the field in three ways: (1) develop a taxonomy of expressed motives for IC valuation or measurement by influential authors; (2) clarify the concept of measurement and valuation from a theoretical point of view to be able to; (3) classify influential methods for IC measurement or valuation according to “why” and “how”. This results in recommendations for the future research agenda. Methodology In order to analyze the motives and methods of influential authors, a literature review was undertaken. The selection of authors was based on their appearance in literature overviews by Bontis (2001), Bontis et al. (1999), Luthy (1998), Petty and Guthrie (2000), Pike and Roos (2004), Stewart (1997) and Sveiby (2002) that summarize the state of the art. Methods were selected that appear in at least four out of these seven publications. However, it became clear that these authors tend to overlook one important area of literature, the literature about the financial valuation of intangible assets (Reilly and Schweihs, 1999; Smith and Parr, 1994, Gro¨jer and Johanson, 2000). These authors were included in the review. This resulted in a sample of ten methods for valuing or measuring IC (see Table I). A systematic review of the work of the authors of these methods was undertaken in search of phrases that articulated the “why” of the methods: the authors’ motives to value or measure IC. This resulted in 37 different quotes expressing the need for measurement or valuation (as reported in Andriessen, 2004). These 37 verbatim texts were used to create a classification of motives. First, they were grouped into 18 categories. Second, these categories were further grouped into three main problems.
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Table I. Classification of methods
How Why
Financial valuation
Value measurement
Improving internal management
Economic value addede (Stewart, 1994) Market-to-book ratio (Stewart, 1997) Tobin’s Q (Stewart, 1997)
Balanced scorecard (Kaplan and Norton, 1992, 1996a, b, 2001) Intellectual capital audit (Brooking, 1996)
Improving external reporting
Economic value addede (Stewart, 1994) Market-to-book ratio (Stewart, 1997) Tobin’s Q (Stewart, 1997)
Transactional and statutory motives
Calculated intangible value (Stewart, 1997) Cost, market and income approaches (Reilly and Schweihs, 1999; Smith and Parr, 1994)
Value assessment Measurement Skandia navigator (Edvinsson and Malone, 1997) Intangible asset monitor (Sveiby, 1997) Intellectual capital index (Roos et al., 1997) Skandia navigator (Edvinsson and Malone, 1997) Intangible asset monitor (Sveiby, 1997) Intellectual capital index (Roos et al., 1997)
In order to classify the “how” of the methods, a theoretical framework was developed based on value theory. This framework provided four criteria that were used to assess the methods and determine what type of valuation or measurement they implied. Combining the motives and the types resulted in a classification of the methods into a “why” by “how” matrix, which was used to classify the state of the art (see Table I). Why value or measure IC? Authors of IC valuation or measurement methods have a wide variety of motives. They have different ways to define the problem they intend to solve. On a more abstract level these problem definitions can be grouped into problems around improving internal management, improving external reporting, or statutory and transactional motives. Improving internal management The issue of improving internal management is a wide one. Various problem definitions fall into this category. The problem definitions found can be grouped into seven categories of problems: (1) What gets measured gets managed. (2) Improving the management of intangible resources. (3) Creating resource-based strategies. (4) Monitoring effects from actions.
(5) Translating business strategy into action. (6) Weighing possible courses of action. (7) Enhancing the management of the business as a whole. The first category of problem definitions is the popular notion that management requires measurement or that measurement leads to better management. Roos et al. (1997) phrase it in terms of what you can measure, you can manage and what you want to manage, you need to measure. However, measurement is neither a necessary nor a sufficient condition for management. Stewart (2001) calls the phrase “you cannot manage what you cannot measure”: . . . one of the oldest cliche´s in management, and it’s either false or meaningless. It’s false in that companies have always managed things – people, morale, strategy, etc. – that are essentially unmeasured. It’s meaningless in the sense that everything in business – including people, morale, strategy, etc. – eventually shows up in someone’s ledger of costs or revenues (Stewart, 2001, p. 291).
Therefore, we need a more detailed problem definition to justify the measurement of intangible resources. A second, more valid group of problem definitions is based on the belief that intangible resources are not managed properly, that they deserve more management attention, and that they need to be managed differently than other resources. This has been the driving force of IC authors like Roos, Sveiby, and Edvinsson. Sveiby, for example, has made it his task to supply managers with a toolbox to help them in managing knowledge-based companies. Included in this second category are problems regarding the lack of awareness about the importance of intangible resources and the use of non-financial measures in managers’ compensation plans (Marr et al., 2003). Yet, improving the management of intangible resources is not a very specific problem. Kaplan and Norton (1992) are more concrete, and they identify a third category of problems. Their aim is to complement financial measures of company performance with operational measures to create a balanced view of results of action already taken and drivers of future financial performance. This means they want to create insight into the value drivers: the vital resources that determine future success. These resources are often intangible, and are the basis for creating resource-based strategies. Marr et al. (2003) call this motive “strategy formulation”. The second aim of the method of Kaplan and Norton (1996a) the balanced scorecard – is to measure performance in a balanced way as a feedback mechanism for management actions. This fourth category of problems lies at the core of the performance measurement community but also plays an important role in the IC community. Marr et al. (2003) call this motive “strategy assessment and execution”. After working with their method for a couple of years Kaplan and Norton (2001) found it addresses a more fundamental problem: how to link a company’s long-term strategy with its short-term actions. Therefore, their problem definition shifted from measuring performance to strategy implementation: But we learned that adopting companies used the Balance Scorecard to solve a much more important problem than how to measure performance in the information era. That problem, of which we were frankly unaware when first proposing the Balanced Scorecard, was how to implement new strategies (Kaplan and Norton, 2001, p. viii).
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This leads to a fifth category of problems. Pike and Roos (2000) describe this category as translating strategic intent into actions. The sixth category of problems is especially concerned with making trade-off decisions. This requires a method that consolidates different indicators into one measure of value. Roos has been one of the strongest advocates of methods that allow for making trade-off decisions. According to Roos et al. (1997), this is where the early IC models (which they referred to as first-generation models) fall short: Intellectual capital systems have long lists of indicators with no prioritization, thus making it impossible for managers to evaluate trade-off decisions (Roos et al., 1997, p. 7).
The last category of problems looks at the business as a whole. An example is the method of Economic Value Addede (EVA, a trademark owned by Stern Stewart and Co). EVA is not a method specifically designed to measure the value of intangibles. Its aim is much wider. The problem EVA addresses is poor management decision making that destroys shareholder wealth. According to EVA advocates, poor decision-making is often a result of using the wrong indicators of wealth creation, like return on investments or return on assets. The problem with most traditional indicators is that they are based on accounting-derived earnings instead of cash flow, and they do not include the cost of capital in the equation. EVA was developed to correct this. Improving external reporting Within the accounting profession, the problem of intangibles is often described as one of “relevance lost” (Johnson and Kaplan, 1987). This includes a loss of relevance of financial reporting to external stakeholders. An overview of problem definitions regarding external reporting can be clustered into five categories: (1) Closing the value gap between book and market value. (2) Improving information to stakeholders about the real value and future performance of the enterprise. (3) Reducing information asymmetry. (4) Increasing the ability to raise capital. (5) Enhancing corporate reputation and affecting stock price. The first category has to do with the popular notion that we need to close the growing value gap between book and market value. However, it is not the objective of the balance sheet to approximate the market value of a company (Rutledge, 1997; White et al., 1997). Upton (2001) phrases this misunderstanding as follows: If accountants got all the assets and liabilities into financial statements, and they measure all those assets and liabilities at the right amounts, stockholders’ equity would equal market capitalization (Upton, 2001, p. 60).
This fallacy underlies the widespread statement that the difference between book value and market value represents intangibles or IC (see, for example, Edvinsson and Malone, 1997; Stewart, 1997, 2001; Sveiby, 1997; Roos et al., 1997). Not only is there no need to make book value equal market value, it is also impossible. Comparing the gap between market value and book value of companies with IC is like comparing the difference between an apple and an orange with a banana (Andriessen, 2001). Pike et al. (2001) add another argument by stressing the fact that all resources of a company
combine and interact with each other. The equation market value ¼ book value + intellectual capital is incorrect because the variables are not separable, as required by the equation. A second and more accurate category of problems addresses disseminating poor information to stakeholders regarding the real value and future performance of the enterprise. Roos et al. (1997) want to give stakeholders a better understanding of the real value of a company. Sveiby (1997) questions how to describe the company as accurately as possible so stakeholders can assess the quality of management and the reliability of the company. Edvinsson and Malone (1997) state that traditional financial data as presented in the annual report are no longer leading indicators of future financial performance. The third category of problems is concerned with the growing information asymmetry between the public and those who have access to information on investments and returns regarding intangibles. Edvinsson and Malone (1997) are looking for ways to provide nuanced, dynamic information to the small investor. They state that the asymmetry leads to a misallocation of capital: As a result, too many deserving companies are underoptimized and undercapitalized, and thus sometimes are unable to complete their destiny. Meanwhile, other, troubled firms are artificially propped up until they collapse, pulling down shareholders and investors with them (Edvinsson and Malone, 1997, p. 8).
The misallocation of capital, in the end, produces social costs like unemployment, reduced productivity, and even diminished national competitiveness. The fourth category of problems focuses on the difficulty companies have in raising capital. A lack of transparency of intangibles makes it difficult for companies that lack tangible assets to raise money from investors or banks. Banking regulations may be biased against lending to companies with few tangible assets, which can be used as security. This may especially disadvantage young, high-tech companies with little record of accomplishment. Brooking (1996) wants her method to help create a basis for raising a loan. Pike et al. (2002) want to improve a company’s ability to raise capital. The fifth motive is enhancing external reputation and market valuation (Pike et al., 2002). At a recent meeting the author visited Edvinsson and stated that the Skandia navigator had saved Skandia about 1 per cent in interest rate on external capital, just by improving the reputation of the company. Statutory and transactional issues Literature on methods for the valuation of intangibles (Reilly and Schweihs, 1999; Smith and Parr, 1994) provides additional statutory and transactional reasons for valuing IC. Statutory provision, administrative ruling, or regulatory authority can mandate a valuation. Alternatively, valuation can be discretionary in the case of a transaction. Table II gives an overview of both types of motives. The first category of motives focuses on transactions. Transactions involving IC include the purchase, sale, or license of an intellectual property right. Gro¨jer and Johanson (2000) call this the tradability motive. This category of problems also includes the sale, merger or acquisition of a business, of which IC is an important component. Marr et al. (2003) refer to this motive as “Strategic development, diversification and expansion”. A valuation may be used to negotiate the transaction deal price.
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3 4 5
Table II. Statutory and transactional motives
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Type Transaction pricing and structuring for the sale, purchase, or license of an intangible asset Financing securitization and collateralization for both cash flow-based financing and asset-based financing Taxation planning and compliance, with regard to all sorts of possible deductions, tax compliance, and estate planning Bankruptcy and reorganization, including the value of the estate in bankruptcy and the assessment of the impact of proposed reorganization plans Litigation support and dispute resolution, including infringement of intellectual property rights and breach of contract Impairment testing of goodwill as required by FASB statement no. 142 (Financial Accounting Standard Board, 2001)
Discretionary Mandatory Mandatory Mandatory Mandatory and discretionary Mandatory
The second category of motives covers the issue of financing securitization. Many financial institutions require an independent appraisal of IC that is pledged as collateral against loan commitments or lines of credit. The third category looks at tax issues. Many tax jurisdictions allow for the periodic amortization of the cost of acquired intangible assets. Special tax regulations relate to the transfer of IC between subsidiaries of the same parent company. Many international conglomerates transfer IC and use IC royalty rates to shift taxable income into countries with lower income tax rates. The fourth category of motives evolves around bankruptcy and reorganization. A valuation of the IC of a debtor in possession may be necessary for bankruptcy-related accounting and taxation considerations. Bankruptcy judges are empowered to authorize the sale of intellectual property rights to outside parties because of reorganization. The fifth category looks at litigation support and dispute resolution. Litigation may require the quantification of economic damages related to breach of contract and intellectual property infringement. Finally the valuation of IC became relevant for external reporting with the introduction of FASB statement no. 142 (Financial Accounting Standard Board, 2001). This statement from the FASB states that goodwill and intangible assets that have indefinite useful lives will no longer be amortized but instead will be tested annually for impairment. This means that their fair value must be compared with their recorded amounts. This requires estimating a fair value of certain types of intangible assets. How to value or measure IC? Available methods use a broad array of approaches under various headings like valuation, financial valuation, measurement and assessment. However, there is a clear and distinct difference between valuation and measurement. This distinction is not yet recognized in the field and the concepts are being confused. What is the nature of value,
what do we mean by valuation and measurement, and what types of methods for valuation or measurement exist? Value Nowadays we think about money when we talk about value, but according to Crosby (1997), it was only during the Middle Ages that money developed as a means of quantifying value. Value closely relates to the concept of “values”. According to Trompenaars and Hampden-Turner (1997), values determine the definition of good and bad, as opposed to norms that reflect the mutual sense a group has of what is right and wrong. A value reflects the concept an individual or group has regarding what is desired. It serves as a criterion to determine a choice from existing alternatives. Following the Longman Dictionary of Contemporary English (Procter, 1978) as well as Trompenaars and Hampden-Turner (1997), value is defined as the degree of usefulness or desirability of something, especially in comparison with other things. The term usefulness is used to emphasize the utilitarian purpose of valuation. This is in line with Rescher’s (1969) value theory. He states that values are inherently benefit oriented. People engage in valuation “to determine the extent to which the benefits accruing from realization of some values are provided by the items at issue” (Rescher, 1969, pp. 61-62). However, usefulness is not the only aspect of value. Things can be valuable because they are beautiful, pleasing, or in other ways desirable, which is why the term desirability is included in the definition. Usefulness and desirability are not mutually exclusive. Things can be desirable because they are useful. Rescher (1969) states that value is not a property inherent in the item at issue. It depends on the subject’s view of usefulness or desirability. In that respect, “value is in the eye of the beholder”. Valuation Valuation requires implicit or explicit criteria, or yardsticks for usefulness or desirability. Rescher (1969, p. 61) describes valuation (he uses the term evaluation) as “a comparative assessment or measurement of something with respect to its embodiment of a certain value”. Rescher (1969) describes the importance of values for valuation as follows: Whenever valuation takes place, in any of its diverse forms . . . values must enter in. It is true that when somebody is grading apples, say, or peaches, he may never make overt reference to any values. But if the procedure were not guided by the no doubt unspoken but nevertheless real involvement with such values as palatability and nourishment, we would be dealing with classification or measurement and not with grading and valuation (Rescher, 1969, p. 71).
Furthermore, he states that any valuation makes use of a value scale, reflecting the fact that this value is found to be present in a particular case to varying degrees. This value scale can be an ordinal scale that reflects the varying degrees of value but does not show us the interval between the positions on the scale. A value scale can also be a cardinal scale. Such a scale is of an interval or ratio level (Swanborn, 1981). With regard to an interval level, the interval between the varying degrees of value is known, whereas on a ratio level it is also known what constitutes zero value. We can represent cardinal scales numerically. The advantage of using money as the denominator of value is that it creates a value scale at the ratio level that allows for mathematical transformations.
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Four ways to determine value So, valuation requires an object to be valued, a framework for the valuation, and a criterion that reflects the usefulness or desirability of the object. Now we have several options. . We can define the criterion of value in monetary terms, in which case the method to determine value is a financial valuation method. . We can use a non-monetary criterion and translate it into observable phenomena, in which case the method is a value measurement method. . If the criterion cannot be translated into observable phenomena but instead depends on personal judgment by the evaluator, then the method is a value assessment method. . If the framework does not include a criterion for value but does involve a metrical scale that relates to an observable phenomenon, then the method is a measurement method. So, a measurement method is not a method for valuation, yet this type of method is often used within the IC community. Swanborn (1981) defines measurement as the process of assigning scaled numbers to items in such a way that the relationships that exist in reality between the possible states of a variable are reflected in the relationships between the numbers on the scale. Measurement methods do not use value scales, but use measurement scales instead. Figure 1 shows the relationship between financial valuation, value measurement, value assessment, and measurement. The decisive factors are the use of values as criteria, the use of money as the denominator of value, and the observability of the criteria or measured variable. Classification of ten existing methods These categorizations of motives and approaches help us to classify the state of the art. Table I shows the position of ten influential models in the “why” by “how” matrix. Five models are financial valuation models that use money as unit of value. Economic Value Addede is used for both improving internal management and external reporting. It is
Figure 1. Financial valuation, value measurement, value assessment and measurement
based on an analysis of the economic value that is added in a company, taking into account the cost of the capital needed to create that value. According to Bontis et al. (1999) and Strassmann (1998, 1999) EVA is a good representation of the financial value of IC. Market-to-book ratio and Tobin’s Q are both based on an analysis of the difference between the market value and book value of companies. Stewart (1997) states that it could be useful for both improving internal management and external reporting. The calculated intangible value method is based on the assumption that the premium on a company’s value is a result of its IC. It is used to acquire loans and for tax purposes (Stewart, 1997; Luthy, 1998). Cost, market and income approaches are more “traditional” approaches to financial valuation that are used for various transactional and statutory purposes. The cost approach is based on the principle that an investor will pay no more for an investment than the cost to obtain an investment of equal utility. The market approach is based on the principle that in a free and unrestricted market, supply and demand factors will drive the price of any good to a point of equilibrium. In the income approach the value of IC is the value of the expected economic income generated by this capital. Two out of the ten methods can be labeled value measurement methods because they contain norms to act as yardsticks of value. The balanced scorecard groups financial and non-financial indicators and accompanying norms into four perspectives. It is predominantly used to improve internal management. The IC audit is a method to internally manage IC. It uses a range of indicators that have yardsticks attached that represent the optimal state of the indicator. Among the ten methods no value assessment methods were found. However, they do exist. Viedma’s Intellectual Capital Benchmarking System (Viedma, 2001) is a method of doing a value assessment that depends on expert judgment. Another example is Edvinsson’s IC Ratinge (see www.intellectualcapital.se). The Skandia navigator, the intangible asset monitor and the IC index do not use values, norms, or other yardsticks and we therefore cannot consider them valuation methods. They are merely measurement methods. They claim to have a purpose in both improving internal management and external reporting. Reflection and discussion The classification of problems as described above shows that there are many different problems to solve. However, thorough diagnosis is needed to determine the specified problem of the situation at hand. This is especially essential when the intention is to improve the internal management of an organization. There can be many reasons why a company is performing sub-optimally or poorly. There can be many ways to optimize a company’s performance. Valuation or measurement may or may not be the right solution. To check whether a valuation or measurement method is the right tool for the job the method should include a diagnosis phase. This phase is missing in all ten methods mentioned in Table I. As a result there is a clear danger that the methods turn out to be “solutions in search of a cause”. The array of problems that is being addressed by many of the methods is so broad that is seems questionable whether they can all be solved using one method. Yet this is what some authors claim. The problem definitions of Edvinsson and Malone (1997), Stewart (1997), Sveiby (1997) and Roos et al. (1997) cover a number of different problem categories within both the internal management and the external reporting domain.
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They claim their methods are a “jack of all trades”. More empirical evidence is needed about the effectiveness of these methods to cover such a broad selection of problems. Three well known methods, the Skandia navigator, the intangible asset monitor and the IC-index, do not measure value, despite their intentions. Edvinsson and Malone (1997, p. 70) state that their Skandia navigator fulfils the task to “Look upward toward more sweeping measures of value”. Roos et al. (1997, p. 91) state that their IC index “can help the company signify to the market its hidden value creation process, and thus help the market make a better assessment of the company’s value”. Yet, both are merely measurement methods that do not provide a valuation. Table I shows that when it comes to improving external reporting there is no value measurement method available among the ten methods studied. This is surprising as external stakeholders will have a strong need for yardsticks to help them judge the IC measures reported by companies. The absence of yardsticks may explain why Rylander et al. (2000) found that users in Sweden were not satisfied with the information on IC as it is presented in annual reports. The link to value creation is unclear and the information is therefore perceived as difficult to interpret and does not provide deep enough insights to deliver any real value to users (Rylander et al., 2000, p. 723).
Conclusion The methods that have been proposed in the last decennium to value or measure IC address a wide array of problems. This article shows they address at least 18 different problems. IC research suffers from too much focus on solutions and a lack of focus on organizational problems. Within the IC community, not enough research has been done into the nature of the problems that valuation or measurement addresses. As part of the consolidation process more evidence needs to be generated about the problems that can be solved using valuation or measurement methods. The methods themselves can be improved by adding a diagnostic phase that will allow users to identify what the problem in their organization is and to judge whether a specific method can help in solving it. Existing methods vary with respect to their approach. The language used is often not very consistent. This article shows that a distinction can be made between financial valuation methods, value measurement methods, value assessment methods and measurement methods. As part of the consolidation process within the IC community, more research is needed into the strengths and weaknesses of each of these approaches, related to the type of problems that need to be solved. This must lead to a more complete and empirically grounded “why” by “how” matrix that can help practitioners to choose the right tool for the job. References Andriessen, D. (2001), “Weightless wealth; four modifications to standard IC theory”, Journal of Intellectual Capital, Vol. 2 No. 3, pp. 204-14. Andriessen, D. (2004), Making Sense of Intellectual Capital, Butterworth-Heinemann, Burlington, MA. Bontis, N. (2001), “Assessing knowledge assets: a review of the models used to measure intellectual capital”, International Journal of Management Reviews, Vol. 3 No. 1, pp. 41-60.
Bontis, N. (2002), “Managing organizational knowledge by diagnosing intellectual capital: framing and advancing the state of the field”, in Bontis, N. (Ed.), World Congress on Intellectual Capital Readings, Butterworth Heinemann, Boston, MA, pp. 621-42. Bontis, N., Dragonetti, N.C., Jacobsen, K. and Roos, G. (1999), “The knowledge toolbox: a review of the tools available to measure and manage intangible resources”, European Management Journal, Vol. 17 No. 4, pp. 91-401. Brooking, A. (1996), Intellectual Capital: Core Asset For The Third Millennium, International Thomson Business Press, London. Crosby, A. (1997), The Measure of Reality; Quantification and Western Society 1250-1600, Cambridge University Press, Cambridge. Edvinsson, L. and Malone, M.S. (1997), Intellectual Capital: Realizing Your Company’s True Value by Finding Its Hidden Brainpower, HarperBusiness, New York, NY. Financial Accounting Standard Board (2001), Statement No. 142; Goodwill and Other Intangible Assets, available at: www.fasb.orgm Gro¨jer, J.E. and Johanson, U. (2000), “Accounting for intangibles at the accounting court”, work in progress, Available at: www.kunne.no/meritum/abstracts/court_a.pdf Johnson, H.T. and Kaplan, R.S. (1987), Relevance Lost, Harvard Business School Press, Boston, MA. Kaplan, R. and Norton, D. (1992), “The balanced scorecard; measures that drive performance”, Harvard Business Review on Measuring Corporate Performance, Harvard Business School Press, Boston, MA, pp. 123-45. Kaplan, R. and Norton, D. (1996a), “Using the balanced scorecard as a strategic management system”, Harvard Business Review on Measuring Corporate Performance, Harvard Business School Press, Boston, MA, pp. 183-211. Kaplan, R. and Norton, D. (1996b), The Balanced Scorecard, Harvard Business School Press, Boston, MA. Kaplan, R. and Norton, D. (2001), The Strategy Focused Organization, Harvard Business School Press, Boston, MA. Luthy, D.H. (1998), “Intellectual capital and its measurement”, Proceedings of the Asian Pacific Interdisciplinary Research in Accounting Conference (APIRA) Osaka, Japan, available at: www3.bus.osaka-cu.ac.jp/apira98/archives/htmls/25.htm Marr, B., Gray, D. and Neely, A. (2003), “Why do firms measure their intellectual capital?”, Journal of Intellectual Capital, Vol. 4 No. 4, pp. 441-64. Petty, R. and Guthrie, J. (2000), “Intellectual capital literature overview: measurement, reporting and management”, Journal of Intellectual Capital, Vol. 1 No. 2, pp. 155-76. Pike, S. and Roos, G. (2000), “Intellectual capital measurement and holistic value approach (HVA)”, Works Institute Journal (Japan), Vol. 42 October/November. Pike, S. and Roos, G. (2004), “Mathematics and modern business management”, paper presented at the 25th McMaster World Congress Managing Intellectual Capital, Hamilton. Pike, S., Rylander, A. and Roos, G. (2001), “Intellectual capital management and disclosure”, paper presented at the 4th World Congress on Intellectual Capital, McMaster University, Hamilton. Procter, P. (1978), Longman Dictionary of Contemporary English, Longman Group Ltd, Harlow. Reilly, R. and Schweihs, R. (1999), Valuing Intangible Assets, McGraw-Hill, New York, NY. Rescher, N. (1969), Introduction to Value Theory, Prentice-Hall, Englewood Cliffs, NJ.
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Roos, G., Roos, J., Dragonetti, N. and Edvinsson, L. (1997), Intellectual Capital; Navigating in the New Business Landscape, New York University Press, New York, NY. Rutledge, J. (1997), “You are a fool if you buy into this”, Forbes ASAP, April. Rylander, A., Jacobsen, K. and Roos, G. (2000), “Towards improved information disclosure on intellectual capital”, International Journal of Technology Management, Vol. 20 No. 5/6/7/8, pp. 715-42. Smith, G. and Parr, R. (1994), Valuation of Intellectual Property and Intangible Assets, John Wiley & Sons, New York, NY. Stewart, G.B. III (1994), “EVA: fact and fantasy”, Journal of Applied Corporate Finance, Vol. 7, Summer, pp. 71-84. Stewart, T.A. (1997), Intellectual Capital; The New Wealth of Organizations, Doubleday/Currency, New York, NY. Stewart, T.A. (2001), The Wealth of Knowledge: Intellectual Capital and the Twenty-first Century Organization, Doubleday/Currency, New York, NY. Strassmann, P.A. (1998), “The value of knowledge capital”, American Programmer, Vol. 11 No. 3, pp. 3-10. Strassmann, P.A. (1999), “Calculating knowledge capital”, Knowledge Management Magazine, October, Available at: files.strassmann.com/pubs/km/1999-10.php Sveiby, K.E. (1997), The New Organizational Wealth: Managing & Measuring Knowledge-Based Assets, Berrett-Koehler Publishers, San Francisco, CA. Sveiby, K.E. (2002), “Methods for measuring intangible assets”, available at: www.sveiby.com/articles/IntangibleMethods.htm Swanborn, P.G. (1981), Methoden van sociaal-wetenschappelijk onderzoek, Boom Meppel, Amsterdam. Trompenaars, F. and Hampden-Turner, C. (1997), Riding The Waves Of Culture, Nicholas Brealey Publishing, London. Upton, W.S. (2001), Business and Financial Reporting; Challenges from the New Economy, FASB, Norwalk, CT. Viedma, J.M. (2001), “ICBS intellectual capital benchmarking system”, Journal of Intellectual Capital, Vol. 2 No. 2, pp. 148-64. White, G.I., Sondhi, A.C. and Fried, D. (1997), The Analysis and Use of Financial Statements, John Wiley & Sons, New York, NY.
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Mathematics and modern business management
Mathematics and modern business management
S. Pike ICS Ltd, London, UK, and
G. Roos
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Cranfield University School of Management, London, UK Keywords Intellectual capital, Asset valuation, Measurement Abstract This paper recognises the move towards making the disclosure of data concerning intangible resources a requirement. It sets down requirements for intellectual capital measurement systems that can be safely used by companies in disclosures and which are transparent and easily used by others. The paper argues that if rigour and safety comparable with ordinary financial disclosures is to be attained then only the rigour of measurement theory applied to intangible resources will suffice. Some existing methodologies are evaluated against the axioms of measurement theory. None evaluated so far are compliant.
1. Introduction Over the last ten years many authors have written at length about the failure of accounting systems to assist managers with the management of their companies and this has spawned a variety of different approaches to company management. The concept of competencies (Kaplan and Norton, 1996) led the way in the 1990s and later in the decade (Stewart, 1997) intellectual capital came to prominence with a very broad range of explanations and implementations. In the latter part of the last decade and into the first few years of this one, there have been a number of high-profile financial collapses and the world has seen the rise and fall of the “dotcoms” and the inability of the markets or venture capitalists to estimate their worth with safety. Regulatory bodies have been pressing and moving towards the mandatory disclosure of certain elements of intangible resources and the recording of elements of goodwill in mergers and acquisition (FAS 141, 142) (Federal Accounting Standards Board, 2001a, b). While traditional accounting cannot track performance with the completeness needed for the valuation of modern companies (The Centre for Exploitation of Science and Technology (CEST), 2000) or for their effective management, there are no alternatives available that do. The most significant recent change has been the growing requirement to make disclosure of some intangible resources mandatory and this will require a level of rigour beyond what is currently the norm. If readers are to be able to trust disclosures and if companies are to make them with safety then they have to be made on a basis which precludes ambiguity. This means that ill-defined terms and the use of flexibly calculated indicators will be unacceptable. It may be argued that simpler indicator-based estimates of performance are acceptable in the internal operation of companies but to hold this view is to increase the measurement overhead rather than reduce it. If a company has a compliant financial accounting system, why run a duplicate system of less rigour. The same argument applies to the measurement of intangibles. If companies are obliged to make reliable
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disclosures which require a rigorous system of measurement and data collection, why duplicate it with an indicator-based system. This paper sets down a set of conditions that measures of intangible resources or intellectual capital should adhere to. It does not deal with the issue of terminology which is to be the subject of a later paper. The paper calls on measurement theory to set these conditions as adherence to theory is the only way to prevent ambiguity. That is, bespoke valuations or the use of indicators which do not follow repeatable processes and for which the underlying data fails to meet agreed conditions are unacceptable. Only in this way will transparency in the markets and confidence in statements be maintained. 2. Measurement 2.1. Measurement theory Serious thinking about measurement can be traced back to Eudoxus in ancient Greece but the ideas of the modern theory of measurement date from the nineteenth century work of Helmholtz (1887) and others. However, its formalisation is a surprisingly recent event. The primary motivation for the formalisation of measurement theory was the need to understand what it means to measure things in the social sciences; things like preference, value, loudness, etc. The catalyst for the formalisation of measurement theory is generally accepted to be the psychologist S.S. Stevens with later interest from the field of quantum physics but it was not until the 1970s that measurement was fully axiomatised with the publications of Scott and Suppes (1958) and Suppes and Zinnes (1963). Measurement is about two things, representation and ordering. Representation concerns itself with operations in which an attribute is represented by a measure and ordering which concerns the amount an entity possesses and practical measurement theory keeps them separate with entities in the real world to be measured being “represented” first and a numerical system then being defined to provide values for the entities to be measured and relations among these values. For a numerical system to represent an empirical relation system they must be isomorphic. The requirements for isomorphism are that the transformation function between the empirical and numerical systems is 1:1 and that the relationships between elements in the sets remain the same on transformation. The pragmatic requirements of empirical systems suited to modern business systems have been set out by M’Pherson and Pike (2001). In addition to the key axioms, they give a practical point which concerns minimality aimed at avoiding huge measurement systems but this is set aside for the time being. Mapping from the empirical to the numerical involves one further consideration and there has been considerable debate about it in the literature over the last 30 years. When looking at what transformations are permissible the nature of the scales used in the measurement becomes important. This, in turn, affects how business performance data is collected and especially the scales used since some preserve order but not relative amounts. The commonly used terminology categorises scales as shown in Table I. The resources used in businesses and the interactions between them are varied and complex. Any measurement scheme used to measure the performance of a business is therefore a multi-attribute system. This raises the issue of the commensurability of the measurement space, i.e. the various primary scales must be projected onto a common
Name
Typical description
Transformations
Allowed statistics
Nominal A classification of the objects Only those that preserve the (Descriptive) Frequencies, fact that objects are different mode, information content. (Associative) Chi-square. (Descriptive) Median, Ordinal A ranking of the objects Any monotonic increasing transformation, although a quantiles and quartiles. (Associative) Spearman’s transformation that is not rank-order correlation strictly increasing loses coefficient, Kendall’s tau, rho information As above plus arithmetic Interval Differences between values Any affine transformation are meaningful, but not the t(m) ¼ c * m+d, where c and mean, standard deviation values of the measure itself d are constants; the origin and unit of measurement are arbitrary As above plus geometric Ratio There is a meaningful “zero” Any linear (similarity) value and the ratios between transformation t(m) ¼ c*m, mean where c is a constant; the values are meaningful unit of measurement is arbitrary. Absolute All properties reflect the Only one-to-one All attribute transformations
measurement space that may have many dimensions but only one common scale on each dimension. Commensurability is usually achieved by normalisation, but it also means that a ratio scale is the minimum acceptable as measures being compared or combined from different areas will otherwise be arbitrary. All measures must have a meaningful zero. 2.2. Requirements for business measures The five conditions suggested for a business measurement scheme capable of measuring business performance and derived from measurement theory are: (1) Completeness. If the system to be measured is the whole company then the attributes of the company which are to be the subject of measurement must completely describe the company. The meanings of the attributes of business performance must be fully defined and their aggregate must reflect all the resources used by the firm and the ways in which they are used. (2) Distinctness. This is a simple requirement aimed at eliminating double counting. An attribute is acceptable as an entity to be measured if there is no element of its meaning that is contained within the meaning of any other attribute. (3) Independence. Independence concerns the relationships between entities being measured and requires that the normal mathematical conditions of commutativity, associativity, transitivity, monotonicity and the Archimedian condition are satisfied. This means that aggregation to overarching measures can be undertaken safely.
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Table I. Measurement scales
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(4) Agreeability. The issue of agreeability concerns the mapping from the empirical to the numerical system. This means requires that the meaning of the attribute in the empirical system is fully reflected in the numerical system where the measurement is actually taken. In other words, the attribute must not be represented in the numerical system by a proxy which has a different meaning. (5) Commensurability. To make the measurements and subsequent aggregation valid, they must be observed using a ratio scale and be normalised onto a common scale. Failure to do this will render meaningless many of the conclusions drawn from the data. Where measures are readily observable physical measures, such as temperature, the correct scale is easily chosen and applied. Many business measures are not of this kind and ratio scale techniques must be used in data collection.
3. Business measurement systems Over the last 10-15 years, many systems have been devised to help managers with business performance and with a special emphasis on non-financial measures. According to Luthy (1998) and Williams (2000), methodologies may be categorised into four groups. These are: (1) Direct intellectual capital methods (DIC). Estimate the $-value of intangible assets by identifying its various components. Once these components are identified, they can be directly evaluated, either individually or as an aggregated coefficient. (2) Market capitalization methods (MCM). Calculate the difference between a company’s market capitalization and its stockholders’ equity as the value of its intellectual capital or intangible assets. (3) Return on assets methods (ROA). Average pre-tax earnings of a company are divided by the average tangible assets of the company. The result is a company ROA that is then compared with its industry average. The difference is multiplied by the company’s average tangible assets to calculate an average annual earning from the intangibles. Dividing the above-average earnings by the company’s average cost of capital or an interest rate, one can derive an estimate of the value of its intangible assets or intellectual capital. (4) Scorecard methods (SC). The various components of intangible assets or intellectual capital are identified and indicators and indices are generated and reported in scorecards or as graphs. SC methods are similar to DIC methods, expect that no estimate is made of the $-value of the intangible assets. A composite index may or may not be produced. MCM and ROA methodologies can be ignored from the outset since they are fundamentally based on financial figures, augmented by selected intangible assets. If the context of measurement is the value of the company then they are at once incomplete. Furthermore, ROA approaches tend to be based on industry comparisons rather than the company itself and many of the MCM approaches view intellectual capital a separable entity from book value. This cannot be the case as is explained in section 4.7.
DIC and to a lesser extent SC methods offer the potential to create a comprehensive picture of an organisation’s health and can be applied at any level of an organisation. They are aimed at management support and DIC is intended to be holistic. Sveiby (1997) uses this classification system and has generated the list of methodologies in Table II. It should be remembered that the aim of this paper is not an exhaustive assessment of all methodologies but is instead, an illustrated description of the attributes required of a measurement system for intangible resources. The methodologies listed by Sveiby but excluding the MCM and ROA methodologies are listed in Table II. With the exception of VAICTM, all MCM and ROA methodologies are excluded and those DIC and SC methodologies aimed at a single specific area of company operations such as human resource management, marked with a grey “type” cell are also excluded as they are, by definition, incomplete. Lev’s value chain scorecard is excluded as there is insufficient data for analysis. In all cases, the analysis that follows assumes that the execution of the methodology is perfect. 4. Assessments of methodologies 4.1. Technology broker The Brooking model defines the goal which gives the context for measurement. The approach is based on the resource based view of the firm (Barney, 1991). It is inclusive of all resources important to the development of the company whether they are owned by the company or not. The resources are categorised into four major component areas and then broken down into 33 lower level resources. While it can be assumed that the components are complete down to the four component level, it is a matter of faith that the 33 lower level resources completely describe the meaning of the four levels above. To be sure that they do would require that their definitions are recorded and found to encompass the whole meaning of the component above. While many of the resources appear distinct, those in the human component are highly questionable from this regard. For example, can we safely demonstrate that vocational qualifications are distinct from work-related knowledge. The agreeability of the metrics chosen is a matter for the individual circumstance and the degree of latitude in selecting proxies that is given. Following the selection of measures and assessment of them is carried out by means of a questionnaire with 178 questions. These questions are varied in nature but often seek subjective opinion using the equivalent of a Likert scale. This means that measurement is on an ordinal scale and is unsuitable for use in many statistical and mathematical processes (see Table III). 4.2. Value explorer The value explorer (see Table IV) of Andriessen and Tiessen (2000) is a competence-based approach described in detail in the appendix to their book. It defines the core competencies of the company and examines them in five ways. The results of the examination are combined to give a strength for each competence and this is then linked to the gross profit of the company to show the contribution each competence, and the intangible assets that underpin them, to profit. This is projected forward into the future. The process of selecting core competencies is similar to that of Hamel and Prahalad (1994) and seeks out only those things in the company that pass the criteria for being core. The description of the company is at once incomplete. Furthermore, there is no
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Table II. Measurement methodologies
Name
Originator ref Description of measure
Type
Para ref
Technology broker
(Brooking, 1996)
DIC
4.1
Value of intellectual capital of a firm is assessed based on diagnostic analysis of a firm’s response to 20 questions covering four major components of intellectual capital Citation- weighted (Bontis, 2000) A technology factor is calculated based on patents the patents developed by a firm. Intellectual capital and its performance is measured based on the impact of research development efforts on a series of indices, such as number of patents and cost of patents to sales turnover, that describe the firm’s patents The value (Andriessen Accounting methodology proposed by explorere and Tiessen, KMPG for calculating and allocating value 2000) to five types of intangibles: (1) Assets and endowments, (2) Skills and tacit knowledge, (3) Collective values and norms, (4) Technology and explicit knowledge, (5) Primary and management processes Intellectual asset (Sullivan, Methodology for assessing the value of valuation 2000) intellectual property Total value (Anderson A project initiated by the Canadian creation, TVCe and McLean, Institute of Chartered Accountants. TVC 2000) uses discounted projected cash-flows to re-examine how events affect planned activities (Pulic, 2000) Measures how much and how efficiently Value added intellectual capital and capital employed intellectual create value based on the relationship to coefficient three major components: (1) capital (VAICe) employed; (2) human capital; and (3) structural capital Human capital (Fitz-Enz, Sets of human capital indicators are intelligence 1994) collected and bench-marked against a database. Similar to HRCA Skandia (Edvinsson Intellectual capital is measured through navigatore and Malone, the analysis of up to 164 metric measures 1997) (91 intellectually based and 73 traditional metrics) that cover five components: (1) financial; (2) customer; (3) process; (4) renewal and development; and (5) human Value chain (Lev, 2002) A matrix of non-financial indicators scoreboarde arranged three categories according to the cycle of development: discovery/learning, implementation, commercialisation
DIC
DIC
4.2
DIC DIC
Data not avail.
ROA
4.3
SC
SC
4.4
SC
(continued)
Name
Originator ref Description of measure
Type
Para ref
IC-indexe
(Roos et al., 1997)
SC
4.5
SC
4.6
SC
4.7
SC
4.8
Intangible asset monitor
Value creation index
Balanced score card
Completeness Possible
Completeness No
Consolidates all individual indicators representing intellectual properties and components into a single index. Changes in the index are then related to changes in the firm’s market valuation (Sveiby, 1997) Management selects indicators, based on the strategic objectives of the firm, to measure four aspects of creating value from intangible assets. By: (1) growth (2) renewal; (3) utilisation/efficiency; and (4) risk reduction/stability (Ittner et al., Drivers of value are derived from an 2000) extensive literature survey and advanced statistics. Metrics are weighted and combined to give a value creation index. The index is compared and combined with financial data (Kaplan and A company’s performance is measured by Norton, 1992) indicators covering four major focus perspectives: (1) financial perspective; (2) customer perspective; (3) internal process perspective; and (4) learning perspective. The indicators are based on the strategic objectives of the firm
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Table II.
Distinctness
Independence
Agreeability
Scale
Unlikely
No
Context specific
Ordinal
Distinctness
Independence
Agreeability
Scale
No
No
Yes
Nominal
reason why a contributory element to a core competence, what they describe as an intangible assets, 14 in number, should not appear in support of another competence. This means that there are elements of meaning common to both and hence both distinctness and independence are lost. The measures to be taken are generic in form: added value, competitiveness, potential sustainability and robustness, and each of these has five internal metrics. It may be assumed that the resultant 25 measures are agreeable even though they are not specific to any particular competence. Measurements within each of the five areas are a “0” or “1”, that is, either the test/statement is true or it is not. This means that the scale
Table III. Technology broker
Table IV. Value explorer
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is nominal and that the use of the mathematical relationship to determine the value contribution of the core competencies is invalid. 4.3.Value added intellectual capital (VAICTM) VAIC is different in character from the other conventional intellectual capital methodologies in that while intellectual capital is derived from resource-based accounting with traditional assets being seen as other types of resource, VAIC is activity based. The company is described as a set of processes and activities, it may be assumed that this can be carried out to completeness with respect to the company and what it does. A process is a value creating or destroying step which begins with some input and ends with an output expressed in terms of monetary gain for the company. Between the inputs and outputs the process involves a number of activities many of which will be common to several processes. There are no rules to guide the definition of processes or activities. With such granularity and with the expression of processes and activities as a matrix of interactions, it is unlikely that the metrics are distinct or independent. Pulic (2000) uses the assumption from Edvinsson’s work that the company value can be described as financial resources and intellectual capital with the latter being divided into human and structural capital. To link the processes to financial data, each process is assessed in terms of a number of ratios: value added (VA), human capital (HC) and structural capital (SC) and ratios of them called VAHU, STVA and VAIC. These are deemed to be the important ratios and are common to all VAIC implementations. They may be considered to be agreeable. All measurements are dependent on ratios of hard financial data either income or cost. The scale system is therefore a ratio scale (see Table V). 4.4. Skandia navigator The underlying metric structure is the Skandia market value scheme (Table VI) in which the hierarchical relationships between the five capital categories are described. Edvinsson’s groundbreaking book contains no sub-division scheme in which the five categories are broken down into lower level attributes which can be measured but moves straight to a metric set which number 111 metrics. This leap from the empirical to the numerical relation system without first going through a set of tested attributes means that the agreeability of the metrics in the numerical relation system cannot be assured. Completeness
Table V. VAICTM
Table VI. Skandia market value scheme
Yes
Completeness Undeterminable
Distinctness
Independence
Agreeability
Scale
No
No
Yes
Ratio
Distinctness
Independence
Agreeability
Scale
No
No
No
Interval
The metrics given are Edvinsson’s suggestions and are not intended to be a definitive set. It is possible that an attribute set can be chosen which is complete with respect to the company as a whole. It is also possible that the attributes can be made distinct and independent although the set in the literature used for illustration are not. For example, many of the attributes are ratios with the same quantity, the number of employees, as the denominator. The measures themselves are a mixture of ratios, absolute numbers and financially-based figures. Many of the simpler metrics can be placed on a ratio or even an absolute scale but many of the ratio metrics and some of the others cannot. There are few instances of ordinal or nominal measures which may be substituted out but overall, the lowest common level of scale must prevail and so it may be judged that metrics belong to the interval scale. The connection to financial figures requires the evaluation of a financial figure and this is given by the product of a coefficient of efficiency and a $-value of the IC, determined as the $-value of investments and costs in 21 items, and an index which is the average of a number of ratio metrics. However, as they are on a non-commensurable interval scale is can be argued that the arithmetic mean that is taken many not be valid.
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4.5. Intellectual capital index The intellectual capital index (Table VII) is attributed to Roos et al. (1997). It shares superficial similarities with the Skandia market value system being based on a similar taxonomy. The IC index and process that underlies it is based on a complete description of the resources used by a company in the creation of value for the long term. It is a two-stage approach with the process guiding the development of the index. In the process, the complete resource set is sub-divided until a set of attributes is derived which can be assessed. In principal, there is no reason why this set of attributes cannot be distinct and independent. In the intellectual capital process, the key issues are the importance of the resources and the importance of the transformations between them. Thus, all possible resources and transformations between them are available in the empirical relation system. The measurements of importance used in evaluating the resources and transformations are based on an interval approach involving the attribution of 100 points between sets of resources and transformations. It is then filtered to display only the resources and transformations of key strategic importance and this becomes the basis of the metric set rather than the metrics themselves. Thus the IC process is complete, distinct and independent but is based on an interval scale. The metrics themselves are now based on an incomplete set in the numerical relation space but the precise metrics are selected by inspecting the value creating activities that underlie the transformations, choke points on those pathways, the pathways with greatest customer perceived cost and greatest cost. While the IC process is a guide, it is not the determinant for the metrics. This part of the index
Completeness No
Distinctness
Independence
Agreeability
Scale
Probably
Probably
Probably
Ratio
Table VII. IC Index
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process can be made to be fully compliant with measurement theory except for the fact that the original metric set in the numerical relation system is incomplete. 4.6. Intangible asset monitor The intangible asset monitor (IAM) (Table VIII) is attributable to Sveiby (1997). It is a resource stock-flow model similar in its terminology to the Skandia market value scheme and the intellectual capital index. The complete resources of the firm are described in terms of internal structure, external structure, competence making up the intangible assets. Tangible assets are treated in the same way. Using the guides of growth, innovation, efficiency and stability, the resources of the firm are broken into attributes for measurement. While the top level of the IAM is complete from the definitions given, the competence and internal structure, collectively referred to as the organisation have the potential for indistinctness and dependence. For the 16 possible empirical relation system areas in this model, users are recommended to break these areas into two to six key areas for measurement. Given the breadth of some of these areas it is arguable that the quality of completeness is maintainable in practice. With the attributes selected, users define the measures and the monitor is formed by the measures taken. In the IAM there is no real attempt to combine the intangible assets to form and overall score or even to combine the tangible and intangible assets to give an estimate of market value as implied by the schematics of the monitor. In the derivative management simulation “Tango”, marketed by Celemi (2003) this aggregation is carried out by an additive process. In principle, there is no reason why metrics should not be agreeable and formed and collected on a ratio scale. 4.7. Value creation index The value creation index (VCI) (Table IX) was devised by Ernst & Young and embraces the fallacy that financial and non-financial contributions to market value are separable when they are not. Non-separability arises from both dimensional analysis considerations and from the consideration that monetary assets are both external (seen by the market) and internal in that they are key to the operation of company processes, which involve intangible assets. The VCI has a radical approach to the construction of the empirical relation system in that it uses a statistical analysis of entities which may be involved in value creation across a large number of large companies. Thus, a set of nine key areas with statistically-proven significance were found. Furthermore, statistical analysis allows a relative importance to be attached to each. The main problem with this is that since it
Completeness Table VIII. Intangible assets monitor
No
Completeness Table IX. Value creation index
No
Distinctness
Independence
Agreeability
Scale
Possible
Possible
Possible
Ratio
Distinctness
Independence
Agreeability
Scale
Yes
Probable
Yes
Ratio
does not start with the whole of the company, but looks instead at important value creating areas, it cannot be complete. Distinctness and probably independence are assured due to the analytical approach involved. Furthermore, if distinctness and independence among the attributes is assured then so is distinctness and independence of the nine key areas from which they would otherwise have been developed. The nine areas are broken into lower level attributes. Candidate attributes for companies in a wide variety of business sectors were selected from the literature and tested for contribution to the key area and for distinctness and independence. Thus, save for the question of completeness, the attributes of the VCI empirical relation system will be compliant with measurement theory. The measures of the attributes are discovered in the statistical process and thus it may be assumed that they are agreeable measures. Measures will be dependent on the industry under consideration but the example metrics in the literature tend to belong to the ratio or even absolute scales. Weighted performance data with the weightings taken from the statistical analysis are combined to form the VCI.
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4.8. Balanced scorecard (BSC) Although the roots of the scorecard go back to the Tableaux de Bord in France in the 1950s, it is generally held that the modern version is attributable to Kaplan and Norton (1996). There some similarities between the BSC and the IAM, especially in the perspectives that they use. The perspectives of the BSC do differ from the IAM in that the BSC does not seek to base itself on the nature of the firm but, instead, takes a strategic focus which at once compromises completeness since the BSC addresses what ought to be at the expense of what actually is. The selection of metrics raises further problems as the most common method of selecting metric is not a structured and considered process aimed at producing a complete, distinct and independent set. By contrast, it is a pragmatic approach resulting from brainstorming. As many metrics as required are developed and care is taken to ensure that they include leading measures, lagging measures and within them is a core set which may be benchmarked. There seems little attempt to align with measurement theory. Since attributes in the empirical relation system are pragmatic, there is usually no problem with designing metrics to meet them. BSC metrics are therefore agreeable. As the metrics are idiosyncratic, they may be of any scale type although interval and above appear common (Table X). 5.Conclusion The results from all the analyses have been collected in Table XI. Table XI shows that none of the methodologies are fully compliant although it must be remembered that only a selection have been analysed. Measurement theory is clearly a stern test although if the measurement of intangibles is to achieve the acceptability of traditional accounting, it must pass this test. Nevertheless, it is also Completeness No
Distinctness
Independence
Agreeability
Scale
No
No
Yes
Interval+
Table X. Balanced scorecard
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Table XI. Summary of results
clear that while there are no candidates suitable as measurement systems, many of the methodologies provide considerable amounts of useful guidance for managers; Rigby (2000) estimates that more than half the global largest 1,000 companies use the balanced scorecard. Surprisingly, completeness is a criterion very few meet although it is simple to achieve. Several of the methodologies begin with a complete description of the company but filter or develop attributes in the empirical relation system in such a way as to destroy completeness. From a valuation and disclosure standpoint, completeness is a crucially important starting point; off-balance sheet transactions might be considered to be the financial world’s analogue. Compliance with distinctness and independence is simply a question of discipline in design. It is fortunate that the intellectual capital community has failed to standardise on any terminology. This eases the issue of defining attributes so that they are valid in the empirical space since there are no fixed positions. Agreeability of the metrics with the attributes is often difficult with unacceptable proxy measures common. Three of the methodologies were compliant as, in general, their metric system was developed alongside the attributes to which they were to connect. However, two of the three were definitely non-compliant. The conclusion to be drawn from this is that attributes and metrics were forced to fit. Had the attributes been developed further, it is possible that acceptable attributes and agreeable measures could have been found. The danger of this type of extension to metric systems is that they become unwieldy. However, none of the metric systems is anything other than tiny when considered against the overhead imposed on company by the current requirements of financial management. Finally, most of the methodologies could be made compliant with the requirement to use ratio scales. Where metrics are subjective, there is no reason why ratio scales cannot continue to be used. The requirement here is that a data collection method, such as pair-wise comparisons as developed by Saaty (1980) are used as they naturally apply ratio scaling. There are numerous other methods which lead to ratio scales and even more that do not. Where there is no attempt to process measurements, scaling may not be an issue but where some combination is contemplated either to form an index or to link with financial data, the proper scale use is mandatory.
Technology broker Value explorer VAICTM Skandia market value scheme IC index Intangible assets monitor Value creation index Balanced scorecard
Complete
Distinct
Ind.
Agreeable
Scale
Possible No Yes Unknown No No No No
Unlikely No No No Probably Possible Yes No
No No No No Probably Possible Probably No
Context specific Yes Yes No Probably Possible Yes Yes
Ordinal Nominal Ratio Interval Ratio Ratio Ratio Interval+
Although there is widespread non-compliance in the sample of methodologies examined, there is enough compliance against each of the criteria to suggest that it is not impossible to design a single methodology that is compliant everywhere.
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References Anderson, R. and McLean, R. (2000), Total Value Creation, CD-ROM available from CICA (Canadian Institute of Chartered Accountants). Andriessen, D. and Tiessen, R. (2000), Weightless Weight – Find your Real Value in a Future of Intangible Assets, Pearson Education, London. Barney, J. (1991), “Firm resources and sustained competitive advantage”, Journal of Management, Vol. 17, pp. 99-120. Bontis, N. (2000), “Assessing knowledge assets: a review of the models used to measure intellectual capital”, working paper, Queen’s Management Research Centre for Knowledge-Based Enterprises. Brooking, A. (1996), Intellectual Capital: Core Assets for the Third Millennium Enterprise, Thomson Business Press, London. Celemi (2003), available at: www.celemi.com/simulations/business/tango/index.php (The) Centre for Exploitation of Science and Technology (CEST) (2000), Measuring the New Intangibles. Edvinsson, L. and Malone, M. (1997), Intellectual Capital: Realizing your Company’s True Value by Finding Its Hidden Brainpower, Harper Business, New York, NY. Federal Accounting Standards Board (2001a), FAS 141, Business Combinations, Federal Accounting Standards Board, Norwalk, CT. Federal Accounting Standards Board (2001b), FAS 142, Goodwill and Other Intangible Assets, Federal Accounting Standards Board, Norwalk, CT. Fitz-Enz, J. (1994), How to Measure Human Resource Management, McGraw-Hill, New York, NY. Hamel, G. and Prahalad, C. (1994), Competing for the Future, Harvard Business School Press, Boston, MA. Helmholtz, H. (1887), “Zahlen und Messen”, Philosophische Aufsatze, Fues’s (Counting and MeasuringCounting and Measuring), translated by Bryan, C.L. (1930), Van Nostrand, Verlag, Leipzig. Ittner, C., Kalafut, P., Larcker, D., Sean Love, S., Low, J., Park, J., Siesfeld, T. and Zito, S. (2000), “Measuring the future: value creation index”, available at: www.ca.cgey.com/news/ invisible_advantage_mediakit/vci.pdf Kaplan, R. and Norton, D. (1992), “The balanced scorecard: measures that drive performance”, Harvard Business Review, January-February, pp. 71-9. Kaplan, R. and Norton, D. (1996), The Balanced Scorecard: Translating Strategy into Action, Harvard Business School Press, Boston, MA. Lev, B. (2002), Intangibles: Management Measurement and Reporting, Brookings Institution, Washington, DC. Luthy, D.H. (1998), “Intellectual capital and its measurement”, Proceedings of the Asian Pacific Interdisciplinary Research in Accounting Conference (APIRA), Osaka, Japan. M’Pherson, P. and Pike, S. (2001), “Accounting, empirical measurement and intellectual capital”, Journal of Intellectual Capital, Vol. 2 No. 3, pp. 246-60.
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Pulic, A. (2000), “An accounting tool for IC management”, available at: www. measuring-ip.at/Papers/ham99txt.htm Rigby, D. (2000), “Balanced scorecard collaborative announces the formation of an XML standards committee”, Management Tools, available at: www.bain.com Roos, J., Roos, G., Dragonetti, N. and Edvinsson, L. (1997), Intellectual Capital: Navigating in the New Business Landscape, Macmillan, Basingstoke. Saaty, T. (1980), The Analytical Hierarchy Process: Planning, Priority Setting, Resource Allocation, McGraw-Hill, New York, NY. Scott, D. and Suppes, P. (1958), “Foundational aspects of theories of measurement”, Journal of Symbolic Logic, Vol. 23, pp. 113-28. Stewart, T. (1997), Intellectual Capital: The New Wealth of Organisations, Doubleday, New York, NY. Sullivan, P. (2000), Value-driven Intellectual Capital: How to Convert Intangible Corporate Assets into Market Value, Wiley, New York, NY. Suppes, P. and Zinnes, J. (1963), “Basic measurement theory”, in Luce, R., Bush, R. and Galanter, E. (Eds), Handbook of Mathematical Psychology, Vol. 1, Wiley, New York, NY, pp. 1-76. Sveiby, K. (1997), The New Organizational Wealth: Managing and Measuring Knowledge Based Assets, Berrett Koehler, San Francisco, CA. Williams, M. (2000), “Is a company’s intellectual capital performance and intellectual capital disclosure practices related? Evidence from publicly listed companies from the FTSE 100”, paper presented at McMasters Intellectual Capital Conference, Hamilton. Further reading Johansson, U. (1997), “A model illustration and implications”, Journal of Human Resource, Costing and Accounting, Vol. 2 No. 1. Lauzel, P. and Cibert, A. (1962), Des Ratios au Tableau de Bord, 2nd ed. Lev, B. (1999), “Seeing is believing – a better approach to estimating knowledge capital”, CFO Magazine, April. Nash, H. (1998), “Accounting for the future: a discplined approach to value-added accounting (in draft). Standfield, K. (1998), “Extending the intellectual capital framework” available at: www.knowcorp.com/article075.htm
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Measuring and intervening: how do we theorise intellectual capital management? Jan Mouritsen
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Copenhagen Business School, Copenhagen, Denmark Keywords Intellectual capital, Measurement, Management information, Asset valuation, Narratives Abstract Measurement of intellectual capital is important, but not only for descriptive purposes. It is important because it enables intervention. If intervention and measurement are coupled, then measurement is an input rather than an output, and then measurement is not to be evaluated on its reflection of reality but rather on its ability to help actors transform their reality. This is particularly true for intellectual capital, which is widely accepted as part of an agenda for transformation and growth – it is a strategic/political agenda. To arrive at this conclusion, the paper discusses relationships between measurement and intervention comparing conventional financial statements with intellectual capital statements.
Introduction There is an irony: never before has so much information been published than through intellectual capital statements, and yet the cry for more measurement is increasingly aired. It is widely suggested that there is a measurement problem in the field of intellectual capital. But it is less clear what the problem is. It is not clear why merely providing a measure of the value of intellectual capital as indicated, e.g. in the market-to-book value the value is already known to the capital market, why then find a metric to measure it? So what are the reasons for measuring intellectual capital? Measurement often refers to correspondence between a phenomenon (such as intellectual capital) and its expression, so that measurement captures the value(s) or inherent dimensions of the phenomenon. The proposition is that measurement makes us certain about the phenomenon in question. Measurement helps us establish a relation between phenomenon and our perception of it. It helps us describe the phenomenon unobtrusively and with correspondence to its inherent properties. From this perspective, accounting helps establish a neutral description of the firm free of bias (Mattessich, 2003; Solomons, 1991). This is a laudable aspiration but it will not necessarily make intellectual capital interesting only because we have measurement systems for it in place (see, for example, Andriessen, 2003). The dilemma is that measurement may not really do what it claims to do, because we are rarely interested in merely describing or capturing the world. We are interested because it allows us to intervene! Does measurement create clarity? Not really, it helps us to act! Does measurement create a correspondence between the representation of the phenomenon and the phenomenon? Probably not, it is more concerned with making the world amenable to intervention! And does measurement create a neutral description of the world? No, it allows action to be performed at a distance! This is at least the thesis of this paper: measurement of intellectual capital is interesting because it is an input that starts action rather than a conclusion that stops action. Let me argue.
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The value of intellectual capital and the role of measurement in accounting Intellectual capital is a valued resource in the knowledge society as Drucker (1993) has told us. He says that: . . . the only – or at least the main – producers of wealth are information and knowledge. . . How knowledge behaves as an economic resource we do not yet fully understand. . . . We need an economic theory that puts knowledge into the centre of the wealth-producing process.
Since knowledge is ill understood, we are curious about how it links to value creation, and we struggle to specify how decisions can develop knowledge and translate this into desirable effects. Some research has been conducted to document relations between leading and lagging indicators in areas some times very close to intellectual capital (Ittner and Larcker, 2001; see also Bontis and Fitz-enz, 2002; Petty and Guthrie, 2000), however, correlations between them are often weak. Even though it is possible to show that on average, employee satisfaction is positively related to customer loyalty, which in turn is positively related to financial results, firms facing losses and red numbers rarely embark on massive investments in employee training and development to create black numbers. The case is typically the opposite. This makes the role of measurement questionable and it does not always seem to speak loudly. The relationships between numbers and action are complex, and measurement may not settle a debate. It is likely to start a debate, develop and push it, or redirect it in new ways. As Giddens (in Beck et al., 1994) puts it, “there is no number without a narrative”, implying that numbers do not speak. They have to be spoken for – they have to be explained – they have to be mobilised. Therefore, it is not clear what we say when we refer to measurement as a solution to the frailties of intellectual capital. It may help answering Drucker’s (1993) question about the economic theory of knowledge, but how? Intellectual capital and its associated reports and statements are ambiguous, but if we look at traditional financial statement with the same critical eyes that we now use to look at intellectual capital statements, they are not so dissimilar in many dimensions. First, the financial statement is also an ambiguous measurement system because it is a complex intermingling of the firm’s affairs with the auditing profession’s concerns. The strength of a financial statement is carried by accounting standards developed by professional bodies over time. The institutionalisation of accounting standards makes a financial statement a negotiation between the firm’s financial receipts and the institution’s procedures to verify transactions. The financial statement is therefore not a pure description of the firm. It is the view of a firm through the eyes of others. The financial statement is therefore not a direct representation of the firm’s value. The equity is not a measure of the value of the firm to an investor. Likewise, the intellectual capital statement does not show the value of the firm to an investor. Second, a community of readers interprets the financial statement and it links those with value creation. This readership is sophisticated and has been through extensive training. After years in universities and business schools, years of practical training to become accountants, auditors, and investment analysts, only then financial statements make sense. Sense of financial information is not a property of the financial statement itself. It is inseparable from the way it is applied and made part of decision-making processes. The huge process of interpretation is evidence that there is a loose coupling between the financial statement and its message. And therefore, there may be many
possible storylines to be detected in a financial statement, but always based on the efforts performed by readers to make sense. The information value of a financial statement is thus also a negotiation just like the production of the financial statement through accounting standards. This concern to understand (Johanson, 2003) is important for intellectual capital because hardly anyone has been trained in reading intellectual capital statements yet. It is not surprising that there is some confusion about their significance. Third, the financial statement is loosely coupled to the firm’s value. The equity is rarely an indication of the firm’s value to an investor, and in many cases it is only loosely related to the auditors’ judgment of the firm. There is more to the firms’ financial well being than the financial results. Just like the intellectual capital statement does not tell the whole story of the firm’s knowledge resources. When comparing conventional financial statements with intellectual capital statements, one observation is presenting itself again and again: the major difference is that we have grown accustomed to reading the financial statement in spite of all its deficiencies. We have created institutions that can read them and make some kind of informed or at least justifiable decisions on their basis. This suggests that measurement of the values described in financial statements is a fragile process and that it somehow and to a certain degree shares these properties with intellectual capital statements. So, measurement problems are basic not only to intellectual capital – but also to financial capital more generally.
Intellectual capital statement as managerial technology An intellectual capital statement has parallel characteristics to financial statements and it is therefore, in principle, “equally” good for purposes of management or intervention – either through the management of the firm or the decisions made in the capital market. An intellectual capital statement creates knowledge about how knowledge is created, developed and applied in the firm (Bontis, 2002; Edvinsson and Malone, 1997; Sveiby, 1997). It summarises the firm’s efforts to develop and use knowledge resources. The intellectual capital statement creates distance to the on-going affairs of the firm, and in this way it facilitates evaluation. Presenting the composition, upgrade and use of knowledge resources over time (Mouritsen et al., 2002) the intellectual capital statement puts forwards evaluative questions: Do we like it? Where should it be changed? Can we agree on new measures? Such questions are managerial ones because they help managers to change knowledge resources and direct them towards new strategies. As a managerial technology, intellectual capital statements can do the following: . Capture the on-going affairs of the business and transport them to a locality where they can be debated and assessed independently of the day-to-day concerns of operations. . Establish a distanced perspective on the myriad of actions that go on all the time to use and qualify knowledge. . Induce evaluative and normative reflection by assessing knowledge management activities.
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Allow decision making because there is time to contemplate on the future of knowledge resources. And then such decisions are implemented and the results will turn up in a subsequent intellectual capital statement.
In principle, the intellectual capital statement facilitates intervention, either from the perspective of internal readers or from external ones. Knowledge about the development and application of the firm’s knowledge resources is integral to the mobilisation of a systematic kind of knowledge management. Here, the interest in intervention is stronger than in representation. Or, alternatively, the interest in intervention drives interest in measurement in the sense that “good” measurement allows intervention to occur. This type of argument persuades Latour (1993) to say that: . . . the problem of correspondence becomes crucial only for those who want to act at a distance. If you are not at a distance, or do not wish to act upon other settings, the notion of correspondence vanishes, and so does the problem of the referent.
To act at a distance means acting to influence others, and therefore, measurement (to establish correspondence) is interesting if it influences others. Measurement is connected to power. This is not happenstance because one key feature of the knowledge society is to make phenomena discussable and transformable. It is characteristic that: . . . the reflexivity of modern social life [is] that social practices are constantly examined and reformed in the light of incoming information about those very practices, thus constitutively altering their character (Giddens, 1990).
Consequently, in modern life, information about it is used to alter it. It transforms practices. Therefore, when we consider intellectual capital measurement it is useful to look not only at its descriptive qualities, but also at its performative qualities. Therefore, it is useful to consider whether value is an outcome of measurement or whether measurement is an input to value creation. Do we measure value or do we produce value through measurement? Measuring value or processes of valuing? It is well known that intellectual capital can be used to complement financial value to arrive at the market value of the firm (e.g. Edvinsson and Malone, 1997). The firm’s market value is the sum of financial and intellectual capital and the value is the sum of recognised conventional assets, recognised intangibles, and non-recognised competencies. But what is “value”. Is it a noun; or is it a verb? It could be both. In conventional accounting values are manipulations of values of transactional receipts. It is a mathematical construct organised via disciplined and rule-based manipulations of business transactions that make up book values by assigning entries as expenses or assets; or as liabilities, revenues or capital. This is measurement when it is the strongest: all the referents are historical and part of the general ledger. It will hardly fill the gap between market and accounting book values of the company, however, because it does not consider the future. But it is reliable and reproducible. The finance perspective focuses on net present value of cash flows. Here value is justified from cash flow projections (Lev and Radhakrishnan, 2003). Compared with the measurement tradition of conventional accounting, which focuses on the balance sheet,
the finance view has to assume the future to arrive at a measurement of value. It does this by assuming stability in the P&L statement’s numbers. This is useful for certain purposes but not for all. Both the conventional accounting and the finance perspectives are concerned with describing a set value of the firm’s intellectual assets that it wishes to unearth from the hidings within the measures themselves. Intellectual capital statements are more concerned in value as a verb – less about a value than to value – what is done to make things valuable. Intellectual capital management is a process of value creation, and it makes little sense to say that the future is a set function of the past, because as knowledge grows in firms, new opportunities surface all the time and therefore it is impossible to arrive at one finite and set value of intellectual capital. In contrast, intellectual capital is a process of discovery and development (Roos et al., 1997). Here, value does not (only) imply calculating a value, but to understand the creation and development of value (Bukh, 2003; Hussi and Ahonen, 2002; Guthrie, 2001; Mouritsen et al., 2002; Petty and Guthrie, 2000). Measurement as object How is measurement accomplished? This process of committing items to the balance sheet is a process of disentanglement, where a separation between entities is constructed, and where the phenomenon in question is established (Callon, 1998). The entities are made visible by a procedure of inscription through which they are made recognisable and represented by names and numbers on paper. This is what happens when accounting transactions are added, subtracted, divided and multiplied with each other. To recognise assets is to show how they are separate from other assets, and therefore the process of disentanglement is one where the asset is “taken away” from the sphere of the firm’s production process where it in use is complementary to other assets. To “take items away” is therefore a transformation of the item because it is described not in action but on hold. Via, for example, International Accounting Standards, assets can be identified and disentangled from the firm’s production function. This form of measurement is an institutional game. It is defined as much outside the firm as inside. The receipts are internal, but they have to pass external legitimation before they can be justified to reflect the firm. However, this also means that there is no direct relationship between the accounting assets and its organisational basis. They are loosely coupled, and their relevance depends on how much an accounting asset can be mobilised to reflect other things in the firm. It is a translation between realms of knowledge rather than a direct representation of the firm, and the accounting statement is interesting for its information value rather than its absolute values. It is related to other phenomena, and there may be many ways to do this. We do not really know how such linkages are made – only, that they exist. This view of measurement sees it as a mechanism to bring closure. Through rules and standards it attempts to freeze assets and put them on hold. By disentangling them from each other, measurement crafts assets and communicates them via the balance sheet and the P&L statement. The assets have been laid to rest, and the relations between them have been silenced. There may be another option. Measurement could be about assets in action. Here, the interest is the relationship between various kinds of assets or resources, which even if they, in some form, may be individually calculable are interesting only for collective
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performance (Lev and Radhakrishnan, 2003). Such assets – which are more in line with the logic of intellectual capital – do not easily conform to the requirements of an external rule setting institution, but have to be related more systematically to the idiosyncratic principles of value creation that can be found in the specific firm. Here, each asset functions in connection with other assets. They are bound to the place where they are put to use, and not the capital market. Also managers, may have difficulties in seeing how they work or indeed seeing them at all. This is why for this type of entangled resource there is some kind of “need” to separate them, because otherwise they cannot be made manageable. To manage a certain extent level of disentanglement is necessary. So, there is a need to look at the collective work of entangled resources and assets, but to do this, some form of disentanglement is necessary. But which one? The object to be measured A problem with knowledge is that it does not have an object. It is not possible just to know! One has to know about something! Knowledge is not an object but more an aspiration to be insightful, to develop one’s appreciation of the problems at hand, and to be reflexive about the world. Knowledge is not a solution in knowledge society. It is a problem! Giddens (1990) says this clearly in his analysis of reflexivity in the modern world: What is characteristic of modernity is not an embracing of the new for its own sake, but the presumption of wholesale reflexivity – which includes reflection on the nature of reflection itself”.
He insists that knowledge is not “knowledge in the ‘old’ sense where ‘to know’ is to be certain”. In contrast, knowledge is never adequate; it is never reached; and it can always grow. Knowledge produces its own demise, because it is used to question knowledge. This is how knowledge society is reflexive. The great philosopher Karl Popper (1972) stated forcefully, that the future of social and organisational systems cannot be predicted, because the growth of knowledge will itself impact on the future of such systems. And the growth of knowledge cannot be predicted because knowledge is used to develop new knowledge in ingenious ways. But how can we manage knowledge if the effects of knowledge are not readily predictable? Knowledge management, as conceived through intellectual capital, is not about precise prediction of items of knowledge but about orienting the production of knowledge towards a purpose (Mouritsen and Larsen, forthcoming). This is why a central component of knowledge management is to develop the object that the firm has to know about. This object is not a thing but an aspiration to be good at something. In intellectual capital statements this something is often the difference that knowledge makes for somebody or something. Knowledge is productive when it can make a difference, and therefore it is no random occurrence that in intellectual capital statements there is typically a great deal of emphasis on explaining how the firm directs its knowledge towards purposes that involve being able to make a difference to a user. As consequence the object of knowledge is to make a difference to somebody or something. In this way knowledge gets directed, and it is possible to know not only that the firm has to know, but to know what it has to know something about. This is a very classical proposition. Socrates and Theaetetus developed this in their interchange about knowledge:
SOCRATES: [. . .] When you speak of cobbling, you mean by that word precisely a knowledge of shoemaking? THEAETETUS: Precisely. SOCRATES: And when you speak of carpentry, you mean just a knowledge of how to make wooden furniture? THEAETETUS: Yes. SOCRATES: In both cases, then, you are defining what the craft is a knowledge of? THEAETETUS: Yes. SOCRATES: But the question you were asked [. . .] was not, what are the objects of knowledge, nor yet how many sorts of knowledge there are. We did not want to count them, but to find out what the thing itself – knowledge – is.
It is difficult to see knowledge independently of what it is to accomplish, Socrates says. And this is why it has to be related to a purpose, which says something about the effects of knowledge. Some purposes do not do this. Expected market share and profitability do not do this. But ambitions to create teaching activities independently of time and space in some schools, and propositions to create quality of life in some medical firms, and ideas of securing personal growth in some consulting firms somehow do (Mouritsen et al., 2002). Even if sometimes worded pathetically, such claims suggest something about the way knowledge has to perform and it is being problematised against effects that are oriented toward the users of the firm’s products and services rather than merely its financial results. These are related, obviously, but not necessarily narrowly in time and space (see also Bukh, 2003, Hussi and Ahonen, 2002). Systematic knowledge management thus requires the firm to direct its knowledge resources towards an object; an object whose justification can be found in the character of the service it provides. Users are thus inherently interesting for systematic knowledge management. And if the development of knowledge resources is surveyed through the intellectual capital statement, then its raison d’etre is justified by its ability to perform; by its competence; by the difference it makes to something or somebody. Theorising measurement and intellectual capital statements Intellectual capital statements reflect on a firm’s process of developing, sharing and maintaining its knowledge base. It assigns purposes to this process and surveys its accomplishments through series of numbers. The intellectual capital statement shows the firm’s efforts to monitor, to qualify and to orchestrate its knowledge resources. It is aimed at persuading an internal or external audience that it develops it knowledge resources so as to develop the relationships between knowledge resources and the firm’s aspirations to be innovative, flexible and customer-oriented. For some, such a story line is not easily acceptable and therefore there is a cry for more measurement and perhaps accountability. However, as the discussion presented above suggests, it is not measurement as such that is in demand; it is the provision of explanation. And this explanation has to be about how entanglement occurs and is productive. What we see here is that relations in intellectual capital and associated intellectual capital statements have to be drawn up. One fruitful kind of theorising – or lines of explanation – is to see the intellectual capital statement as the space for intellectual capital and suggest that only here is intellectual capital possible. What is then outside intellectual capital? There would be all sorts of transactions that we enrol into an explanation that we call intellectual capital. Just as profits in the financial
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statement is only there on the paper, intellectual capital may just be there on the paper. Profits, after all, are the result of all kinds of valuation processes and it cannot be directly seen if the financial statement were not in place. So, perhaps intellectual capital only exists on the paper and the relation to practices has to be pointed out. How do such practices get pointed out? Either they do not because by and large, we already know them. This is the case of the financial accounting statement. We know, for example, which industry a particular firm belongs to and thus also its primary technology, markets and competition. We have prior knowledge. Or the practices have to be outlined on the paper. This is what intellectual capital statements do. They show how for some firms, intellectual capital is a story line that explains – or proposes – how various sorts of activities can be attached to the movement of intellectual capital and thus all the disparate singular events that can be seen in practices are integrated with each and put into a large storyline about the functioning of intellectual capital and about how management look towards it to upgrade it and monitor its effects. Then it is suddenly clear, that narratives and numbers are related. They are inseparable because they help to constitute each other. Narratives of achievement, e.g. in the production of quality of life for some people, or flexible education and training etc. can suddenly be integrated with “small” efforts to develop training, IT and customer relations. It is by putting narrative, efforts, indicators, pictures and ambition together that suddenly it becomes clear what kind of knowledge resource is interesting to firms (Mouritsen et al., 2002). Then the world is inscribed on paper. It is pulled in and made evaluate-able. And by combining and recombining the elements of the intellectual capital statement itself, it can actually change and transform people’s ideas about what happens in the firm. Sometimes the intellectual capital statement changes the firm in the eyes even of management. It is interesting to note Latour’s (1993) point about such paper work: All these inscriptions can be superimposed, reshuffled, recombined, and summarized, and totally new phenomena emerge, hidden from the other people from whom these inscriptions have been extracted.
Here, what Latour (1993) says is that paperwork (inscriptions) is highly flexible. It is possible to add, subtract, multiply or divide numbers and new phenomena will emerge. It is possible to integrate indicators with efforts and narratives and suddenly get a new version of what intellectual capital is and is doing in the firm. It is noteworthy that such accomplishments will not emanate from practices as such. They will have to be motivated somewhere. They require reflexivity and therefore they require some notion that the present could be different from the future. For this to happen, the flexibility of learning from inscriptions – all the things that are already available on the paper that constitute the intellectual capital statement – it is possible to redefine the world. It is a potentiality. It may not always happen, but the prospect is central to how we see such things as intellectual capital that, in principle, is said to develop firms. If this perspective is granted some value, we have to be concerned not to take too literally the proposition that we now have to test theories rather than develop theories of intellectual capital as it has been argued in the useful and excellent paper by, for example, Marr et al. (2003). They are frustrated by the many perspectives that operate in the field of intellectual capital. This is an understandable frustration, but perhaps the problem is that it is not yet so clear how a theory should look like. Marr et al. (2003)
pay attention to the various approaches developed throughout the 1990s to understand capabilities and to establish correlations between indicators. However, both accounts are, in my mind, elements of something else. A lot of the literature on, for example, resources and capabilities provides narratives rather than testable propositions. Not only resources and capabilities but also concerns about quality customer orientation, business excellence, flexibility and other words that one cannot be against, are completely derived of content. They can be used for almost anything in firms, and therefore they are typically provisional propositions that may turn into narratives but not until they have been equipped with business models (management challenges), effort and indicators, and possibly even pictures and illustrations. It is this whole network of concepts that will determine what such words mean. The other part of Marr et al.’s (2003) review is the concern with measurement indicating the need to document the effects of intellectual capital in various areas. This is an important aspect of the debate about intellectual capital, and it is important to tease out the correlations we can find. But should we assume that indicators have a one-to-one relationship with discernible organisational practices? Probably not, and this makes the intermingling of indicators with efforts, business models, narratives and the like a central point of the analysis. So, in this optic, measurement is separated from what it is about. This is a bit strange. Therefore, it may be, as Marr et al. (2003) suggest, that there are few generalised or tested hypotheses. But perhaps this is the lesson. We should not find them, because we should look at how the two dimensions of their paper fit together. How “content- free” concepts like competencies and resources (and even strategy and mission) and indicators are related. By splitting these elements, perhaps the untangling has been too thorough. At least, it is possible to go the other way and consider them one thing – a completely entangled phenomenon – so that it is possible to look at how narratives of competence and resource get established and prolonged. I am fairly convinced that measurement is an input to this rather than an output. And this may be the theory of intellectual capital: IC is the intermingling of words and practices and indicators, mobilised to (if stated optimistically) reflexively develop the ability of an entity to do something for others; or (if formulated less optimistically) to develop white collar productivity. Conclusion Measurement is important for intellectual capital but not only for the conventional reasons. It is not primarily interesting for its ability to capture the essence of the intellectual business. It is also interesting for its ability to perform as an input to reflexivity through which things can be changed and mobilised. Measurement is not only a conclusion; it is the beginning. This fits well with a theory of intellectual capital oriented towards construction – construction of relations between disparate elements of action around intellectual resources. Such a theory would suggest that the intellectual capital statement is itself an arena for developing intellectual capital rather than mapping it. Through such an agenda it is possible to develop an appreciation of how the individual activities and efforts performed in the name of knowledge can be associated with strategies, business models and indicators. The statement itself is an activity that makes intellectual capital real for the firm. And this is how we can see intellectual capital, as an “integrative”
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devise where the future is constructed, and made an asset, as Leif Edvinsson would insist (Mouritsen et al., 2001). Measurement is not separate from the activities they refer to but inherently part of an ongoing problematisation of the firm’s activities. It may help generate a stand against where new questions can be asked, and new courses of action can be devised. Here the purposes of intellectual capital are drawn forward and it is assumed that numbers cannot say this by themselves. This is why some attention to the purpose of measurement is relevant. This relevance comes in two steps. One type of relevance is what typically can be read from accounting type statements such as concerns about the composition of assets and liabilities; the concerns about investment and upgrades and the concerns about effects. This allows a distanciated view of intellectual capital even if it is structured according to certain generalised interests. This allows one interpretation of intellectual capital. The second step is to understand the firm’s knowledge strategy and its implementation. This requires a slightly more situated account of the firm’s intellectual resources and links between strategy, business model, activities, and indicators. Together they form a perspective on the firm’s intellectual capital and they make it visible – a visibility which is not, however, the end of the story but its beginning; its possible transformation. References Andriessen, D. (2003), “The value of weightless wealth; designing a method for the valuation of intangible resources”, PhD thesis. Beck, U., Lash, S. and Giddens, A.G. (1994), Reflexive Modernization – Politics, Tradition and Aesthetics in the Modern Social Order, Polity Press, Cambridge. Bontis, N. (Ed.) (2002), World Congress on Intellectual Capital Readings: Cutting Edge Thinking on Intellectual Capital and Knowledge Management from the World’s Experts, Heinemann-Butterworth, Oxford. Bontis, N. and Fitz-enz, J. (2002), “Intellectual capital ROI: a causal map of human capital antecedents and consequents”, Journal of Intellectual Capital, Vol. 3 No. 3, pp. 223-47. Bukh, P.N. (2003), “The relevance of intellectual capital disclosure: a paradox?”, Accounting, Auditing & Accountability Journal, Vol. 16 No. 1, pp. 49-56. Callon, M. (1998), The Laws of the Markets, Blackwell, Oxford. Drucker, P. (1993), Post-Capitalist Society, Blackwell, Oxford. Edvinsson, L. and Malone, M.S. (1997), Intellectual Capital, Piatkus, London. Giddens, A.G. (1990), The Consequences of Modernity, Polity, Cambridge. Guthrie, J. (2001), “The management, measurement and reporting of intellectual capital”, Journal of Intellectual Capital, Vol. 2 No. 1, pp. 27-41. Hussi, T. and Ahonen, G. (2002), “Managing intangible assets – a question of integration and delicate balance”, Journal of Intellectual Capital, Vol. 3 No. 3, pp. 277-86. Ittner, C.D. and Larcker, D. (2001), “Assessing empirical research in management accounting: a value based management perspective”, Journal of Accounting and Economics, Vol. 32, pp. 349-410. Johanson, U. (2003), “Why are capital market actors ambivalent to information about certain indicators on intellectual capital?”, Accounting, Auditing & Accountability Journal, Vol. 16 No. 1, pp. 31-8.
Latour, B. (1993), We Have Never Been Modern, Harvester Wheatsheaf, New York, NY. Lev, B. and Radhakrishnan, S. (2003), “The measurement of firm-specific organisation capital”, working paper 9581, National Bureau of Economic Research, Cambridge, MA. Marr, B., Gray, D. and Neely, A. (2003), “Why do firms measure their intellectual capital?”, Journal of Intellectual Capital, Vol. 4 No. 4, pp. 441-64. Mattessich, R. (2003), “Accounting representation and the onion model of reality: a comparison with Baudrillard’s orders of simulacra and his hyperreality”, Accounting, Organizations and Society, Vol. 28 No. 5, p. 443. Mouritsen, J. and Larsen, H.T. (forthcoming), “The 2nd wave of knowledge management: re-centring knowledge management through intellectual capital”, British Accounting Review. Mouritsen, J., Larsen, H.T. and Bukh, P.N. (2001), “Valuing the future: intellectual capital supplements at Skandia”, Accounting, Auditing & Accountability Journal, Vol. 14 No. 14, pp. 399-422. Mouritsen, J., Bukh, P.D., Larsen, H.T. and Johansen, M.R. (2002), “Developing and managing knowledge through intellectual capital statements”, Journal of Intellectual Capital, Vol. 3 No. 1, pp. 10-29. Petty, R. and Guthrie, J. (2000), “Intellectual capital literature review: measurement, reporting and management”, Journal of Intellectual Capital, Vol. 1 No. 2, pp. 155-76. Popper, K. (1972), Objective Knowledge: An Evolutionary Approach, Clarendon Press, Oxford. Roos, G., Ross, G., Edvinsson, L. and Dragonetti, N.C. (1997), Intellectual Capital: Navigating in the New Business Landscape, Macmillan Business, Houndsmills. Solomons, D. (1991), “Accounting and social change: a neutralist view”, Accounting, Organizations and Society, Vol. 16 No. 3, pp. 287-95. Sveiby, K. (1997), The New Organizational Wealth: Managing and Measuring Knowledge-based Assets, Berrett-Koehler, San Francisco, CA. Further reading Mouritsen, J., Larsen, H.T. and Bukh, P.N. (2001), “Reading intellectual capital statements: describing and prescribing knowledge management strategies”, Journal of Intellectual Capital, Vol. 2 No. 4, pp. 359-83.
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Shaken, not stirred Defining and connecting indicators for the measurement and valuation of intangibles
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Karin Grasenick Joanneum Research, Institute of Technology and Regional Policy, Graz, Austria, and
Jonathan Low Predictiv, Inc., West Palm Beach, Florida, USA Keywords Intangible assets, Measurement, Accounting valuations Abstract The necessity and importance of measuring intangibles has become increasingly accepted in the business, financial and academic communities as a means for a better understanding of the value creation processes in private, public and not-for-profit enterprises. Intangible indicators are seen as idiosyncratic, unique to each enterprise and not standardised. Interpretation, dissemination and further research suffer from the lack of definition and measurement standards. This paper examines guidelines and suggestions for measurement instruments and discusses their limits. A framework for classifying intangibles and indicators through the utilisation of evaluation experience is derived in order to support the movement towards global agreement on terms, definitions, standards and measures. Further research is discussed concerning quality standards for measurement systems.
Journal of Intellectual Capital Vol. 5 No. 2, 2004 pp. 268-281 q Emerald Group Publishing Limited 1469-1930 DOI 10.1108/14691930410533696
Introduction Financial statements have lost considerable meaning as the sources of wealth creation in the global economy have changed over time. A new set of metrics must be formulated and agreed on. The disclosure of intangibles or intellectual capital measurements derives its power from the fact that they are drivers of value that can be measured and evaluated by management. The adjective “intangible” usually accompanies different concepts such as assets, investments, and resources. There is not a unique nor unanimously accepted definition or classification of intangibles. One reason for this is that the boundaries, constituents and definitions of intangibles vary according to the perspectives of the different interest groups considering them, for example whether evaluating the potential impact of accounting concepts on a firm or national level, or analysing them from a managerial point of view in order to extract value from key business investments and assets. In the literature, numerous proposals on the definition of intangibles exist. There seems to be no clear evolutionary path of intangible asset management as a discipline. Measurement instruments have been developed during the last decade with the purpose of reporting the contribution of human competencies, knowledge and skills to a firm’s value and to foster their further expansion. Correlations between intangibles and other drivers of value show clear empirical evidence of their importance; it has been shown, however, that their interaction cannot be explained easily within a consistent theoretical framework. Despite the limitations to theoretical foundations for the functioning of intangibles, practical managerial needs have to be acknowledged and addressed. Examining
practical measurement and reporting advice for managers throughout the literature shows that difficulties start with classification differences, usually developed according to differing viewpoints on how and for which purpose an organisation’s assets are described. If the managerial need to be supported by a monitoring system is interpreted as evaluation of a firm’s activities, evaluation literature can be taken into account. This paper outlines a process to select, apply and relate indicators within a standardised framework for further development of intellectual capital statements. Explanatory power and relationships of indicators are discussed in detail, as information derived from measurement instruments is finally reported and interpreted – either for internal usage or external reporting thereby based on more or less common assumptions on the “theory of the firm”.
The meaning of intangibles: correlations and uncertainties The acknowledgement of the importance of intangible assets for a firm’s, an organization’s or a region’s economic success has led to efforts for integration in accounting standards. At the macroeconomic level OECD research has identified a number of business intangibles such as R&D, education and training of work force that correlate positively with GDP or productivity growth (according to Eustace, 2000). Evidence of a consistent relationship between the quality of human resources and the value of firms was found (Garcia-Ayuso et al., 2000). In several recent studies (Bassi et al., 2000), evidence on the profitability of training investments has been found. Furthermore, Lev and Sougiannis (1999) reported that there is a growing number of empirical studies revealing a substantial impact of R&D on productivity and shareholder value, and Deng et al. (1999) suggested that patent attributes are statistically associated with subsequent stock returns and market-to-book ratios. However, further studies revealed that within these definitions important aspects of the formation and mode of functioning of intangibles remain undiscovered. Examples that have been studied carefully are investments in research and development (R&D) and information and communication technologies (ICT). Identical values of invested intangible assets have been shown to lead to different results. On a regional level, recent studies have shown that the impact of R&D investment leads to different levels of innovation activities and results, depending on institutional composition and cooperation in regions (OECD, 2001; Richiardi, 2000). As innovation is the result of complex processes, interactions, feedback loops and learning abilities it cannot be measured by single indicators (Edquist, 1997). The importance of ICT as a driver of business performance has been recognised. However, direct relationship between ICT expenditure and firm performance cannot be easily demonstrated. ICT functions as an enabler of innovation and growth embedded in complex factors as, for example, the receptiveness of entrepreneurial culture. Learning abilities, organisational flows and work practices can all be measured by indicators but gaining broad acceptance of these measures has been challenging. Again, caution is necessary in inferring superior performance based on any single measure – or even a simple combination of measures (Brynjolfsson and Yang, 1997; Brynjolfsson and Hitt, 1998). The processes involved are complex and do not yield readily to analytical methods. OECD (2001) offers a comprehensive treatment of the
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theoretical and statistical problems, together with comprehensive references to the on-going work of researchers. One distinction that supports further development of more rigorous, therefore, more helpful definitions beyond the categories in use is presented by Eustace (2000). He and his colleagues divide assets into three categories: conventional assets (tangible assets) recognised in the contemporary balance sheet, “new” intellectual assets (intangible goods), e.g. brand value, and intangible competencies that foster innovation, structural, market and human resources (Eustace, 2000). Although notoriously difficult to separate, the second group – intangible competencies – are valued by successful companies as vitally important in differentiating their market offer from those of their competitors (Porter, 1987; Hamel and Prahalad, 1994). Classification efforts on a firm level Non-monetary-oriented concepts that measure and manage intangibles usually concentrate on intangible competencies, based on a firm’s strategy. Indicators are derived from identified key success factors. The most well-known representatives are the balanced scorecard (Kaplan and Norton, 1996), the intangible asset monitor (Sveiby, 1997), the intellectual capital approach (Edvinsson and Malone, 1997) and the IC-index (Roos et al., 1997), the performance prism (Neely et al., 2003), MERITUM guidelines (Can˜ibano et al., 2002), Danish guidelines (Mouritsen et al., 2003a). Although the variety of concepts has been established while focussing on different measurement interests as, for example, strategy formulation, benchmarking or internal motivation (Marr et al., 2002), a broad range of authors conceive of “intellectual capital” as composed of three categories (Edvinsson and Malone, 1997; Roos et al., 1997; Sveiby, 1997): (1) Human capital is defined as the knowledge that employees bring and take with them when they join or leave the firm. It includes the knowledge, skills, experiences and abilities of people. (2) Structural capital is defined as the pool of knowledge that remains with the firm at the end of work, after employees have left (Stewart, 1997). It comprises the organisational routines, procedures, systems, cultures, databases, etc. Some of this may be intellectual property. (3) Relational capital is defined as all resources linked to the external relationships of the firm such as customers, suppliers or R&D partners. It comprises that part of human and structural capital affecting the firm’s relations with stakeholders (investors, creditors, customers, suppliers, etc.) plus the perceptions that are held about the firm (brand, reputation, etc.). Within those broad categories, however, further differentiation can be established to include customers and markets, networks and alliances, human resources, processes and innovation, leadership, adaptability, transparency, workplace organization and culture (Low et al., 1997; Low and Kalafut, 2002). The recently published Danish guidelines for intellectual capital statements refer to four types of knowledge resources, namely employees, customers, processes and technologies. (Mouritsen et al., 2003a). Hence this framework seems to leave alliances with suppliers, research partners etc. and strategy execution out of their recommendations. Strategy execution, however, is
also a fundamental dimension of managerial excellence and, in particular, of communicating information or perceptions about other intangibles. Concepts for measuring intangible assets show a range of common objectives and grounds (Grasenick and Ploder, 2002), creating a set of generic and uniform metrics has so far been an elusive goal. Similar constructs and measures dedicated to a firm’s intangible values are labelled differently. The concepts rely on different perspectives for controlling, reporting or planning, which can be of a strategic character or give a particular focus on knowledge creating processes. If intangibles are used as a component of the firm’s rhetoric to mobilize change, there is no need for “getting things in order” by means of an exhaustive and exclusive classification scheme. However, if the task is to understand the importance of intangibles as part of the business model or production function, rigorous definitions are necessary. In order to achieve a general baseline to foster interpretability and comparability of intangibles, efforts to derive definitions should first concentrate on measurements that are easy to obtain. A possible approach for a common model is to follow Eustace’s (2002) differentiations in his attempts to separate recognisable assets (as further enhancements of a firm’s balance-sheet) from organisational competencies (see also above). Intangible competencies are found in the relationships between human, organisational and customer related intangible assets that develop through interaction in collective performance. They are more than the sum of the human, structural and relational resources of the firm. Managing them is about how to let the knowledge of a firm work for it and have it create value (Roberts, 1999). This can be achieved by strengthening the connectivity between those resources through the appropriate intangible activities. Measuring the impact of intangibles in this manner requires carefully differentiating framework conditions from the inexplicable residual aspects of intangibles that cannot be easily applied to standardised instruments. These are central to the uniqueness of a firm’s success. For separated framework conditions, definitions of intangibles and a set of rules should be defined. These rules must begin with an agreement on terms and a set of definitions for those terms. Once the intangibles’ community of interest can agree to those, discussion can then begin on more complicated issues like how to measure the impact of those intangibles, what channels to employ for distributing the information collected and how best to monitor the veracity of that information. Evaluation and measurement theory should be taken into account in order to discuss how to achieve a set of easy-to-handle indicators. The following paragraphs will derive and exemplify the development of a standardised framework for intangible indicators combining investments, processes and results based on a literature review. Defining indicators, setting frameworks Efforts to understand intangible assets start with classification differences, according to different viewpoints on how and for which purpose we need to describe an organisation. Whenever a number of units is classified, measurement takes place. Deriving a measurement system for intangible assets is especially difficult as the knowledge of their mode of function is largely correlational rather than theoretical, as the paragraphs
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above make clear. Important value drivers are usually different in nature and quality, hence no system of units can be derived that, at least in principle, relates all derived “variables” to a common set of logically simple qualities (as, for example, in physics or pure economics). Indicators may represent complex, not directly measurable aspects of reality through metrics. A good indicator must provide simple information that can easily be communicated and understood. Like financial accounting data, indicators for intangible assets are not necessarily relevant as such. Classified and displayed indicators represent a selected base for interpretation of ongoing business activities of a firm. In terms of a firm’s management, indicators should clearly be connected to the process of mobilizing resources for goal achievement leading to financial success. They should describe measurement points as a chain through the process of economic value creation. If the managerial need to be supported by a monitoring system is interpreted as evaluation of a firm’s activities, evaluation literature can be taken into account in order to achieve a standardising framework for further development of intellectual capital statements. MEANS, a programme of the European Commission, elaborates a useful framework for classifying indicators for the evaluation of socio-economic programmes by their level of objectives (European Commission, 1999). Socio-economic programmes mobilise resources (financial, human and institutional) in order to achieve a global objective. In order to evaluate a programme, a series of related objectives is identified and specific objective-dependent indicators are related to them in order to keep track and understand the process of goal achievement. The indicators are classified into five categories, namely resource, output, result, specific impact and global impact, as explained in Table I. Additionally important for discussion of achieved results and managerial decision finding are indicators that foster further comparison by deriving effectiveness and efficiency measurements: . Effectiveness can be obtained as the percentage of two values of the same output, result or impact indicator. . Efficiency is measured by comparing what was obtained with the resources mobilised by relating two indicators, e.g. average time spent for acquisition related to actual contracts. Referring to intangibles, indicators for inputs, outputs and results could be defined for the categories human, structural and external or customer capital. Inputs for a firm always have a financial baseline. Outputs and results turn through interaction of a firm’s competencies to intellectual capital and finally to tangible goods. For a model reducing itself to framework indicators, standards can be defined. They have to be pragmatic in order to guarantee comparison as well as connectivity to financial inputs and impacts that might be included in accounting statements. The Danish guidelines for analysing intellectual capital statements follow, to a certain extent, evaluation principles when differentiating indicators along resources, activities and effects (Mouritsen et al., 2003b). Resources thereby refer exclusively to “knowledge resources”, whereas “activities” should subsume
Level of objective
Type of indicator
Definition
Example
Resource (input)
Financial (human, material, organisational or regulatory) means Everything that is obtained by the input expenditures Immediate effect for direct addressees or recipients
Money spend for training, search for new employees
Operational objective
Output (descriptor needed?)
Immediate specific objective
Result (immediate outcome/advantage as result of output)
Sustainable specific objective
Specific impact (sustainable outcome as consequence beyond its direct or immediate results)
Strategic objective aim
Global impact (outreach)
Number of advertisements in newspapers, number of training days financed Number of new employees, number of trainees with new qualification, number of phone calls Results of output, e.g. number of new customers through phone calls, increased throughput per employee
Sustainable effect for direct addressees or recipients, referring directly to the aim of the input and intermediate outputs Global effect for the entire Financial success of the population firm
Source: European Commission (1999, p. 29)
indicators related to a firm’s activities to improve “knowledge resource”. Examples for activity indicators are “course days per employee”, “investment in education”, “meetings with users” etc. Indicators stated for resources are, for example, “no. of employees”, “no. of patent rights” or “percentage of turnover from civil projects”. An assessment of the evaluation principles described above shows a higher flexibility in assigning indicators to different levels of objectives, which might be helpful for certain analytical perspectives. Certainly an impact like turnover is a necessary requirement for new investments and activities and might therefore be seen as a resource. However, a more rigorous reorganisation of indicators would support standardization and readability of statements and their interpretation. Through this reorganisation an equivalent of the evaluation category “output” with “resources”, “results” with “activities” and “specific impact” with “effects” can be defined. These definitions support the reflection and interpretation of collected indicators, by clarifying their limitations and preventing overestimation of achieved results (the number of training days per employee, for example, are per se no guarantee for higher motivation or efficiency, as will be exemplified below). Outcomes can be determined by assessing their financial impact and monitoring the resources required to achieve them. Although indicator chains are loosely coupled and the complex correlations underlying a firm’s success cannot be described, the search for problems and strategic discussion is only supported by awareness of their explanatory power and hence their applicability in relation to each other. The retention of the terms “resources”, “activities” and “results” might be helpful as they intuitively describe the framework needed to understand a firm’s measurement needs. When complemented with the terms “investments” and “(financial) impact” a
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Table I. Definition of indicators by level of objectives according to MEANS collection
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perfect match with evaluation standards can be achieved as shown in Table II. In an organisational context the new terminology might be easier to understand intuitively and hence to follow. Indicators used accordingly to the specific interests and planned activities should form a chain leading from inputs to intended impacts. Figure 1 exemplifies the standardisation procedure that could be undertaken. Being able to connect investments to intangible assets and their financial output is crucial for a firm’s need to determine profitability. Additionally, the combination of financial with intangible categories fosters better managerial decision making while facilitating the movement toward an integration of intellectual capital and financial statements that can provide the basis for better managerial analysis and execution in the future. Mouritsen et al. (2003a, b) compare intellectual capital statements with financial statements and conclude that the process of analysis is similar for both (see Table III). This comparison treats the statement as parallel, independent systems. However, financial statements mark the possible scope for strategic activities (no money, no training) and final aim of managing a firm’s intangibles. Hence the relation of financial and intellectual analysis questions could be summarised as shown in Table IV. Implementing intellectual capital statements still leaves considerable uncertainty as to the latent capabilities and embedded intangibles that could be examined further if activities and effects do not result in the targeted outcome. If correlations do not emerge, specific consultation of further (embedded) intangibles or external developments can be taken into consideration, as, for example, for motivational or cultural aspects or market developments and changes in customer behaviour. Examining published indicator lists The literature on intellectual capital statements provides categorical systems and processes on how to derive indicators according to the specific measurement needs of a firm. Usually, lists of possible indicators for each category are added. A short inspection of these lists shows many different kinds of indicators are collected and somehow rearranged with indices, instruments and umbrella terms. It is left to the user to find out which of them might make sense and how to interpret (or measure) them. Additionally, no relationships between resources, strategic financing and overall impacts are drawn. Marr et al. (2002) with their collection of examples for “knowledge asset indicators” derived from different intellectual capital statements have clearly shown the need for further improvement and elaboration towards standards (see Table V).
Table II. Comparing evaluation and intellectual capital analysis practices
MEANS evaluation guidelines Danish guidelines Recommended principles
Input
Operational objective
Immediate objective
Sustainable objective
Resource
Output
Result
Specific impact Global impact Effects Effects Financial impact
Resources Investments Resources
Activities Activities
Strategic aim
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Figure 1. Deriving framework indicators for IC-statements
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Examining the first category, stakeholder relationships, clearly shows this mixture of various kinds of indicators and instruments. This leads to three disadvantages: (1) Lists of indicators are not helpful in relating financial inputs for a specific category to intended effects. (2) Different kinds of measurements are mixed up. Some of the instruments try to capture enablers or embedded aspects of intangibles. Instruments for embedded residual aspects of a firm’s activities are not clearly separated from indicators that could easily be standardised and regularly derived from a common database. (3) A baseline for standardization on which broad agreement is likely cannot be easily drawn, either for a specific firm’s managerial interests nor for further research and development. Other categories like “stakeholder relationships” include descriptions referring to variables, possible indices and instruments that should be discussed and restructured as examination shows (see also Table VI): . Number of partners, distribution networks and licensing agreements are resource indicators. Their quality cannot necessarily be easily derived from a standardised indicator. Instruments for quality indices can be defined additionally. . Length of relationship would be an activity indicator which can be easily recorded in standardised IC-framework statements. . Partner satisfaction and customer retention index might vary in different companies, however instruments could be standardised. . Market share can be defined as an important global impact indicator.
Table III. Main questions for financial and intellectual capital statements
Financial statement
Intellectual capital statement
What are the firm’s assets and liabilities? What has the firm invested?
How is the firm’s knowledge resource comprised? What has the firm done to strengthen its knowledge resources? What are the effects of the firm’s knowledge work?
What is the firm’s return on investment? Source: Mouritsen et al. (2003b, p. 5)
Financial statement
Table IV. Connecting financial and intellectual capital statements with main questions
Intellectual capital statement
What are the firm’s assets and liabilities? How are What are the firm’s assets and liabilities? How are the firm’s knowledge resources comprised? the firm’s knowledge resources comprised? What has the firm invested? What has the firm invested? What has the firm done to strengthen its knowledge resources? What are the effects of the firm’s knowledge work? What is the firm’s return on investment? What is the firm’s return on investment?
Stakeholder relationships
Number/quality of partnering agreements; number/quality of distribution agreements; number/quality of licensing agreements; public opinion survey; market share; length of relationship; partner satisfaction index; customer retention Demographics indicators, for example: number of employees; number of employees in alliances; average years of service with firm; average age of employees; full-time permanent employees; as percentage of total employment; employees working at home/total employees; number of women managers Competence indicators, for example: employees with high qualifications; people with PhD and/or masters degree/total employees; average years of service with the firm; number of years in specific professions; definition of a competence map Attitude indicators, for example: average level of happiness (measured with Likert-type scale); savings from implemented suggestions from employees; number of new solutions, products and processes suggested; qualitative descriptions of employees (commitment, loyalty, entrepreneurial spirit, enthusiasm); motivation and behaviour indicators Human resource management practices indicators, for example: training expenses/employees employee turnover; time in training; expenses for employee-development activities (social and personal); indicators about activities to motivate employees; indicators about recruitment practices Scalability/capacity measures; facilities/equipment versus plan; time to execute server updates; system integration; use of knowledge-sharing facilities Management philosophy; number of internal disputes and complaints; qualitative measures about employee satisfaction; feedback; values; behaviour; motivation; commitment; loyalty; opinion survey Process quality; number of codified processes; networking practices; norms; database availability; intranet use Revenues from patents; number of patents and registered designs; value of copyrights; value of patents versus R&D spend; trademarks; brand recognition survey
Human resources
Physical infrastructure Culture Practices and routines Intellectual property
Source: Marr et al. (2002)
Indicator ! capital
Investments
Stakeholder relationships Special Recommendations
(Investment in) public opinion survey
Resources
Activities
Number of partnering, licensing agreements Descriptions of quality of partnering, licensing agreements
Length of relationship
Effects
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Table V. Knowledge assets indicators
Financial impact Market share
Partner satisfaction index (measured by . . .) Customer retention (measured by . . .)
Table VI. Suggestions on reframing collections of stakeholder relationships related instruments and indicators
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Working towards standardisation means being able to concentrate on measurable and comparable indicators. For these indicators a list of definitions and procedures for deriving (relative) values can be defined. Standardisation should thereby start with indicators that can be linked to the financial framework. Measurement of a person’s motivation can change in different firms, teams, departments, with different management etc. Such factors are related to culture and unfold with interaction and therefore should be included in a standard framework only cautiously. For the evaluation of a firm’s activities to improve, motivation of a specific indicator chain could be added according to actual requirements. However, even if a new chain of indicators can be helpful in producing economic decisions, the cost of classification change and data retrieval can be higher than the marginal benefits. Here the issue involves choosing between possible proxies rather than constructing new indicators. Other types of data, like demographic information, could be restructured according to the intangible framework matrix illustrated above. Competence indicators like degrees and overall years in profession relate to demographic information. Further subdivision into different scopes of functions (e.g. research, sales, administration, depending on a firm’s activities) would be useful. As shown above, indicators like “number of years in service” etc. should be treated as resources already connected to the latent capabilities of a firm, e.g. its culture, management style etc. The category “culture” itself, however, is not suitable to be part of a common instrument. Recommendations and toolboxes for specific needs measuring and changing culture should be provided instead. Setting the collected instruments and indicators for human resources in the recommended evaluation framework helps to clarify the missing links and demonstrates the necessity for further discussion and completion (see Table VII).
Conclusions and further research Firms are generally unique in the prioritisation of the importance of their intangibles and use that uniqueness to create competitive advantage. Companies typically try to identify, measure and manage primarily those intangibles they have assessed as the most important for their long-term value creation. However, the cause-effect relation is not easy to establish and to demonstrate to the satisfaction of constituencies that must be convinced. At this stage in the evolution of the field it is the perception of the firm, and not a generally accepted “fact” that establishes value at a particular level. The interest in the intangible resources of future value has led to various systems for measuring intellectual capital. Still no clear definitions of intangibles and no theory explaining their mode of function can be provided. In order to support theoretical research as well as practical managerial interests, standardisations of terminology and guidelines for the definition, usage and interpretation of indicators would be an important further step towards a common baseline. Due to the very nature of intangibles, standardisation efforts have to concentrate on a framework, leaving many firm-specific residuals aside. Within this framework efforts should revise chains of clearly defined indicators according to empirical evidence and categories agreed as common dominators. Choosing indicators could be improved significantly by reflecting their explanatory
Indicator ! capital
Investments
Human
Training expenses/employees
Resources
Activities
Number of employees (with PhD) Average age of employees Full-time employees, etc.
Average years of service with firm, employees working at home/total employees, etc.
Time in training
Special Description of recommendations recruitment practices
Effects
Financial impact
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Number of new solutions, products and processes suggested
Savings from implemented suggestions
Number of women managers
Definition of a competence map, qualitative descriptions of employees (commitment) Questionnaires Expenses for employee-development on happiness motivation activities (social and and behaviour, personal) derived indices
power: limited by definition and metric but expanded through relationships to others as outlined in the paragraphs above. The framework of standard indicators might be combined with specific instruments to keep track of unique competencies according to a model that best suits a firm’s specific needs. However, an inadequate amount of information is currently available on how category classification, indicators and temporary interests (e.g. cultural change efforts or activities to improve employees’ motivation) should be composed to reliable management systems. Again, a baseline is needed for research and practice. Without theoretical foundations and different motivations, quality criteria for firm-specific measurement needs should be defined as an early, co-evolutionary step in the process of determining standardizable intangible value drivers. These quality criteria could integrate the exemplified processes for reliable indicators and support selection and further development of measurement instruments.
Table VII. Suggestions on reframing collections of human resource related instruments and indicators
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References Bassi, L., Lev, B., Low, J., McMurrer, D. and Siesfeld, G. (2000), “Measuring corporate investments in human capital”, in Blair, M. and Kochan, T. (Eds), The New Relationship: Human Capital in the American Corporation, Brookings Institution Press, Washington, DC, pp. 334-82. Brynjolfsson, E. and Hitt, L. (1998), “Beyond the productivity paradox”, Communications of the ACM, Vol. 41 No. 8, pp. 49-55. Brynjolfsson, E. and Yang, S. (1997), “The intangible costs and benefits of computer investments: evidence from the financial markets”, Proceedings of the International Conference on Information Systems, Atlanta, GA. Can˜ibano, L., Sa´nchez, P., Garcı´a-Ayuso, M. and Chaminade, C. (2002), Guidelines for Managing and Reporting on Intangibles, Meritum, Madrid. Deng, Z., Lev, B. and Narin, F. (1999), “Science and technology as predictors of stock performance”, Financial Analysts Journal, Vol. 55 No. 3, pp. 20-32. Edquist, C. (1997), Systems of Innovation: Technologies, Institutions and Organizations, London. Edvinsson, L. and Malone, M.S. (1997), Intellectual Capital, HarperCollins Publishers, New York, NY. European Commission (1999), Evaluating Socio-economic Programmes: Selection and Use of Indicators for Monitoring and Evaluation, European Commission, Luxembourg. Eustace, C. (Ed.) (2000), The Intangible Economy: Impact and Policy Issues. Report of the European High Level Expert Group on the Intangible Economy, European Commission, Luxembourg. Eustace, C. (2002), “A new perspective on the knowledge value chain”, PRISM working paper, London. Garcia-Ayuso, M., Moreno, I. and Molina, G. (2000), “Fundamental analysis and human capital: empirical evidence on the relationship between the quality of human resources and fundamental accounting variables”, Journal of Human Resources, Costing and Accounting, Vol. 5 No. 1, pp. 45-57. Grasenick, K. and Ploder, M. (2002), “Intangible asset measurement and organisational learning: the integration of intangible asset monitors in management processes”, in Neely, A., Walters, A. and Austin, R. (Eds), Performance Measurement and Management: Research and Action, Cranfield School of Management, Cranfield, pp. 235-42. Hamel, G. and Prahalad, C. (1994), Competing for the Future, Harvard Business School Press, Cambridge, MA. Kaplan, R.S. and Norton, D.P. (1996), The Balanced Scorecard: Translating Strategy into Action, Harvard Business School Press, Boston, MA. Lev, B. and Sougiannis, T. (1999), “Penetrating the book-to-market blackbox: the R&D effect”, Journal of Business, Finance and Accounting, Vol. 26 No. 3/4, pp. 419-45. Low, J. and Kalafut, P. (2002), Invisible Advantage: How Intangibles Are Driving Business Performance, Perseus Publishing, Cambridge. Low, J., Kalafut, P. and Robinson, J. (1997), Measures That Matter, Ernst & Young LLP, Cambridge. Marr, B., Schiuma, G. and Neely, A. (2002), “Assessing strategic knowledge assets in e-business”, International Journal of Business Performance Management, Vol. 4 No. 2-4, pp. 279-95.
Mouritsen, J., Bukh, N., Rosenkrands, M., Larsen, H.T., Nielsen, C., Haisler, J. and Stakemann, B. (2003a), Intellectual Capital Statements: The New Guideline, Danish Ministry of Science Technology and Innovation, Copenhagen. Mouritsen, J., Bukh, N., Rosenkrands, M., Larsen, H., Nielsen, C., Haisler, J. and Stakemann, B. (2003b), Analysing Intellectual Capital Statements, Danish Ministry of Science, Technology and Innovation, Copenhagen. Neely, A., Adams, C. and Kennerley, M. (2003), Performance Prism: The Scorecard for Measuring and Managing Stakeholder Relationships, Prentice-Hall, Indianapolis, IN. OECD (2001), Cities and Regions in the New Learning Economy, OECD, Paris. Porter, M. (1987), “From competitive advantage to corporate strategy”, Harvard Business Review, Vol. 65 No. 5/6, pp. 43-59. Richiardi, M. (2000), “CIS-2: toward an identification of regional systems of innovation. STEP economics”, working paper. Roberts, H. (1999), “Classification of intellectual capital”, Meritum Project Meeting, Stockholm. Roos, J., Roos, G., Edvinssons, L. and Dragonetti, L. (1997), Intellectual Capital: Navigating in the New Business Landscape, Macmillan, London. Stewart, T.A. (1997), Intellectual Capital, Doubleday/Currency Publishers, New York, NY. Sveiby, E. (1997), The New Organizational Wealth: Managing and Measurement Knowledge Based Assets, Berret Koehler, San Francisco, CA. Further reading Bassanini, A., Scarpetta, S. and Visco, I. (2000), “Knowledge, technology and economic growth: recent evidence from OECD countries”, paper presented at the 150th Anniversary Conference at the National Bank of Belgium, Brussels. Can˜ibano, L., Garcı´a-Ayuso, M. and Sa´nchez, P. (2000), “Accounting for intangibles: a literature review”, Journal of Accounting Literature, Vol. 19, pp. 102-30. Johanson, U., Martensson, M. and Skoog, M. (2001), “ Mobilizing change through the management control of intangibles”, Accounting, Organizations and Society, Vol. 26, pp. 715-33. Kaufmann, S. (1993), Origins of Order: Self Organization and Selection in Evolution, Oxford University Press, Oxford. Lev, B. (2001), Intangibles: Management, Measurement, and Reporting, Brookings Institute, Washington, DC. Marr, B., Gray, D. and Neely, A. (2003), “Why do firms measure their intellectual capital?”, Journal of Intellectual Capital, Vol. 4 No. 4, pp. 441-64. Mouritsen, J., Larsen, H.T. and Bukh, P.N. (2001), “Valuing the future: intellectual capital supplements at Skandia”, Accounting, Auditing & Accountability Journal, Vol. 14 No. 4, pp. 399-422.
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Using content analysis as a research method to inquire into intellectual capital reporting J. Guthrie, R. Petty and K. Yongvanich Macquarie Graduate School of Management, Macquarie University, Sydney, Australia, and
F. Ricceri Department of Economics, University of Padova, Padova, Italy Keywords Intellectual capital, Annual reports, Disclosure, Research methods, Stakeholders Abstract Increasingly, researchers in the field of intellectual capital (IC) need to be able to justify the specific research methods they use to collect the empirical data that they examine to support and test opinions regarding the merit of different approaches to managing and reporting IC. Of the various methods available to researchers seeking to understand intellectual capital reporting (ICR), content analysis is the most popular. The aim of this paper is to review the use of content analysis as a research method in understanding ICR and to offer some observations on the practical utility of the method. Further, the paper examines several research method issues relating to the use of content analysis that have been discussed in the social environmental accounting literature, but not as yet in the IC literature, which we believe are relevant to investigations underway in the field of ICR. This paper reports on several developmental issues we have confronted when using content analysis to examine the voluntary disclosure of IC in annual reports by various organisations. The paper also suggests two theoretical foundations for further investigation into the voluntary disclosure of IC by organisations, and suggests why content analysis is well matched to both these theories as a means to collect empirical data to test research propositions.
Introduction The research and published literature on measuring and reporting intellectual capital (IC) is growing rapidly (e.g. Can˜ibano et al., 2000; Guthrie et al., 2001). In an introduction to a special issue of the JIC on “The transparent enterprise”, Guthrie et al. (2003) indicate that extant research is divided into several branches, each with its own set of problems and with its preferred theories and research methodologies. One such branch deals with intellectual capital reporting (ICR). Within this branch there are several foci including the value relevance of specific IC indicators, for example research and development expenses (Lev and Sougiannis, 1996), the capitalisation of intangibles (e.g. Gu and Lev, 2001) and the integration of IC data into
Journal of Intellectual Capital Vol. 5 No. 2, 2004 pp. 282-293 q Emerald Group Publishing Limited 1469-1930 DOI 10.1108/14691930410533704
Original paper presented at the Performance Measurement Association Intellectual Capital Symposium, 1-2 October 2003 Cranfield, UK. This work is part of our ongoing interest in “Intellectual capital reporting” and underpins the authors’ previously published empirical works (Abeysekera and Guthrie, 2003a, b, 2004; Bozzolan et al., 2003; Guthrie et al., 1999, 2004; Guthrie and Petty, 2000). The authors are indebted to the comments of two anonymous referees and would also like to express their appreciation to the two editors of this JIC special issue – Bernard Marr, Centre for Business Performance, Cranfield School of Management and Jay Chatzkel – for their helpful comments. The responsibility for the contents of this paper nonetheless remains entirely that of the authors.
decision relevant reports (e.g. Collier, 2001; Mouritsen et al., 2001). Recent work on guidelines for IC reporting (e.g. Meritum, 2001; DATI, 2000; DMSTI, 2003) has also furthered interest in the development of a framework for identifying, managing and reporting IC. These research investigations all use the annual report as the representative measure of publicly available IC information. The substance or content of the disclosures made by organisations in their annual reports is an area of interest to many researchers. Several studies, which focus on what is being reported, use content analysis as a research method to capture and organise diverse empirical data. Studies using content analysis as a research method have been conducted using data from Australia (Guthrie and Petty, 2000; Guthrie et al., 1999), Canada (Bontis, 2003), Hong Kong (Petty, 2003a), Ireland (Brennan, 2001), Italy (Bozzolan et al., 2003), South Africa (April et al., 2003), Sri Lanka (Abeysekera and Guthrie, 2003a, b, 2004) and Sweden (Olsson, 2001). Of course, alternative research approaches have been adopted to investigate other areas of IC that are not grounded in content analysis. For instance, Marr et al. (2003) review research in the field of IC measurement and provide a theoretical view on why firms measure IC and offer convincing empirical evidence in support of their theoretical assertion that the measurement of IC is valuable without using content analysis. We fully acknowledge the legitimacy of the various streams of research and the array of research methods being employed in the field of IC, particularly at this still nascent phase of development within the field. The measurement and management of intangibles is a diverse and expansive area and there is room for many different approaches. The focus of this paper, however, is on ICR and the application of content analysis as a tool that aids our understanding of the type of IC information that organisation are disclosing in their annual reports. Research theory Several theoretical lines of inquiry have profited from the application of content analysis as an approach to data collection and analysis. Stakeholder theory and legitimacy theory are two of the better known. Stakeholder theory According to stakeholder theory, an organisation’s management is expected to take on activities expected by their stakeholders and to report on those activities to the stakeholders. The theory suggests that all stakeholders have a right to be provided with information about how organisational activities impacts on them (for example, through pollution, community sponsorship, safety initiatives, etc), even if they choose not to use the information, and even if they cannot directly play a constructive role in the survival of the organisation (Deegan, 2000). Stakeholder theory ascribes organisational accountability to organisations, which extends beyond their economic or financial performance. It suggests that they will elect to voluntarily disclose information about their intellectual, social, and environmental performance, over and above mandatory requirements. Stakeholder theory has an ethical (moral) branch, and a positive (managerial) branch. The ethical branch argues that all stakeholders have the right to be treated fairly by an organisation, and that managers should manage the organisation for the
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benefit of all stakeholders (Deegan, 2000). The positive branch argues that a stakeholder’s power to influence corporate management is viewed as a function of the stakeholder’s degree of control over resources required by the organisation (Ullmann, 1976). The more critical the stakeholder resources are to the continued viability and success of the organisation, the greater the expectation that stakeholder demands will be addressed. Thus, the positive version of stakeholder theory predicts that management is more likely to focus on the expectations of powerful stakeholders, that is, those who control resources (Deegan, 2000). This theory can be tested in a host of ways using content analysis. The various interest groups deemed to have an interest in controlling certain aspects of an organisation can be efficiently communicated with via the annual report. Content analysis can be used to test whether this is happening with items of IC disclosures. Are companies responding as stakeholder theory might predict they would in offering a voluntary account of their intellectual capital and the value of their intangible assets? This is a question that has received some attention (Petty, 2003b), but more work is needed to form a conclusive opinion. Legitimacy theory Legitimacy theory is closely linked to stakeholder theory. It posits that organisations continually seek to ensure that they operate within the bounds and norms of their respective societies. Adopting a legitimacy theory perspective, a company would voluntarily report on activities if management perceived that the particular activities were expected by the communities in which it operates. Legitimacy theory relies on the notion that there is a “social contract” between the company and the society in which it operates. The social contract is used to represent the multitude of expectations that the society has on how the organisation should conduct its operations. These societal expectations are not fixed. They change over time. This requires the company to be responsive to the environment in which it operates (Deegan, 2000). Lindblom (1994) proposes that if an organisation perceives that its legitimacy is in question it can adopt a number of combative strategies. First, the organisation can seek to educate and inform its “relevant publics” about (actual) changes in the organisation’s performance and activities. Second, it can seek to change the perceptions of the “relevant publics” – but not change its actual behaviour. Third, it can seek to manipulate the perceptions of the “relevant publics” by deflecting attention from the issue of concern to other related issues through an appeal to, for example, emotive symbols. Finally, the organisation might seek to change external expectations of its performance. According to Lindblom, a company can use the public disclosure of information to implement each of the above strategies. Certainly, this is a perspective that many empirical studies of SER have adopted to explain these voluntary disclosures. Following legitimacy theory, organisations must continually appear to be operating in a manner that is consistent with societal values (Guthrie and Parker, 1989, 1990). This is often achieved through communication via company prepared reports. Lindblom (1994) suggests that organisations may use disclosures to demonstrate management’s concerns for, societal values, or to divert community attention from the prevailing negative impact of the organisations’ activities. A number of prior studies
examined voluntary annual report disclosures and viewed the reporting of social and environmental (SEA) information as a method that organisations used to respond to public pressure (Deegan and Rankin, 1996; Guthrie and Parker, 1989, 1990; Neu et al., 1998; Patten, 1991, 1992; Walden and Schwartz, 1997). Legitimacy theory is closely tied to the reporting of intellectual capital and to the use of content analysis methods as a measure of such reporting. Companies are more likely to report on their IC if they specifically have a need to do this, as they cannot legitimise their status via the hard assets that are recognised as symbolic of traditional corporate success. The extent of IC reporting is, at this juncture, best measured using content analysis. Thus, legitimacy theory, IC and content analysis are intertwined. A review of the use of content analysis in the IC literature Content analysis has been conducted on annual reports by a number of IC researchers, as they are a good instrument to measure comparative positions and trends in reporting. Annual reports have been used to investigate the ICR practices of firms (Bozzolan et al., 2003; Brennan, 2001; Guthrie et al., 1999, 2003; Olsson, 2001), and also to investigate the differences in reporting across firms in different countries (Subbarao and Zeghal, 1997). Researchers in Australia were early adopters of content analysis as a method to examine organisational practices in managing and reporting IC. Guthrie and Petty (2000) carried out a content analysis of the annual reports of the 20 largest Australian listed companies (by market capitalisation) in an attempt to understand the extent to which these companies report their IC. The authors used a framework developed by Sveiby (1997), which categorises intangibles according to whether they relate to an organisation’s internal structure, external structure, or the employee competence within an organisation. Using this framework, it was found that the key components of IC are poorly understood, inadequately identified, inefficiently managed and inconsistently reported. Brennan (2001) carried out a similar study of companies in Ireland. The author analysed the annual reports of 11 listed companies and ten private companies. The author used an identical framework to code data for the content analysis of annual reports as that used by Guthrie and Petty (2000), and reported results similar to the Australian study. However, the cultural and other cross-country differences mean the findings of the study are not meaningfully comparable with Guthrie et al. (1999). A study by Olsson (2001) examined the annual reports of the 18 largest Swedish companies, selected on the basis of market capitalisation in the Swedish stock market. Olsson (2001) developed a list of five elements to ascertain the level of human capital reporting. The study found that none of the companies used more than 7 per cent of reporting space to deliver human resource information in their annual reports. Furthermore, the information that was reported was found to be highly deficient in either the quality or extent of the disclosure. Data collection and evaluation using content analysis Development of the disclosure instrument Since the 1960s, researchers have sought to explain differences in the amount of information disclosed in company annual reports. To do this, researchers have
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typically quantified the level of company annual report disclosures by means of a disclosure instrument comprised of a list of items that could appear in a company’s annual report. Until recently, few firms have attempted to measure and assess IC (Guthrie and Petty, 2000). There are a variety of conceptual frameworks that can be used to classify and record IC. In our previous work (Guthrie and Petty, 2000) we modified an existing framework. We recently re-modified it (Guthrie et al., 2003). The most recent framework is provided in Table I. The framework for IC elements developed by Brooking (1996) and adopted and modified by the Australian Society of CPAs and the Society of Management Accountants of Canada (1999, p. 14) was combined with the Guthrie and Petty (2000) framework to produce a slightly modified structure with three main categories and 18 elements. Internal capital includes the systems, policies, culture and other “organisational capabilities” developed to meet market requirements. External capital covers the connections that people outside the organisation have with it, and human capital includes the know-how, capabilities, skills, and expertise of the employees[1]. Size and industry effects Recently, Bozzolan et al. (2003) found a significant size and industry effect on reported IC disclosures using Italian data. Previous research shows that in social and environmental reporting (SER) the size of companies in terms of total assets and total sales is an important variable for most areas of voluntary reporting (Gray et al., 1995a, p. 62). Prior studies in the SER literature (Cowen et al., 1987; Patten, 1991, 1992; Roberts, 1992) have also found that industry influences the amount of SER disclosure. Some industries are more likely to disclose in certain areas of social responsibility because they are subject to greater governmental pressure to provide such information (Cowen et al., 1987). The effect of size and industry variables should be a consideration in developing the instrument to be used for the content analysis. However, to date few studies have modified the coding instrument in an effort to control size and industry effects across a sample of companies[2]. The generalised nature of most coding forms is clearly a limitation on the accuracy of results. Introducing greater situational specificity into the coding process represents an avenue for improvement.
1. Internal capital
Table I. Intellectual capital elements used in the coding instrument
1. 2. 3. 4. 5. 6.
Intellectual property Management philosophy Corporate culture Management processes Information/networking systems Financial relations
2. External capital 7. Brands 8. Customers 9. Customer satisfaction 10. Company names 11. Distribution channels 12. Business collaborations 13. Licensing agreements
3. Human capital 14. 15. 16. 17. 18.
Employee Education Training Work-related knowledge Entrepreneurial spirit
Research method issues Annual reports All forms of data reaching the public domain can be considered part of the accountability-discharge activity of an organisation (Gray et al., 1995a, b). Ideally, all communications by an organisation should be monitored if one is to capture all corporate IC external reporting. However, the problem with this standard is that it is impossible to be certain that all communications have been identified (Gray et al., 1995a, b). Reducing the focus of investigation to annual reports offers a relevant and useful proxy. Annual reports are highly useful sources of information, because managers of companies commonly signal what is important through the reporting mechanism. The annual report is viewed as a communication device that allows a corporation to connect with various external and internal stakeholders (Guthrie and Petty, 2000). Annual reports also have the advantage of being regularly produced and offer an opportunity for a comparative analysis of management attitudes and policies across reporting periods (Niemark, 1995, pp. 100-1). The vast amount of prior social and environmental reporting (SER) research (e.g. Cowen et al., 1987; Guthrie and Parker, 1989, 1990; Roberts, 1992; Neu et al., 1998) establishes the annual report as a major medium for communicating social and environmental information to public. Campbell (2000) indicated that annual reports can be accepted as an appropriate barometer of a company’s attitude towards social reporting for two reasons: the company has complete editorial control over the document (except the audited financials section); and it is usually the most widely distributed public document produced by the company. In many jurisdictions, annual reports are required by legislation and are produced on a regular basis by all companies. This makes comparisons relatively easy (Tilt, 2001).
Content analysis Content analysis of annual reports has been used, and held to be empirically valid, in SER research (Gray et al., 1995b; Guthrie and Parker, 1990). As a technique for gathering data, it involves codifying qualitative and quantitative information into pre-defined categories in order to derive patterns in the presentation and reporting of information. Content analysis seeks to analyse published information systematically, objectively and reliably (Krippendorff, 1980; Guthrie and Parker, 1990; Guthrie, 1983). Content analysis has been commonly used in the SER literature to evaluate the extent of disclosure of various items (i.e. Guthrie and Mathews, 1985; Guthrie and Parker, 1990; Zeghal and Ahmed, 1990; Hackston and Milne, 1996). Content analysis is a method of codifying the text of writing into various groups or categories based on selected criteria. It assumes that frequency indicates the importance of the subject matter (Krippendorff, 1980). For content analysis to be effective, certain technical requirements should be met (Guthrie and Mathews, 1985). First the categories of classification must be clearly and operationally defined. Second, objectivity is key – it must be clear that an item either belongs or does not belong to a particular category. Third, the information needs to be able to be quantified. Finally, a reliable coder is necessary for consistency.
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Unit of analysis Content analysis requires the selection of a unit of analysis. According to Holsti (1969, p. 116) a recording unit is “the specific segment of content that is characterised by placing it into a given category”. In the accounting literature a debate has arisen (Gray et al., 1995b) regarding the use of words, sentences or portions of pages as the basis for the coding. Gray et al. (1995b) posit that sentences are preferred in written communication if the task is to infer meaning. Most SER content analyses use sentences as the basis for coding decisions. Using sentences for both coding and measurement is likely to provide complete, reliable and meaningful data for further analysis (Milne and Adler, 1999). Another unit of analysis is the paragraph. The paragraph method is more appropriate than word count in drawing inferences from narrative statements as we commonly establish meaning with paragraphs rather than through the reporting of a word or sentence. Usually the amount of disclosure is measured by counting the frequency at both the category and element levels. An organisation’s overall index is calculated according to the total amount of information disclosed. Disclosure indexes are often also calculated for each category. Unerman (2000) has usefully presented arguments for measuring the volume of SER disclosures in terms of the proportions of a page, taking into account non-narrative SER disclosures (e.g. charts, tables, photographs). While Frost and Wilmshurst (2000) excluded pictures in their analysis, they indicated that this was a limitation because pictures might be used by management to impress on stakeholders their approach towards the management of environmental issues. However, there are complications in attempting to quantify the impact that pictures have. Frost and Wilmshurst (2000) argue that “a picture may be worth a thousand words” but to measure pictures based on an unweighted word count is highly subjective. Further, some pictures cannot deliver the intended message without surrounding text. These arguments complicate the debate as to the weight that should be used to determine what amount of disclosure a picture is equal to. Data capture The IC information collected from the reading and analysis of annual reports is coded onto the coding sheets. Each item is coded according to the section under which the item appears. To facilitate this, the annual report is divided into five sections: the vision/strategy section; the director’s section; the business/operational section; the financial section; and, the remaining sections. The nature of disclosure is categorised as either qualitative or quantitative and the incidence of occurrence (i.e. number of paragraphs) is generally noted. The paragraph count reveals the proportionate of space allocated for a given element since each “story” is competing for its right of space in the annual report. Reliability and validity of content analysis Those conducting content analysis need to demonstrate the reliability of their instruments and/or the reliability of the data collected using those instruments to permit replicable and valid inferences to be drawn from data derived from content analysis (Guthrie, 1983; Milne and Adler, 1999).
According to Milne and Adler (1999), reliability in content analysis involves two separate issues. First, we seek to attest that the coded data set produced from the analysis is reliable. This is usually achieved by the use of multiple coders and reporting that the discrepancies between the coders are minimal. Another factor to consider is the reliability associated with the coding instrument. Establishing the reliability of particular coding tools (i.e. ensuring well-specified decision categories with well-specified decision rules) reduces the need for multiple coders. Krippendorff (1980, pp. 130-2) identifies three types of reliability for content analysis: stability, reproducibility and accuracy. Guthrie et al. (2003) detail several methods to increase the reliability in recording and analysing data. First, by selecting disclosure categories from well-grounded relevant literature, and clearly defining them. Second, by establishing a reliable coding instrument with well-specified decision categories and decision rules. Third, by training the coders and showing that coding decisions made on a pilot sample have reached an acceptable level. Quality of disclosure In the SER research, it is recognised that the quantity of disclosure does not indicate what is actually being disclosed (e.g. Frost and Wilmshurst, 2000). Prior studies in the SER literature, which examined both the amount of disclosure and the quality of the data disclosed (Deegan and Gordon, 1996; Deegan and Rankin, 1996; Gray et al., 1995b; Guthrie and Parker, 1990; Hackston and Milne, 1996) have defined the quality aspect of disclosures. Deegan and Gordon (1996) and Deegan and Rankin (1996) examined the volume of news of the disclosure as an indicator of its quality. Guthrie and Parker (1990), focusing on “what was said and how it was said”, examined theme, evidence (monetary, non-monetary, declarative, none), amount, and location of a disclosure to infer its quality. Gray et al. (1995b) examined themes, evidences, amount, auditable, and news. Hackston and Milne (1996) examined the amount of disclosure, themes, news and evidence. To mitigate information loss from considering only the quantum of information disclosure we favour an approach that takes the quality of disclosure into account by examining, inter alia, the reporting theme, the form of disclosure, and location of the disclosure. Studying the quality of disclosure by examining the relative emphasis on each theme, whether the disclosure is quantified or not, and the location of disclosure (e.g. chairman’s report versus a general section on operational activity) is the approach most likely to yield meaningful results. This approach not only provides a description of the disclosure practices of organisations, but also indicates the key issues that need to be focused on in subsequent in-depth investigations on how these organisations identify, measure, and report their IC. Limitations of content analysis There are several limitations in using content analysis (Gray et al., 1995b; Milne and Adler, 1999; Unerman, 2000). The major limitation is the subjectivity involved in coding (Deegan and Rankin, 1996; Frost and Wilmshurst, 2000). Milne and Adler (1999) emphasised that in order for valid inferences to be drawn from content analysis, the reliability of both the data and the instrument must be achieved.
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There is also the problem that stems from unduly emphasising quantity over quality of disclosure. This usually results in information loss and can be mitigated by examining the quality and type of data communicated (Gray et al., 1995b). Summary and conclusions Content analysis is one of the more widely used research methods applied in investigating the frequency and type of ICR. It is a method in need of further refinement and development if research advances are to be made in the field of ICR. Consistency in the application and framework, and understanding the limitations of the method is key to generating meaningful results. Many of the studies that use content methodology cannot be meaningfully compared because of the use of inconsistent data collection instruments. In some cases, the context and location of makes this inevitable. In others, a consensus on investigative approach would enhance the external validity of the findings. The use of the paragraph method is generally preferred to the sentence or word methods, but this observation may be contingent on investigative context in some cases. There is scope for extending content analysis to capture pictorial information. However, we find current attempts to do this too subjective. Theory development is also vital to evolving the body of work into ICR. Stakeholder theory and legitimacy theory present two options for researchers that are compatible with the use of content analysis techniques. Notes 1. An annexure providing definitions, explanations and illustrations of the IC elements in the content analysis instrument can be obtained from the first author by request. 2. Petty (2003b) is a notable exception. References Abeysekera, I. and Guthrie, J. (2003a), “An empirical investigation of annual reporting trends of intellectual capital in Sri Lanka”, Critical Perspectives on Accounting. Abeysekera, I. and Guthrie, J. (2003b), “Status of intellectual capital reporting in a developing nation”, Research in Accounting in Emerging Economies, forthcoming. Abeysekera, I. and Guthrie, J. (2004), “Human capital reporting in a developing nation: an analysis of practice”, British Accounting Review, forthcoming. April, K.A., Bosma, P. and Deglon, D. (2003), “Intellectual capital measurement and reporting: establishing a practice in South African mining”, Journal of Intellectual Capital, Vol. 4 No. 2, pp. 165-80. Australian Society of CPAs and The Society of Management Accountants of Canada (1999), Knowledge Management: Issues, Practice and Innovation, Australian Society of Certified Practising Accountants, Melbourne. Bontis, N. (2003), “Intellectual capital disclosures in Canadian corporations”, Journal of Human Resource Costing and Accounting, Vol. 7 No. 1/2, pp. 9-20. Bozzolan, S., Favotto, F. and Ricceri, F. (2003), “Italian annual intellectual capital disclosure: an empirical analysis”, Journal of Intellectual Capital, Vol. 4 No. 4, pp. 543-58. Brennan, N. (2001), “Reporting intellectual capital in annual reports: evidence from Ireland”, Accounting, Auditing & Accountability Journal, Vol. 14 No. 4, pp. 423-36.
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Petty, R. (2003a), “The disclosure of intangible information by listed companies in Hong Kong”, working paper, University of Hong Kong, Hong Kong. Petty, R. (2003b), “The correlation between the voluntary disclosure of intellectual capital indicators and financial success”, paper presented at the Citigroup Global Consumer and Investment Bank (Hong Kong) Conference, August. Roberts, R.W. (1992), “Determinants of corporate social responsibility disclosure: an application of stakeholder theory”, Accounting, Organizations and Society, Vol. 17 No. 6, pp. 595-612. Subbarao, A.V. and Zeghal, D. (1997), “Human resources information disclosure in annual reports: an international comparison”, Journal of Human Resource Costing and Accounting, Vol. 2 No. 2, pp. 53-73. Sveiby, K.E. (1997), The New Organizational Wealth: Managing and Measuring Knowledge-Based Assets, Berrett-Koehler, San Francisco, CA. Tilt, C.A. (2001), “The content and disclosure of Australian corporate environmental policies”, Accounting, Auditing & Accountability Journal, Vol. 14 No. 2, pp. 190-212. Ullmann, A.E. (1976), “The corporate environmental accounting system: a management tool for fighting environmental degradation”, Accounting, Organizations and Society, Vol. 1 No. 1, pp. 71-9. Unerman, J. (2000), “Methodological issues: reflections on quantification in corporate social reporting content analysis”, Accounting, Auditing & Accountability Journal, Vol. 13 No. 5, pp. 667-80. Walden, D. and Schwartz, B.N. (1997), “Environmental disclosures and public policy pressure”, Journal of Accounting and Public Policy, Vol. 16 No. 2, pp. 125-54. Zeghal, D. and Ahmed, S.A. (1990), “Comparison of social responsibility information disclosure media used by Canadian firms”, Accounting, Auditing & Accountability Journal, Vol. 3 No. 1, pp. 38-53. Further reading Mathews, M.R. (1997), “Twenty-five years of social and environmental accounting research – is there a silver jubilee to celebrate?”, Accounting, Auditing & Accountability Journal, Vol. 10 No. 4, pp. 481-531. Weber, R.P. (1985), Basic Content Analysis: Quantitative Application in the Social Sciences, The Sage CommText Series, Sage, Beverly Hills, CA.
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Theory and method on intellectual capital creation Addressing communicative action through relative methodics David O’Donnell The Intellectual Capital Research Institute of Ireland, Ballyagran, Ireland Keywords Intellectual capital, Research methods Abstract Intellectual capital is a diverse and multidisciplinary field where there is much scope for interdisciplinary research. Such interdisciplinarity demands that we first transcend boundaries between IC researchers and disciplines and then transcend any subsequently perceived ontological and/or methodological barriers. Moving from the particular to the general, this paper draws on the contours of the Habermasian communicative relation to present some theoretical insights on how intellectual capital is created linguistically in social space. The ontological and methodological implications of this particular approach to research lead to the general argument for adopting a “relative view” on both ontology and methodology in order to craft navigational routes into interdisciplinary social space in the IC field. Such an approach allows IC researchers to draw on extant, and seemingly incommensurable, methodologies and techniques from analytical positivism, systems theory and the hermeneutic tradition in a scientifically justifiable post-foundationalist manner. The theory of communicative action regards the dialectic of knowing and not knowing as embedded within the dialectic of successful and unsuccessful mutual understanding (Habermas, 1987a, p. 314). Relative view: The collective results of absolute and relative procedures and relative methodics within the framework of a methodological base approach, using other methodological approaches in relation to an area under study (Arbnor and Bjerke, 1997, p. 454).
Introduction The diverse and very multidisciplinary field of intellectual capital (IC), if it is to develop further, needs grounding in interdisciplinary theory or theories. With theory, and appropriate methodology, we may be able to identify some fundamental principles, characteristics or commonalities that will focus research in the IC field. This demands that we first transcend boundaries between IC researchers and disciplines and then transcend any subsequently perceived ontological and/or methodological barriers to interdisciplinary knowledge creation. This is the general post-foundationalist challenge posed in this paper with every value, convention, norm, order, Journal of Intellectual Capital Vol. 5 No. 2, 2004 pp. 294-311 q Emerald Group Publishing Limited 1469-1930 DOI 10.1108/14691930410533713
The author must acknowledge the very perceptive suggestions made by two anonymous reviewers of this journal, the guidance received from both guest editors Bernard Marr and Jay Chatzkel, feedback from the E*Know-Net conference in Madrid in 2002, and particularly, the quality of the communicative relations at the Cranfield PMA IC Symposium in October 2003. The usual disclaimer applies. Comments to the author welcome:
[email protected]
epistemology, ontology, discipline, theory and method all available for critical discussion – and potential inclusion in the field. Acknowledging the fact that “all attempts at discovering ultimate foundations . . . have broken down” (Habermas, 1984, p. 2), naı¨ve exclusionism and congealed “tyrannies of the truth” (Nietzsche), of whatever ilk, are emphatically rejected here. Adopting Bo¨hr’s complementarity and correspondence principles as general guides, interdisciplinary theory development demands that we pragmatically draw on tried and tested insights and methods from prior studies in relevant disciplines and from across diverse ontological world views and apply these pragmatically and appropriately to the research task of the here-and-now. Moving from the particular to the general, this paper draws on the contours of the Habermasian (1984) communicative relation to present some theoretical insights on how intellectual capital is created linguistically in social space[1]. An exploration of the ontological and methodological implications of this particular approach to research leads to the general argument for adopting a “relative view” (Arbnor and Bjerke, 1997) on both ontology and methodology in order to craft navigational routes into interdisciplinary social space in the IC field[2]. Such an approach allows interdisciplinary oriented IC researchers to draw on extant, and seemingly incommensurable, methodologies and techniques from analytical positivism, systems theory and the hermeneutic tradition in a scientifically justifiable postfoundationalist manner. Incommensurability, by definition, means that these traditions cannot be simply combined – and allowing antagonistic, as distinct from critically constructive, debates on diverse world views and methodologies in the IC field is probably ultimately futile. Our first task, as researchers/practitioners, is to find a means of communicating with, explaining our approaches to, learning from, and understanding each other. The structure of the paper is as follows: first, some background history to the particular research agenda is presented and some perceived barriers identified in general terms; the broad contours of the Habermasian communicative relation as applied to IC creation are then outlined and some of its ontological and methodological implications identified; a relative view across ontological barriers is then proposed as a methodological solution to the particular research agenda; the paper concludes with the general argument that a pragmatic adoption of the relative view, by transcending ontological boundaries, can bring much needed coherence to the interdisciplinary nature of IC research. Background to the particular It is not the intention in this paper to review the extant IC literature, but it is now increasingly accepted that IC is probably becoming the primary source of organisational value – notwithstanding the fact that we have yet to clearly define it. This complex, dynamic and still very fuzzy construction is viewed here simply as a dynamic process of situated collective knowing that is capable of being leveraged into economic and social value. Nor do we have any consensus on the vexed boundary between IC creation and how it is leveraged into value, whether as intellectual property (IP), financial value, some form of social value, or otherwise. Further, the intangible nature of substantive aspects of this complex process of value creation is particularly challenging. How do we gain empirical access to a process of value creation that is deemed to be largely intangible? How do we make some pragmatic sense of something that we cannot yet adequately describe, define, identify or understand – let alone
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measure? Intellectual capital, similar to other abstractions such as “economy” or “organisation” or “management” is a human construction, reproduced by a wide variety of texts, discourses and practices that help us to make some sense, or perhaps nonsense, of our world(s). Our discourse as researchers does not simply mirror social reality, which after Wittgenstein and others many of us now accept as being impossible – but in fact, following Hardy et al. (2000), our discourses also create social realities in the IC field – and, perhaps, have some influence, beneficial or otherwise, on practice. Since the mid-1990s I have developed an interest in the later, and much more pragmatic, social theory and philosophy of Ju¨rgen Habermas (1984, 1987a, b, 1996), in particular his Theory of Communicative Action (Habermas, 1984, 1987b) that has its point of departure in the communicative relation between people[3]. In recent years my main research agenda is based on developing the intuitive idea that social theoretical insights from this theory can be applied in attempting to gain a theoretical grasp on the intangible nature of the process of IC creation. The crux, of course, arrives with the application of theory to the researcher’s task of generating new knowledge on how IC is created. As Habermas (1996, p. x) himself puts it in applying this theory to law and democracy in Between Facts and Norms: [T]he basic assumptions of the theory of communicative action . . . branch out into various universes of discourse, where they must prove their mettle in the contexts of debate they happen to encounter.
This is particularly the case when my first available source of data is a large cross-sectional survey designed to generate analytical knowledge at the same time as I find myself reading about the positivist dispute in German sociology in the early 1960s between Popper, Adorno and Habermas! The subject-object relation of the philosophy of consciousness (from Descartes through Kant and Hegel to Smith and Marx) the foundation of the analytical-positivist approach, is, according to Habermas (1987a), and many others, now exhausted – hence his “linguistic turn” away from individual action to interaction and a focus on the communicative relation between people through speech act and argumentation theory. Systems theory, of course, could provide another focus with Parsons, von Bertalanffy, Churchman, Luhmann’s appropriation of autopoiesis, Weiner’s cybernetics, or the complex adaptive systems approach now prominent at the Santa Fe´ Institute all available. Habermas also draws on systems theory – but yet another crux! The communicative relation is primarily a “lifeworld”, as distinct from a “system”, phenomenon – which would indicate a move solely to interpretive case study, ethnographic, or co-creation research within the hermeneutic tradition. What then to do with good analytical data, focus-group transcripts, semi-structured interviews, co-creation consultancy experiences and so on – and how to continue meaningful discussion with colleagues who work within purely systems or analytical frameworks? All these paradigms, dominant logics or congealed Nietzschean tyrannies of truth within various research milieu can be very frustrating and restraining in indicating to us what we can and cannot do, what is supposedly valid or not, what methods one should or should not use – what is eventually publishable or not, and where. Further, Mouritsen et al. (2001a, p. 110) identify extant discourses where intellectual capital: . . . may be an effect; it may be a departmental strategy; it may be a mathematical formula, but how it works is difficult to unravel. Against this background it is not difficult to understand
why some authors have struggled to find the referent of intellectual capital – what is intellectual capital mapping and trying to bring into the open?
Such are some of the joys and tribulations of theory, method and research for any practitioner who stumbles across the academic divide! The focus in this paper is explicitly on the “process” of IC creation and how to do interdisciplinary research on this process. As a diverse multidisciplinary group of researchers and practitioners how do we overcome restrictive norms and conventions and do interdisciplinary research in the IC field. How do we do both interdisciplinary theory and method? We have no consensus yet on what intellectual capital is – it may, therefore, appear somewhat presumptuous to focus here on how IC is created. Notwithstanding this qualification, one aspect of IC creation eminently worthy of mapping is the quality of dialogue, communication, collaboration and argumentation in knowing-intensive settings – this is the referent here and it is grounded theoretically in the Habermasian communicative relation – which is primarily a lifeworld, as distinct from system, phenomenon. Living in a “wholly decentred society” where the philosophy of consciousness is exhausted – the isolate Cartesian Robinson Crusoe having eventually run into the insular dead ends of the subject-object relation – I intentionally also take the “linguistic turn”[4] to a consideration of the quality of dialogue, or speech acts, in diverse Crusoe-Friday relations within knowing-intensive settings. Human interaction as manifest in the communicative relation, and not individual action, is the unit of theoretical analysis, and the means of human interaction, notwithstanding its inability to fully mirror or capture social reality, is dialogue – with Habermas’ elaboration of this process as communicative action one of the most sophisticated in social theory. Before exploring how one might conduct such a particular research agenda, we step back a little, and perusing other fields where the perennial debate on method is ongoing, one hopefully reaches the pragmatic conclusion that starting antagonistic debates on method in the IC field is unnecessary, probably ultimately futile, and of little if any benefit, or indeed interest, to practitioners. To draw on one example, Fitzgerald and Howcroft (1998) note that: The dispute between “hard” positivist and “soft” interpretivist research paradigms is a perennial one in the [information systems] field. Notwithstanding this . . . the debate should be recognised as being somewhat vacuous, since each approach has its strengths and weaknesses. Indeed, if the debate could be resolved, it would have been long ago. However, given the privileged hegemony enjoyed by the “hard” approach, “soft” research will always be accorded an inferior status if it is to be judged against the prevailing “hard” standards (Fitzgerald and Howcroft, 1998, p. 313). However, given that the debate cannot be resolved, a strategy of dissolution may be more appropriate. Thus, the debate should be conducted at a different level – a macro one where, rather than advocates of interpretivism proffering a one-sided over-statement of the weaknesses of the positivist approach but still providing defensive apologist methodological equivalents of positivist canons to placate criticism, the whole research agenda should be fundamentally re-oriented to accommodate “soft” research approaches. One possible measure of the achievement of such a balance would be when journal calls for quantitative research papers are as common as calls for qualitative ones – ideally, both at zero (Fitzgerald and Howcroft, 1998, p. 323).
This macro-approach is suggestive of multiple methods and a pragmatic integration, pluralism or postfoundationalist dissolution. Fitzgerald and Howcroft (1998) provide a succinct summary of each hard-soft dichotomy (or continuum) in terms of ontology,
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epistemology, method and axiology (Table I). As a starting point, what we can learn here is that it would help if we make any such assumptions explicit. Method is open here for both hard and soft approaches – the question now becomes – how do we use, or if necessary transcend, each dichotomy/continuum, in ways that are both appropriate and credible in applying insights from the Theory of Communicative Action to the research domain of IC creation using both soft (lifeworld) and hard (analytical;systems) perspectives? To introduce the particular theoretical argument, the first quotation at the head of this paper signals my ultimate research goal of gaining some conceptual grasp, however partial, on the intangible nature of IC creation. As knowing-intensive work is highly reflexive, the norms governing the mode of discourse within the communicative relation, the dialectical to-and-fro in the search for the better argument, will be expected to influence the intellective sophistication and productivity of the group, network or community of practice and, perhaps, the eventual economic and social value of the IC created – whatever the definition of IC adopted. The aspect of IC creation addressed here, namely “critical appraisal norms (CAN)” (O’Donnell, 2000; O’Donnell et al., 2000a, b, 2003a) is explicitly based on the set of symmetric and reciprocal procedural relations and validity claims within the Habermasian (1984, 1987a, b) communicative relation. These procedures are universal – yet the content of such communicative dialogues remains contextual and particular. Further, in order to address communicative action, this approach demands that one adopts both participant and observer perspectives. This research agenda is, therefore, a post-foundationalist attempt to demonstrate at a very general level how a particular theoretical focus on one key aspect of IC creation may be approached by drawing on three different ontological-methodological traditions – analytical positivism, systems theory and the actor’s approach – with the first foundation based on one of these approaches – in this case, the actor’s approach. The second quotation above signals methodology – one way of transcending congealed ontological barriers, the general argument of this paper, is for interdisciplinary IC researchers to adopt “relative methodics” (Arbnor and Bjerke, 1997) as the guiding principle of complementarity that allows knowledge created from diverse disciplinary perspectives, incommensurable ontological world views, and different methodological approaches, to be “contextually modified” or “reshaped” and made useful in generating new knowledge in the IC field. The paper now proceeds to an illustrative discussion of the communicative relation, the referent in the object domain of this particular research agenda, where some of the ontological and methodological implications of its theoretical architectonic are identified.
Communicative action: lifeworld-in-system The instrumental, teleological or means-end rationalities of the systems of money and power are geared to profit, success, efficiency, control, or market share; in contrast, the communicative rationality of the human lifeworld is geared to understanding and agreement (Habermas, 1987a). This shift from instrumental success to communicative understanding is a core distinction in all of Habermas’ work. The boundary between system (money, power) and human lifeworld is not a clear-cut one – even within knowing-intensive organisations – they interpenetrate and reciprocally influence each other, although most discourses on business, science and technology issues assume a system (in the Habermasian sense) perspective, with the hard approaches particularly dominant in the business literature.
Soft Ontological level Relativist. Belief that multiple realities exist as subjective constructions of the mind. Socially-transmitted terms direct how reality is perceived and this will vary across different languages and cultures Epistemological level Interpretivist. No universal truth. Understand and interpret from researcher’s own frame of reference. Uncommitted neutrality impossible. Realism of context important Subjectivist. Distinction between the researcher and research situation is collapsed. Research findings emerge from the interaction between researcher and research situation, and the values and beliefs of the researcher are central mediators Emic/insider/subjective. Origins in anthropology. Research orientation centred on native/insider’s view, with the latter viewed as an appropriate judge of adequacy of research
Hard
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Realist. Belief that external world consists of pre-existing hard, tangible structures which exist independently of an individual’s cognition
299 Positivist. Belief that world conforms to fixed laws of causation. Complexity can be tackled by reductionism. Emphasis on objectivity, measurement and repeatability Objectivist. Both possible and essential that the researcher remain detached from the research situation. Neutral observation of reality must take place in the absence of any contaminating values or biases on the part of the researcher Etic/outsider/objective. Origins in anthropology. Research orientation of outside researcher who is seen as objective and the appropriate analyst of research
Methodological level Qualitative. Determining what things exist rather than how many there are. Thick description. Less structured and more responsive to needs and nature of research situation
Quantitative. Use of mathematical and statistical techniques to identify facts and causal relationships. Samples can be larger and more representative. Results can be generalised to larger populations within known limits of error Exploratory. Concerned with discovering patterns Confirmatory. Concerned with hypothesis testing in research data, and to explain/understand them. and theory verification. Tends to follow positivist, Lays basic descriptive foundation. May lead to quantitative modes of research generation of hypotheses Induction. Begins with specific instances that are Deduction. Uses general results to ascribe used to arrive at overall generalisations that can properties to specific instances. An argument is be expected on the balance of probability. New valid if it is impossible for the conclusions to be evidence may cause conclusions to be revised. false if the premises are true. Associated with Criticised by many philosophers of science, but theory verification/falsification and hypothesis plays an important role in theory/hypothesis testing conception Field. Emphasis on realism of context in natural Laboratory. Precise measurement and control of situation, but precision in control of variables and variables, but at expense of naturalness of behaviour measurement cannot be achieved situation, since real-world intensity and variation may not be achievable Idiographic. Individual-centred perspective which Nomothetic. Group-centred perspective using uses naturalistic contexts and qualitative methods controlled environments and quantitative to recognise unique experience of the subject methods to establish general laws Axiological level Relevance. External validity of actual research question and its relevance to practice is emphasised, rather than constraining the focus to that researchable by “rigorous” methods Source: Fitzgerald and Howcroft (1998)
Rigour. Research characterised by hypothetico-deductive testing according to the positivist paradigm, with emphasis on internal validity through tight experimental control and quantitative techniques
Table I. Summary of “soft” versus “hard” research dichotomies
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The Theory of Communicative Action (Habermas, 1984, 1987b) demands both system and lifeworld perspectives allied to a consideration of the mediating influence of Law. Members of a social collective normally share a largely intangible, taken-for-granted, tacit, ready-to-hand (Heidegger) lifeworld that only exists in a “uniquely pre-reflexive form of background assumptions, background receptivities or background relations” (Honneth et al., 1981, p. 16). Such lifeworlds can be conceived of as “culturally transmitted and linguistically organised stock(s) of interpretative patterns” (Habermas, 1987b, p. 124) – such stocks of interpretative patterns viewed here as the source of the processual flows of knowing from which intellectual capital is created through communicative relations. Leveraging this into financial or commercial or social value is yet another highly complex question, and not addressed in this paper. Habermas (1984) defines communicative action as follows: Communicative action refers to the interaction of at least two subjects capable of speech and action who establish interpersonal relations (whether by verbal or extra-verbal means). The actors seek to reach an understanding about the action situation and their plans of action in order to coordinate their actions by way of agreement. The central concept of interpretation refers in the first instance to negotiating definitions of the situation [that] admit of consensus (Habermas, 1984, p. 86). Only the communicative model of action presupposes language as a medium of uncurtailed communication whereby speakers and hearers, out of the context of their preinterpreted lifeworld, refer simultaneously to things in the objective, social and subjective worlds in order to negotiate common definitions of the situation (Habermas, 1984, p. 95).
Human action can be divided into two broad categories (Table II): action oriented to success, which is the usual idea of rationality dominant in organisation theory, economics and the broad business literature, and communicative action, which is aimed at gaining intersubjective understanding (Versta¨ndigung). Action oriented to success, teleological action or goal directed action, can again be divided into two distinct sub-categories, namely instrumental action and strategic action: We call an action oriented to success instrumental when we consider it under the aspect of following technical rules of action and assess the efficiency of an intervention into a complex of circumstances and events. We call an action oriented to success strategic when we consider it under the aspect of following rules of rational choice and assess the efficacy of influencing the decisions of a rational opponent. Instrumental actions can be connected with and subordinated to social interactions of a different type – for example, as the “task elements” of social roles; strategic actions are social actions by themselves. By contrast, I shall speak of communicative action whenever the actions of the agents involved are co-ordinated not through egocentric calculations of success but through acts of reaching understanding. In communicative action participants are not primarily oriented to their own individual successes; they pursue their individual goals under the condition that they can harmonise
Table II. Types of action
Action situation
Oriented to success
Non social Social
Instrumental action Strategic action
Source: Habermas (1984, p. 285)
Action orientation Oriented to reaching understanding – Communicative action
their plans of action on the basis of common situation definitions. In this respect the negotiation of definitions of the situation is an essential element of the interpretive accomplishments required for communicative action . . . Social actions can be distinguished according to whether the participants adopt either a success-oriented attitude or one oriented to reaching understanding. And under suitable conditions, these attitudes should be identifiable on the basis of the intuitive knowledge of the participants themselves (Habermas, 1984, pp. 285-6, emphasis in original).
This begs the key methodological question: how do I, as a researcher, address communicative action, gain access to “the intuitive knowledge of the participants themselves”, or indeed distinguish it from other action types? Following Habermas’ argument: The method of interpretive understanding places the usual type of objectivity of knowledge in question, because [I, as an interpreter], though without aims of action of [my] own have to become involved in participating in communicative action and find [myself] confronted with the validity claims arising in the object domain itself. [As a researcher I have] to meet the rational internal structure of action oriented to validity claims with an interpretation that is rational in conception. [I, as an interpreter] could neutralise the latter only at the cost of assuming the objectivating status of an observer; but from that standpoint internal interrelations of meaning are entirely inaccessible. There is then a fundamental connection between understanding communicative actions and constructing rational interpretations. This connection is fundamental because communicative actions cannot be interpreted in two stages – first understood in their actual course and only then compared with an ideal-typical model. Rather, [I, as an interpreter/researcher] who participates virtually, without [my] own aims of action, can descriptively grasp the meaning of the actual course of a process of reaching understanding only under the presupposition that [I] judge the agreement and disagreement, the validity claims and potential reasons with which [I am] confronted, on a common basis shared in principle by [me] and those immediately involved. At any rate, this participation is imperative for a social-scientific interpreter who bases [my] descriptions on the communicative model of action (Habermas, 1984, pp. 116-17, emphasis in original, personalisation added).
The methodological implications here are obvious – one must get “in there” to a knowing-intensive lifeworld and adopt the “internalist” perspective of a performative participant. One must then attempt to distinguish between instrumental and various forms of strategic action (open; latent; manipulative; exploitative), and communicative action. With respect to communicative action within the communicative relation, its three main validity claims are implicitly part of language, and therefore, are always potentially present. However, all three validity claims are not necessarily in focus at any one time, the context and utterances suggesting which particular validity criterion may be questioned. At the micro-level, this is of potential theoretical and practical relevance in gaining access to the intangible or immaterial nature of IC creation. Although language cannot fully mirror reality, participative dialogue provides us with potential access to the intuitive self-understanding of the actors in particular lifeworlds. Following Parsons, Habermas provides us with guidelines on how to conceptualise lifeworlds that can structure an investigation of one aspect of the process of IC creation with a point of departure from the procedural aspects of the communicative relation and their corresponding validity claims (Table III). The structural components of particular lifeworlds (culture, community of practice, selves) meet their corresponding processual needs (cultural reproduction, social integration, socialisation and selves-development)
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Table III. Contours of a Habermasian lifeworld-in-system
Source: O’Donnell and Henriksen (2002, p. 95)
Social integration Socialisation
1.1 Interpretative schemata fit for consensus: valid processes of knowing (loss of meaning) 2.1 Obligations (unsettling of collective identity) 3.1 Interpretative accomplishments (rupture of tradition)
Culture
2.2 Legitimately ordered interpersonal relations (anomie) 3.2 Motivations for actions that conform to norms (withdrawal of motivation)
1.2 Legitimations (withdrawal of legitimation)
Structural components Community of practice
1.3 Behaviour patterns effective in learning and development (crisis in orientation and development) 2.3 Social memberships and ownership (alienation) 3.3 Interpretative capabilities and personal identities (psycho-pathologies)
Selves
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Cultural reproduction
Reproduction processes
Solidarity of members Personal responsibility
Rationality of knowledge
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through three dimensions along which communicative action is conducted (reaching understanding, coordinating interaction, effecting socialisation) which in turn are rooted in the structural components of ordinary everyday language, communication and human interaction. The process of communicative action within particular IC creating lifeworlds can be evaluated using the dimensions of rationality of knowledge, member solidarity, and personal/group responsibility (O’Donnell, 2000; O’Donnell et al., 2000a, b, 2003a). Both positive and negative (within brackets) outcomes are shown in Table III. Communicative action, under the functional aspect of reaching understanding, facilitates the transmission and renewal of cultural knowledge; under the aspect of coordinating action, it facilitates social integration and the establishment of group solidarities; and under the aspect of socialisation, it facilitates the formation of personal and community identities (Habermas, 1987b). Everyday language and communication within the communicative relation is viewed as the referent of intellectual capital creation and the validity claims of comprehensibility, objective truthfulness or efficiency, normative rightness and sincerity provide empirical entry points for such research – from the initial perspective of a real or virtual participant. In sum, the rational internal structures of this process of communicative action can be characterised in terms of: . the three ontological world-relations of actors and the corresponding concepts of the objective, social, and subjective worlds; . the validity claims within the communicative relation of comprehensibility, propositional truth/efficacy, normative rightness, and sincerity/authenticity (critical appraisal norms); . the concept of a rationally motivated agreement, that is, one based on the intersubjective recognition of criticisable validity claims; and . the concept of reaching understanding as the cooperative negotiation of common definitions of the situation. This procedural structure can be shown to be universally valid in a specific or particular sense, thus satisfying the scientific requirements of objectivity (Habermas, 1984, p. 137) in a post-foundationalist manner. Again, one must stress that only the procedural aspects of the communicative relation are deemed to be universal (the thread keeping critical modernism alive) – content and specifics remain contextual. The ability to raise validity claims within this communicative relation is central to the reflexive nature of the dynamic process of IC creation. When two people communicate with each other, face-to-face speech, body language, electronically mediated or otherwise, each utterance that ego makes can be implicitly or explicitly accepted or challenged by alter on a simple “yes” or “no” basis. Ego is seen as making a claim to validity with each utterance and alter can either accept or reject this claim. The first and general validity claim relates to comprehensibility – a claim rarely challenged in everyday discourse, but an often insurmountable obstacle to interdisciplinary dialogue between positivists, systems theorists, hermeneuticists, critical theorists and postmodernists – that is, if we even deign to engage in discourse with each other! The validity claims of propositional truth and/or efficacy relate to the objective world of facts and/or states of affairs; for example, if ego suggests to alter that an analytical approach is the only way to get a paper published in the Academy of Intellectual Capital Journal this claim can be explicitly rejected by alter with a “no” who may then provide evidence of papers that have been published from both systems
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theory and the actors approach; if a member of an IC research group suggests that embedded interpretive case study work is the only methodological route to valid and reliable data, others may explicitly refuse to accept the validity of this proposed research strategy, seek further evidence from others, or produce their own evidence to suggest that multiple world views and methodologies should be acceptable in an emerging field. The validity claim of normative rightness relates to the social world “around here” – what is generally considered normative, socially acceptable and very often culturally “taken for granted” behaviour; for example, a new member joins a product development group and after an number of meetings continues to refuse to divulge the source literature for some of his ideas only to be politely informed that “Hey, you can’t keep key stuff like that from us around here!” – that is, the validity of this member’s ego-strategic-instrumental action is not accepted by the other members as it does not conform to the knowledge-sharing norms of this particular group. The validity claim of sincerity/authenticity relates to the (inter)subjective world; this validity claim is often accepted or rejected implicitly and silently by alter who decides whether ego is being genuine, sincere or authentic on the one hand – or dishonest, manipulative, exploitative or latently strategic on the other. As this brief discussion on validity claims demonstrates, communicative action is a fragile process and when this process is colonised (Table III) or endangered by system influences – intentionally engendered or otherwise – the quality of communication in the lifeworld, the quality of the lifeworld itself, and by implication, the quality of IC eventually created, if any, will probably suffer. If one accepts this argument, it follows that anything which negatively influences the ability to raise such validity claims within the set of communicative relations will reduce, or perhaps even destroy, the healthy functioning of particular knowing intensive communities – with implications for knowledge creation, knowledge sharing, learning, innovation and collective value creation processes. This is the knowing-intensive lifeworld. IC creating lifeworlds, however, are usually tied to system or organisational settings. A lifeworld approach, from the methodological perspective of a participant, taken by itself, runs the risk of an “hermeneutic idealism” – by conceptualising IC creation solely from the perspective of the intuitive knowledge or self-understanding of participants and remaining “blind to causes, connections and consequences that lie beyond the horizon of everyday practice”. This transition, according to Habermas, from one problem area to the other of this action-system disjecta membra is tied to a “change of methodological attitude and conceptual apparatus” in that “functional integration only comes into view when the lifeworld is objectified as a boundary-maintaining system” (see McCarthy, 1984, pp. xxviii-xxix). With this ontological transition one moves over to take the perspective of an observer – which, in turn, brings techniques and methods from analytical and systems approaches back into this particular research agenda. From such an observer perspective, however: . . . relevant phenomena . . . are [usually] described in a language that objectivistically disregards actors’ self-understanding. This language neither seeks nor gains an entry into the intuitive knowledge of participants. Under the artificially defamiliarising gaze of [a] system observer who conceives [oneself] as a system in an environment, or that of [an] ethnologist who approaches even [one’s] own native practices and language games as an uninitiated stranger, every context of social life crystallises into a hermeneutically inaccessible second nature, about which counter-intuitive knowledge is gathered as it is in the natural sciences (Habermas, 1996, p. 48; personalisation added).
The lifeworld approach, (grounded in its correlate – the communicative relation, viewed as a, if not the, source of IC creation) at first glance, appears to be best suited to interpretive case study, ethnographic or co-creation research – somewhat on the “soft” social constructionist side as in Table I – and from the perspective of a performative participant. However, by shifting “methodological attitude and conceptual apparatus”, it is also possible, indeed necessary, to view an IC creating lifeworld-in-system using systems methodology, complex adaptive, Luhmannian or otherwise. Further – but perhaps now not so surprising to those of us who have pragmatically decided to transcend positivist/interpretivist disputes – it is possible, because of the social theoretical precision with which Habermas describes these validity claims as real social facts, to operationalise the analytical construct critical appraisal norms (CAN) and to also conduct some analytical research on the communicative relation using perceptual measures. Other system influences such as the nature of hierarchy, nature and dispersion of power, influence of human resource and reward systems, level of trust relations and so on can also be investigated from the more traditional objectivist perspectives – but in a post-foundationalist manner; the internalist, in this particular research case, retains precedence over the externalist perspective. To do this, one must break through conventional ontological barriers as the communicative relation, similar to Bohr’s wave-particle duality, can have both lifeworld and system-like properties; and further, it is quite impossible to know everything simultaneously about both. This is the social theoretical map, and empirical entry points, within which one can now think reasonably substantively about one key aspect of the intangible nature of IC creation – and do research. So, how does one coherently do participant-observer or internalist-externalist or lifeworld-system perspectives empirically and transcend or break through conventional ontological barriers? Relative methodics provides one possibility. Relative methodics One seminal approach to using multiple methodologies at a pragmatic macro-level is provided by Arbnor and Bjerke’s (1997) Methodology for Creating Business Knowledge, a classic in Scandinavia in the original Swedish version but not that well known within the English speaking Anglo-Hiberno-American communities. It is difficult to do justice to the scientific clarity and eloquent pragmatism of this text in a short paper such as this, but their insights are particularly appropriate to a post-foundationalist approach to research that demands using both soft and hard methodologies – and participant and observer perspectives – and in the process, break through congealed ontological barriers. A very brief outline must suffice here where the only addition made is to simply position the Theory of Communicative Action (both system and lifeworld). Arbnor and Bjerke (1997) identify six paradigmatic social science perspectives (Figure 1) based on what they term “ultimate presumptions of reality”. Our first task as researchers is to make the presumptions of reality on which it is based explicit in any piece of work. These in turn determine one’s views on human nature, the appropriate methodology and techniques to apply, and the normative discourse that tends to emerge within each paradigm. On this latter point contrast the difference between the dialogue at working lunches between positivists, systems theorists, interpretivists, critical theorists and postmodernists! All are represented in the IC field – the question is how do we communicate with each other? – and perhaps more importantly – how do we use and make some sense of each other’s techniques and findings? Moving from the first
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Figure 1. Six social science paradigms
perspective on the left towards the sixth on the right illustrates the “decisive difference” between creators of knowledge who focus on explaining (Erkla¨ren – the positivist lunch table) or understanding (Verstehen – the hermeneutic table). These six paradigms are reduced to three broad research approaches by Arbnor and Bjerke (1997): the analytical approach, the systems approach, and the actors approach (Figure 2). The analytical and systems approaches are explanaticist whereas the actors approach is broadly hermeneuticist. Arbnor and Bjerke (1997, pp. 453-4) provide a detailed discussion of each of the three main approaches and, much more importantly, provide a common terminology: . Paradigm. Ultimate presumptions of: conception of reality, conception of science, scientific ideals, and ethics/aesthetics. . Methodological approach. An approach for creating knowledge; based on a set of ultimate presumptions, using methods within a field of activities or a subject area.
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Figure 2. Three methodological approaches related to six paradigmatic perspectives
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Operative paradigm. A way of operation constructed for practical study reasons; consists of methodical procedures and methodics, in a relation between a methodological approach and an area under study. Methodical procedure. The way in which a creator of knowledge arranges, develops, and/or modifies a technique given a priori and/or previous results/theories within the framework of a methodological approach in relation to an area under study. Methodics. The way in which a creator of knowledge relates and arranges the techniques made into methods in a study plan and the way in which a study is actually conducted within the framework of a methodological approach in relation to an area under study. Method. A concrete guiding principle for creating knowledge in practice in the relation between a methodological approach and an area under study. Technique. Rules given a priori for using various tools to create knowledge in practice. Absolute view. The collective results of methodological procedures and methodics within the framework of one methodological approach – exclusive of any other methodological approach – in relation to an area under study. Relative view. The collective results of absolute and relative procedures and relative methodics within the framework of a methodological base approach, using other methodological approaches in relation to an area under study. Methodological base approach. The methodological approach against which a creator of knowledge assesses – against its ultimate presumptions – any inconsistent techniques and/or theories (from other methodological approaches) in order to use them to create knowledge within the framework of this methodological approach. Relative procedure. Methodical procedure whereby inconsistent techniques, theories, and/or results (from other methodological approaches) are arranged
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within the framework of a methodological base approach in relation to an area under study. Relative methodics. The way in which a creator of knowledge relates and arranges the techniques made into methods through absolute and relative procedures in a study plan, and the way in which a study is actually conducted within the framework of a methodological base approach in relation to an area under study. Area under study. That field of reality toward which a creator of knowledge aims his or her ambitions of creating knowledge.
This text provides us with a number of key concepts such as “relative view”, “absolute view”, “relative methodics”, and so on that allows one to navigate pragmatic pathways through hard-soft dichotomies/continua across ontological barriers and, in the process, produce useful research findings. All approaches are theoretically valid within their own “absolute” terms of social scientific reference – acknowledging that terms such as “absolute” and “ultimate” now have a much more modest meaning than heretofore. The general question now becomes: how can we all have lunch together? The interdisciplinary IC field needs a common language wherein all participants can feel comfortable being themselves and with their own preferred foundations while at the same time recognising others who may have different foundations or “absolute” views. But this is only a partial, if apparently civilized, solution – we cannot really use each other’s results or methodologies-techniques without transgressing the canons of our individual “ultimate” presumptions – or can we? In a decentred post-foundationalist world we most certainly can! Arbnor and Bjerke (1997) stress that these three approaches cannot be combined – this would be illogical. One might, for example, naı¨vely attempt to view a knowing-intensive organisation “as three parts, one of which is explained causally, one described in terms of finality, and the third understood as dialectic!” (Arbnor and Bjerke, 1997, p. 439) – one doubts that such an analysis of a knowing-intensive lifeworld-in-system would get very far in any journal review process or contribute any meaningful insights to guide practice! However, Arbnor and Bjerke (1997) very cogently argue that: [S]tarting from an absolute view . . . it is not only possible but in many situations clearly desirable to let the different approaches be included in a kind of complementary principle (to paraphrase the physicist Niels Bo¨hr); that is, no language in itself and by itself can capture reality in its entirety . . . What takes place (and should take place) is that one approach is then made into a methodological base approach; that is, the creator of knowledge confesses to one of the methodological approaches and its ultimate presumptions. Some methodological procedures (and part of the methodics) are conducted accordingly. Within the framework of the chosen approach, other methodological approaches can be used at the same time and as the study proceeds. What happens is that a special form of methodical procedure is used, one in which researchers-consultants-investigators try to consider circumstances based on the point of departure of another methodological approach, against their own base. The former circumstances will then be reshaped, they will take on another character and meaning. We call these special procedures relative, and the methodics that result relative methodics . . . This requires, however, that we truly know the presumptions on which these “methods of navigation” are based, otherwise we can run into trouble (Arbnor and Bjerke, 1997, pp. 439-40, emphasis in original).
Space does not allow for further discussion on relative methodics in this paper – but it provides useful methodological guidelines for addressing communicative action in a
knowing-intensive lifeworld-in-system. I must now explicitly confess, in this particular research case, to a strong partiality to the actor’s approach as a choice of “ultimate” foundation – and I can now use interpretive case study, ethnographic and dialectical forms of co-creation research on communicative action, the communicative relation and critical appraisal norms (CAN) from this “absolute” view from within IC creating contexts, and from the perspective of a performative participant, virtual or real. Language, notwithstanding its limits, provides the data for rational interpretation. By taking a relative view, I can also broaden the focus and adopt the methods of systems theory where and when they are deemed to be appropriate within a group or organisation. I can operationalise a construct (CAN) based on the procedural aspects of the communicative relation using analytical methods – and conduct statistical analysis accordingly to investigate possible relationships with other perceptual constructs of interest such as trust, reflexivity, rewards, power dispersion and so on – but not claiming universal generalisability and explicitly acknowledging the sectoral, time specific or other contextual nature of such findings. Results from both systems and analytical methods will, therefore, require some “contextual modification” or “reshaping” against the social theoretical base of the actors, approach that a post-foundationalist view of the world and an understanding of the limits of language demands. Very tentatively applying Bohr’s complementarity principle to this particular research agenda, and in the social as distinct from the physical sciences, the communicative relation should be describable in terms of lifeworld concepts and in terms of analytical/system concepts, and the two descriptions are together taken as a complete description of the properties of the communicative relation, despite the fact that no communicative relation can simultaneously correlate with both sets of concepts completely. Further, this particular methodological solution has some probable general applicability in the IC field. Conclusion Intellectual capital is a very diverse and multidisciplinary field where there is much scope for interdisciplinary research. Such interdisciplinarity, however, demands that we transcend any perceived barriers between IC researchers and disciplines and any subsequently perceived methodological and ontological barriers. Moving from the particular to the general, the main argument presented here in order to overcome such barriers is for interdisciplinary oriented IC researchers to adopt Arbnor and Bjerke’s (1997) “relative view” on methodology and ontology. Such an approach allows IC researchers to draw on extant, and seemingly incommensurable, methodologies and techniques from analytical positivism, systems theory and the hermeneutic tradition in a philosophically, social theoretically, and scientifically justifiable post-foundationalist manner. This paper is also a cursory attempt to present the architectonic of one particular research strategy on IC creation in terms of both theory and, particularly, method. Adopting the actor’s approach as a base and guided by relative methodics, the point of theoretical departure outlined here, with the aim of gaining a theoretical-empirical grasp, however partial, on the intangible nature of IC creation, is the set of symmetric and reciprocal relations presupposed in Habermas’ (1984) procedural, if ideal, conceptualisation of communicative action. The relations and validity claims built into the communicative relation, and the constraints under which they stand, are substantive and real social phenomena. They are, therefore, open to broad empirical investigation from both participant and observer perspectives – with relative
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methodics providing the pragmatic principle of complementarity that can transcend the perceived classical ontological barriers between lifeworld and system. I conclude with the general argument of the paper – applying a post-foundationalist relative view on methodology to the interdisciplinary research task of generating new knowledge in the IC field provides us with a common language that allows IC researchers from different disciplinary, theoretical and methodological traditions not only to transcend ontological barriers, but perhaps more importantly, to communicate substantively with each other. Notes 1. I draw here on some previous, mainly theoretical, work of a Habermasian nature (O’Donnell, 1999, 2000; O’Donnell and Henriksen, 2002; O’Donnell and O’Regan, 2000; O’Donnell and Porter, 2003; O’Donnell et al. 2000a, b, 2003a, b). 2. I am indebted to Lars Bo Henriksen at Aalborg University for introducing me to the work of Arbnor and Bjerke. 3. Thomas McCarthy’s (1984) “Translator’s introduction” remains the best synopsis of the theory of communicative action available; Hirschheim et al. (1996) provide a good overview of how this theory can be applied to the IS field; Samra-Fredericks’s (2000) interpretive research is explicitly based on Habermas’ validity claims; Roslender and Fincham (2003) provide a discussion on IC from the more emancipatory or critical intent of Habermas’ work. 4. The Danish Guidelines on IC, drawing on “knowledge narratives” (Bukh et al., 2001; Mouritsen et al., 2001a, b), provides one seminal example of how taking the linguistic turn can produce useful research findings. References Arbnor, I. and Bjerke, B. (1997), Methodology for Creating Business Knowledge, Sage, London. Bukh, P.N.D., Larsen, H.T. and Mouritsen, J. (2001), “Constructing intellectual capital statements”, Scandinavian Journal of Management, Vol. 17 No. 1, pp. 87-108. Fitzgerald, B. and Howcroft, D. (1998), “Towards dissolution of the IS research debate: from polarisation to polarity”, Journal of Information Technology, Vol. 13 No. 4, pp. 313-26. Habermas, J. (1984), The Theory of Communicative Action – Vol 1: Reason and the Rationalization of Society, McCarthy, T. (trans.), Polity, Cambridge. Habermas, J. (1987a), The Philosophical Discourse of Modernity, Lawrence, F. (trans.), Polity, Cambridge. Habermas, J. (1987b), The Theory of Communicative Action – Vol 2: Lifeworld and System: A Critique of Functionalist Reason, McCarthy, T. (trans.), Polity, Cambridge. Habermas, J. (1996), Between Facts and Norms, Rehg, W. (trans.), Polity, Cambridge. Hardy, C., Palmer, I. and Phillips, N. (2000), “Discourse as a strategic resource”, Human Relations, Vol. 53 No. 9, pp. 1227-48. Hirschheim, R., Klein, H.K. and Lyytinen, K. (1996), “Exploring the intellectual structures of information systems development: a social action theoretic analysis”, Accounting, Management and Information Technologies, Vol. 6 No. 1/2, pp. 1-64. Honneth, A., Kno¨dler-Bunte, E. and Widmann, A. (1981), “The dialectics of rationalization: an interview with Ju¨rgen Habermas”, Telos, Vol. 49, pp. 5-31. McCarthy, T. (1984), “Translator’s introduction”, in Habermas, J., The Theory of Communicative Action, Vol. 1, Polity, Cambridge, pp. vii-xxxix.
Mouritsen, J., Bukh, P.N.D., Larsen, H.T. and Johansen, M.R. (2001a), “Developing and managing knowledge through intellectual capital statements”, Journal of Intellectual Capital, Vol. 3 No. 1, pp. 10-29. Mouritsen, J., Larsen, H.T. and Bukh, P.N.D. (2001b), “Intellectual capital and the ‘capable firm’: narrating, visualising and numbering for managing knowledge”, Accounting, Organizations and Society, Vol. 26 No. 7/8, pp. 735-62. O’Donnell, D. (1999), “Habermas, critical theory, and selves-directed learning”, Journal of European Industrial Training, Vol. 23 No. 4/5, pp. 251-61. O’Donnell, D. (2000), “Intellectual capital creation: a Habermasian perspective”, working paper, The Intellectual Capital Research Institute of Ireland, Ballyagran. O’Donnell, D. and Henriksen, L.B. (2002), “Philosophical foundations for a critical evaluation of the social impact of ICT”, Journal of Information Technology, Vol. 17 No. 2, pp. 89-99. O’Donnell, D. and O’Regan, P. (2000), “The structural dimensions of intellectual capital: emerging challenges for management and accounting”, Southern African Business Review, Vol. 4 No. 2, pp. 14-20. O’Donnell, D. and Porter, G. (2003), “Making space for communities of practice: creating intellectual capital through communicative action”, in Beyerlein, M., McGee, C., Klein, G.D., Nemiro, J.E. and Broedling, L. (Eds), The Collaborative Work Systems Fieldbook, Jossey-Bass/Pfeiffer, San Francisco, CA, pp. 375-87. O’Donnell, D., O’Regan, P. and Coates, B. (2000a), “Intellectual capital: a Habermasian introduction”, Journal of Intellectual Capital, Vol. 1 No. 2/3, pp. 187-200. O’Donnell, D., O’Regan, P., Coates, B., Turner, T. and MacCurtain, S. (2000b), “Critical appraisal norms in intellectual capital creation”, in Combes, C., Grant, D., Keenoy, T. and Oswick, C. (Eds), Organizational Discourse: Word-views, Work-views and World-views, Proceedings of the 4th International Conference on Organizational Discourse, Kings College, University of London, London. O’Donnell, D., O’Regan, P., Coates, B., Kennedy, T., Keary, B. and Berkery, G. (2003a), “Human interaction: the critical source of intangible value”, Journal of Intellectual Capital, Vol. 4 No. 1, pp. 82-99. O’Donnell, D., Porter, G., McGuire, D., Garavan, T.N., Heffernan, M. and Cleary, P. (2003b), “Intellectual capital creation: a Habermasian community of practice introduction”, Journal of European Industrial Training, Vol. 27 No. 2/3/4, pp. 80-7. Roslender, R. and Fincham, R. (2003), “Intellectual capital: who counts, controls?”, Proceedings of the 3rd Critical Management Studies Conference, Lancaster University, Lancaster, June. Samra-Fredericks, D. (2000), “What was that? Speaking validity claims to shape strategic direction in the boardroom”, in Combes, C., Grant, D., Keenoy, T. and Oswick, C. (Eds), Organizational Discourse: Word-views, Work-views and World-views, Proceedings of the 4th International Conference on Organizational Discourse, King’s College, University of London, London.
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The dynamics of value creation: mapping your intellectual performance drivers Bernard Marr Cranfield School of Management, Cranfield, UK
Giovanni Schiuma University of Basilicata, Potenza, Italy, and
Andy Neely Cranfield School of Management, Cranfield, UK Keywords Intangible assets, Intellectual capital, Balanced scorecard, Resources Abstract The paper highlights the importance of visual representations of strategic intent in order to understand how organizational resources – especially intangible assets and intellectual capital – are used to create value. Based on the literature the paper provides a taxonomy of organizational value drivers. Grounded in the resource-based view of the firm, which argues that organizational resources or assets are bundled together and interdependent, it then highlights shortcomings in the strategy map approach based on the balanced scorecard. The paper then introduces the value creation map that utilizes both direct and indirect dependencies to map value creation. It is suggested that this approach complements the strategy map approach by extending its view of value creation from direct to both direct and indirect dependencies. Subsequently, the paper presents a case study of how the value creation map was applied to understand the new product development process in a leading furniture manufacturing firm.
Journal of Intellectual Capital Vol. 5 No. 2, 2004 pp. 312-325 q Emerald Group Publishing Limited 1469-1930 DOI 10.1108/14691930410533722
Introduction Organizations perform well and create value when they implement strategies that respond to market opportunities by exploiting their internal resources and capabilities (Penrose, 1959; Andrews, 1971). Therefore, managers need to understand what are the key resources and drivers of performance and value in their organizations. Traditionally, those resources were physical, such as land and machines, or financial capital. More recently the concept of intellectual capital has been identified as a key resource and driver of organizational performance and value creation (Itami, 1987; Teece, 2000; Nahapiet and Ghoshal, 1998; McGaughey, 2002; Delios and Beamish, 2001). The concept of performance drivers suggests causal relationships between resources and organizational value creation. Penrose argues that it is never resources themselves that create value, but the services that the resources can render (Penrose, 1959, p. 25). In order to understand how organizational resources translate into value Kaplan and Norton (2000, 2003) suggest visually mapping the causal relationships into a strategy map. Based on the perspectives of the balanced scorecard (Kaplan and Norton, 1992, 1996a, b) a strategy map contains outcome measures and performance drivers, linked together in a cause-and-effect diagram. Whereas evidence exists of causal relationships between non-financial assets and performance (Rucci et al., 1998; Ittner and Larcker, 1998) there are also some critical voices (Norreklit, 2000, 2003)
claiming that the relationships in the balanced scorecard are logical rather than causal. The argument of simply mapping performance drivers and outcomes also seems to break down when we take into account some of the theories put forward by the resource-based view of the firm (Wernerfelt, 1984; Rumelt, 1984; Barney, 1991). Penrose (1959), for example, argues that resources or assets of firms exist as a bundle, and others (Dierickx and Cool, 1989; Lippman and Rumelt, 1982) state, that these resource bundles impact performance with causal ambiguity and that it is difficult to identify how individual resources contribute to success without taking into account the interdependencies with other assets. With this article we aim to demonstrate the importance of interdependencies between organizational assets, both tangible and intangible. We believe that causal approaches such as strategy maps could benefit from a better understanding of how resources interact to create value. A better understanding of value creation can then be used as the basis for validation as well as decision-making (Ittner and Larcker, 2003). We begin this article by defining the key driver for organizational success. Next, we discuss the notion of strategy mapping in further detail and discuss its appropriateness to map how intellectual capital contributes to organizational performance and highlight some of its shortcomings. We then introduce the concept of value creation maps as a possible tool to overcome some of the shortcomings. Finally we present a case study in which we apply the value creation map. Drivers of organizational performance – a taxonomy Over a century ago Alfred Marshall (1890), in his Principles of Economics, acknowledges knowledge as an important resource and a powerful engine of production. In 1959, Edith Penrose defines the economic function of an organization to be the management of its resources, which underlie the production of services. This means that the value generated is a function of the way in which resources are managed. Penrose (1959) splits resources into physical assets and human capital. In the same year Peter Drucker (1959) published an article in which he writes that business enterprises are primarily an organization of highly specialized and knowledge intensive professionals, emphasizing the increasing importance of knowledge in organizations. Hiroyuki Itami introduces the concepts of invisible assets in a book first published in 1980 in Japan (Itami, 1987). Itami defines invisible assets as information-based assets, which includes technology, consumer trust, brand image, corporate culture, as well as management skills. According to Itami (1987) they are the most important resources for long-term success because only invisible assets can be used simultaneously in several areas. In the same year as Itami’s (1987) book was published in English, Johnson and Kaplan (1987) published their influential book highlighting how financially biased metrics are loosing their relevance to organizations. Aaker (1989) writes that assets and skills are the basis of competition; in the same year Hall (1989) introduces the concept of intellectual assets or intangible assets (Hall, 1992) as critical value drivers. Intangible assets are defined as those assets whose essence is an idea or knowledge, and whose nature can be defined and recorded in some way (Hall, 1992). The author splits them into intellectual property (those assets for which the organization has property rights) and knowledge assets (those assets for which the organization does not has property
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rights). Intangible assets drive capability differentials, which in turn drive sustainable competitive advantage, which is why organizations need to bring intangible resources and core competences into their strategic thinking (Hall, 1993). In his 1991 Fortune article, Tom Stewart (1991) writes, “Every company depends increasingly on knowledge – patents, processes, management skills, technologies, information about customers and suppliers, and old-fashioned experience” (Stewart, 1991). He continues, “Added together, this knowledge is intellectual capital. He defines intellectual capital as the sum of everything everybody in your company knows that gives you a competitive edge in your marketplace”. Quinn (1992) maintains that the majority of economic and production power of organizations lies in its intellectual capability. Hall (1992) uses the classification of intangible resources and splits them into assets and skills: assets include trade marks, patents, copyrights, registered designs, contracts, trade secrets, reputations, networks (personal and commercial relationships); whereas skills are comprised of know how or culture. In a survey of 95 firms Hall (1992) identified company reputation, product reputation and employee know-how as most important contributors for overall success. Following the pioneering work of the above-mentioned authors, various authors have defined taxonomies for intellectual capital. Hudson (1993) defines intellectual capital as a personal asset of individuals and a combination of genetic inheritance, education, experience, and attitude about life and business. Nahapiet and Ghoshal (1998) move away from a personal definition towards organizational intellectual capital; they use the term intellectual capital to refer to the knowledge and knowing capability of a social collectivity, such as an organization, intellectual community, or professional practice. Brooking (1996, 1997) goes even broader and defines intellectual capital as market assets, human centered assets, intellectual property assets, and infrastructure assets. Edvinsson (1997), former director of intellectual capital at Skandia, defines intellectual capital as human capital plus structural capital. He uses the reduction approach in the Skandia value scheme that identifies intellectual capital by deducting financial capital from overall value, which leaves intellectual capital; deducting human capital from intellectual capital leaves structural capital; deducting customer capital (customer relationships) leaves organizational capital; deducting value of processes leaves innovation capital; deducting intellectual property (patents, trade marks) leaves intangible assets as balancing value. Roos and Roos (1997) define intellectual capital in the broadest sense as human capital (knowledge capital, skill capital, motivation capital, task capital), business process capital (flow of information, flow of products and services, cash flow, co-operation forms, strategic processes), business renewal and development capital (specialization, production processes, new concepts, sales and marketing, new co-operation form), as well as customer relationship capital (customer relationship capital, supplier relationship capital, network partner relationship capital, investor relationship capital). Although the previously mentioned authors agree on the significance of intellectual capital as a resource underpinning organizational performance, there is considerable lack of consensus on a precise definition of intellectual capital. Some, like Hudson (1993) limit the scope of the term to only individual knowledge, whereas others like Brooking (1996) and Roos and Roos (1997), also include in their conceptualization organizational relationships, infrastructure, culture, routine, and intellectual property.
In order to gain a common understanding of terminology used in this article we will provide a taxonomy of organizational assets below. This taxonomy is the result of an extensive literature review on the subject. Organizational assets are classified as financial assets, physical assets, relationship assets, human assets, culture assets, practices and routine assets, and intellectual property assets.
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Financial assets Financial capital has traditionally been an important asset for any organization. Cash is needed by organizations in order to invest into other resources. Itami (1987) describes that money, as one of the invisible assets of an organization, is in fact a necessary input as well as an output of operations in form of cash flow.
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Physical assets Penrose (1959) defines physical assets as tangible things such as plant, equipment, land and natural resources. Williamson (1975) emphasizes the importance of physical assets to gain a competitive advantage. Here, physical assets comprise all tangible infrastructure assets, such as structural layout and information and communication technology. It includes databases, servers, and physical networks like intranets. Relationship assets Relationship assets are in the relationship between an organization and its external stakeholders as well as in the exchange of knowledge between them. Relationships can include official relationships such as partnering or distribution arrangements as well as non-formalized relationships such as relationship with customers or suppliers. Roos and Roos (1997) mention relationships with customers, suppliers, network partners, as well as with investors. Itami (1987, p. 19) highlights the information or knowledge exchange between organizations and their external environment. Information flows from the firm to the external environment include corporate reputation, brand image, corporate image, and influence over the distribution channel and its suppliers. Human assets Penrose explicitly distinguishes human resources from other assets of the firm. Human assets are identified as a key asset of the firm. Becker (1964) and Schultz (1981) use the phrase human capital defining a core asset of an organization. Hall (1992) emphasizes skills and know-how as important assets and Roos (1998) defines human assets as the knowledge, skills, and experience of employees. Human assets, therefore include employee’s skills, competences, commitment, motivation and loyalty. Some of the key components are know-how, technical expertise, and problem solving capability, creativity, education, and attitude. Culture assets Brooking (1996) maintains that corporate culture is an asset when the culture of an organization reinforces the achievement of the overall goals. Nahapiet and Ghoshal (1998) refer to it as social capital and context. Itami (1987) writes that corporate culture gives each person in an organization a common and distinctive method for transmitting and processing information; it defines a common way of seeing things, sets the decision-making pattern, and establishes the value system (Itami, 1987, p. 23).
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Culture assets embrace categories such as corporate culture, organizational values, and management philosophies. Culture assets provide employees with a shared framework to interpret events; a framework that encourages individuals to operate both as an autonomous entity and as a team in order to achieve the company’s objectives. Practices and routines as assets Shared knowledge in organizations is expressed in routines (Nelson and Winter, 1982) and practices. Roos and Roos (1997) classify organizational capital as important assets which include production or other processes, specialization, and flow of information. Itami (1987) also emphasizes the firm’s routines to manage and transmit information as a valuable invisible asset. Practices and routines include internal practices, virtual networks and routines, theses can be formalized or informal procedures and tacit rules. Formalized routines include process manuals providing codified procedures and rules; informal routines would be tacit rules of behavior or workflows. Practices and routines determine how processes are being handled and how work flows through the organization. Intellectual property assets Grindley and Teece (1997) conclude, from their studies of the semi-conductor industry, the increasing importance of patentable intellectual property. They state that patents and trade secrets have become a key element of competition in high-tech organizations and in fact claim that intellectual property is more critical than ever to competitive advantage. Edvinsson (1997) describes the intellectual property of Skandia as their patents and trade marks. Hall (1989) defines intellectual property as those assets to which the organization has property rights, such as patents, trademarks, registered designs, and copyrights, which all afford legal protection to the owners of certain classes of intellectual assets. Here we define intellectual property as the sum of assets such as patents, copyrights, trademarks, brands, registered design, trade secrets and processes whose ownership is granted to the company by law. They represent the tools and enablers that allow a company to gain a protected competitive advantage. Visualising value creation Measurement in a business enterprise determines action since it acts as a motivator of behavior (Drucker, 1959). Ridgway (1956 p. 247) writes that “even where performance measures are instituted purely for purposes of information, they are probably interpreted as definitions of the important aspects of that job or activity and hence have important implications for the motivation of behavior”. However, if organizational performance is measured using a set of measures and no indication of priority is given, individuals are forced to rely on their own judgment as to what is the most important value driver. To avoid dysfunctional consequences of performance measurement (Ridgway, 1956), Kaplan and Norton (2000) introduced strategy maps as tools to chart how intangible assets are converted into tangible outcomes. The authors maintain that strategy maps “give employees a clear line of sight into how their jobs are linked to the overall objective of the organization, enabling them to work in a coordinated, collaborative fashion toward the company’s desired goals” and “provide a visual
representation of a company’s critical objectives and the crucial relationship among them that drives organizational performance” (Kaplan and Norton, 2000, p. 168). Based on the four perspectives of the balanced scorecard (Kaplan and Norton, 1992, 1996a, b) “strategy maps show how an organization will convert its initiatives and resources – including intangible assets such as corporate culture and employee knowledge – into tangible outcomes” (Kaplan and Norton, 2000, p. 168). Figure 1 shows the template for strategy maps with its four perspectives – financial, customer, internal processes, and learning and growth. The strategy map seems a useful tool to chart how intangibles translate into corporate goals. However, many scholars emphasize the interconnectivity of assets, especially between the different intangibles or intellectual assets. Scholars supporting the resources-based view of the firm (Wernerfelt, 1984; Grant, 1991; Petergraf, 1993; Barney et al., 2001; Barney, 2001) consider the firm as a bundle of resources or assets in which the different assets depend on each other to create value. Let’s take the strategy template in Figure 1 as an example to illustrate the interrelationship between assets. The map contains employee competencies and technology, as well as corporate culture as assets and corporate performance drivers in the learning and growth perspective. Each of these assets cannot be seen separated from one another. Employee competencies, for instance, depend on the technology available in the organization. The latest technology is worth little without the right knowledge and competencies of how to operate it. In turn, all the latest understanding and knowledge of how to operate technology is worthless if employees do not have access to the technology. Following the same logic, corporate culture influences employee competencies and vice versa. Roos and Roos (1997, p. 419) support this view and write that a “balance sheet
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Figure 1. Strategy map
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approach to intellectual capital is inherently a ‘snapshot in time’ of the intellectual capital situation and does not provide information on the transformation from one intellectual capital category into another”. Baruch Lev (2001) notes that “intangibles are frequently embedded in physical assets (for example, the technology and knowledge contained in an airplane) and in labor (the tacit knowledge of employees), leading to considerable interactions between tangible and intangible assets in the creation of value”, he continues “when such interactions are intense, the valuation of intangibles on a stand-alone basis becomes impossible” (Lev, 2001, p. 7). In summary, this means that the contribution of one asset, lets say technology, can rarely be expressed independently from other assets, such as skills, expertise, or corporate culture. We believe that efficient management of organizational assets is impossible without understanding the interrelationships and interdependencies of such assets. We therefore suggest the mapping of direct dependencies (as done in strategy maps) as well as indirect dependencies in what we call value creation maps. Below we will outline how to develop a value creation map.
The value creation map – direct and indirect relationships The first step in designing a value creation map follows the same principles as this of designing a strategy map. The design starts from the top, from the organizational objectives, mission, and vision, in other words – why the organization exists. Differing slightly from the balanced scorecard approach, it is suggested to adopt a wider stakeholder approach when defining the organizational objectives (Neely et al., 2002). Working down, the assets that represent the key value drivers are identified. To select its key value driver organizations can use a “matrix of direct dependences”. In such a matrix the organizational assets are listed in the rows, classified according to the above-mentioned taxonomy. The performance dimensions, i.e. strategic objectives, are listed in the columns. It is therefore possible to weigh the relative importance of each different asset for the achievement of each performance dimension. The above weighting identifies the importance of the assets in an isolated and static fashion, similarly to the strategy map view. However, as indicated by various scholars, it is often the dynamic interaction of various assets that creates value. This next step, therefore, maps out how the selected key assets will help the organization to achieve its performance. In this step the interactions between the different assets as well as their overall links to performance will be visualized. A “matrix of the indirect dependences” is created in which both the rows and columns contain the identified key assets. It is possible to create a matrix for each overall performance objective. The cells of the matrix contain a judgment, expressing the level of importance, e.g. moderate importance or strong importance (the size of arrows of map shows the two levels of importance). Using the data from both the matrix of direct and indirect dependencies it is now possible to create the value creation map for each performance dimension. Figure 2 illustrates a simplified example of such a map for the organization’s objective of creating customer satisfaction. It visualizes the value drivers and how they might interact to deliver value, in this case customer satisfaction. Below we will illustrate a case study of how the value creation map is applied in practice.
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Figure 2. The value creation map
Case study – the value creation map at Calia In the following we present the findings from a longitudinal case study of how the value creation map was applied in the new product development (NPD) department of a world-leading furniture manufacturing firm. The main aim of this case study is to demonstrate how the theoretical framework of a value creation map can support management decision making in practice. The reason for selecting the NPD process is based on Itami’s (1987) observation that those in charge of product development combine different assets – especially different aspects of knowledge in order to develop new products. “Information flow is everywhere in the development stage” (Itami, 1987, p. 18). Calia Salotti designs, produces, and sells residential upholstered furniture. It is a large furniture manufacturer with the leading market shares in North America and Europe. It has 600 employees and produces about 250 different models each year. In the year 2000 the company produced a turnover of US$75 million. About 90 per cent of its production is designed for the export market in Europe and the USA. NPD is a core process with strategic importance at Calia Salotti. Product features are predominately determined by customer needs and the design involves highly stylistic content with a limited life cycle. This explains the need for continuous product innovation. The production relies on quality based on the craftsmanship of highly skilled workers; this gives Calia a competitive advantage as it makes it difficult for other firms to imitate. The NPD in Calia is characterized by non-formalized processes that are based on know-how and knowledge with a tacit dimension, creative intuition and craftsmanship of some key individuals operating in different phases of the process. The process of creating and applying the value creation map was highly iterative and involved a series of semi-structured interviews as well as feedback sessions in groups with managers and team leaders involved in the NPD process. In the first step to design the value creation map, the management selected the main performance dimensions it wanted to improve. In Calia’s case, conformity of the prototype production with the product design was selected as a key dimension that needed improvement. Product design includes the new product concept and the design specifications. The product concept consists of designing a 1:10 scale model in various angles. The design specifications include information that identifies the model as well as the technical and non-technical characteristics required to develop the model.
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Frequently the final prototype produced varies from the initial product design. The inconsistency of the prototype production with the product design causes a trial and error approach that increases the iterations between design and prototype production, and therefore increases time-to-market. The main performance indicators in the NPD process are time to prototype a new model and the number of iterations between design and production. The overall objective was to improve both indicators in order to shorten time-to-market. Once the strategic objective was identified managers selected the key value driver, using the “matrix of the direct dependences”. Each manager and team leader completed a list of the factors that would contribute to the improvement of the conformity of the prototype with the product design. This list was created in semi-structured interviews that were based on the above taxonomy of assets but translated into their own language. The change in language was achieved through various pilot interviews to identify relevant assets in each category but using terminology and more language that was less abstract and more context appropriate. Individuals selected what they believed were the key drivers of the performance dimension in question. In a group feedback session facilitated by a senior researcher the answers were consolidated and the following assets were selected as key drivers of their performance: . technical expertise of the designers; . problem solving capacity; . software for design; . working practices; and . manuals with codified procedures. The next step was the identification of indirect dependences. Calia’s matix of indirect dependencies is based on structured interviews with individual managers and team leaders in which the matrix of indirect dependencies was completed. The results of all interviews were then combined and agreed on in a feedback group session. The result is presented in Table I. By combining, both direct and indirect dependencies, it is now possible to create a value creation map. The map was created by the researchers and sent to all managers and team leaders for their feedback. After some final minor Improvement of conformity of the prototype with the product design
Table I. Calia’s matrix of the indirect dependences
Technical expertise of designers Problem solving capacity Software for design Working practices Manuals with codified procedures
Software for Working design practices
Manuals with codified procedures
Technical expertise of the designers
Problem solving capacity
– – – B
A – – A
– – – –
– A A –
A – – –
B
A
–
A
–
Notes: A Moderate importance; B strong importance
modifications the value creation map was agreed on to reflect the organizational reality. The final map is depicted in Figure 3. Once the value creation map is drawn and consent is achieved, it can be used for communication and decision making. On the basis of the value creation map the management in Calia identified that attention needed to be focused on the working practices and the manuals with codified procedures. The following problems were identified and needed to be addressed: . know-how gap between the person building the prototype and the designers; . low level of technical expertise among the designers; . absence of codified rules for design and prototyping activities; . highly tacit working practice; . poor integration between design and prototyping in terms of transfer of knowledge and knowledge sharing; and . instructions by the design team for the prototype builders lack necessary technical specifications and are often quite ambiguous.
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Working practices were improved by increased team working involving both designer and prototype builders. Before the product design is passed on to prototype builders, designer and prototype builders discuss the product design and identify possible problems concerning the production of the prototype. On the basis of this discussion designers can change the product design or include necessary technical specifications of the product design much earlier in the process to avoid increasing iterations between the two teams. In addition new design software was purchased and introduced to increase and improve the specifications in the product design. The software allows producing drawings in a 1:1 scale, which forces designers to specify technical details and dimensions of the product. The inter-functional team work facilitates knowledge sharing and contributes to improving the level of technical understanding and
Figure 3. Calia’s value creation map
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planning knowledge among designers and design knowledge among prototype builders. To improve the level of codification of working practices a design manual has been produced. The aim of the manual was to externalize the knowledge, since a lot of the working practices are highly tacit in nature and rooted in the actions of individuals (Nonaka and Takeuchi, 1995). The externalization was conducted by a team of external analysts who, first of all, watched the expert designers and prototype builders and described their operational abilities. Second, they discussed their observations and descriptions with the subjects (designers and prototype builders) which resulted in correction and enrichment of the documents. The tools used in this codification process included written documents, statements in natural language, cause-effect diagrams, as well as photographs and video sequences. Today the manual is the codified cognitive property of the firm, outlining both the design and prototype production activity. It is used by designers and prototype builders in order to standardize working practices, improve problem solving capacity, and to facilitate easier access to technical knowledge about design specifications for designers. Once these initiatives were implemented it was possible to measure the impact on the NPD performance. Both performance indicators, time to prototype a new model and the number of iterations between design and production, were significantly improved[1]. This, in turn, positively impacted time-to-market, one of the most crucial performance indicators for Calia.
Conclusion In this article we have outlined the literature highlighting the importance of visual representations of strategic intent in order to understand how organizational resources are used to create value. In order to create common understanding of organizational value drivers we provide a taxonomy of organizational assets, which is based on an extensive review of the existing literature. Grounded in the resource-based view of the firm (Wernerfelt, 1984), which argues that organizational resources or assets are bundled together and interdependent, we then highlighted shortcomings in the strategy map approach (Kaplan and Norton, 2000, 2003). We then introduced the value creation map that utilizes both direct and indirect dependencies to map value creation. It is suggested that this approach complements the strategy map approach by extending its view of value creation from direct to both direct and indirect dependencies. Subsequently, we presented a case study of how the value creation map was applied to understand the new product development process in a leading furniture manufacturing firm. The application of the value creation map allowed managers to focus their attention on the critical resources and their contribution to performance. This research supports the thesis of earlier work claiming that organizational resources, and in particular its knowledge-based assets, are dynamic in nature (Roos and Roos, 1997) and are dependent on each other to create value (Lev, 2001; Dierickx and Cool, 1989). We therefore challenge the usefulness of strategy maps based on the balanced scorecard as a means to fully understand how intangible assets create organizational value. We call for further research to investigate the interrelationships between the different organizational assets and further investigation into approaches and tools to better understand and visualize organizational value creation.
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Managerial knowledge to organisational capability: new e-commerce businesses Anjali Bakhru Open University Business School, Milton Keynes, UK Keywords Knowledge management, Electronic commerce, Intellectual capital, Business formation Abstract The knowledge and skills of individuals are widely considered to represent an important component of a firm’s intellectual capital. The value of individuals’ knowledge is also recognised from a capability-based perspective. While routines and capabilities are considered to act as the interface for the knowledge of individuals, an important and related issue is to examine how and to what extent individuals’ knowledge acts as the source of knowledge for the creation of firm-based routines and capabilities. Four firms across two online sectors, online broking and ISPs, are selected for the empirical case study research. The findings highlight the importance of the role of prior organisational experience in the development of new routines and capabilities. It is shown that variations in the role of prior organisational experience across firms and sectors are better understood in respect of the architectural and component knowledge of which managerial knowledge consists.
Introduction The knowledge and skills of individuals are widely considered to represent valuable, intangible firm assets and, in so doing, represent an important component of a firm’s intellectual capital. The value of individual skills and knowledge is also recognised from a capability-based perspective, where it is argued that underlying a firm’s routines and capabilities is the knowledge of individuals (Grant, 1996). The relationship between an organisation’s knowledge assets and its performance is central to both an intellectual capital as well as a capability-based perspective (Carlucci et al., forthcoming). However, while a key focus of an intellectual capital approach is the valuation of knowledge assets and the intellectual capital of which they are a part, the focus of this paper is on understanding the process of utilising and integrating knowledge assets within the organisation. More specifically, while routines and capabilities are considered to act as the interface for the knowledge of individuals, an important and related issue is to examine how and to what extent managerial knowledge comes to act as the source of knowledge for the creation of firm-based routines and capabilities. New markets provide an interesting opportunity to assess the challenge of developing new routines and capabilities and further afford the opportunity to assess the capability development process across different types of firms, where new market entry is essentially the challenge of diversification for established companies and that of entrepreneurship for new companies. Journal of Intellectual Capital Vol. 5 No. 2, 2004 pp. 326-336 q Emerald Group Publishing Limited 1469-1930 DOI 10.1108/14691930410533731
Capability-based determinants of new market success Organisational capabilities are increasingly considered to be an enduring source of competitive advantage from a resource-based perspective given the causal ambiguity
surrounding their development and the path dependent nature of learning (Nelson and Winter, 1974). If organisational capabilities are a key determinant of competitive advantage, then the critical challenge facing firms entering new markets is their ability to establish the capabilities needed to compete in these markets (Bakhru, 2003). Given the importance of capability development for firm success in new markets, competition in new markets may be viewed as a race to build capabilities. However, it is not an equal race. All firms, both new and old, bring with them prior knowledge, some of which may or may not be rendered less valuable by changes in customer tastes, industry structure and technology (Barney, 1995). Our starting point is to examine what we know about the origins and development of capabilities in new markets. The importance of existing capabilities for new market entry is only more recently being explored in research on firm diversification (Chandler, 1992; Markides and Williamson, 1994; Grant, 1996; Klepper and Simons, 2000). Recognition of the role of capabilities in firm diversification stems, in large part, from attempts to re-examine the notion of related and unrelated diversification. The link between firm performance and type of diversification strategy is not a clear one, where the superior advantage of related diversification, as advocated by Rumelt (1974), is not consistently borne out in practice (Markides and Williamson, 1994). While definitions of relatedness have tended to focus on industry or market similarity and, hence, the degree of operational relatedness, it is argued that definitions of relatedness are better understood at the level of firm-based competences (Grant, 1988, 1996; Markides and Williamson, 1994). The importance of capabilities in firm diversification is borne out by Chandler (1992), where he states that, before the 1960s, industrial enterprises in the USA and Europe rarely moved into markets where their learned capabilities did not give them a distinct competitive advantage. Similarly, in their study of the US television receiver industry, Klepper and Simons (2000) show the importance of prior related experience, where it was found that those radio producers with the most relevant experience entered the television industry. On average, these firms entered earlier, survived longer and had larger market shares than non-radio producers. While the research on diversification focuses on established firms, we know that new markets are characterised by the presence of both new and old firms. Established firms have the benefit of existing capabilities. This assumes, however, that existing capabilities retain value in new markets and, further, that firms are able to transfer the learning embodied within existing capabilities to a new setting. New firms, in contrast, have to rely on the knowledge of individuals and, hence, the ability of the latter to create the capabilities required. Significantly, there are likely to be circumstances where both new and old firms are faced with the challenge of creating new capabilities. To understand the nature of this challenge and, more specifically, the role of individuals’ knowledge in the capability development process, there is a need to understand the origins of capabilities. Origins of capabilities Organisational routines are considered to create the link between knowledge at the level of the individual and capabilities at the level of the organisation (Grant, 1996). However, the means by which firms create and develop organisational capabilities are the subject of considerable speculation and ad hoc theorising, but little systematic research. Prior research identifies the role of management in the capability
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development process and the importance of the prior work experience of individuals in relation to the creation of new ventures. Linking knowledge to capabilities The assumption here is that capabilities are considered to underlie the transformation of firm inputs (resources) into outputs (products or services), where Grant (1991) uses the term “organisational capabilities” to refer to a firm’s capacity for undertaking a particular productive activity. The importance of knowledge in the capability development process is with reference to Grant’s (1996) assertion that capabilities are hierarchically organised. Higher order capabilities tend to be cross-functional in design and consist of more than one lower order or functional capability, while functional capabilities can be considered to comprise the tasks specific to a functional area. At the base of this hierarchy lies the specialised knowledge of individuals. The value of individuals’ knowledge can only be realised if the benefits of specialisation can be overcome, where the organisational challenge can be considered to be, to efficiently integrate the knowledge of individuals at each level of the capability hierarchy. Routines act as this co-ordinating mechanism, where they embody not only that knowledge which is explicit but also that which is tacit. Hence, the origin of routines and capabilities is the knowledge that individuals possess. Implicit in this approach is that there is no distinction between the processes through which “capabilities” and “dynamic capabilities” are created. While dynamic capabilities can be considered to be a set of specific and identifiable processes such as product development, strategic decision-making and alliancing (Eisenhardt and Martin, 2000), they are elsewhere referred to as higher-order or cross-functional capabilities. As such, it is difficult to reconcile any notion that the process through which dynamic capabilities are created is intrinsically different from that through which other capabilities are developed. In accordance with Zollo and Winter (2002), dynamic capabilities are here considered to be those “routinised” activities directed towards change. Role of managerial knowledge in new firms The importance of the managerial role with respect to the development of capabilities is cited in relation to the selection and evolution of capabilities. Prior research highlights the importance of the top management team’s influence on the evolution of the firm’s capability set (Levinthal, 1995; Kazanjian and Rao, 1999), where managerial input in the selection and development of capabilities can differ greatly across firms (Amit and Schoemaker, 1993). However, it is with reference to research on new ventures that there is an attempt to link the knowledge assets of founders with the creation of new routines and capabilities. The starting-point is the assumption that even new firms have repositories of knowledge (Kogut and Zander, 1992), where the knowledge critical to the development of new routines and capabilities must ultimately be derived from the individuals within the new venture. It has been recognised that people who form new firms themselves have histories (Helfat and Lieberman, 2001), where Grant and Romanelli (2001) argue that the fundamental building block of capabilities in new organisations is the prior work experience of individuals through working in established organisations. This is a theme reflected within the entrepreneurship literature, where the suggestion is that the
prior work experience of founders is the source of the knowledge assets critical for the creation of new routines and capabilities in the new venture. Entrepreneurship has been variously defined, focusing either on the act of new venture creation or the act of new market entry (Lumpkin and Dess, 1996). Irrespective of definition, the role of entrepreneurs is widely considered to comprise two main elements: business opportunity recognition; and venture creation. It is the knowledge that founder managers bring with them that permits them to both identify and establish new ventures. Research focuses on the fact that the source of this knowledge is the prior work experience of the founders themselves. Business opportunities are likely to have been identified and formalised based on an individual’s previous work experience (Shane, 2000). The prior experience of founders is cited in respect of the benefits of prior new venture experience (Sykes, 1986; Stuart and Abetti, 1990), the importance of prior managerial experience (McEnrue, 1988), the importance of venture capitalists’ experience (Ehrlich et al., 1994), and where the lower rate of failure of start-ups is associated with more experienced management (Lussier, 1995). More specifically, recent research links the prior managerial experience of founders to a capability-based perspective. Alvarez and Busenitz (2001) state that key entrepreneurial resources include not only the recognition of business opportunities but also the process of combining and organising resources. Hence, a key component of the knowledge gained through prior work experience, i.e. managerial knowledge, is a manager’s experience of creating and developing routines that is relevant to the challenge of new venture creation.
Role of existing routines within established firms Given that new markets tend to be characterised by the entry of both new and established firms, an important and related issue is the origins of capabilities in established firms. We know that the innovation through which new markets emerge can be competence-enhancing or competence-destroying (Anderson and Tushman, 1991). Where existing capabilities retain value, it is likely that firms are able to transfer the organisational learning embodied in existing routines and capabilities that are relevant to the new market. However, where existing capabilities are not those required to meet the requirements for success in new markets, then firms are faced with the challenge of adapting existing routines or creating new routines. In terms of assessing the capability-based challenge of new market entry, it is important to categorise new markets in terms of how innovation impacts existing capabilities. An analogy is made to Teece’s (2000) work on systemic and autonomous innovation, where it is argued that autonomous innovation can be considered to occur where entry into a new market does not affect existing routines significantly, either with respect to the knowledge underlying component routines or to the architecture of routines (Henderson and Cockburn, 1994) and vice versa for systemic innovation. Established firms relative to new firms are likely to have greater difficulty with adaptation in new markets subject to systemic innovation. We also know from Leonard-Barton (1992) that “core capabilities” come to act as “core rigidities”, where capability development becomes constrained by the technical and managerial systems over time. Implicit in this view is the role of existing routines, acting as a constraint or otherwise, in the adaptation or creation of new routines in established firms.
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Methodology The aim of the research is to examine the origins of capabilities within firms and, more specifically, the role of individuals’ knowledge in this process, seeking to answer the question: “What is the role of individuals’ knowledge in the creation of new organisational routines?”. Since there is limited theory on where organisational capabilities come from and the processes through which they are created, an inductive case study approach to the research is adopted. The starting-point for this paper is that the creation of new markets affords a good opportunity to assess the process of capability development across different types of firms, where new online markets are selected as the site for the empirical research. New markets are especially useful for studying the development of capabilities since new business ventures require the deliberate creation of new organisational capabilities (Kazanjian and Rao, 1999). The sample is an intentional one selected for theoretical reasons to account for different types of firms and new markets representative of different types of innovation. Two UK-based, business-to-consumer sectors are chosen: online broking and Internet service providers (ISPs). The sectors are chosen on the basis that the innovation implicit in the creation of these new online markets provides examples of autonomous and systemic innovation respectively. The assumption is that the innovation implicit in the creation of the ISP sector is an example of systemic innovation, where an entirely new configuration of resources and capabilities is required for firms entering this sector. In contrast, the assumption is that online broking is representative of a new market which has emerged as a result of autonomous innovation. While a new business model has been created with the development of online broking, it is essentially a channel innovation where existing capabilities along with their configuration are likely to retain value. Four companies are selected for the case study research, where the aim is to select one new and one established firm from each of the two sectors, online broking and ISPs. The definition of “new” and “established firms” relates to whether the firm existed prior to new market entry. The four firms are: NatWest Stockbrokers (online broking), SELFTrade (online broking), Freeserve (ISP) and Aviators Network (ISP). However, Freeserve is not a pure example of an established firm given that it represents the corporate venture subsidiary of Dixons that was founded to diversify into the ISP sector. The unit of analysis is the capability development process within each of the case study firms, where the prior organisational experience of respondents acts as the measure of individuals’ knowledge. Data was collected between April and June 2002 via semi-structured interviews of between one and two hours’ duration with senior managers across key functional areas. Respondents were selected on the basis of their role in overseeing the development of core functional areas both prior to and since the start of online trading. Respondents were given the opportunity to identify whether and to what extent prior organisational experience was considered relevant to the development of their online operations. Findings The case findings support the role of individuals’ knowledge in the capability development process and, more specifically, the role of prior organisational experience as the source of the knowledge necessary for the development of routines and
capabilities. Importantly, the findings suggest that the role of prior organisational experience varies within the managerial hierarchy and the relevance of prior organisational experience is confined to senior level employees. In all the cases studied, there was a distinction between the role of the senior management team and the next layer of senior managers. The importance of the prior organisational experience of the top or senior management team relates to their ability to develop the overall blueprint for the creation of capabilities within online operations or “capability blueprint”: (1) Construct. Individuals’ knowledge. (2) Measure. Prior organisational experience. (3) Interpretation. Prior organisational experience relates to ability of senior management team to create the overall “blueprint” for the creation of capabilities within online operations. (4) Case examples: . NWS: blueprint for online service developed by committee, where heads of key functional areas were represented; . SELF Trade: senior management team hired to set up firm and recruit other senior hires; . Freeserve: CEO as key architect of organisational blueprint; and . Aviators: Monu Ogbe, owner and founder, created overall organisational blueprint. Capabilities consist of one or more sets of interacting routines, where organisational capabilities are considered here to refer to the core functional and cross-functional activities of the firm. As such, the “capability blueprint” refers here to the overall structure or architecture of the firm’s capability set, including consideration of the main tasks or processes of which these core functions comprise. With respect to SELF Trade, the prior organisational experience of the founding management team is considered by respondents to be relevant in respect of creating the overall blueprint of the firm in the first few months prior to launch, both with regard to developing the organisational structure and to assessing the functional, operational and technological needs of the new venture. As Martin Braund (Head of IT/Operations) states: So I spent most of my initial time looking at IT vendors, recruiting staff, selecting partners for things like banking . . . which took up most of my time during the first couple of months, I guess.
The role of the senior management team in terms of determining the capability blueprint is reinforced in the case of Aviators. Owner and founder, Monu Ogbe, believes that development of the firm has been hindered by the inadequate development to-date of the firm’s marketing and sales capability, although he acknowledges his direct influence on this: I would be delighted not to have a single salesman, not to do a single bit of traditional selling, but for the Web site or for it all to happen organically and virally to leverage the (technical) phenomenon.
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His initial focus was on developing the technological capabilities at the expense of developing the firm’s marketing capability, where his own prior organisational experience is confined to that of a technical specialist without any general management responsibilities. In contrast, while the importance of prior organisational experience is shown in respect of other senior hires, the next layer of management tends to be more directly responsible for the creation of organisational routines: . construct: individuals’ knowledge; . measure: prior organisational experience; and . interpretation: prior organisational experience of next layer of managers relates to their ability to create operational and technical routines within functional areas. The relevance of the prior organisational experience of other senior level managers relates more to their “technical” knowledge considered vital to creating specific functional and operational routines. With respect to SELF Trade, there was a need to hire individuals with a clear idea of how to set up each of the functional areas without resorting to trial-and-error learning, especially given temporal constraints and the fact that broking is a regulated industry with common standards. Martin Braund explains the reason for hiring experienced individuals: You need the experience as well, because we couldn’t afford to be training people, because you know there were a million and one things to do. So you needed people who were confident in their own subject matter to come in, to set departments up, to know how functions were going to work, to learn the new systems they had to deal with, you know, to understand all the external relationships, you know, CREST, banking, the Stock Exchange . . . So those first couple of months were about getting the right people in.
Given the fact that the ISP sector is a new one that could not have existed prior to the development of the Internet, the initial emphasis was on hiring individuals with entrepreneurial and/or generalist managerial experience given the uncertainty of the new sector and specific operational needs as well as the lack of related market experience. Within Freeserve, there has been increasing emphasis on developing specialisms within each of the core functional areas as the company matures and its business model becomes more defined. This has been accompanied by the recruitment of individuals with prior experience in related media and/or customer service sectors. The creation of the ISP service by Aviators relied heavily on the technical skills of its original founder, Monu Ogbe and his associate Tom Dawes-Gamble, both of whom were experienced software developers and were able to create the technological capabilities necessary to build the ISP service. Other employees were essentially hired for their potential, given that they were new graduates with little prior work experience or specialist technical skills, where they were expected to learn by doing. While the online broking sector exhibits the importance of hiring managers with industry-specific knowledge, this was considered desirable though not necessarily possible in the ISP sector. As Deborah Sherry of Freeserve explains: One of the things that’s an issue when you go into the market is trying to find people and you want people with experience and nobody’s had experience with this.
However, as Caroline Taylor, Head of Portal Strategy, states, much prior business experience can be considered important and relevant to devising business processes within Freeserve, irrespective of specific organisational background: I’ve worked for a number of years now and I think there are lots of things I could bring to the Freeserve party, you know, in terms of experience . . . there are a finite number of ways of doing something . . . You bring the experience of how to do things and how not to do things and also you are applying it to a new business environment.
While the importance of prior organisational experience for new firms is supported, it seems that it is more important in relation to senior rather than more junior level recruits. As Peter Boucher, Head of Communications at SELF Trade, states, the firm has a tacit policy of not hiring less senior hires with “blue chip” company experience in the belief that much prior organisational experience is context-specific and therefore not widely applicable: We’ve tried not to go out and get everyone blue chip: a) it costs a fortune but b) sometimes when you rent, when you get someone from Unilever, for example, what you think you are hiring you don’t actually get because a lot of them is actually left behind at Unilever.
The importance of prior organisational experience of the senior management team is secondary to the importance of existing organisational routines in the case of established firm, NWS. The development of online broking within NWS was viewed internally as a channel innovation that was managed as an IT development project. The original blueprint for the new online service was developed by a committee, where the heads of key functional areas were represented. It seems, however, that the aim of the senior management team was to build an online broking system that could be integrated with the existing structure of organisational routines, where existing routines acted as the guiding template for the new development. As Richard Hunter, Head of Dealing Services, states, the aim was to integrate the system into existing operations so that there was no change from the client perspective: But from a client perspective, after they have pressed the button, they won’t notice any difference, as if they had placed the deal over the phone. There will be no difference at all.
With the exception of the development of a client relations team and an Internet support desk that would operate on a 24 hour basis, the project required few additional organisational routines. Similarly, in the case of SELF Trade, the group’s front end Web interface acted as the template for the UK venture’s front end Web interface around which new routines would be created. Discussion The importance of a capability-based perspective is that it enables us to explain how knowledge at the level of individuals is transformed into knowledge that can be productively used at the organisational level. The primary contribution of this research is that it empirically tests and provides support for the role of individuals’ knowledge in the creation of routines and capabilities in new ventures. The findings further serve to develop theory relating to the role and type of knowledge in the creation of new routines and capabilities. In all the firms studied, the value of prior organisational experience in the capability development process is demonstrated, although it is confined to those senior managers
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directly involved in the capability development process. Prior research on the role of managers in the selection of capabilities is supported, where the top layer of senior managers are responsible for creating the overall architecture or structure of capabilities or “capability blueprint”. However, in a departure from existing theory, the research distinguishes the role of prior organisational experience within the managerial hierarchy. The research distinguishes between the role of the prior organisational experience of the top layer of senior managers from the next layer of senior managers, where the role of the latter is in the creation and development of the specific operational and technical routines required. The importance of this finding is that it is possible to characterise further the managerial knowledge relevant to the capability development process. While we use the term “managerial knowledge” generally, to refer to the knowledge assets of individual managers gained through prior organisational experience, this research serves to define two specific types of managerial knowledge relevant to the challenge of developing capabilities. The nature of the managerial task is to develop the requisite organisational routines in addition to the structure of which they are part. Hence, the nature of the managerial task is to develop the component knowledge underlying new routines as well to develop the architectural knowledge critical for the integration of one or more interacting sets of routines. The managerial knowledge of the top layer of senior managers that is relevant to the capability development process is the architectural knowledge they bring with them. In contrast, the managerial knowledge of the next layer of senior managers that is relevant to the capability development process is the component knowledge that can be applied to the creation and development of functional organisational routines. If we consider managerial knowledge as consisting of both architectural and component knowledge, it can better explain the findings of the research in relation to the role of prior organisational experience across different types of firms, and in new markets created out of different types of innovation. In the case of established firm, NWS, the development of new routines was primarily informed by the firm’s existing routines and their existing architecture. The online broking service was developed according to the existing project methodology in relation to developing the technological capabilities required, where the aim was on re-usability of existing systems and integrating new routines with existing transactional and operational routines associated with the broking service. The role of managerial knowledge was limited to the extent that senior management were involved in the overall design of the capability blueprint for the online service. While the managerial challenge in respect of capability development is in respect of developing the requisite component knowledge and architectural knowledge necessary for the creation of functional organisational routines, the cases highlight the initial priority on obtaining the requisite component knowledge in new markets created out of autonomous innovation. In the online broking sector, an example of a new market created out of autonomous innovation, the case of SELFTrade shows the importance of hiring individuals with the component knowledge necessary to ensuring that the new venture was fully operational within a matter of months. However, in the ISP sector, an example of a new market created out of systemic innovation, firms were confronted with the issue that hiring recruits with prior relevant experience was difficult. While the organisational routines initially developed have to be operational, the knowledge
underlying component routines is likely to evolve through a trial-and-error approach to learning. This was not necessarily a drawback given that business models were uncertain at the time of launch and have evolved over time. The ISP sector further illustrates that where innovation is systemic, the value of prior organisational experience is necessarily to the architectural component of managerial knowledge and the ability of individuals to create new routines and capabilities. Finally, while the cases support the role of senior management in the capability development process, this may further relate to the fact that the value of organisational routines is often context-dependent in various ways (Nelson and Winter, 1982; Galunic and Rodan, 1998). In the case of SELFTrade, the evidence suggests that a limitation of prior organisational experience is the context-specific nature through which it is acquired and learnt. It is sometimes difficult to transfer the organisational experience necessary to the development of routines in another organisational setting. SELFTrade focuses on recruiting senior level employees from “blue chip” firms in the belief that they, relative to more junior level employees, are better able to transfer the component and architectural knowledge relevant to the creation of new routines. References Alvarez, S.A. and Busenitz, L.W. (2001), “The entrepreneurship of resource-based theory”, Journal of Management, Vol. 27, pp. 755-75. Amit, R. and Schoemaker, P.J. (1993), “Strategic assets and organisational rent”, Strategic Management Journal, Vol. 14, pp. 33-46. Anderson, P. and Tushman, M. (1991), “Managing through cycles of technological change”, Research Technology Management, Vol. 34 No. 3, pp. 26-33. Bakhru, A. (2003), “Competitive advantage in new markets: the case of online business”, unpublished doctoral thesis, Cass Business School, City University, London. Barney, J. (1995), “Looking inside for competitive advantage”, Academy of Management Executive, Vol. 9 No. 4, pp. 49-61. Carlucci, D., Marr, B. and Schiuma, G. (forthcoming), “The knowledge value chain – how intellectual capital impacts business performance”, Journal of Technology Management. Chandler, A. (1992), “Organizational capabilities and the economic history of the industrial enterprise”, Journal of Economic Perspectives, Vol. 6 No. 3, pp. 79-100. Ehrlich, S.B., De Noble, A.F., Moore, T. and Weaver, R.R. (1994), “After the cash arrives: a comparative study of venture capital and private investor involvement in entrepreneurial firms”, Journal of Business Venturing, Vol. 9 No. 1, pp. 67-82. Eisenhardt, K.M. and Martin, J.A. (2000), “Dynamic capabilities: what are they?”, Strategic Management Journal, Vol. 21, pp. 1105-21. Galunic, D.C. and Rodan, S. (1998), “Resource recombinations in the firm: knowledge structures and the potential for Schumpeterian innovation”, Strategic Management Journal, Vol. 19, pp. 1193-201. Grant, R.M. (1988), “On ‘dominant logic’, relatedness and the link between diversity and performance”, Strategic Management Journal, Vol. 9, pp. 639-42. Grant, R.M. (1991), “The resource-based theory of competitive advantage: implications for strategy formulation”, California Management Review, Spring, pp. 114-35. Grant, R.M. (1996), “Prospering in dynamically-competitive environments: organizational capability as knowledge integration”, Organization Science, Vol. 7 No. 4, pp. 375-87.
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Grant, R.M. and Romanelli, E. (2001), “Capabilities creation in new and established organizations”, working paper, Georgetown University, Washington DC. Helfat, C.E. and Lieberman, M. (2001), “The birth of capabilities: market entry and the importance of pre-history”, paper presented at the Academy of Management Annual Meeting, Washington DC. Henderson, R. and Cockburn, I. (1994), “Measuring competence? Exploring firm effects in pharmaceutical research”, Strategic Management Journal, Vol. 15, pp. 63-84. Kazanjian, R.K. and Rao, H. (1999), “Research note: the creation of capabilities in new ventures – a longitudinal study”, Organization Studies, Vol. 20 No. 1, pp. 125-42. Klepper, S. and Simons, K.L. (2000), “Dominance by birthright: entry of prior radio producers and competitive ramifications in the US television receiver industry”, Strategic Management Journal, Vol. 21 No. 10/11, pp. 997-1016. Kogut, B. and Zander, U. (1992), “Knowledge of the firm, combinative capabilities, and the replication of technology”, Organization Science, Vol. 3, pp. 383-97. Leonard-Barton, D. (1992), “Core capabilities and core rigidities: a paradox in managing new product development”, Strategic Management Journal, Vol. 13, pp. 111-25. Levinthal, D. (1995), “Strategic management and the exploration of diversity”, in Montgomery, C.A. (Ed.), Evolutionary and Resource- Based Approaches to Strategy, Kluwer Academic Publishers, Boston, MA. Lumpkin, G.T. and Dess, G.G. (1996), “Clarifying the entrepreneurial orientation construct and linking it to performance”, Academy of Management Review, Vol. 21 No. 1, pp. 135-72. Lussier, R. (1995), “Startup business advice from business owners to would-be entrepreneurs”, S.A.M. Advanced Management Journal, Vol. 60 No. 1, pp. 10-13. McEnrue, M.P. (1988), “Length of experience and the performance of managers in the establishment phase of their careers”, Academy of Management Journal, Vol. 31 No. 1, pp. 175-85. Markides, C. and Williamson, P.J. (1994), “Related diversification, core competencies and corporate performance”, Strategic Management Journal, Vol. 15 No. 5, pp. 149-65. Nelson, R. and Winter, S. (1974), “Neoclassical vs evolutionary theories of economic growth: critique and prospectus”, The Economic Journal, December, pp. 886-905. Nelson, R. and Winter, S. (1982), An Evolutionary Theory of Economic Change, Harvard University Press, Cambridge, MA. Rumelt, R.P. (1974), Strategy, Structure and Economic Performance, Harvard University Press, Cambridge, MA. Shane, S. (2000), “Prior knowledge and the discovery of entrepreneurial opportunities”, Strategic Management Journal, Vol. 11, pp. 448-69. Stuart, R.W. and Abetti, P.A. (1990), “Impact of entrepreneurial and management experience on early performance”, Journal of Business Venturing, Vol. 5 No. 3, pp. 151-62. Sykes, H.B. (1986), “The anatomy of a corporate venturing program: factors influencing success”, Journal of Business Venturing, Vol. 1 No. 3, pp. 75-93. Teece, D. (2000), Managing Intellectual Capital, Oxford University Press, Oxford. Zollo, M. and Winter, S.G. (2002), “Deliberate learning and the evolution of dynamic capabilities”, Organization Science, Vol. 13 No. 3, pp. 339-51.
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COMMENTARY
Moving through the crossroads
Moving through the crossroads
Jay Chatzkel Progressive Practices, Anthem, Arizona, USA
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Keywords Intellectual capital, Knowledge management, Innovation Abstract The field of intellectual capital is at a crossroads. To move through the crossroads and to the next stage both practitioners and academics must substantially demonstrate the relevance of intellectual capital as a working discipline useful to achieve strategic goals and to improve levels of performance. While the field has generated a growing body of knowledge and practice over the last two decades, there is a need for both a great leap in how value can be generated and captured using an intellectual capital perspective, as well as acknowledging that there are multiple ways of knowing and different models for intellectual capital exchange. Much of this new development will come from an expanded, continuing dialogue between practitioners and academics.
The conditions The field of intellectual capital seems to be transitioning to its next stage. To move through the crossroads to this next stage we must substantially demonstrate the relevance of intellectual capital as a working discipline that is useful to organizations to use to gauge and generate significant value and to effectively navigate to achieve strategic goals. Otherwise, the notion of intellectual capital and all its stands for will be seen as merely one more set of very interesting ideas that is continuingly elusive to grasp and use. Intellectual capital is a new field, initiated less than two decades ago. It was pioneered by practitioners who perceived that the value equation for organizations was radically changing. Academics becoming increasingly involved as they sought to ascertain how intangibles were fundamental to an increasingly higher proportion of the value in organizations, as well as being the basis for generating that value. Over the last decade the probing work of both academics and practitioners has created a basic platform for the field and built up a rich and growing body of experience and guiding theory. At the same time there is a strong and continuing need to ensure that the field is credibly grounded in core, applicable concepts and navigated with the aid of rigorously validated, articulated frameworks. As with many other vital fields of endeavor, the more that we have discovered has revealed that there are many more discoveries to be made. Our efforts going into the future must reflect both the richness and growing complexity. With this phase of intellectual capital maturing, we are coming to understand there is need to expand the dialogue between academics and practitioners. This is the conversation that is necessary to work through the sets of important issues that are surfacing to gain a fuller appreciation of how value is created and managed for outcomes. As practitioners go beyond their original efforts to resolute specific organizational needs, such as intellectual property portfolio management or establishing rudimentary sets of measures, academics need to take on the role of providing more comprehensive clarification of concepts, increasingly rigorous standards for research, reliable structures to determine how intellectual capital is
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generated and operates, and offer models that map appropriate relationships to other disciplines.
Many ways of knowing and the need for synthesis Transitioning to the next stage of intellectual capital involves more than being better at sorting out and becoming more efficient at what we already know. Moving through the crossroads to the next stage of the field also involves major qualitative and transformational changes that are just beginning to be articulated. These incipient understandings present a view of the characteristics of the field as more of a living dynamic experiment than one that is best subjected to a rational, deductive examination. We must go beyond an either/or situation. In their own ways, both of these overall perspectives are equally compelling and both need to be pursued. In a fundamental way, we need to grasp that there may be a number of ways of knowing what the field is, each with its own validity and each with its own limitations. In the end, we will need to appreciate the value of each of these perspectives and seek greater synthesis. In that way we can avoid making the mistake of only asking the questions that we know we can get the answers to, with the result that our answers will not yield an adequate response for our needs. As one of the PMA IC Symposium attendees, Leif Edvinsson, said, “The array of issues to be explored presents far more opportunities than are normally under discussion.” He believes that while intellectual capital at a crossroad might be one perspective, “another perspective might be seeing intellectual capital as evolving in several different levels, all highlighting that intellectual capital is about different and more intelligent perspectives than the pure ‘business administration’ perspective”. He pointed out that: . On the individual level it is evident that insights from neurology are coming into the picture on how to nourish not only our so called competence but also exercise your brain potential. . On the enterprise level it is more and more evident that the intellectual capital multiplier effect is emerging when the individual talent is leveraged by the structural capital. If this is done well it has an 80 percent correlation to the value adding. So, the most important leadership perspective should be on this multiplier effect, beyond traditional knowledge management. . On the society level it is also evident that we are now moving into the urban design of knowledge cities with a nourishing and healthy impact and attraction on the knowledge workers to settle there. Edvinsson noted: The academic agenda is to some degree still focused on definitions and the more scientific qualified measuring, while the surrounding context of intellectual capital is moving on with an even increased speed. Therefore, it is becoming of strategic importance for the academic community to work both with the quality dimensions of intellectual capital research as well as with support of rapid prototyping, such as how to measure intellectual capital in new clusters, such as the research and development community or intellectual capital of cities as well as intellectual capital of public sector.
Another attendee, Richard Hall, felt that for the field to be viable it must meet the compelling and future challenge of incorporating the dimension of innovation in the management of intellectual capital. Hall stated that:
Moving through the crossroads
Innovation is the key to future success. While the processes to facilitate incremental innovation, that is, continuous improvement, are well understood, the means by which we can initiate, direct and implement radical innovation, i.e. step change improvement, are less well understood. The new knowledge that is associated with radical innovation is likely to be substitutive, as opposed to additive. In other words, the application of the new knowledge requires the old knowledge base to be unlearned and replaced with the new knowledge, e.g. replacing analogue with digital technology.
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According to Hall, there are then two challenges in managing intellectual capital: the challenge of initiating relevant radical innovation; and the challenge of applying the new substantive knowledge that will be required to implement the radical innovation. An additional view was raised by Ahmed Bounfour, who argued that while the transaction perspective is the dominant perspective of capitalism and has made efficiency requirements the main driver for appraising individual and corporate actions, provision should also be made for a “community perspective” that is much more characterized by networking and knowledge sharing. The transaction perspective is more product-oriented and the market value aspects of intangible resources are emphasized. The community perspective is seen to operate more on a “gift and counter gift” model of a knowledge economy where capabilities development relationships predominate. In reality, both of these perspectives will exist simultaneously and we will need to allow for at least two sets of criteria to gain an adequate understanding of reporting on intangibles that account for valuations in each. Getting there These are some of the provocative range of perspectives that need to be taken into account as we move across through our threshold and onto the next stage of intellectual capital. To move through our crossroads, academics and practitioners need to seek out all relevant perspectives and take them into account. This demands both precision and imagination, reflecting on a full range of experience, as well as sufficient rigor to ensure the ground we are creating is sound enough to satisfactorily base our expanded level of judgments and actions.
