Building Organizational Memories: Will You Know What You Knew? (Premier Reference Source)

Building Organizational Memories:

Will You Know What You Knew? John P. Girard Minot State University, USA

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Published in the United States of America by Information Science Reference (an imprint of IGI Global) 701 E. Chocolate Avenue, Suite 200 Hershey PA 17033 Tel: 717-533-8845 Fax: 717-533-8661 E-mail: [email protected] Web site: http://www.igi-global.com and in the United Kingdom by Information Science Reference (an imprint of IGI Global) 3 Henrietta Street Covent Garden London WC2E 8LU Tel: 44 20 7240 0856 Fax: 44 20 7379 0609 Web site: http://www.eurospanbookstore.com Copyright © 2009 by IGI Global. All rights reserved. No part of this publication may be reproduced, stored or distributed in any form or by any means, electronic or mechanical, including photocopying, without written permission from the publisher. Product or company names used in this set are for identi.cation purposes only . Inclusion of the names of the products or companies does not indicate a claim of ownership by IGI Global of the trademark or registered trademark. Library of Congress Cataloging-in-Publication Data Building organizational memories : will you know what you knew? / John P. Girard, editor. p. cm. Includes bibliographical references and index. Summary: “This book provides relevant theoretical frameworks, latest empirical research findings, and practitioners’ best practices in the area of organizational memory”--Provided by publisher. ISBN 978-1-59904-540-5 (hbk.) -- ISBN 978-1-59904-542-9 (ebook) 1. Corporate culture. 2. Organizational learning. 3. Knowledge management. I. Girard, John P., 1961- II. Title. HD58.7.B799 2009 658.4’038--dc22 2008037388 British Cataloguing in Publication Data A Cataloguing in Publication record for this book is available from the British Library. All work contributed to this book set is original material. The views expressed in this book are those of the authors, but not necessarily of the publisher.

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Editorial Advisory Board Raul M. Abril, Universitat Pompeu I Fabra, Spain JoAnn Girard, Sagology, USA Michael Sutton, Westminster College, USA Jerry Westfall, Liberty University, USA

List of Reviewers Raul M. Abril, Universitat Pompeu I Fabra, Spain Alex Bennet, Mountain Quest Institute, USA David Bennet, Mountain Quest Institute, USA Nick Bowersox, TUI University, USA Carla Cabarle, Minot State University, USA Kimiz Dalkir, McGill University, Canada Stefano De Luca, University of Rome Tor Vergata, Italy Prescott C. Ensign, University of Ottawa, Canada John Girard, Minot State University, USA Parissa Haghirian, Sophia University, Japan David Jones, Shibumi Management, Canada Juha Kettunen, Turku University of Applied Sciences, Finland Arnold Kransdorff, Pencorp, UK María de los A. Martín, National University of La Pampa, Argentina Susan McIntyre, Defence R&D, Canada Ralf Müller, Umeå University, Sweden Luis Olsina, National University of La Pampa, Argentina Haris Papoutsakis, Technological Education Institute (TEI) of Crete, Greece Nicholas P. Robinson, McGill University, Canada Suzanne Roff-Wexler, Compass Point Consulting, USA Michael Sutton, Westminster College, USA Jerry Westfall, Liberty University, USA Lori Willoughby, Minot State University, USA

Table of Contents

Foreword . ........................................................................................................................................... xiv Preface................................................................................................................................................. xvii Acknowledgment . ............................................................................................................................ xxvi Section I The Enablers of Organizational Memories Chapter I Organizational Culture and the Management of Organizational Memory.............................................. 1 Peter Stoyko, Canada School of Public Service, Canada Chapter II Downsizing and Building Organizational Memory: A Paradoxical Relationship between “Brain-Drain” and “Brain-Gain”........................................................................................................... 18 Nicholas N. Bowersox, TUI University, USA Chapter III Effective Stakeholder Knowledge Sharing for Effective Organizational Memory............................... 30 Nicholas P. Robinson, McGill University, Canada Prescott C. Ensign, University of Ottawa, Canada Chapter IV Revising the SECI Model for American Organizational Culture.......................................................... 44 Jerry Westfall, Liberty University, USA Chapter V Knowledge Transfer within Multinational Corporations: An Intercultural Challenge.......................... 57 Parissa Haghirian, Sophia University, Japan

Section II The Components of Organizational Memories Chapter VI Valuing a Multiplicity of Views: How to Tap Informal Networks to See the (W)hole......................... 70 Patrice Dunckley, Mindful Connections, USA Suzanne Roff-Wexler, Compass Point Consulting, USA Chapter VII Organizational Knowledge Sharing Networks...................................................................................... 81 Haris Papoutsakis, Technological Education Institute (TEI) of Crete, Greece Chapter VIII Lessons Learned as Organizational Project Memories.......................................................................... 97 Raul M. Abril, Universitat Pompeu i Fabra, Spain Ralf Müller, Umeå University, Sweden and Norwegian School of Management BI, Norway Chapter IX Will You Recall What You Knew? . .................................................................................................... 115 Jerry Westfall, Liberty University, USA Chapter X Added Value of Ontologies for Modeling an Organizational Memory............................................... 127 Maria de los Angeles Martin, National University of La Pampa, Argentina Luis Olsina, National University of La Pampa, Argentina Chapter XI The Collective Process and Memory of Strategic Management.......................................................... 148 Juha Kettunen, Turku University of Applied Sciences, Finland Section III Organizational Memories in Action Chapter XII Organizational Memory Challenges Faced by Non-Profit Organizations........................................... 165 Kimiz Dalkir, McGill University, Canada Chapter XIII Creating and Sustaining Meta-Organizational Memory: A Case Study.............................................. 184 Susan G. McIntyre, Defence R&D Canada

Chapter XIV Associative Patterning: The Unconscious Life of an Organization..................................................... 201 David Bennet, Mountain Quest Institute, USA Alex Bennet, Mountain Quest Institute, USA Chapter XV A Manifesto for the Preservation of Organizational Memory Associated with the Emergence of Knowledge Management Educational Programs............................................................................ 225 Michael JD Sutton, Westminster College, USA Section IV Selected Readings Chapter XVI An Organizational Memory Tool for E-Learning................................................................................ 245 Marie-Hélène Abel, University of Compiègne, France Chapter XVII Understanding Organizational Memory.............................................................................................. 263 Sajjad M. Jasimuddin, University of Dhaka, Bangladesh & University of Southampton, UK N.A.D. Connell, University of Southampton, UK Jonathan H. Klein, University of Southampton, UK Chapter XVIII Managing Knowledge in Organizational Memory Using Topic Maps................................................ 272 Les Miller, Iowa State University, USA Sree Nilakanta, Iowa State University, USA Yunan Song, Iowa State University, USA Lei Zhu, Iowa State University, USA Ming Hua, Iowa State University, USA Compilation of References................................................................................................................ 285 About the Contributors..................................................................................................................... 314 Index.................................................................................................................................................... 319

Detailed Table of Contents

Foreword . ........................................................................................................................................... xiv Preface................................................................................................................................................. xvii Acknowledgment . ............................................................................................................................ xxvi Section I The Enablers of Organizational Memories Chapter I Organizational Culture and the Management of Organizational Memory.............................................. 1 Peter Stoyko, Canada School of Public Service, Canada This chapter describes how organizational culture is both a “vessel” for preserving organizational memory and a force that conditions the way organizational memory is managed by other means. A detailed breakdown of the specific elements of organizational culture is conducted in order to describe this dual relationship. It is argued that the goal of managers should be the creation of a learning-oriented culture while avoiding the politicization of culture. Given that culture can not be manipulated directly, managers need to develop a sophisticated repertoire of leadership skills and a keen sense for socio-psychological dynamics. Specific advice on this count is offered at various points. Chapter II Downsizing and Building Organizational Memory: A Paradoxical Relationship between “Brain-Drain” and “Brain-Gain”........................................................................................................... 18 Nicholas N. Bowersox, TUI University, USA Recent business practices over the past decade have been tainted with corporate restructuring strategies such as downsizing, reorganizations, and job redesigns. With the hopes of increasing efficiency, gaining productivity, and reducing costs, many companies have participated in such efforts. However, one must consider the irony behind this shrewd, if not tactfully harsh, business practice. While organizations continue to decrease their workforce in an effort to regain acceptable profit margins, cut back on “waste” and become “leaner”, they also stress the importance of sharing knowledge among employees

and building organizational memory. How can a company effectively share knowledge and build organizational memory when its employee base is shrinking? This is an interesting question that has stirred much debate over recent years, both in the public and private sector. As such, this book chapter attempts to explore the paradoxical relationship between downsizing (brain-drain) and building organizational memory (brain-gain). Chapter III Effective Stakeholder Knowledge Sharing for Effective Organizational Memory............................... 30 Nicholas P. Robinson, McGill University, Canada Prescott C. Ensign, University of Ottawa, Canada This chapter argues that a trusting corporate culture predicated on values that emphasize sharing and encourage interactions amongst stakeholders at all levels spawns knowledge sharing activities and leads to the development of robust organizational memory reserves. The authors argue that the importance of knowledge management in the information age will make it essential that competitive companies inculcate stakeholders with the values necessary to encourage the production, sharing, and storage of knowledge for the benefit of the organization and its stakeholders. The authors demonstrate that having the proper systems and processes in place and fostering a culture that values sharing should help organizations to develop and use latent knowledge reserves. An experiential learning model is used to illustrate how mere data can be transformed into commercially viable knowledge. Chapter IV Revising the SECI Model for American Organizational Culture.......................................................... 44 Jerry Westfall, Liberty University, USA This chapter discusses the revision of the SECI model originally based on Japanese organizational culture into a model based on American organizational culture. The argument presented is that the original SECI model was developed from a Japanese perspective that does not align well with the American perspective. The American perspective is much different than in other cultures because individualism is paramount, but when compared to the group-centric culture of Japan, the differences are made evident. The hope is that by converting the model to a culturally relevant one that it can be better used as a foundation for understanding organizational knowledge transfer thereby improving organizational memories. Chapter V Knowledge Transfer within Multinational Corporations: An Intercultural Challenge.......................... 57 Parissa Haghirian, Sophia University, Japan A growing interest in the various aspects of knowledge transfer within multinational corporations has been evidenced by a recent surge in empirical research. Despite the fact that the number of empirical studies investigating various aspects of knowledge transfer within multinational corporations has significantly increased, very few insights into the influence of culture on knowledge transfer, however, have come to light. In fact, the cultural aspects and the individuals involved in the transfer and communication of corporate knowledge within multinational corporations seemed to have been overlooked by researchers. This chapter attempts to fill this gap and investigates the impact culture has upon knowledge transfer

processes within multinational corporations. It presents a comprehensive intercultural knowledge transfer model and identifies which aspects of national culture hinder and which aspects foster an effective transfer of knowledge. Section II The Components of Organizational Memories Chapter VI Valuing a Multiplicity of Views: How to Tap Informal Networks to See the (W)hole......................... 70 Patrice Dunckley, Mindful Connections, USA Suzanne Roff-Wexler, Compass Point Consulting, USA This chapter provides perspective and practical techniques that individuals and organizations can use to maximize knowledge transfer efforts. It illustrates the importance of using informal sources of information sharing to create a complete picture. The authors assert that using the traditional formal channels of transfer can leave holes when attempting to share the whole. Overall, the chapter offers practical, easily executable solutions that individuals can apply and that leaders can teach to fill the gaps that often go unnoticed. Influenced by sense making, storytelling, psychology, and visual mapping, the authors offer tools and provide coaching for using the tools, contained in text boxes throughout the chapter. The intent is to both introduce concepts and make them straightforward for the reader to implement. Chapter VII Organizational Knowledge Sharing Networks...................................................................................... 81 Haris Papoutsakis, Technological Education Institute (TEI) of Crete, Greece This chapter explores the ways that Knowledge Sharing Networks support the flow of organizational knowledge within a firm. Based on the assumption that tools people need to work with others are different from the ones they need to work alone; it demonstrates how the use of groupware permits “anytime, anyplace” collaboration within the organization. Furthermore, it takes a close look at information technology tools that enable leaders not only to encourage their employees to share knowledge personally, but also to put their knowledge in a form that others can easily access it now or in the future. In doing so, Knowledge Sharing Networks play an important role in preserving organizational memory. Chapter VIII Lessons Learned as Organizational Project Memories.......................................................................... 97 Raul M. Abril, Universitat Pompeu i Fabra, Spain Ralf Müller, Umeå University, Sweden and Norwegian School of Management BI, Norway This chapter suggests established research approaches to capture and validate project lessons learned. Past research indicates that due to the temporal nature of projects, improper management of knowledge, especially lessons learned, constitutes a risk for present and future projects. The authors argue that case study research is appropriate for developing lessons learned and that an inductive methodology can be used to generate hypotheses. These hypotheses are validated through an analysis of their Goodness of Fit into learning related business questions.

Chapter IX Will You Recall What You Knew? . .................................................................................................... 115 Jerry Westfall, Liberty University, USA This chapter discusses employee recall due to training presentations. Recall is an employee’s ability to remember what they knew or have learned via a training activity. This recall is improved when one utilizes structured training material. This eliminates selective scanning and provides program control for the training material. This chapter is specifically concerned with the transition from the externalization phase to the combination phase of the SECI model where the authors turn organizational tacit knowledge into explicit knowledge. They use these explicit knowledge materials to train employees for the purpose of organizational improvement. Research into employee recall is somewhat limited at this point, but the economic and personal impact for the employee and the organization are considerable when compared to the over US$2 trillion dollars spent annually by organizations on employee training worldwide. The motivation then is to design our explicit training materials so that we receive maximum benefit from improved employee recall leading to overall improvement of our organizations. Chapter X Added Value of Ontologies for Modeling an Organizational Memory............................................... 127 Maria de los Angeles Martin, National University of La Pampa, Argentina Luis Olsina, National University of La Pampa, Argentina With the aim to manage and retrieve the organizational knowledge, in the last years numerous proposals of models and tools for knowledge management and knowledge representation have arisen. However, most of them store knowledge in a non-structured or semi-structured way, hindering the semantic and automatic processing of this knowledge. In this chapter the authors specify a case-based organizational memory ontology, which aims at contributing to the design of an organizational memory based on cases so that it can be used to support better decision-making. One ontology goal is to serve as a base for the organizational knowledge exchange with semantic power, which can facilitate the reuse, interoperability, and automatic processing by agents. In addition, the ontology aims to be at a high level from which other more specific representations can be formulated. In order to illustrate its utility a practical case is shown. Chapter XI The Collective Process and Memory of Strategic Management.......................................................... 148 Juha Kettunen, Turku University of Applied Sciences, Finland This study analyses how strategic management is integrated with budgeting in the cities using the Balanced Scorecard approach, which provides a general framework to communicate and implement strategies. The approach is useful in accomplishing the strategic objectives, measures, and targets decided by city councils. It is important to align the strategic plans of various units at the different organizational levels of the city and link them together in the budgeting process, which is the main management system in most public sector organizations. The study shows how the electronic collaborative technologies can support strategic planning, implementation, and preservation of organizational knowledge. The management information system provides a platform to integrate organizational knowledge and development to facilitate strategic management.

Section III Organizational Memories in Action Chapter XII Organizational Memory Challenges Faced by Non-Profit Organizations........................................... 165 Kimiz Dalkir, McGill University, Canada Research on how organizational memories can be created, preserved and made available for future reuse in NPOs is presented. An initial review of the existing literature on organizational memory research is summarized. Particular emphasis is placed on the technologies used to support organizational memories and cultural considerations, particularly with respect to incentives. Three case studies are then be described to illustrate the particular challenges faced by the NPO sector: the Second Start school for students with behavioral problems, La Centrale, an artist-run centre, and Oxfam Quebec, an international aid organization. The chapter concludes with a proposed typology that can be used to characterize organizational memory models and systems that are best suited to different types of NPOs, which will vary with respect to main features such as organizational maturity, size and complexity. Chapter XIII Creating and Sustaining Meta-Organizational Memory: A Case Study.............................................. 184 Susan G. McIntyre, Defence R&D Canada The case study of the Chemical, Biological, Radiological-Nuclear, and Explosives (CBRNE) Research and Technology Initiative (CRTI), a Canadian government meta-organizational collaborative initiative, is presented. Multiple federal departments and agencies have a joint responsibility for creating a knowledge base and a national memory for the purposes of protecting the country against CBRNE threats posed by terrorists. The conditions of a meta-organization present particular opportunities and challenges for organizational learning and organizational memory. Organizational learning and knowledge management theory provide the premises for addressing these issues. An intentional knowledge management strategy has been instrumental in organizational learning, resulting in a knowledge base for a collective organizational memory. Ongoing challenges are being addressed by the strategy. Chapter XIV Associative Patterning: The Unconscious Life of an Organization..................................................... 201 David Bennet, Mountain Quest Institute, USA Alex Bennet, Mountain Quest Institute, USA This chapter begins with a brief discussion of the basic concepts related to the unconscious life of an organization, and then addresses specific aspects of knowledge, learning, and memory, developing a language and framework for comprehending their application to organizations. Knowledge is addressed in terms of an information part and a proceeding part. Tacit knowledge is divided into embodied, intuitive, affective, and spiritual parts, with each of these aspects carried over to corresponding descriptions of memory. Organizational memory is then considered in light of a rapidly changing, uncertain environment. It is forwarded that organizational sustainability in an uncertain world requires a dynamic and responsive organizational memory. This highlights the challenge of keeping tacit memory updated as

experienced personnel retire. Ideas and actions are briefly suggested to enhance and sustain organizational memory. Chapter XV A Manifesto for the Preservation of Organizational Memory Associated with the Emergence of Knowledge Management Educational Programs............................................................................ 225 Michael JD Sutton, Westminster College, USA This chapter introduces the research domain of knowledge management educational programs and issues associated with the preservation of knowledge about these programs. The chapter comprises a preliminary literature review of the academic and research perspectives along with the broader educational perspectives associated with knowledge management educational programs in the academy and in the workplace. The manifesto concludes with an imperative suggesting the critical need to immediately collect and preserve all significant knowledge artifacts comprising curriculum, courses, and instruction associated with past, current, and future knowledge management educational programs. Since knowledge management is continuing to grow as an emerging field, future educators will need access to the preserved organizational memory associated with instructional successes and failures in this new field. Section IV Selected Readings Chapter XVI An Organizational Memory Tool for E-Learning................................................................................ 245 Marie-Hélène Abel, University of Compiègne, France Learning can be considered an outcome associated with acquiring new competencies (Sicilia, 2005) and adding new knowledge. A competence is a way to put into practice some knowledge in a specific context. The process of competency acquisition starts from a need in this specific context. It may induce the search and the selection of relevant resources. Numerous resources may be used during e-learning, their access is a real problem. Different approaches may be adopted to exploit them. This chapter describes the tool E-MEMORAe, which supports an organizational goal-driven approach based on the concept of learning organizational memory. In such a memory, ontologies are used to define knowledge that indexes resources; the capitalization and the organization of knowledge, information, and resources relating to a specific context can be realized. End-users have a direct access to the memory. The organizational environment E-MEMORAe was evaluated in the context of two courses taught at the university (algorithms, mathematics). Chapter XVII Understanding Organizational Memory.............................................................................................. 263 Sajjad M. Jasimuddin, University of Dhaka, Bangladesh & University of Southampton, UK N.A.D. Connell, University of Southampton, UK Jonathan H. Klein, University of Southampton, UK

Although the need to preserve knowledge in organizations is now recognized, organizational theorists still disagree on a number of issues relating to organizational memory (OM). Existing literature exhibits contradictory arguments regarding OM which can make the relevance and application of OM concepts to KM difficult to understand. This chapter describes some of the disagreements surrounding OM in order to provide a deeper understanding of how OM might help to manage knowledge. Chapter XVIII Managing Knowledge in Organizational Memory Using Topic Maps................................................ 272 Les Miller, Iowa State University, USA Sree Nilakanta, Iowa State University, USA Yunan Song, Iowa State University, USA Lei Zhu, Iowa State University, USA Ming Hua, Iowa State University, USA Organizational memories play a significant role in knowledge management, but several challenges confront their use. Artifacts of OM are many and varied. Access and use of the stored artifact are influenced by the user’s understanding of these information objects as well as their context. Theories of distributed cognition and the notion of community of practice are used to develop a model of the knowledge management system. In the present work we look at a model for managing organizational memory knowledge. Topic maps are used in the model to represent user cognition of contextualized information. A visual approach to topic maps proposed in the model also allows for access and analysis of stored memory artifacts. The design and implementation of a prototype to test the feasibility of the model is briefly examined. Compilation of References................................................................................................................ 285 About the Contributors..................................................................................................................... 314 Index.................................................................................................................................................... 319

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Foreword

Fasten your BlackBerry, adjust your Bluetooth earpiece, and recharge your iPod! Today’s business world is taking off faster than you can say “information bombardment”. The ever-pounding forces of technological innovation and integrated globalization will place unrelenting pressure on our organizations and ourselves. Can your firm adapt fast enough? Can you yourself adapt smart enough? The field of organizational memory and its closely related cousins (knowledge management, intellectual capital, human capital, and organizational learning) has grown at an exponential rate. Over the past 15 years we have seen a remarkable increase in articles, books, conferences, and job titles all related to the primary issue of harvesting organizational memory. In fact, it was Thomas Stewart, former editor at FORTUNE Magazine (and subsequent editor at Harvard Business Review) who provided the initial impetus when in a June 2001 cover story he exclaimed: “Brainpower, how intellectual capital is becoming America’s most valuable asset”. Organizational memory quickly became part of a new lexicon describing novel forms of economic value. It belonged to a paradigm where sustainable competitive advantage was tied to individual and organizational knowledge. Reliance on traditional productive tangible assets such as raw materials, fixed capital, and land no longer accounted for investments made and wealth created by new and prospering companies. Instead, leveraging knowledge assets became the key reason attributed to corporate success stories during the dawn of the Internet age. The overall field of research in the early 1990s was supported primarily by practitioners. These socalled Chief Knowledge Officers were entrusted with an important – albeit invisible – corporate asset. The task of exploring the development of organizational memory and later, understanding how to better exploit it for competitive gain was not easy at all. At the time, there were no degrees, university programs, or training seminars that targeted this field. However, several pioneering CKOs gravitated towards each other and created global networks of expertise. Many consider Leif Edvinsson, of Sweden, as one of the Godfather’s of this group. He spearheaded the development of the world’s first intellectual capital statement at Skandia, which provided the foundation for a new language, framework and operationalization of organizational memory. This initial momentum was supported by a string of popular books several years later. Endorsements by highly respected scholars such as Dr. Baruch Lev (New York University) and Dr. Tom Davenport (Babson College) coupled with practitioner icons such as Hubert Saint-Onge (formerly of CIBC) helped to round out the love affair with this phenomenon. The convergence of a new management discipline with the advent of the Internet age provided the perfect ingredients for a new discipline with a promising future. It was at that perfect juncture in time that I decided to make a move away from my position as an analyst at CIBC. I did the unthinkable. I embarked on a doctoral program to study a nascent field with very little extant literature, barely any case studies, absent tools for measurement, and no academic journals to speak of. I would not recommend this strategy for any aspiring academics!

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In retrospect, it was the best decision I could have ever made. The field of organizational memory accelerated into the consciousness of the corporate world faster than anything it had seen before. Moreover, it was not just an Anglophonic phenomenon. Research and practice were taking place all over the globe, mostly led by the Scandinavians, but with accelerated support from continental Europe, and Asia, in addition to most Anglophonic nations. Notwithstanding, the single most important driver in support of this academic field was that it was truly cross-functional and multi-leveled. There are very few fields of management endeavor that can make this claim. Organizational memory attracts researchers from strategy, human resources, information systems, accounting, finance, marketing, and library science just to name a few. This bolsters the support for new models of conceptualization as well as new methods for measurement. Furthermore, the multi-level aspect of organizational memory provides even more novel perspectives. For example: • • • •

Individuals possess personal competence and experience, but how does one build this over time when the stresses of information bombardment and work-life balance take-over? Groups and teams work synergistically in collaborative networks to accomplish tasks that one single individual can not, but how do we overcome the bottlenecks that provide friction for tapping into this higher-order memory? Organizations invest heavily in technology so that tacit knowledge is converted into codified formats that are more readily classified and searched, but how can human’s interact more readily with non-human systems? Multi-national corporations establish joint ventures in developing countries to tap into local expertise, how is that organizational memory then harvested back at headquarters?

The aforementioned scenarios are simple examples of at least four levels of analysis that the field of organizational memory taps into: individual, group, organization and cross-organization. By joining multi-functional perspectives with multi-levels of analysis, the field of organizational memory has been able to not only grow at an accelerated pace, but also maintain its momentum beyond the normal leveling-off of any new discipline. It is for this reason, that no one can argue that this is simply a management fad. On the contrary, this domain has supported the launch of new degrees, new programs, new corporate departments, and new ways of thinking about management. Perhaps the most impressive evidence suggesting a transition in thinking about a new structure and process supporting a company’s organizational memory is in the inclusion of intellectual capital as a strategic performance measure. Since in 1994 as a PhD student, I have been transfixed on studying this phenomenon. There are several things that I have uncovered. First, the majority of senior managers I have interviewed in both business and government clearly support the notion that the effective management of organizational memory is critical to future success. No wonder that with the fast pace of change in most global markets, firms that can adapt and learn quickly survive, and those that do not, die. Second, individual productivity is significantly hampered by information bombardment. For most knowledge workers, e-mail is the “killer app” that is on 24/7 on most desktops. Even if you turn your computer off at night, your BlackBerry will have no problem at all buzzing through all hours of the night while you sleep, warning you of the pending doom of an overfilled inbox the following morning. How do you know what to filter out versus what to concentrate on? Third, knowledge sharing and the multiplicative network properties of communication are clearly understood by organizational behaviorists who all support teamwork in organizations. Unfortunately, the simple act of sharing knowledge in a team is not that easy. In fact, it is not that natural. Most knowledge

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workers pride themselves on what they know, in fact for many of them it’s how they get compensated. Because of this, the hoarding of information becomes the competitive weapon of choice. It then becomes extremely difficult to exploit organizational memory, when most organizational members are not talking to one another for fear of losing their own intangible value. Fourth, technology can definitely support the process of building organizational memory. But, it can also kill it. The advent of Intranets, repositories, collaborative workspaces, Wikis, blogs, and voice recognition software can all aid in the development of organizational memory. However, these all come at a price, both financially and culturally. When all is said and done, intellectual capital development ultimately is a people process. As such, senior leadership plays a critical role in establishing the appropriate culture and values for supporting collaborative behaviors and codification processes so we benefit from everyone’s memory and not just the chosen few. Finally, a large challenge for this field resides in the communication gap between researchers and practitioners. Although we have come a long way since the early 1990s. The opportunities to bridge the gap between theory and practice continue. The majority of scientific work published in top tier peer-reviewed journals is targeted to other academics. Journal articles are written in a specific scientific language, contain jargon, words, phrases, and are structured in a way that non-academics cannot quickly comprehend. Many of the problems that practitioners have with scientific papers are not with the ideas that are expressed, but are with the way that they are presented. Most academics offer a set of practical insights at the end of their manuscripts. However, this is not sufficient to allow industry professionals to directly consume the body of academic knowledge. As such, the direct knowledge distribution model, in which practitioners are supposed to read academic articles and utilize their practical insights, has partially failed. However, on the flipside, I am very proud to be involved with the McMaster World Congress on Intellectual Capital. Since 1996, my university has taken a global leadership position in bridging the gap between theory and practice. We host an annual conference that targets academic researchers, industry professionals, and students to comingle as they attack the problems in this field together. This has been a labor of love with outstanding results. In fact, John Girard himself and many of the contributors in this text are former attendees of the World Congress. Often, socialization and organizational memory development needs to be politely coerced in the form of a physical gathering. Clearly, the influential models developed by various authors such as Polanyi, Nonaka, and Prusak coupled with the editorial prowess of Stewart provide much of the intellectual foundation for the organizational memory field. However, what is evident from my experience thus far is that the future of this field will surely benefit from the wide and diverse publication base that covers both academic institutions and corporate organizations. Furthermore, the global coverage of countries represented as well as the sheer number of authors that have influenced the field’s rise, bodes well for its future health as a body of literature that is both influential and meaningful to managers in the knowledge era. Nick Bontis McMaster University, Canada Nick Bontis is the world’s leading expert on intellectual capital and its impact on performance. He helps organizations leverage their most important intangible asset for sustainable competitive advantage. He earned his PhD from the prestigious Ivey Business School, University of Western Ontario where he received the top scholastic achievement award. His doctoral dissertation went on to become the number one selling thesis in Canada. He is currently an award-winning tenured professor at McMaster University and world-renowned academic researcher and professional speaker. Nick is also chief knowledge of.cer of Knexa Solutions - the world’s first knowledge exchange and auction. A Canadian and US patent application has been filed for Knexa’s dynamic pricing system. For more background information, see www.NickBontis.com.

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Preface

Toward an Understanding of OOganizational Memories The Challenge Much has been written about how organizations create and exchange knowledge to achieve a competitive advantage. To date most researchers have concentrated on the present and how organizational leaders may use knowledge to create value today. This book builds on the many great works in the knowledge management domain; however, it is unique in that the focus will be on what leaders should be doing now (or soon) to ensure the next generation of organizational leaders know what they knew. The following is a real-world example of why this area of research is important; there are many more reasons articulated in the pages ahead. During an interview on CBS News on September 11, 2006, New York Fire Department Deputy Fire Chief John Norman described the unfathomable loss of life of the Department’s Special Operations Command five years earlier. On that tragic day, September 11, 2001, Special Operations Command lost 95 men – totaling 1600 years of experience. This is simply unimaginable when one considers this specialized unit pioneered techniques for urban rescue and terrorist attacks. Surely, it would be impossible to reconstitute the unique and vital knowledge of these brave men. Au contraire, Norman’s team proved that they had plans in place to quickly rebuild their team and once again become the best in world. Five years later the knowledge loss was virtually unnoticeable as the team responded to 50 calls (Pitts, 2006). This story is not meant to demean the heartbreaking loss of very brave men, but rather it is to commemorate the outstanding leadership, courage, and culture of a team that would not give up. Fortunately, most organizations do not have to suffer the tragic loss that Norman described, but perhaps we can learn from their tragedy. Virtually all organizations must deal with organizational memory loss to varying degrees. Could your organization rebuild from such devastation? Regrettably, organizational memory loss is not new, consider: One horrible day 1,600 years ago, the wisdom of many centuries went up in flames. The great library in Alexandria burned down, a catastrophe at the time and a symbol for all ages of the vulnerability of human knowledge. The tragedy forced scholars to grope to reconstruct a grand literature and science that once lay neatly cataloged in scrolls. (E. Linden, 1991) The message is clear; organizations must develop a strategy to maintain the intellectual capital that makes them unique. To be sure, most organizations cannot capture all of their tacit and explicit knowledge; however, that is not necessary and perhaps not even desirable. Rather organizational leaders must put in place the tools and techniques to ensure that mission critical knowledge is maintained for the next generation.

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The term organizational memory is used to describe the preservation of enterprise knowledge – it is equally applicable to public, private, or not-for-profit organizations. As is often the case when the business and academic worlds converge, there is no consensus of the exact meaning of the term organizational memory. Many executives intuitively understand the term, though, few agree on the exact definition. To begin the debate, the following definition was included in the call for chapters for this book: “Organizational memory is the body of knowledge, past, present, and future, necessary to achieve the strategic objectives of an organization. Enabled by technology, leadership, and culture, organizational memories include repositories of artifacts, communities of people, and organizational knowledge sharing processes, which focus on achieving the organizational vision.” Many other definitions are included in the chapters ahead; however, we need not worry about the lack of consensus, but rather, on the solution to the organization woe.

Organizational Memory Loss The premise of this book is that, in general, building organizational memories creates a sustainable competitive advantage. More specifically, I argue that if executives know what their organizations knew in the past, they will be better prepared to make well-informed decisions. In turn, these knowledge-based decisions will ensure the organization is better at whatever it is that it does. In short, understanding the past will help guide organizations into the future. So why is it that organizations “forget what they knew”? Perhaps if we can answer this question we will, collectively, be more capable of building organizational memories to aid future leaders. There are a variety of issues that contribute to this organizational malady, many of which are considered in detail in the chapters ahead. However, it seems prudent to consider how the tenets of organizational forgetting make possible the building of organizational memories. The literature is rich in this domain and the scope of brief introduction precludes an extensive review – for a more detailed review consider the works of de Holan & Phillips, 2004; Govindarajan & Trimble, 2006 and Kwiatkowski, Duncan, & Shimmin, 2006. With a view to building a foundation from which we may examine organizational memories, this terse review will focus on two of the four components of organizational forgetting articulated by Pablo de Holan and his colleagues (de Holan, Phillips, & Lawrence, 2004). According to de Holan et al. (2004), there are two modes of forgetting, intentional or accidental. Likewise, they suggest there are two sources of knowledge, from existing stock and newly innovated. Combining the two premises, results in matrix that describes the four categories of organizational forgetting that de Holan et al. (2004) discovered in their research. The four quadrants of this matrix provide an

Source of Knowledge

Table 1. Forms of organizational forgetting (de Holan et al., 2004, 47) From Existing Stock Newly Innovated

Memory Decay

Unlearning

Failure to Capture

Avoiding Bad Habits

Accidental

Intentional

Mode of Forgetting

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excellent framework to consider how managers may wish to consider the application of organizational forgetting. For our purposes the accidental mode will be of most interest. Memory decay is the accidental loss of existing organizational knowledge. To better understand the implications, it may be worth reviewing what we mean by the term knowledge. One of the most accepted definitions of knowledge is the one proposed by Davenport and Prusak in their seminal work Working Knowledge: How Organizations Manage What they Know, “Knowledge is a fluid mix of framed experience, values, contextual information, expert insight that provides a framework for evaluating and incorporating new experiences and information” (1998, 5). From an organizational point of view, managers must consider the impact or consequences of failing to maintain the existing store of experience, values, contextual information, and expert insight. As Davenport and Prusak so eloquently remind us, “In organizations, it [knowledge] often becomes embedded not only in documents or repositories but also in organizational routines, processes, practices, and norms” (1998, 5). The implication of their suggestion is that we must consider both the explicit and tacit forms of knowledge that may be accidentally forgotten. In other words, this is not simply an exercise in trying to codify all existing knowledge. Perhaps one of the best examples of memory decay is the finding that the National Aeronautics and Space Administration (NASA) have lost the knowledge necessary to travel to the moon. It appears that NASA lost the only set of blueprints for a critical component of the rocket used to carry astronauts to the moon. However, the loss of this explicit knowledge is not the only problem as some observers suggest that even if NASA had the codified knowledge to build another rocket, no one possesses the tacit knowledge necessary to fly the Saturn rocket (Petch, 2001). In his book “Lost Knowledge” author David DeLong discusses the drivers of lost knowledge and suggests that NASA’s loss may have been the result of an aging population and the complexity of their knowledge (2004). Clearly, the former was part of the problem in the moon example as most of the engineers, scientists, and indeed astronauts involved in the 1960s and 1970s Apollo project have long since retired. Managers must start looking forward rather than backwards. Of course, there will be retirements – there will also be deaths, terminations, transfers, and a variety of other reasons for employees and their knowledge departing. Although the spike in retirements associated with the baby boomers is making executives take notice, the reality is not a new problem, nor is it a challenge that will diminish in the future. It terms of building organizational memories we should consider the future value, positive or negative, of forgetting what was known. Described as “failing to incorporate new knowledge into the broader organizational memory,” failure to capture is the second category of accidental organizational forgetting (de Holan et al., 2004, 48). Much like memory decay, this is an unintentional act and once managers are aware of the consequences of not capturing the knowledge then steps may be taken to remedy the situation. To a large degree, the solution to both the memory decay and failure to capture challenges lies in understanding the enablers of organizational memories and developing the processes to eliminate the accidental forgetting that is common place in many organizations – this is the focus of this book.

Information Anxiety As important as accidental forgetting may be, it is not the only reason executives should consider building organizational memories. A separate, but sometimes related, organizational ailment is information anxiety. The broad issue of information anxiety and its effects on individuals and organizations has been studied since at least 1605. Possibly the first mention of this challenge was in Sir Francis Bacon’s book entitled “The Advancement of Learning” (Bacon, 1915). It was nearly 400 years until the term information anxiety emerged in the popular press as the title of Richard Wurman’s best-selling book

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(1989). Wurman defined Information Anxiety as “the black hole between data and knowledge,” a definition that attracted the attention of many business leaders as many were struggling with the challenges of organizational memory loss. According to Wurman, the five components of information anxiety are: 1. 2. 3. 4. 5.

Not understanding information Feeling overwhelmed by the amount of information to be understood Not knowing if certain information exists Not knowing where to find information Knowing exactly where to find the information, but not having the key to access it (Wurman, 1989, p. 44)

Other research supports Wurman’s general construct, for example, the authors of Gartner Research’s Information Overload Survey concluded there are four information issues affecting competition: siloed information; too much information; un-indexed information; and ineffective searching procedures (A. Linden, Ball, Arevolo, & Haley, 2002). In a second report, Linden suggests there are seven drivers of information overload: quantity; relevance; redundancy; information illiteracy; unqualified information; distraction by the obvious and the glossy; and business models struggling (A. Linden, 2001). Kirsh (2000) related four causes of what he calls cognitive overload, which are too much information supply, too much information demand, and the need to deal with multi-tasking and interruption, and the inadequate workplace infrastructure to help reduce metacognition. Two empirical studies linked Wurman’s concept of information anxiety to organizational memory loss (Allison, 2006; Girard, 2005a). In both cases the findings were similar, the study respondents reported Accessing Information, Wurman’s latter category, as the most troubling component of information anxiety. In other words, the respondents knew exactly where to find a particular piece of information but they were unable to access it. In terms of building organizational memories this finding is extremely significant. There is little sense investing in organizational memory systems if the repositories of artifacts, communities of people, and organizational knowledge sharing processes are not available to those who need them most.

Enterprise Dementia When the two closely related components of Information Anxiety and Organizational Memory Loss coexist in an organization, the result is Enterprise Dementia. The convergence of these debilitating conditions is often apparent in organizations which have undergone downsizing, reorganization, or other major human capital or structural changes. Common to many of these organizations are brittle organizational structures with little deliberate redundancy. For a more detailed explanation of the phenomenon see Girard, 2005b, 2006. This relationship may go some way in explaining the unexpected and confusing results of a variety of recent research within the field of knowledge management. For example, two studies, completed by experts in the field, suggest that the implementation of a knowledge management program did not result in significantly less information overload (A. Linden et al., 2002; Parlby, 2000). A KPMG study found that 65% of respondents with a knowledge management program suffered from information overload whilst 69% of respondents without a knowledge management program suffered from information overload – hardly the vast improvement promised by so many gurus. The Gartner Research study actually reported a 50% increase in information overload in knowledge management enabled organizations (A. Linden et al., 2002).

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Our brief analysis of enterprise dementia and its subcomponents of organizational memory loss and information anxiety highlight the requirement for action. This review reinforces the need for executives to consider how they can best preserve their organizations knowledge, in easily accessible manner, with a view to eliminating enterprise dementia. In the following section, there is an overview of the chapters penned by leading researchers and practitioners in the field. Each chapter adds to the body of knowledge in the organizational memory domain and offers organizational leaders actionable words of wisdom.

The Wisdom of Many This book is particularly unique in several distinct ways. First, this is one of the very first academic collections to consider what leaders should be doing today to ensure the preservation of intellectual capital for the next generation. Second, the book considers organizational memories in the broadest possible way. To be sure, some will question the breadth and depth of the domain as articulated by the authors. Third, this book includes chapters from a diverse group of interested parties; this diversity is geographic, linguistic, professional, and experiential. The book is organized into 15 chapters based on our definition of organizational memories. The first five chapters consider the enablers of organizational memories, specifically technology, leadership, and culture. The next five chapters focus on the components of organizational memories, which include repositories of artifacts, communities of people, and organizational knowledge sharing processes. The final five chapters examine organizational memories in action or more specifically how executives may use the enablers and components to achieve their organizational vision.

Section I: The Enablers of Organizational Memories In Chapter I, Peter Stoyko describes how organizational culture is both a “vessel” for preserving organizational memory and a force that conditions the way organizational memory is managed by other means. Stoyko argues that the goal of managers should be the creation of a learning-oriented culture while avoiding the politicization of culture. In Chapter II, Nick Bowersox suggests business practices over the past decade have been tainted with corporate restructuring strategies such as downsizing, reorganizations, and job redesigns. With the hopes of increasing efficiency, gaining productivity, and reducing costs, many companies have participated in such efforts. He explores the paradoxical relationship between downsizing (brain-drain) and building organizational memory (brain-gain). In Chapter III, Prescott Ensign and Nicholas Robinson argue that a trusting corporate culture predicated on values that emphasize sharing and encourage interactions amongst stakeholders at all levels spawns knowledge sharing activities and leads to the development of robust organizational memory reserves. Prescott and Nicholas demonstrate that having the proper systems and processes in place and fostering a culture that values sharing should help organizations to develop and use latent knowledge reserves. In Chapter IV, Jerry Westfall discusses a revision of the SECI model originally based on Japanese organizational culture into a model based on American organizational culture. Jerry suggests that by converting the model to a culturally relevant one that it can be better used as a foundation for understanding organizational knowledge transfer thereby improving organizational memories. In Chapter V, Parissa Haghirian explores a recent surge in empirical research surrounding knowledge transfer within multinational corporations. Parissa suggests cultural aspects involved in the transfer and communication of corporate knowledge within multinational corporations seem to have been overlooked. In attempt to fill the gap, Parissa presents a comprehensive intercultural knowledge transfer model and

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identifies which aspects of national culture hinder and which aspects foster an effective transfer of knowledge.

Section II: The Components of Organizational Memories In Chapter VI, Patrice Dunckley and Suzanne Roff-Wexley provide practical techniques that individuals and organizations can use to maximize knowledge transfer efforts. They offer easily-executable solutions that leaders can teach to fill the gaps that often go unnoticed. Influenced by sense-making, storytelling, psychology, and visual mapping, Patrice and Suzanne offer tools and provide coaching for using the tools throughout the chapter. In Chapter VII, Haris Papoutsakis explains how Knowledge Sharing Networks play an important role in preserving organizational memory by supporting the flow of organizational knowledge within a firm. Haris demonstrates how the use of groupware permits “anytime, anyplace” collaboration within the organization. In Chapter VIII, Raul Abril and Ralf Müller argue that case study research is appropriate for developing lessons learned and that an inductive methodology can be used to generate hypotheses. These hypotheses are validated through an analysis of their Goodness of Fit into learning related business questions. Raul and Ralf argue that a common understanding should be achieved before organizational learning influences decisions and/or actions. In Chapter IX, Jerry Westfall discusses an employee’s ability to remember what they knew or have learned due to training presentations. Jerry is specifically concerned with the transition from the externalization phase to the combination phase of the SECI model. The motivation is to design explicit training materials that enhance employee recall and lead to overall improvement of our organizations. In Chapter X, María de los A. Martín and Luis Olsina, articulate a case-based organizational memory ontology to support better decision making. The goal of the high-level ontology is to support organizational knowledge exchange with semantic power, and facilitate the reuse, interoperability and automatic processing by agents. In Chapter XI, Juha Kettunen analyses how strategic management is integrated with budgeting in cities using the Balanced Scorecard approach. Juha shows how the electronic collaborative technologies can support strategic planning, implementation and preservation of organizational knowledge.

Section III: Organizational Memories in Action In Chapter XII, Kimiz Dalkir reviews three case studies that illustrate how organizational memories can be created, preserved, and made available for future reuse in NPOs. Kimiz suggests a proposed typology that can be used to characterize organizational memory models and systems that are best suited to different types of NPOs, which will vary with respect to main features such as organizational maturity, size, and complexity. In Chapter XIII, Susan McIntyre presents the case study of a Canadian government meta-organizational collaborative initiative. An intentional knowledge management strategy has been instrumental in organizational learning, resulting in a knowledge base for a collective organizational memory. Susan describes the ongoing challenges being addressed by the strategy. In Chapter XIV, David and Alex Bennet begin with a brief discussion of the basic concepts related to the unconscious life of an organization, then address specific aspects of knowledge, learning, and memory, developing a language and framework for comprehending their application to organizations. Organizational memory is then considered in light of a rapidly changing, uncertain environment.

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In Chapter XV, Michael Sutton introduces the research domain of knowledge management educational programs and issues associated with the preservation of knowledge about these programs. Sutton concludes with an imperative suggesting the critical need to immediately collect and preserve all significant knowledge artifacts comprising curriculum, courses, and instruction associated with past, current, and future knowledge management educational programs.

R Abril, R. M., & Müller, R. (2009). Lessons Learned As Organizational Project Memories. In J. P. Girard (Ed.), Building Organizational Memories: Will You Know What You Knew? Hershey, PA: IGI Global. Allison, M. P. (2006). The effects of quality improvement high-performance team membership on information anxiety. Unpublished Ph.D., Touro University International, United States -- California. Bacon, F. (1915). The advancement of learning. London: Dent. Bennet, D., & Bennet, A. (2009). Associative Patterning: The Unconscious Life of an Organization. In J. P. Girard (Ed.), Building Organizational Memories: Will You Know What You Knew? Hershey, PA: IGI Global. Bowersox, N. (2009). Downsizing and Building Organizational Memory: A Paradoxical Relationship Between “Brain-Drain” and “Brain-Gain”. In J. P. Girard (Ed.), Building Organizational Memories: Will You Know What You Knew? Hershey, PA: IGI Global. Dalkir, K. (2009). Organizational Memory Challenges Faced by Non-Profit Organizations. In J. P. Girard (Ed.), Building Organizational Memories: Will You Know What You Knew? Hershey, PA: IGI Global. Davenport, T. H., & Prusak, L. (1998). Working knowledge: How organizations manage what they know. Boston, Mass: Harvard Business School Press. de Holan, P. M., & Phillips, N. (2004). Remembrance of Things Past? The Dynamics of Organizational Forgetting. Management Science, 50(11), 1603-1613. de Holan, P. M., Phillips, N., & Lawrence, T. B. (2004). Managing Organizational Forgetting. (Cover story). MIT Sloan Management Review, 45(2), 45-51. DeLong, D. W. (2004). Lost knowledge: Confronting the threat of an aging workforce. Oxford, New York: Oxford University Press. Dunckley, P., & Roff-Wexley, S. (2009). Valuing a Multiplicity of Views: How to Tap Informal Networks to See the (W)hole. In J. P. Girard (Ed.), Building Organizational Memories: Will You Know What You Knew? Hershey, PA: IGI Global. Ensign, P. C., & Robinson, N. P. (2009). Effective Stakeholder Knowledge Sharing for Effective Organizational Memory. In J. P. Girard (Ed.), Building Organizational Memories: Will You Know What You Knew? Hershey, PA: IGI Global. Girard, J. P. (2005a). Combating information anxiety: A management responsibility. Organizaciju Vadyba: Sisteminiai tyrimai, 35(1), 65-79. Girard, J. P. (2005b). Taming enterprise dementia in public sector organizations. International Journal of Public Sector Management, 18(6), 534-545.

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Girard, J. P. (2006). Where is the Knowledge we have lost in Managers? Journal of Knowledge Management, 10(6), 22-38. Govindarajan, V., & Trimble, C. (2006). How Forgetting Leads to Innovation. Chief Executive, (216), 46. Haghirian, P. (2009). Knowledge Transfer within Multinational Corporations - An Intercultural Challenge. In J. P. Girard (Ed.), Building Organizational Memories: Will You Know What You Knew? Hershey, PA: IGI Global. Kettunen, J. (2009). The Collective Process and Memory of Strategic Management In J. P. Girard (Ed.), Building Organizational Memories: Will You Know What You Knew? Hershey, PA: IGI Global. Kirsh, D. (2000). A few thoughts on cognitive overload. Intellectica (Revue de l’association pour la recherche cognitive), 30(1), 19-51. Kwiatkowski, R., Duncan, D. C., & Shimmin, S. (2006). What have we forgotten -- and why? Journal of Occupational & Organizational Psychology, 79(2), 183-201. Linden, A. (2001). Information not yet at your fingertips? Here’s why. (Research Note): Gartner Research. Linden, A., Ball, R., Arevolo, W., & Haley, K. (2002). Gartner’s survey on managing information (Research Note): Gartner Research. Linden, E. (1991, September 23). Lost Tribes, Lost Knowledge. Time Magazine, 138. Martín, M. d. l. A., & Olsina, L. (2009). Added Value of Ontologies for Modeling an Organizational Memory. In J. P. Girard (Ed.), Building Organizational Memories: Will You Know What You Knew? Hershey, PA: IGI Global. McIntyre, S. (2009). Creating and Sustaining Inter-Organizational Memory. In J. P. Girard (Ed.), Building Organizational Memories: Will You Know What You Knew? Hershey, PA: IGI Global. Papoutsakis, H. (2009). Organizational Knowledge Sharing Networks. In J. P. Girard (Ed.), Building Organizational Memories: Will You Know What You Knew? Hershey, PA: IGI Global. Parlby, D. (2000). Knowledge management research report 2000. London: KPMG Consulting. Petch, G. (2001). The cost of lost knowledge. Retrieved September 23, 2006, from http://www.destinationkm.com/print/default.asp?ArticleID=513 Pitts, B. (2006, 11 September). FDNY: The Next Generation. CBS News, from http://www.cbsnews. com/stories/2006/09/11/eveningnews/main1999146.shtml Stoyko, P. (2009). Organizational Culture and The Management of Organizational Memory In J. P. Girard (Ed.), Building Organizational Memories: Will You Know What You Knew? Hershey, PA: IGI Global. Sutton, M. (2009). A Manifesto for the Preservation of Organizational Memory Associated with the Emergence of KM Educational. In J. P. Girard (Ed.), Building Organizational Memories: Will You Know What You Knew? Hershey, PA: IGI Global. Westfall, J. (2009a). Revising the SECI Model for American Organizational Culture. In J. P. Girard (Ed.), Building Organizational Memories: Will You Know What You Knew? Hershey, PA: IGI Global.

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Westfall, J. (2009b). Will You Recall What You Knew? In J. P. Girard (Ed.), Building Organizational Memories: Will You Know What You Knew? Hershey, PA: IGI Global. Wurman, R. S. (1989). Information anxiety. New York: Doubleday.

John Girard Minot State University, USA John Girard, PhD is an associate professor at Minot State University where he is the lead professor for knowledge management. John teaches graduate and undergraduate management courses and conducts research examining the relationships existing between information anxiety, organizational memory loss, and contemporary knowledge management theories. In 2004, whilst acting as director of knowledge management at National Defence Headquarters in Ottawa, he accepted an associate professorship at Minot State University, retiring at the rank of Lieutenant-Colonel. John is an award-winning researcher who speaks regularly on the subject of knowledge management and how enterprises may reap the benefits of creating and exchanging organizational knowledge. He has spoken in the US, Canada, Europe, Asia, Africa, Australia, and South America at such events as KM World, APQC’s Knowledge Management Conference, the World Congress on Intellectual Capital, KM Australia, and many others events – see www.johngirard.net.

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Acknowledgment

I would like to acknowledge and thank all of those involved in the development of this book. The entire team at IGI Global was very supportive and helpful. In particular, I wish to thank Julia Mosemann, the Development Editor at IGI Global. Her patience was amazing (and appreciated) while her guidance was always timely, useful, and valued. The team of reviewers deserves special attention as they very generously provided their time and expertise to ensure a high-quality review process. Often the work associated with chapter review is underestimated and forgotten – thanks to all of you for your great work. I owe a huge debt of gratitude to my best friend, partner, and soul mate, JoAnn Girard. As the defacto coeditor of this book, JoAnn spent literally hundreds of hours reviewing the chapters. Without her attention to detail, eye for errors, and remarkable knowledge, this volume never would have come to fruition. In addition to her amazing editorial prowess, she provided unconditional support and encouragement throughout the entire process – thanks for everything! Finally I would like to thank the leading researchers and practitioners who contributed chapters to this book. Without their insights this book would simply not be possible. John P. Girard, PhD Editor [email protected] www.johngirard.net

Section I

The Enablers of Organizational Memories



Chapter I

Organizational Culture and the Management of Organizational Memory Peter Stoyko Canada School of Public Service, Canada

ABSTRACT This chapter describes how organizational culture is both a “vessel” for preserving organizational memory and a force that conditions the way organizational memory is managed by other means. A detailed breakdown of the specific elements of organizational culture is conducted in order to describe this dual relationship. It is argued that the goal of managers should be the creation of a learning-oriented culture while avoiding the politicization of culture. Given that culture can not be manipulated directly, managers need to develop a sophisticated repertoire of leadership skills and a keen sense for sociopsychological dynamics. Specific advice on this count is offered at various points.

IN More and more managers are using the language of organizational culture and corporate culture. It is not difficult to imagine why. Many managers want to know how people come to share perceptions, interpretations, and attitudes, as well as how workplace symbolism shapes the way people feel and act. The goal may not be conformity per se, as there are countless benefits to intellectual diversity. Nonetheless, there is a widespread belief

that certain types of intellectual commonality can reduce unproductive conflict, promote collaboration, and align work towards a single purpose—all without the need for overbearing supervision. There is also something about cultural pride that can lift the heart and inspire the mind to better serve the common good. Organizational culture is a potentially powerful force. That potential goes largely unrealized. It is partly due to the non-instrumental nature of culture. An organization’s culture can not be

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Organizational Culture and the Management of Organizational Memory

manipulated directly, as a manager might allocate resources or dictate a course of action. Culture is influenced indirectly and evolves erratically over time. The deliberate influencing of culture requires a sophisticated repertoire of leadership skills and a keen sense for socio-psychological dynamics. Organizational culture also goes largely untapped because of its multidimensional nature. When we speak about culture, we are actually referring to several distinct things: from the shared principles people espouse to the open secrets people fain ignorance of; from fickle fads and fashions to enduring taboos and norms; from arduous rites of passage to the status symbols of power; the list goes on. This complexity is not widely recognized. Despite four decades of scholarship on organizational culture, the term is used in countless ways, usually without precise meaning. In the workplace, wherever conceptual laxity and empty buzzwords reign, sloppy thinking and cynicism are sure to prevail. Much needs to be done to rehabilitate the concept for general consumption. Knowledge managers have a big stake in this rehabilitation. Organizational culture relates to the management of organizational memory in two ways. First, organizational culture is a means by which meaning is transmitted over time within a workplace. Workers pass down lessons through oral histories. Knowledge is embedded in collective work habits. The shared assumptions and mental models that evolve within a collective frame the way work is understood and decisions are made. These are all examples of how organizational culture is a “vessel” that contains ideas and experiences from the past. Second, organizational culture influences the way information and knowledge is shared and preserved by other means. For example, the bonds of trust formed within a workplace affect how candid and direct workers dare to be. Social boundaries, such as those which surround cliques, can undermine the flow of information. Values and norms can affect people’s willingness to reflect on work and



codify worthwhile lessons. These examples show how culture is part of the work environment that conditions the way people think and act. This chapter will explore the complexities of how organizational culture and organizational memory intertwine. This includes a discussion of the cultural features that help or harm the management of memory. One particular set of features is helpful: a learning-oriented culture of candor, constructive debate, joint reflection, respect for the past, and habitual knowledge sharing and preservation. A very different set of cultural features is harmful: a politicized culture of internecine conflict, territoriality, fad surfing, and sharky, egoistic careerism. What can a manager do to cultivate the good and weed-out the bad? The chapter will provide answers to that question at various points. Some comments about the future will round-out the discussion.

ORGANIZAIONALre If you ask a sample of managers about what they think “organizational culture” means, two typical responses will emerge. The first response is the notion of culture as a unified social and ideological orientation. For example, the managers may talk about an organization as having a “bureaucratic culture” or an “entrepreneurial culture.” They are speaking metaphorically about an organization as having a general attitude, disposition, or “personality.” The culture may be described as “strong” or “weak” (i.e., more or less coherent, evident, and changeable) but, other than that, any specific features will likely be described in vague, impressionistic terms. The second typical response is the notion of culture as a social milieu or climate. This can include any aspect of the social and physical context that influences the way people feel and think about their workplace. The culture may be described in terms of the general “currents” (or other environmental metaphor) that push and pull individuals in particular directions

Organizational Culture and the Management of Organizational Memory

or lead them to think in particular ways. Managers may also speak about the aesthetics, acoustics, and frenetics of an organization—those things which give the place a palpable “vibe.” Uncoincidently, both notions of organizational culture have analogues within the management literature. Most pop management and leadership books that address organizational culture will describe it as a unified orientation or sense of “weness” (collective identity and social cohesion). This literature evolved with the rise of the pop genre in the 1980s, although there is a scholarly variant that dates back to the late 1960s. In contrast, the organizational climate literature was launched in the late 1930s, specifically Lewin et al. (1939). Historically, this literature has been broader in scope and more quantitative. Today, the notions of organizational climate and organizational culture tend to be used interchangeably in management parlance, with climate used less. The term “climate” is most often invoked by authors looking specifically at workplace conditions and social threats (e.g., a “climate of fear and intimidation” and a “climate of hostility and intolerance”). These depictions of organizational culture are problematic for several reasons. The most obvious problem is the mixing of metaphors, a sure sign of the lack of theoretical clarity. The bigger problem is the heavy reliance on a purely metaphorical characterization in the first place. If organizations only have cultures in a vague, metaphorical sense, then it is difficult to make precise and verifiable claims about the role of symbolism and attributed meaning in the workplace. Yet organizations, like other types of long-standing social collective, can have cultures in the literal sense. When resorting to metaphor, it is also difficult to determine where organizational culture begins and ends. Many scholars and practitioners have treated culture as potentially anything within the organization. Any concept that means potentially anything is just not useful as a concept. These frustrations led Andrew Pettigrew (1979) and several followers (notably: Lundberg,

1990; Hatch, 1993 and 2004; Martin, 2002) to unpack the concept of organizational culture and itemize the component elements. This chapter builds on these efforts with the aim of creating a nearly comprehensive list. This is important because it allows us to see how specific aspects of organizational memory relate to specific elements of organizational culture. Before that can be done, it is necessary to say a few words about selection criteria while stipulating a definition. An organizational culture signals to workers what is acceptable, what is worthwhile, and what makes sense. These signals are acquired gradually as a person learns from older hands and gains a sense of membership in a collective—a process of acculturation. Lundberg (1990) best describes the defining features of an organizational culture: Organisational culture is: a shared, common frame of reference, i.e. it is largely taken for granted and is shared by some significant portion of members; acquired and governs, i.e. it is socially learned and transmitted by members and provides them with rules for their organisational behaviour; a common psychology, i.e. it denotes the organisation’s uniqueness and contributes to its identity; enduring over time, i.e. it can be found in any fairly stable social unit of any size, as long as it has a reasonable history; symbolic, i.e. it is manifested in observables such as language, behaviour and things to which are attributed meanings; at its core, typically invisible and determinant, i.e. it is ultimately comprised of a configuration of deeply buried values and assumptions; is modifiable, but not easily so. (p.19, emphasis added) It follows that culture does not include social structures but is about the shared symbolic and acquired-psychological aspects of the workplace (to draw from a traditional sociological distinction between social structures and belief systems). A culture does not have to be shared by everyone. Indeed, many workplaces contain distinctive



Organizational Culture and the Management of Organizational Memory

subcultures within internal groups and in rare cases these may actually oppose the dominant culture (contracultures). Not every organization will have a fully fledged culture or even a culture at all. Some time must pass and shared experience accumulate before a culture coalesces within a collective. The component elements of organizational culture are listed in Figure 1 (Stoyko, 2009). The elements are grouped into three categories: (1) ideas and attitudes, (2) behaviors, and (3) object orientations. The inclusion of physical objects might be considered controversial at first blush. What is being referred to here, however, is only the socially constructed perceptions of the physical work environment. For example, the arrangement

of the physical work environment into cubicles and offices is not an aspect of culture, although it is a design decision that is often influenced by organizational culture. In contrast, there is a social status associated with having an office and a higher status associated with coveted office space. This social status, along with other widely recognized meanings attributed to workspaces, is an aspect of culture. Think of organizational culture as an iceberg with most of it unseen because it sits below the surface of the water. The visible part—the peak jutting out of the water—includes language, fashion, lore, vision, and group routines. The part around the waterline that takes effort to see but is nonetheless observable includes spirits, aspira-

Figure 1. Elements of organizational culture IDEAS & ATTITUDES Shared Values & Principles Fashions (prevailing styles, fads, and aesthetic preferences) Opinion Conformity Collective Identity (group and organizational) Shared Vision and Aspirations (i.e., image of desired future and future achievement) Common Language (terminology, phraseology, metaphors, concepts, body language such as gestures, symbols) Shared Assumptions, Core Beliefs, and Mindsets (ideology/world view/ philosophies, issue orientation/policy disposition, mental models/ theories/classification schemes, blind-spots, habits of thinking,) Spirits (workforce morale, camaraderie/esprit de corps, mood/“buzz”) Group Bonds of Trust (a.k.a. “social capital”) Common Knowledge (shared semantic understanding and how-to) Workplace Lore (myths/legends/stories, oral histories, accepted gossip, insider jokes, open secrets) BEHAVIOURS Social Regulation (manners/social graces, norms and taboos; i.e., the informal “rules of the game”) Observance of the Past (customs, traditions, rituals, rites of passage) Informal Group Routines and Habits (including embedded skills) Group Dynamics (informal group boundaries, cliques, alliances, informal roles, social and group status) OBJECT ORIENTATIONS Widely Recognized Symbolic Meaning Associated with Artifacts (notably status symbols) Atmosphere created by Physical Work Environment



Organizational Culture and the Management of Organizational Memory

tions, stable opinions, and preferences. The rest composes the largest portion of the iceberg, with the deep center of buoyancy being the values, assumptions, principles, and mental models. The visible is most readily diagnosable. The deep and invisible elements are the most difficult to detect and change because they are the most strongly embraced. They influence thinking in ways that are not always conscious and straightforward. Identifying them may require collective reflection exercises involving probative questioning, although the analytically astute observer with some critical distance may be able to surmise their content after careful study. Culture is knowable because of its shared nature but a trained eye is crucial. This description puts paid to the myth that organizational culture can be manipulated directly in an instrumental fashion. Culture can be changed quickly and decisively, but only insofar as any aspect of an organization can be vandalized by the powerful in short order. For example, group bonds of trust form after a long track-record of honesty, openness, consistency, mutual consideration, and reciprocity. Yet these bonds can be broken by a quick succession of betrayals by a cadre of managers. Likewise, management interventions that lead to high levels of employee turnover may cause a culture to even loose deeply held values and principles in a relatively short span of time. Many advocates and demonstrators of core values may flee and their cherished values supplanted by those of newcomers—a situation that often happens during mergers or other major reorganizations. The manager’s introductory lesson to organizational culture is to first do no harm, especially if that manager happens to parachute in from outside of the organization. How does a manager develop the “antenna” required to properly diagnose the state of an organization’s culture? It starts with an active presence in the workplace and a commitment to ernest conversational exchange with others. Many managers remain aloof because they lack a basic

situational awareness and access to “street level” cultural signals. Situational awareness includes attention to socio-psychological details (related to interpersonal and group dynamics), including the nuances and subtleties of communication and attention. This is helped greatly by thinking in terms of the component elements of culture outlined here. More will be said about each element and the leadership interventions that are beneficial. For the moment, it is sufficient to acknowledge the diagnostic complexities involved.

ORGANIZAIONALre AS VESSEL OF MEOR In a society, culture tells people who they are and where they have been, including the seminal ideas that have moved the society forward. An organizational culture serves much the same purpose as a “vessel” of collective memory. Organizational culture is a roll-up of the experiences, observations, formative events, preferences, and lessons over time. Those things that do not resonate with the larger population and people in positions of persuasive authority are usually filtered out. Ultimately, the fragments that remain are molded into something coherent that most members can relate to (consciously and unconsciously). This coherence has its own inertia, so that new experiences and lessons are compared and judged according to what has come before. Culture is a living memory. Yet, as this description implies, this memory is not entirely composed of knowledge (defined as semantic understanding and how-to), information (declarative statements), and “wisdom” (axiomatic statements). This makes a portion of organizational culture less interesting to knowledge managers who are focused on culture as a vessel of useful meaning from the past. Things such as tastes, preferences, and group bonds do not generally offer knowledge preservation as such.



Organizational Culture and the Management of Organizational Memory

Organizational memory embedded in culture is not necessarily accurate given that the filtering process is highly fallible. Organizational cultures that generously accommodate divergent ideas or place a high value on novelty are less censorious. However, in most organizational cultures, valuable knowledge will likely be filtered out if it is deemed heterodox: ahead of its time, behind the times, beside the point, of dubious worth, contrarian, eccentric, et cetera. These are labels that are normally attached to things which do not conform to deeply held assumptions, values, principles, and mental models (the cultural core). Indeed, societal cultures throughout history have inspired institutional resistance to innovative artists, discoverers, and philosophers who were then forced to toil in obscurity unless they were lucky enough to find a powerful sponsor and champion. When looking at the enduring lessons found in organizational myths and oral histories, for example, the revisions, omissions, and erosions ought to be taken into careful consideration. An organization’s memory is knowledge, information, and experience that can be brought to bear on the present, although that use may not necessarily bring about improvement (Stein & Zwass, 1995, p. 89). An uncritical over-reliance on past knowledge can make it difficult for organizations to adapt to changing circumstances. For example, organizational memories may be bad if they “lead to bias against necessary change, conformist tendencies, an unhealthy fixation on past mistakes, and a reluctance to consider worthwhile ideas from elsewhere.” (Stoyko and Fang, 2007, p. 12) Organizational memory is not a substitute for intelligence, it merely serves intelligent thinking (Spender, 1996). A robust organizational memory is one in which knowledge is mirrored in many places throughout the organization (Morgan, 1996, pp. 92-106). If a piece of knowledge is lost because, for instance, a document is destroyed, then it still exists elsewhere in the organization and a good document management system will retrieve it



with relatively little fuss. Given that cultural knowledge is necessarily shared, it is mirrored in many places within an organization, making it a particularly durable form of memory. Thus, although culture is a partial and highly fallible form of organizational memory, one advantage is durability. Sometimes this durability may only be in the forensic sense; that is, if an organizational culture erodes significantly after several major downsizing and employee defections, as an example, then valuable knowledge may be pieced together by interviewing experienced employees who continue to serve as custodians of old stories, linguistic conventions, animating concepts, and such. Organizational memory management is often a form of triage and retrieval (Delong, 2004). Which elements of organizational culture can act as a “vessel” of useful knowledge and information? The rest of the section revisits Figure 1 to answer that question. The most obvious “vessel” is common knowledge, or semantic understanding and how-to understanding that are shared by a broad crosssection of employees. Semantic understanding is insights about ideas, objects, and events, as well as how they operate (Sparrow, 1998). How-to understanding is insights about the way things are accomplished, including tacit feel, skills, and unconscious interpretations (Ibid). Common knowledge can have a short shelf-life because it is only useful for the duration of a project, tenure of a governing executive, or the existence of a strategy. This type of common knowledge can not be said to be imbedded in culture. It becomes part of the culture as it is actively passed along to new employees, through formal teaching (e.g., orientation sessions, mentorship relations, and on-the-job training) or informal and spontaneous knowledge sharing. This knowledge sometimes comes in the form of “the tricks of the trade”; that is, proven rules-of-thumb that are circulated by members of occupational and professional groups throughout an organization.

Organizational Culture and the Management of Organizational Memory

Workplace lore includes several types of accounts of the past which bestow useful lessons. Oral histories and stories—also called myths or legends if they achieve a reverence and become highly stylized—can convey knowledge in a way that is easy to relate to and retell. As Seely Brown and Duguid (2000) explain: Stories are good at presenting things sequentially (this happened, then that). They are also good for presenting them causally (this happened because of that). Thus stories are a powerful means to understand what happened (the sequence of events) and why (the causes and effects of those events) … More generally, people tell stories to try to make diverse information cohere … Stories, moreover, convey not only specific information but also general principles. These principles can then be applied to particular situations, in different times and places. (pp. 106-107) This powerful mechanism of knowledge transfer also comes with dangers. Distortions occur when shoehorning information into the story format, which requires protagonists, plot, episodes, and a dénouement. These distortions include adding extra drama, exaggerating claims, embellishing to cover-up gaps in knowledge, abandoning information that does not fit with the story-line, simplifying motives, and resorting to simplistic (mono-causal) explanations. Moreover, the anecdotal nature of evidence in stories can also lead to empirical errors. As Kida (2006) points out, statistical evidence is often a better basis for decision-making, yet statistics are routinely ignored because they tend to be dry and technically complex, whereas stories can be enjoyable and engage the imagination (p. 17). Shared assumptions, core beliefs, and mindsets contain information and knowledge, as well as frame the way people think about new knowledge. This includes an orientation towards the world in general (ideology, world view, and philosophy), a particular domain of knowledge (issue orienta-

tion and policy disposition), and a practical topic (mental model, theory, and classification scheme). When management pundits talk about the dangers posed by past success, they are referring to the ways in which previous methods of solving problems and thinking about issues become unquestionable despite outliving their usefulness. When these operate at the level of assumptions, belief, or mindset, they are more difficult to dislodge. Often, workers will disregard new information and knowledge that does not correspond to an existing mindset (confirmation bias) or jump to conclusions without considering new information at all (pre-mature cognitive commitment). For the manager, the goal is to help others avoid automatic ways of thinking and look at past contributions as simply one source of insight instead of embracing a singular perspective. This is the promotion of mindfulness, which involves being more conscious of cultural “scripts”, avoiding false barriers to thinking, paying greater attention to context, and being open to new categories and points-of-view (Langer, 1990, pp. 9-18; Van Hecke, 2007, pp. 133-143). Language is a conveyor of knowledge and a framer of thinking, although linguists dispute the specific mechanisms at play. The way concepts are defined and labeled, plus the use of metaphors and catch-phrases, help people understand various subjects. Even the simple act of labeling is a deliberate singling-out of something for special consideration. This can be especially helpful as precise terminology and insightful coinages becomes widely used and, in so doing, help others better understand complicated phenomena. The coinage or adoption of new terms and metaphors can also help leaders persuade in subtle but lasting ways. There is a danger when buzzwords, loaded terms, and clichés are used habitually as a substitute for rigorous thinking. Indeed, the move towards passive sentence structures and latinate diction in English-speaking workplaces is arguably a sign of organizational cultures that discourage confrontational debate and encourage



Organizational Culture and the Management of Organizational Memory

the passive acceptance of claims (Watson, 2003; Humphrys, 2004). As Fritz Machlup (1962) observes, knowledge can be embedded in work processes. This can include informal, social patterns of work behavior, such as rites and rituals, as well as informal group routines, habits, and dynamics. Ideas about how best to do things often spread, becoming routine or habitual work practices. These cultural manifestations are rarely sanctioned officially, although they can form part of an “unwritten curriculum” as experienced workers teach less experienced ones. In some cases, these practices can be undesirable habits that allow people to shirk responsibilities or do the minimal requirements (satisfice). Organizations with poor labor relations often give rise to peer pressure among classes of workers that ensure these habits persist as part of the culture. As this overview stresses, organizational culture can be a useful yet imperfect “vessel” of organizational memory. The shortcoming is not that knowledge, information, and experience from the past are partial. Filtering is a necessary part of culture and other parts of organizational activity. However, this filtering is biased by the specific medium (to obliquely paraphrase Marshall McLuhan) and can potentially distract attention from sources of better, new knowledge. Managers ought to keep these biases in mind to achieve the critical distance necessary to identify and diagnose the state of organizational memory.

ORGANIZAIONAL AS CondONDIIONEROF MEOR Nancy Dixon (2000) claims that one of the big misconceptions of knowledge management is that organizational culture must change before widespread knowledge transfer can occur (pp. 2-6). That is certainly true for all but the most poisoned workplaces. Dixon is speaking about the widespread misconception that culture must



change as a prerequisite for any kind of effective organizational change. Yet it is equally true that technological and organizational systems can not be implemented in a purely asocial way if they are to be successful. Knowledge management techniques designed to preserve organizational memory—from the more technological, such as electronic document repositories, to the more social, such as communities of practice—are inherently socio-technical systems. The technologies and formal procedures require users (as individuals and groups) to learn and adapt to some degree. Conversely, if a technology is to avoid languishing underutilized, it has to be designed and implemented in a way that accommodates individual proclivities and social circumstances. Culture plays a role on both sides of this equation. Even if a supportive organizational culture is not strictly a prerequisite for the systematization of knowledge transfer, there are several elements of culture that act as obstacles. Identifying and coping with these obstacles is a determinant of success. Therefore, it is useful to revisit Figure 1 and look at how culture plays a role in efforts to manage organizational memory. Along the way, the ideal features of an organizational culture will emerge. Taken as a whole, this culture can be thought of as a learning-oriented or a learning-supportive organizational culture. A few disclaimers are in order. Organizations rarely have monolithic cultures that can be aptly described with a tidy label. It is also a mistake to assume that there is only one type of organizational culture that is conducive to the effective management of organizational memory. Finally, as Rozenzweig (2007) points out, research on the cultural attributes that lead to success tend to be biased by the halo effect: respondents to surveys and interviews tend to uncritically perceive organizational cultures as having desirable attributes if they also think that the organization is successful. That said, it is still possible to pro-

Organizational Culture and the Management of Organizational Memory

vide constructive insights into beneficial cultural characteristics. Flows of information and knowledge can be undermined by organizational boundaries. Not enough attention is accorded to informal group boundaries that form around cliques, alliances, and occupational groups. These groups regulate access to insider information and knowledge, as well as determine who gets to be an insider. They are often difficult to spot until patterns of communication, networking, and friendship are observed over time, or until members of a subgroup tip their hand and overtly acknowledge their social status and allegiances. A variety of dynamics can also develop between groups, such as when members of one informal group or alliance become hostile towards another group. This type of behavior also poses the risk of group-think, or the tendency of an isolated group of individuals to repeatedly reaffirm prevailing opinions without benefiting from corrective outsider perspectives. On a related note, a great deal of scholarship has taken place on the relationship between bonds of trust and the sharing of information (e.g. AlAlawi et al., 2007). As mentioned, bonds of trust form as members of a group behave with honesty, forthrightness, consistency, mutual consideration, and reciprocity. These bonds do not have to form between each pair of individuals in a workplace in order for a workplace to be considered to have high levels of trust. In most cases, what employees look at are the relationships that have built-up between themselves (and those in similar circumstances) and supervisors. People want to be treated with due regard and fairness. They also want the psychological safety to be able to speak candidly, forthrightly, and authentically without fear of reprisals if they say something that others disagree with or object to. Thus, information and knowledge is shared most (and hoarded least) when the prevailing culture gives people the sense that they are in a “safe space” for social interaction. Information and knowledge will be better scrutinized to ensure quality and relevance

when people are able to critique openly and have acquired the social graces to do so constructively and considerately. Group norms and taboos can also influence information sharing. In some organizational cultures, the failure to share vital information can result in snubs, rebukes, sarcastic jabs, ostracism, or other social sanctions. Yet in other organizational cultures, the sharing of information to the wrong people (or to right people in the wrong order) may result in similar sanctions. In either case, norms dictate what is acceptable and expected of people. These are the informal “rules of the game” that regulate behavior. These norms can also encourage collaboration. For example, the Internet-search firm Google is noteworthy for developing norms that encourage employees to help others solve problems when a general request for aid is circulated via email or instantmessaging system. Those who are seen as helping the most—repeatedly sharing their expertise on-the-fly with seemingly little effort—are seen as heroes, whereas those with little to contribute are often made to feel guilty. This has little to do with official job requirements. There is no written rule. It is the organic development of reciprocal expectations within a highly cohesive and pressure-filled workplace. It comes with a downside—personal stress, guilt, workload, and burnout—but nonetheless supports the reapplication of existing knowledge and expertise. Group spirits and collective identity can go a long way towards encouraging knowledge sharing and preservation activities. As people see themselves as members of a larger collective—one in which they recognize their own personal identities and aspirations as reflected—they are more willing to expend discretionary effort on memory management tasks (e.g., codifying what they know). Indeed, these organizational citizenship behaviors tend to be more prevalent in organizations with higher levels of morale, camaraderie, and job satisfaction (and are influenced by noncultural factors, such as the nature of job tasks).



Organizational Culture and the Management of Organizational Memory

Without a prevailing cultural sense of the common good, people have less intrinsic motivation and enthusiasm for preserving the shared history of the organization. It is difficult for a worker to see the point of expending the extra effort. Moreover, organizational cultures with clear visions and aspirations—those that are widely held instead of those which are simply written down after a contrived group exercise—are more likely to develop a coherent identity. As Podsakoff et al. (2000) point out, there are a number of different types of organizational citizenship behavior (pp. 516-526), some of which have a more obvious relationship to knowledge sharing and preservation. When an organization’s knowledge management system requires extra work, then “sportsmanship” behaviors (tolerance of inconveniences and impositions) and organization compliance behaviors (obedience to rules, procedures, and protocols) help ensure followthrough. As mentioned, helping behaviors and “civic virtue” (commitment in the organization as a whole) are important for voluntary and impromptu memory management. Most importantly, self-development behaviors include an interest in continually updating knowledge and skills, which is a key mechanism by which shared knowledge is renewed and stewarded over time. All told, the combination of the availability of organizational learning mechanisms (e.g. formal systems for scanning, storing, and disseminating information) and a supportive learning culture play a significant role in promoting these behaviors (Somech and Drach-Zahavy, 2004, p. 293). Self-centered work-flows and work-styles are major barriers to knowledge sharing. As lone workers do their jobs in isolation, pockets of knowledge build up that escape the notice of colleagues and remain vulnerable to loss. Interdependence and ongoing sharing are instrumental to mirroring knowledge and reducing that vulnerability. These work-flows and styles are mostly a function of job design, the information technology infrastructure, and the design of formal

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procedures. These are structural, not cultural, aspects of the workplace. Yet informal group work routines and habits can help or harm knowledge sharing regardless of the structural amenities in place. Indeed, self-centered work-flows and styles can be an undesirable “cultural residue” from a previous reliance on highly discrete and specialized job arrangements. Such situations are further reinforced if the culture lacks teamwork values (e.g., an acknowledgment of the mutual benefits of multidisciplinary or multifunction collaboration) and principles (e.g., a clear understanding how credit is to be shared in a team to preserve fairness). Moreover, collaborative values improve uptake of knowledge management technologies, although the use of technologies can also be uneven because of the influence of local subcultures (Alavi et al., 2006: 216-217). Reflecting on both recent experience and the distant past have a basis in group attitudes and informal habits. A general respect for the organization’s past and traditions, as well as the contribution of experienced colleagues, should be encouraged so long as it does not lead to a hidebound focus and uncritical acceptance of received ideas. The ability to routinize informal reflection on experience and then sharing the lessons learned is a source of organizational memory. Indeed, studies of after-action reviews—brief postmortems for teams focused on answering a battery of questions that are essential for drawing constructive lessons—have shown that they are particularly effective when they pass from being formal requirements to informal habits. This overview has described many of the cultural dynamics that shape the management of organizational memory. The main theme of this overview is that learning-oriented cultural elements are particular beneficial. However, management is as much about mitigating the bad as fostering the good. This leads us to a discussion of the more severe ways organizational culture can undermine memory management.

Organizational Culture and the Management of Organizational Memory

THE POLITICIZED ORGANIZATIONAL CULTURE When most of us think about organizational politics, we usually think of the discord caused by highly ambitious, conniving, and unscrupulous villains—the cynical Machiavellis of the world of work. The truth is that all workers regularly engage in political behaviors, either consciously or unconsciously. These are surreptitious actions that benefit an individual at the expense of colleagues or the general welfare of the organization. Manipulative interpretations (spin) of the meaning of information and knowledge are widespread, as are the organizational pressures to “sell” messages with trickery. This happens in service of either personal self-interest, the interests of a work unit, or an ideology. Indeed, very little information and knowledge that exists in the workplace can be considered politically neutral. Most people are not accomplished “office politicians” but are nonetheless drawn into political struggles on a regular basis. Organizational culture plays a central role in regulating and encouraging political behavior. Many politically manipulated meanings are embedded in the language and knowledge contained within a culture. Culture determines which political moves raise eyebrows and which are waved-off as “par for the course.” Knowledge managers need to be aware of the dangers of politicized organizational cultures because they tend to be particularly detrimental to the management of memory. For example, cultures that encourage individual power-brokering and competitiveness will motivate people to hoard information (DeLong and Fahey, 2000). This section itemizes a number of politico-cultural threats to organizational memory management. This is not an exhaustive list of threats but a list that managers ought to be particularly wary of. Few things are more likely to sever bonds of trust and poison work-relations than destructive careerism. Destructive careerism includes credit-

claiming behaviors, blame-avoidance behaviors, ingratiation behaviors, and other forms of impression management—all intended to advance a person’s career at the expense of others. These are highly divisive when they involve dishonesty, unfairness, undue manipulation, and roguish egoism. This has an impact on the management of memory, as it can result in everything from hoarding information to sabotaging it. That much is obvious. Beyond the obvious, there is a particular group of informal careerist tendencies that, when embedded in or condoned by culture, can harm organizational memory. The most common and effective ingratiation behavior is opinion conformity (Rosenfeld et al., 1995, p. 35). Revisiting Figure 1, the formation of prevailing opinions is a form of culture. Yet, when people conform their opinions at the behest of the wrong motives (such as getting a step up the job ladder) then they damage the collective good. When this conformity involves turning a blind eye to flaws in information and knowledge, then organizational memory will carry forth the flaws that potentially undermine future decision-making. When this opinion conformity becomes a part of the culture, it can also have a long-lasting distortionary effect on the interpretation and application of information, which further undermines the effective functioning of memory management. Fad surfing is the habitual adoption of new ideas and courses of action based solely on novelty, superficial appeal, or personal benefit. Its prevalence is a symptom that past lessons are undervalued within a culture, a big sign of memory management problems. Novelty is prized without careful consideration of what has gone before. New fads arrive with much fanfare but, once a fad peters out, there is a disincentive to draw constructive lessons from the episode. Those who overzealously supported the fad may be embarrassed by a postmortem or may harbor grudges against those who did not jump onto the bandwagon (Best, 2006). Or the next fad has

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Organizational Culture and the Management of Organizational Memory

already been launched, leaving little opportunity to take stock of the previous one. Both situations prevent organizational memory formation. Faddish agendas tend to be articulated using vague buzzwords and promises, which make it easier for them to be sold because they can mean “all things to all people” and are thus difficult to pin down and rebut (Ibid). Moreover, buzzwords often outlive the fad within an organization’s shared language and add to an ongoing susceptibility to faddish thinking. This is the tainting of an organization’s memory with ephemera. Fad surfing may not simply be the act of a powerful decision-maker pursuing whims and self-aggrandizement. A culture that values novelty and an impatience for success over tried-and-tested methods will be susceptible to faddish thinking. Managers can offer a counter-weight by hailing the virtues of constructive skepticism, encouraging the consideration of risks and opportunity costs, and implementing practices that force the drawing of constructive lessons. Rankism is the valuing of knowledge, insight, and opinion based solely on the organizational or social status of the person offering it. It occurs when the formal position or social status of an individual determines how favorably particular claims and arguments are perceived, regardless of the merits of the case. Many half-truths and fallacies persist within an organization because they are not appropriately scrutinized. Meanwhile, important insights from those without a lofty status are ignored. Of course, in hierarchical organizations, the final decision-making power resides in the hands of those higher up. Rankism is different in that it is a type of fallacious thinking (the appeal to authority) combined with an enduring allegiance to particular ideas because of the status of those who are the original advocates. Accurate and reliable organizational memories do not come with this cultural baggage. A great deal of information and knowledgemanagement technology relies on clarity of meaning. Meta-tagging protocols for labeling

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documented information, for example, can accommodate many different synonyms and slang terms to help people find what they are looking for. Unfortunately, these systems breakdown when evasive language and spin-doctoring become part of the culture. Evasive language is the use of vague buzzwords, loaded terms, clichés, and catch-phrases to obscure meaning. This typically happens when people are trying to hide gaps in knowledge or make themselves look smart. Spin-doctoring is the deliberate manipulation of language in order to unduly and surreptitiously influence others or distract attention. For knowledge managers, these tendencies undermine findability, to use Peter Morville’s term (2005). Findability is the ability to discover and access relevant information as required, an essential characteristic of any document system designed to preserve memory. Moreover, evasive language and spin-doctoring undermine the ability to make productive use of information once found because it contains vague and slippery advice. Here the manager’s job is to promote plain language, such as precise terminology, clarifying definitions, and active verbs. Calling-out suspected evasion with probative questions (and encouraging others to do so) is an important countervail. These measures only have widespread impact if they become a common habit and shape the way language is used in the workplace. These measures are not designed to eliminate jargon (such as legalese) that comes into an organization through employees who are also influenced by a cross-cutting professional or occupational practice. Professional jargon serves an important function and, from the knowledge manager’s point-of-view, tends to be easily defined and well referenced. Open secrets or “conspiracies of silence” are cases whereby “a group of people tacitly agree to outwardly ignore something of which they are all personally aware.” (Zerubavel, 2006, p.2) It is essentially a form of common knowledge that reveals uncomfortable truths and is therefore

Organizational Culture and the Management of Organizational Memory

unmentionable and undiscussable in public (op. cite, p. 3). This is a unique vessel of organizational memory in that it can be preserved in hushed conversations between trusting individuals or be implicitly denied in countervailing myths and legends. A strange characteristic of open secrets is that mentioning them in a way that does not conform to the traditional “script” often invokes angry rebukes. Offended and scared people will demand that others leave the matter alone. All told, these open secrets are persistent inaccuracies within an organization’s memory and are driven by the force of culture. They are especially problematic in the way they discourage inquiry and memory retrieval. Highlighting an open secret and exposing it to reason will inevitably result in political animosity and a long-fought campaign of correction. The politico-cultural dynamic that knowledge managers are perhaps most familiar with is territoriality. This is the zealous guarding of a personal or group fiefdom within an organization. It can include the guarding of responsibilities, personnel, and resources. Territoriality makes any form of integrative management difficult. Given that the effective management of organizational memory involves breaking down organizational barriers to implement technologies and change work patterns, overcoming territoriality is a necessary struggle. Yet territoriality includes a specific variant that relates directly to the management of memory: controlling access to information, knowledge, and expertise. Often hoarding happens when someone is attempting to wield power in a self-serving way. Yet it can also become habitual as an individual or group gains a sense of ownership, propriety, or suspicion with respect to sought-after knowledge. As Simmons (1998) points out, territoriality can come in particularly malicious forms, such as: the hiding of employees and denying the existence of information; placing valuable information amid a haystack of other documents in order to conceal; and false cooperation that gives the impression of full disclosure (pp. 57-66).

The challenge with territoriality occurs when it has become culturally condoned within many workplaces. Many valid justifications exist to limit access to information. For example, the information may not be complete and ready for circulation. As another example, information may contain trade secrets (private sector) or national-security secrets (public sector). These are relatively straightforward cases for knowledge managers to handle. Yet when territoriality becomes imbedded in culture—forming a habit to protect and conceal as an entitlement—it is particularly difficult to locate problematic cases and cope with them. The design of information and knowledge management systems is crucial for providing fewer opportunities for territorial manipulation. In the final analysis, managers wanting to promote the good and mitigate the bad have to demonstrate the behaviors they expect of others. This is where transformational leadership plays a role. Transformational leadership involves developing a personal mastery, integrity, and consideration for others as an inherent part of a person’s character. In other words, it is not simply a set of skills to be applied, but a vocation and a life style. Bonds of trust and the willingness of others to deeply consider certain messages depend heavily on managers developing this authentic form of leadership. Of course, the influence that a leader will have on a culture depends on the stage of cultural formation: it is easier to influence culture during the early stages of development than after the build-up of several years or decades of cultural meaning and behavior (Schein, 2004). Yet there is a strong correlation between transformational leadership among senior decision-makers and the use of organizational learning mechanisms, as well as a correlation between a learning-supportive culture and the use of such mechanisms (Barkai and Samuel, 2005, p. f5). This type of leadership is a factor in promoting organizational citizenship behaviors (Podsakoff et al., 2000, p. 516). Most importantly, the honesty and integrity

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Organizational Culture and the Management of Organizational Memory

modeled by leaders—as well as outward signs of supportiveness for openness, debate, truthfulness, and differing views—will generate a shared belief in the value of disagreement and questioning, as well as the norms of truthfulness and candid communication (Serpa, 1985, p. 429).

THE FUTURE OF ORGANIZATIONAL CULTURE AND MEMORY The picture only gets more complicated as we look ahead to what the future might bring. Socio-economic changes in economically advanced democracies, coupled with changing workplace norms, will most likely make it more difficult for knowledge managers to tap organizational culture. Societies are becoming more ethno-culturally and intellectually diverse. Populations are also becoming less deferential towards authority of all kinds. It is possible to overstate the tendency of younger generations to be less conformist and more individualist: every generation thinks of itself as more rebellious than the previous one. However, successive generations are weakening the hold that organizational culture has on their personal identities. Organizational cultures still play a major role in socializing young workers into the workforce—and will do so for the foreseeable future. Yet those cultures will have to be increasingly accommodating of individual variation and less reliant upon coercive forms of conformity. In many organizations, this implicit “social contract” will pay dividends insofar as intellectual diversity and greater autonomy are reliable sources of innovation. This might lead to greater worker empowerment but the reductions in cultural coherence will erode the cultural transmission of past knowledge and experience. Just as the implicit social contract in the workplace is changing, so is the explicit employment contract. For a long time, people used to self-identify with their organization. For example, a person

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might think of themselves as an “I.B.M. man” or a lifelong civil servant. Today, people are more likely to switch employers repeatedly throughout their career, as well as have more than one career during their life time. They see their career as part of their personal identity, but do not form the same personal identification with an organization. In some industries and cohorts, employee turnover is extremely high, with people climbing job ladders with successive moves up-and-out to other organizations. There are two main implications of this trend. First, turnover is a major cause of organizational memory loss. Higher turnover and lower organizational attachment are also causes of less stable organizational cultures. This makes it more difficult for organizations to develop coherent collective identities. It also makes it more difficult for managers to rely on organizational culture as a vessel of memory unless there is a stable core of old-timers to act as culture bearers. Second, this trend will likely cause workers to become more inter-culturally aware. People develop exposure to a larger number of organizational cultures and learn to function according to a wider array of socio-psychological dynamics. It is expected that people will develop preferences, which in turn will compel organizational cultures to become less punctilious (abiding, discreet, careful, and imitative) and more accommodative (open, tolerant, flexible, and improvisational). This pressure will only increase as the competition for scarce talent intensifies due to demographic change and the growth of knowledge-intensive work. The tendency of organizations to externalize a significant portion of their functions has led to an erosion of organizational memory. Organizations are increasingly surrounded by constellations of contractors, suppliers, and freelancers. When finished with a project, much of the organizational memory leaves along with the out-sourced labor. This trend further undermines organizational culture as a conveyor of past experience. As functions become less organizational and more transactional with networks of outsiders, organizational culture

Organizational Culture and the Management of Organizational Memory

is maintained by a smaller population. Outsiders are not carriers of organizational culture because they lack the prolonged exposure to others within the collective. They may have insights about the culture because they are detached observers but they will almost always lack an intimate knowledge of it. As organizations become increasingly multinational, the cultures of organizational branches will usually take on a very different character due to the intermingling influence of local and national cultures. This is a common source of organizational subcultures, as more than one culture suffuses together to create something different. Even with the spread of international business norms and fashions, local and national cultures will continue to influence worker values, attitudes, and behaviors. Fortunately for organizational memory management, organizational culture can potentially have a mediating effect on the more self-centered or distrusting aspects of a local or national culture (Pauleen et al., 2007, pp. 13-14). The traditional knowledge embedded in local and national cultures may also prove useful for members of the larger organization (Mason, 2007), thus having a cross-fertilizing influence.

CONCLUSION This chapter has stressed the dual nature of organizational culture with respect to organizational memory. Organizational culture serves as a “vessel” of organizational memory. It also conditions the way organizational memory is preserved by other means. To fully understand how culture serves both purposes, it is necessary to look at the specific elements that make up culture. As this is done, it becomes clear that organizational memory is not a panacea. The way organizational culture filters and encodes memory is highly fallible and results in many potential distortions. Culture can also serve as both an enabler and barrier to organizational memory management. Culture can

breed a hidebound conservatism and it can lead to destructive politics. Yet a culture that supports learning can supplement and enhance sociotechnological systems for preserving memories. As the relationship between organizational culture and organizational memory is described, advice is offered to managers about what to do to create a culture that supports learning. Managers are advised to develop an understanding of the elements of culture and, as a matter of first resort, refrain from damaging a culture unknowingly. As cultural elements and dynamics become more familiar, the manager ought to maintain an active presence in the workplace, gain a situational awareness, and actively glean cultural signals. Developing a culture that supports learning involves creating a “safe space” wherein people can speak candidly, reflect on what they do, and act authentically. Yet, an influential leader plays a significant role by ensuring this psychological safety and modeling the behaviors expected of others. This includes a cultivation of mindfulness, respect for the past, use of plain language, and constructive skepticism. When routinized and valued, these practices fuel the necessary scrutiny to improve the substance of an organization’s memory and improve the application of that memory. It also involves the combating of divisive politico-cultural dynamics that eat away at the integrity of an organizational memory. These are not quick fixes but long-term commitments.

REFEREN Alvesson, M., & Berg, P. O. (1992). Corporate culture and organizational symbolism. New York, NY: Walter de Gruyter. Alavi, M., Kayworth, T. R., & Leidner, D. E. (2006). An empirical examination of the influence of organizational culture on knowledge management practices. Journal of Management Information Systems, 22(3), 191-224.

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Al-Alawi, A. I., Al-Marzooqi, N. Y., & Mohammed,Y. F. (2007). Organizational culture and knowledge sharing: critical success factors. Journal of Knowledge Management, 11(2), 2242. Barkai, I., & Samuel, Y. (2005). The use of organizational learning mechanisms: environmental, managerial, and cultural correlates. Academy of Management Proceedings, f1-f6. Best, J. (2006). Flavor of the month. Berkeley & Los Angeles, CA: University of California Press. Chang, S. C., & Lee, M. S. (2007). A study on relationship among leadership, organizational culture, the operation of learning organization and employees’ job satisfaction. The Learning Organization, 14(2), 155-185. Chen, C. J., & Huang, J. W. (2006). How organizational climate and structure affect knowledge management: the social interaction perspective. International Journal of Information Management, 27(2), 104-118. DeLong, D. W. (2004). Lost knowledge. Oxford: Oxford University Press. DeLong, D. W. & Fahey, L. (2000). Diagnosing cultural barriers to knowledge management. Academy of Management Executive, 14(4), 113127.

Humphrys, J. (2004). Lost for words. London: Hodder & Stoughton. Kida, T. (2006). Don’t believe everything you think. Amherst, NY: Prometheus Books. Knapp, E. & Yu, D. (1999). Understanding organizational culture: how culture helps or hinders the flow of knowledge. Knowledge Management Review, 2(1), 16-21. Kotter, J. P. & Heskett, J. L. (1992). Corporate culture and performance. New York, NY: Free Press. Lai, M. F., & Lee, G. G. (2007). Relationship of organizational culture towards knowledge activities. Business Process Management Journal, 13(2), 306-322. Langer, E. J. (1989). Mindfulness (New York, NY: Perseus Books). Lewin, K., Lippitt, R., & White, R. K. (1939). Patterns of aggressive behavior in experimentally created “social climates.” The Journal of Social Psychology, 10(3), 271-299. Lundberg, C. C. (1990). Surfacing organisational culture. Journal of Managerial Psychology, 5(4), 19-26. Machlup, F. (1962). The production and distribution of knowledge in the United States. Princeton, NJ: Princeton University Press.

Dixon, N. (2000). Common knowledge. Boston, MA: Harvard Business School Press.

Martin, Joanne. (2002). Organizational culture. Thousand Oaks, CA: Sage.

Hatch, M. J. (2004). Dynamics in Organizational Culture. In M. S. Poole & A. H. Van de Ven (Ed.), Handbook of Organizational Change and Innovation (pp. 190-211). Oxford: Oxford University Press.

Mason, R. (2007). Culture: an overlooked key to unlocking organizational knowledge. In D. J. Pauleen (Ed.), Cross-cultural perspectives on knowledge management (pp. 21-34). Westport, CT: Libraries Unlimited.

Hatch, M. J. (1993). The Dynamics of Organizational Culture. Academy of Management Review, 18(4), 657-693.

Morgan, G. (1996). Images of organization—executive edition. Thousand Oaks, CA: Sage.

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Morville, P. (2005). Ambient Findability. Sebastopol, CA: O’Reilly.

Organizational Culture and the Management of Organizational Memory

Pauleen, D. J., Wu, L-L., & Dexter, S. (2007). Exploring the relationship between national and organizational culture, and knowledge management. In D. J. Pauleen (Ed.), Cross-cultural perspectives on knowledge management (pp. 3-19). Westport, CT: Libraries Unlimited. Pettigrew, A. (1979). On studying organizational culture. Administrative Science Quarterly, 24(4), 570-581. Podsakoff, P. M., MacKenzie, S. B., Paine, J. B., & Bachrach, D. G. (2000). Organizational citizenship behaviors: a critical review of the theoretical and empirical literature and suggestions for future research. Journal of Management, 26(3), 513-563. Rosenfeld, P., Giacalone, R. A., & Riordan, C. A. (1995). Impression management in organizations. New York, NY: Routledge. Rosenzweig, P. (2007). The halo effect. New York, NY: Free Press. Schein, E. H. (2004). Organizational culture and leadership—third edition. New York, NY: Jossey-Bass. Seely Brown, J., & Duguid, P. (2000). The social life of information. Boston, MA: Harvard Business School Press. Serpa, R. (1985). Creating a candid corporate culture. Journal of Business Ethics, 4(5), 425-430.

Simmons, A. (1997). Territorial games. (New York, NY: AMACOM). Somech, A., & Drach-Zahavy, A. (2004). Exploring organizational citizenship behaviour from an organizational perspective: the relationship between organizational learning and organizational citizenship behaviour. Journal of Occupational and Organizational Psychology, 77(3), 281-298. Sparrow, J. A. (1998). Knowledge in organizations. Thousand Oaks, CA: Sage. Spender, J. C. (1996). Organizational knowledge, learning and memory: three concepts in search of a theory. Journal of Organizational Change Management, 9(1), 63-78. Stein, E. W., & Zwass, V. (1995). Actualizing organizational memories with information systems. Information Systems Research, 6(2), 85-117. Stoyko, P. (2009). Organizational culture in an age of diversity. Ottawa, ON: Fugitive Knowledge Press. Stoyko, P. and Fang, Y. (2007). Lost & found. Ottawa, ON: Canada School of Public Service. Van Hecke, M. L. (2007). Blindspots (Amherst, NY: Prometheus Books). Watson, D. (2003). Death sentences. London: Penguin Books. Zerubavel, E. (2006). The Elephant in the Room. Oxford: Oxford University Press.

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Chapter II

Downsizing and Building Organizational Memory:

A Paradoxical Relationship between “Brain-Drain” and “Brain-Gain” Nicholas N. Bowersox TUI University, USA

ABSTRACT Recent business practices over the past decade have been tainted with corporate restructuring strategies such as downsizing, reorganizations, and job redesigns. With the hopes of increasing efficiency, gaining productivity, and reducing costs, many companies have participated in such efforts. However, one must consider the irony behind this shrewd, if not tactfully harsh, business practice. While organizations continue to decrease their workforce in an effort to regain acceptable profit margins, cut back on “waste” and become “leaner”, they also stress the importance of sharing knowledge among employees and building organizational memory. How can a company effectively share knowledge and build organizational memory when its employee base is shrinking? This is an interesting question that has stirred much debate over recent years, both in the public and private sector. As such, this book chapter attempts to explore the paradoxical relationship between downsizing (brain-drain) and building organizational memory (brain-gain).

INTRODUCTION Unfortunately, downsizing is a way of life in today’s global business economy. Through methods that include mergers, acquisitions, corporate restructuring, and outsourcing, downsizing is

considered normal and is often expected when company profits are below normal. Despite its popularity, many studies such as Cascio (1993) claim that downsizing does more harm than good. This harm is not just limited to measurable factors like productivity or profitability, but also to less

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Downsizing and Building Organizational Memory

easily measurable factors such as organizational memory. In fact, previous research supports the notion that organizations which can effectively create, share, and transfer knowledge at the individual, group, and organizational levels are more effective than those that cannot (Kogut & Zander, 1992). The effective sharing of knowledge leads to organizational learning which, in turn, is a precursor to building organizational memories (Balasubramanian, 1995). Here, it seems we have a paradigm that exists. Are downsizing and building organizational memory simultaneously compatible with one other? Can an organization eliminate employees and still effectively commit itself to build organizational memory? These are the types of questions that this book chapter will explore, but first, for the sake of the reader, let’s examine the layout and structure of this chapter. To begin, the relevance of organizational downsizing and how it is used as a modern business strategy will be discussed. Secondly, this chapter will discuss the concept of organizational memory – specifically how the term came about, its history, and why it is important. Third, this chapter will examine the concepts of single-loop and double-loop learning, as discussed in the works of Argyris and Schon (1996), and how collective learning can harness a framework for building organizational memories. Finally, this chapter will tie together the two main topics of this paper, downsizing and organizational memory, by proposing relevant areas for future research as well as the practitioner benefits of this book chapter.

D a Business St To begin, it is first important to understand what downsizing is. It is best defined by Freeman and Cameron (1993) as an intentional reduction in personnel intended to improve the effectiveness of the firm. Historically, downsizing has always

been associated with firms that were on the decline. However, in respect to current scholarly usage, it is important to make the distinction between organizational downsizing and organizational decline. According to McKinley, Zhao, and Rust (2000), “downsizing is an intentional proactive management strategy, whereas decline is an environmental or organizational phenomenon that occurs involuntarily and results in erosion of an organization’s resource base” (p. 227). In today’s modern business era, though, downsizing is viewed from a positive perspective. In other words, it is not necessary for a firm to be on the decline before reducing its employee base. In fact, business consultants, stockholders, and senior management alike view corporate downsizing as a legitimate business tool to reorganize a corporation, thus allowing the company to regain its ability to be more productive and efficient. Perhaps a common interpretation of organizational downsizing is the economic perspective which is based on the principle that firms are driven towards efficiency (McKinley et al., 2000). Inherent in this theory is the belief that firms downsize for the purposes of reducing costs while improving efficiency and productivity. At the same time, managerial actions and their outcomes are highly related. According to those who support this notion, downsizing is used as a tool to increase future economic performance. There has been a great deal of scholarly research focusing on the post-downsizing results associated with this economic view. For example, Cascio (1993) claims that downsizing does more harm than good. In an example, Cascio points out that in a Fortune 100 company a bookkeeper making $9 per hour was let go due to downsizing, only to be rehired back as a consultant making $42. Why, you may ask? Senior management realized that without this employee they lost precious organizational memory that was vital to the company’s success. As a result, the company rehired this employee at $33 per hour more to reacquire the learned expertise that the

19

Downsizing and Building Organizational Memory

organization was missing. Although this “fire and rehire” approach may seem illogical, it does a fine job of illustrating the conflicting paradigms of downsizing and organizational memory. In a study conducted by the US government, the quality of the workforce remaining after a downsizing will largely determine either the success or failure of the corporation (Serving the American public: Best practices in downsizing, 1997). According to Griggs and Hyland (2003), shrinking the number of employees to improve productivity is the preferred method of downsizing among senior management in organizations. In addition, they state that the United States witnessed its heaviest downsizing in the 1990’s as companies failed to meet stockholder expectations. As a result, employees were let go and many firms began outsourcing work to other nations where labor rates were much cheaper. Additional studies have shown that a firm’s reliance on outsourcing has increased drastically over the past 20 years. According to Bremen and Fowler (1994), outsourcing has been used across all business sectors and by all types of firms, both large and small. In fact, it is a preferred method to reduce the corporate payroll and increase the financial health of the company. However, outsourcing can lead to a horrific problem – a loss of knowledge on the learning and memory capacity of organizations. By outsourcing a position, the main organization loses the learned expertise inherent in the employee whose position was eliminated. In addition, the knowledge being reacquired by the outsourcing company is no longer intact within the main organization. It now resides in the organizational memory and knowledge repositories of the outsourcing company. Regardless of the type of downsizing, a loss of organizational learning and memory may occur. Although downsizing is often done with the intention of generating positive results (increasing efficiency, gaining productivity, and reducing costs), this largely is not the case as illustrated above in the example from Cascio (1993). How-

20

ever, it would be biased to state that downsizing never succeeds. Consider Boeing, one of the largest aircraft producers in the world. In the 1990’s, the company was forced to downsize approximately 55,000 people over a five-year period, largely due to decreased airline orders and reduced military spending. The Boeing Company worked closely with the local community, government agencies, and colleges to develop and create Reemployment Centers to assist laid-off workers in coping with the transition into other employment areas. In creating these centers, the company was able to minimize the economic hardships that may have been endured by both the laid-off workforce as well the local community. As such, the company was able to successfully execute a downsizing strategy, while at the same time showing their commitment to the duties of corporate social responsibility. According to Fisher and White (2000), there are two common ways to view the degree of scope of the downsizing. The first method, which is one of the more common ways, describes downsizing as a percentage based on the ratio between the numbers of employees removed from the downsizing over the total number of employees in the organization. From the perspectives of organizational memory, this technique assumes that the knowledge held in that individual is not retained elsewhere in the organization. The second method of viewing downsizing looks at the organization as a whole, where the networks of individuals generate learning. From this perspective, we can see that the impact of downsizing could be more severe than a simple ratio method that figures the percentage of employees reduced from the firm’s workforce. In the sections that follow, this chapter will discuss organizational memory and how it is formed through collective organizational learning. As such, the scope of this chapter will view downsizing by looking at the organization as a whole, where the networks of individuals generate learning.

Downsizing and Building Organizational Memory

Organizational Memory According to Balasubramanian (1995), organizational learning produces organizational memory. Thus, learning systems can influence both present and future members of the organization through the shared accumulation of experiences and knowledge. When organizations learn, they are able to create organizational memories, which are key ingredients in all organizational cognitive processes (Ulrich, Glinow, & Jick, 1993). Scalzo (2006) defines organizational memory as “the knowledge and information from the organization’s past which can be accessed and used for present and future organizational activities” (p.61). While this definition is accurate, it is also quite simplistic in nature. As with many academic fields of research, organizational memory is a construct that is loosely defined and under-developed. A brief review of the literature in the field has uncovered some additional definitions, which provide an underlying level of breadth and depth to this complex construct. A careful analysis of these definitions highlights the fact that organizational memory involves various aspects of the knowledge management process. Day (1994) states that organizational memory manipulates both the interpretation of information as well as the actions performed. As a result, we can conclude that organizational memory is multi-faceted. However, to better

understand how downsizing affects a firm’s organizational memory, it is critical to understand the concept of organizational learning.

Collective Organizational Larning Builds Oional Memory In searching for a universal definition of organizational learning, it is clearly evident that the research in this area is quite fragmented with no widely accepted model (Fiol & Lyles, 1985). Argyris (2002), one of the key researchers in this field, defines organizational learning as the detection and correction of errors. While it is true that error correction might seem to constitute learning, it can be argued that learning is incomplete if the immediate error is corrected rather than those errors lying deeper in the organization (Falconer, 2006). Further, Dodgson (1993) describes organizational learning as: the way firms build, supplement, and organize knowledge and routines around their activities and within their cultures and adapt and develop organizational efficiency by improving the use of the broad skills of their workforces. (p. 377) Fisher and White (2000) define organizational learning as:

Table 1. Organizational memory defined. Adapted from Park and Bunn (2003) Author(s)

De. nition

Ackerman (1994)

Organizational knowledge with persistence

Anand, Manz and Glick (1998)

Information and knowledge known by the organization and the process by which the information is acquired, stored and retrieved

Moorman and Miner (1997)

Collective beliefs, behavioral routines, or physical artifacts that vary in their content, level, dispersion and accessibility

Moorman and Miner (1998)

Learned ways of thinking and behaving

Walsh and Ungson (1991)

Stored information about a decision stimulus and response that, when retrieved, comes to bear on present decisions

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Downsizing and Building Organizational Memory

a reflective process, played out by members at all levels of the organization, that involves the collection of information from both the external and internal environments. This information is filtered through a collective sensemaking process, which results in shared interpretations that can be used to instigate actions resulting in enduring changes to the organization’s behavior and theories-in-use. (p. 245) This definition is rooted in both the cognitive and social views of organizational learning, where it is assumed that the organization is a social entity in which members interact to form a collective consciousness that is much greater than the sum of the individual contributions. Learning organizations are those that purposefully develop strategies and processes for retaining knowledge, and thereby enhancing organizational learning (Dodgson, 1993). These types of organizations analyze information from both internal and external sources where it accumulates as knowledge, and thus becomes a part of the organization’s memory (Weick, 1979). This concept of a learning organization has gained attention in recent years as being a key method in making organizations more adaptable to change (Balasubramanian, 1995). In addition, many firms are turning to the concept of organizational learning as a way to increase competitive advantages over the competition. In the past, learning was primarily looked at from the individual level, whereas now it is viewed as a collective effort. When organizations choose to adopt a learning strategy, what types of competitive advantages do they hope to gain? According to Dodgson (1993), the modern business environment is tumultuously unpredictable and highly susceptible to change. As a result, organizations are forced to learn so that they may easily adapt to the constant changes that are taking place. Learning enables quicker adaptations to such change. Balasubramanian (1995) also states that learning increases information sharing and communication among employees.

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Finally, Landry (1992) states that organizational learning is a key ingredient for innovation. Some researchers, however, would argue that organizations cannot learn (Senge, 1990). Individuals learn and are part of the collective network of employees who comprise the entire organization (Huber, 1991). Further, Nonaka and Takeuchi (1995) state that individuals are necessary components for an organization to create knowledge. The following quote demonstrates this school of thought quite well: Organizational knowledge creation … [is the] process that organizationally amplifies the knowledge created by individuals and crystallizes it as a part of the knowledge network of the organization. This process takes place within an expanding ‘community of interaction’ which crosses intraand inter-organizational levels and boundaries. (Nonaka and Takeuchi, 1995, p. 97) Senge (1990) believed that the process to create knowledge was carried out through teams in the modern organization. After all, it is teams that are the critical element in today’s organization. Additional research in this field can be attributed to Argyris and Schon (1996) who distinguish organizational learning behaviors into the concepts of single-loop and double-loop learning. To begin, Argyris and Schon (1974) suggest that people have mental maps about how to act in situations. These maps guide people’s actions rather than the theories they espouse. They suggest that two theories of action – theories-in-use and espoused theory – are involved. A theory of action is first a theory: its most general properties are concepts that all theories share, and the most general criteria that apply to it – such as generality, centrality and simplicity - are criteria applied to all theories (Argyris & Schon, 1974). The distinction made between the two contrasting theories of action is between those theories that are implicit in what we do as practitioners

Downsizing and Building Organizational Memory

and managers, and those on which we call to speak of our actions to others. The former can be described as theories-in-use. They govern actual behavior and tend to be tacit structures. The words we use to convey what we do, or what we would like others to think we do, can then be called espoused theory” (Smith, 2001). Further, when someone is asked how he would behave under certain circumstances, the answer he usually gives is his espoused theory of action for that situation. This is the theory of action to which he gives allegiance, and which, upon request, he communicates to others. However, the theory that actually governs his actions is his theory-in-use. (Argyris and Schon 1974, p. 6-7) In developing their model for theories-in-use, Argyris and Schon (1974) have carefully examined three variables that are involved. They are governing variables, action strategies, and consequences. Governing variables are those dimensions that are trying to be held within acceptable limits, while action strategies are the actions put into place by people to keep their governing variables within acceptable limits. Finally, consequences are the results of an action. Consequences can be unintended or intended, and may also be for the self or for others (Anderson, 1997). Where the consequences of the strategy used are what the person wanted, then the theory-in-use is confirmed. This is because there is a match between intention and outcome. There may be a mismatch between intention and outcome. In other words, the consequences may be unintended. They may also not match, or work against, the person’s governing values. Argyris and Schon suggest two responses to this mismatch, and these are can be seen in the notion of single and double-loop learning. (Smith, 2001) They propose that single-loop learning occurs when the organization learns in such a way that only modifies strategies for actions. Chosen

rules are operationalized rather than questioned. In other words, a firm would look for another strategy that would address the governing variable. The organization will detect and correct the error and continue forward with present policies. Dodgson (1993) equates single-loop learning to activities that add knowledge to the firm without severely altering the organization’s activities. Fiol and Lyles (1985) refer to single-loop learning as lower-level learning, while Senge (1990) refers to it as adaptive learning. Double-loop learning occurs when errors are corrected by changing the values and then the actions. In other words, the chosen rules are questioned which may result in an alteration to the governing variable, and a shift in the way a consequence is framed. Fiol and Lyles (1985) refer to this as higher-level learning while Senge (1990) refers to this as learning to expand an organization’s capabilities. The quotation below is how the processes of single-loop and doubleloop learning are described by Argyris and Schon (1978): When the error detected and corrected permits the organization to carry on its present policies or achieve its presents objectives, then that errorand-correction process is single-loop learning. Single-loop learning is like a thermostat that learns when it is too hot or too cold and turns the heat on or off. The thermostat can perform this task because it can receive information (the temperature of the room) and take corrective action. Double-loop learning occurs when error is detected and corrected in ways that involve the modification of an organization’s underlying norms, policies and objectives. (Argyris and Schon, 1978, p 2-3) Figure 1 graphically represents their model. Argyris and Schon (1978) take this model one step further by explaining a concept called deutero-learning, which describes the ability of the firm to perform single-loop and double-

23

Downsizing and Building Organizational Memory

Figure 1. Model of single-loop and double-loop learning (Adapted from Argyris and Schon, 1996)

G overning V ariable

A ction S trategy

C onsequences

S ingle-loop learning D ouble-loop learning

loop learning at the same time. Single-loop and double-loop learning will only occur if the firm is aware that learning must occur. It is important to note that both double-loop learning and deuterolearning are only concerned with the “how” and “why”, while single-loop learning is concerned with accepting change. One of the biggest issues with understanding organizational learning has been bridging the gap between individual learning and collective learning (Fiol & Lyles, 1985). Weick (1995) proposes a framework for understanding the various levels of learning within the organization. In his model, he states that there are four levels. The first level is the intrasubjective level, or that of the individual. The second level is the intersubjective level. It is here that information is interpreted and shared meaning is established between groups. The third level is the generic level where knowledge is stored for future use. This level would represent organizational memory. The fourth level is the extrasubjective level which views learning from the macro perspective. It includes both organizational culture and institutional artifacts. Argyris and Schon (1978) have long argued that the generic level represents the knowledge developed through organizational learning. This knowledge process can only be understood by observing the interaction of employees at the intersubjective level. Fisher and White (2000) state that this organizational learning level is one

24

of the most vulnerable to corporate downsizings. Glynn, Lant, and Milliken (1994) support this. They state that organizational learning is situated within an interactive context as opposed to the minds of individuals. Further, they propose that learning in organizations comprise of networks of people that are connected through nodes or critical paths. When organizations downsize, critical elements of these networks are lost causing damage to the critical paths. This has the negative effect of damaging vital knowledge flows among the networks, thereby decreasing the capacity for the organization to learn, and ultimately to build organizational memory.

Th Paradoxical Relationship Bween Downsizing and Organizational Memory According to Fisher and White (1997), the information processing perspective says that the loss of an individual is related to the amount of information held in that individual’s memory that is not a part of the organization. On the other hand, the learning network perspective states that organizational memory is formed in the connections between individuals that are part of a learning community. This perspective is highly important in realizing the potential negative impacts of downsizing on organizational memory. If the

Downsizing and Building Organizational Memory

networks of individuals, or learning communities, allow organizational learning to occur, thereby generating organizational memory, and these networks are broken, then the irreparable harm to the organization’s ability to learn and generate memory could be severely damaged. This idea is easy to conceptualize when you consider that an individual is likely to have multiple networks and interrelationships among individuals. Consider a learning network of nine individuals which we will call members A, B, C, D, E, F, G, H, and I (Figure 2). Let’s assume that this learning network is comprised of all nine members of the finance department for a small corporation. We know that these employees may have different core duties in performing their individual jobs but do interact with one another to complete subtasks. After all, it does seem logical that they would share knowledge since they all work in the finance department. Although the members may only interact occasionally, this interaction between them signifies collective organizational learning which, in turn, will build organizational memory. Each member of this network will share individual pieces of knowledge that collectively can be distributed to

all members. As you can see, all members of the network are connected to member A, so member A is a vital link in the sustainability of the network. Please also note that within this collective learning network, there are two smaller learning networks. We can see that members A, B, C, and E are connected as well as A, F, H, and I. But what might happen if member A was removed from the network through downsizing? In other words, of the nine employees in the finance department, member A lost his job due to downsizing. To examine this, let’s once again consider the common ways in which downsizing can be viewed, as described by Fisher and White (2000). Recall that the first method describes downsizing as a percentage based on the ratio between the numbers of employees removed over the total number of employees. So, in this network, we originally had nine members and lost one, so the learning network lost 11% of its members. That may seem relatively insignificant to the senior management of the company. After redistributing member A’s workload equally among the remaining eight members, management may feel as if the loss was properly handled. Remember, though, that member A was the vital link in the

Figure 2. Collective learning network

Figure 3. Collective learning network with the effects of downsizing

C

D

E

A

F

E

G

H

I

G

B

C

B

D

F

H

I

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Downsizing and Building Organizational Memory

learning network. Each member was connected through that person. In addition, member A was part of two other subgroups within that network. Now, our learning network is “broken”. The nodes connecting many of its members have been severed due to the loss of member A. Figure 3 depicts this. Now consider the second perspective of analyzing downsizing, which looks at the organization as a whole where the networks of individuals generate learning. It is clearly evident that we have a major issue. If we look at Figure 3 above, we can see that what was once a highly complex and vibrant learning network is extremely fragmented. All members of the network were previously connected through member A. Now we can see that within these 8 remaining members, two learning communities now exist. The first learning community is learners B, C, and E and the second learning community is learners F, H, and I. These two communities lost member A. In addition, these two communities are no longer a part of the larger community. Within the finance department, we now have two small learning communities and two employees who are no longer connected to any learning community. Through this simplistic example, you can see that downsizing can drastically shrink the interconnectivity of a learning network. Whereas previously, 100% of the members were connected, now only 75% of the members are connected as a result of only an 11% loss of members. You can see that the effects of downsizing can be drastically understated using a headcount ratio method. By favoring the second way in which we can view downsizing, it is obvious that the loss of only one person can be critical to the entire learning community, especially if that person is a vital link in the learning network. Freeman and Cameron (1993) support this by stating that downsizing may cause dramatic structural changes to the organization, where only minimal changes were intended. Fisher and White (1997) state that “downsizing may not only lead to the loss of individuals with

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valuable organizational memory but also may damage the network connections that are critical to both innovation and organizational learning” (p. 455). Since organizational learning can produce organizational memory (Balasubramanian, 1995), and downsizing can damage the networks that connect learning communities, the author of this chapter proposes that downsizing is negatively correlated to organizational memory.

Impcions for Future Research and for Practitioners In integrating previous theory and practical experiences, it is clearly evident that forms of organizational downsizing may perhaps cause more harm than good for the learning organization, especially those downsizings which are not strategically planned and do not consider the collective learning networks of the organization. In examining the key points of this book chapter, it is now important to look at the areas for future academic research as well as the practitioner implications. This book chapter highlights several key areas for future research. First, it is important to note that additional quantitative and qualitative case studies should be conducted to validate the potential impacts that downsizing has on organizational memory. These studies should consider various types of downsizings as well as various types of firms (i.e. large vs. small, different industries and business segments, etc.). Research should also examine the functionality of social networks as well as how they are formed and can change over time due to the addition and deletion of members, change in organizational policy, etc. Understanding the structure of social networks will allow organizational theorists and knowledge management professionals to better understand the contribution these networks play in building organizational memory. Additional

Downsizing and Building Organizational Memory

studies should also be done to detect the formal and informal changes in network structure before and after downsizing. Assuming that the competitive nature of business will inspire downsizing as a business strategy in the future, it is critical to more thoroughly understand its impacts on the organization. In addition to areas for future academic research, it is equally important to consider the implications of this book chapter for practitioner benefit. Above all else, it is imperative that downsizing and its repercussions be carefully analyzed. A solid action plan must be in place. Senior management should carefully examine the organization to determine who possesses critical information that is needed for the present and future success of the company (Scalzo, 2006). In addition, an implementation plan should be set in motion to ensure that such knowledge is captured and made more accessible for present and future employees. This implies that the information should be collected, codified into a retrievable format, and stored in some type of knowledge repository. In addition, it is equally important to determine the structure of the collective learning networks that comprise the organization. Know where the vital nodes are to be certain not to disable an entire learning community. When an employee is removed from a learning network, there must a plan in place to repair the nodes inherent to that employee so that the learning community does not lose its functionality.

CONCLUSION Despite the negative connotations associated with organizational downsizing, many firms continue to utilize it as a business strategy to increase efficiency and productivity and to reduce costs. Through the results of previous research, though, it is shown that many companies have failed to report significant and positive achievements from downsizing. This book chapter has taken

an investigative look into the correlation between downsizing and organizational memory. Specifically, this chapter examined how downsizing hinders organizational learning, which in turn, results in a decreased potential to build organizational memory. In addition, this chapter suggests specific areas that additional research needs to be conducted in. Finally, suggestions are provided for practitioners in the field.

REFERENCES Ackerman, M. S. (1994). Augmenting the organizational memory: A field study of answer garden. Paper presented at the CSCW. Anand, V., Manz, C. C., & Glick, W. H. (1998). An organizational memory approach to information management. Academy of Management Review, 23(4), 796-809. Anderson, L. (1997). Argyris and Schon’s theory on congruence and learning. from http://www. scu.edu.au/schools/sawd/arr/argyris.html Argyris, C. (2002). Double-loop learning, teaching and research. Academy of Management and Learning, 1(2), 206-218. Argyris, C., & Schon, D. (1974). Theory in practice: Increasing professional effectiveness. San Fransisco: Jossey-Bass. Argyris, C., & Schon, D. (1978). Organizational learning: A theory of action perspective. Boston: Addison-Wesley. Argyris, C., & Schon, D. (1996). Organizational learning II: Theory, method and practice. Reading: Addison Wesley. Balasubramanian, V. (1995). Organizational learning and information systems. IS World Net(May). Bremen, M., & Fowler, C. (1994). The organisational correlates and consequences of subcon-

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tracting: evidence from a survey of South Wales business. Journal of Management Studies, 31, 847-864.

Huber, G. P. (1991). Organizational learning: The contributing processes and the literatures. Organization Science, 2(1), 25-34.

Cascio, W. F. (1993). Downsizing: What do we know? What have we learned? Academy of Management Executive, 7(1), 95-104.

Kogut, B., & Zander, U. (1992). Knowledge of the firm, combinative capabilities and the replication of technology. Organization Science, 3.

Day, G. S. (1994). The capability of market-driven organizations. Journal of Marketing, 58, 37-52.

Landry, J. (1992). Information characteristics as constraints to innovation. Paper presented at the Twenty-Fifth Hawaii International Conference on System Sciences, CA.

Dodgson, M. (1993). Organizational learning: A review of some literatures. Organization Studies, 14(3), 375-394. Falconer, L. (2006). Organizational learning, tacit information and e-learning: A review. The Learning Organization, 13(2), 140-151. Fiol, C. M., & Lyles, M. A. (1985). Organizational learning. Academy of Management Review, 10, 803-813. Fisher, S. R., & White, M. A. (1997). Downsizing and organizational learning: A question of compatibility. Academy of Management Proceedings, 454-458. Fisher, S. R., & White, M. A. (2000). Downsizing in a learning organization: Are there hidden costs? Academy of Management Review, 25(1), 244-251. Freeman, S. J., & Cameron, K. S. (1993). Organizational downsizing: A convergence and reorientation framework. Organization Science, 4, 10-28. Glynn, M. A., Lant, R. K., & Milliken, F. J. (1994). Mapping learning processes in organizations: A multi-level framework linking learning and organizing. In C. Stubbart, J. R. Meindl & J. Porac (Eds.), Advances in managerial cognition and organizational information processing, 5, 53-83. Greenwich: JAI Press Inc. Griggs, H. E., & Hyland, P. (2003). Strategic downsizing and learning organizations. Journal of European Industrial Training, 27(2-4), 177-187.

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McKinley, W., Zhao, J., & Rust, K. G. (2000). A sociocognitive interpretation of organizational downsizing. Academy of Management Review, 25(1), 227-243. Moorman, C., & Miner, A. S. (1997). The impact of organizational memory on new product performance and creativity. Journal of Marketing Research, 34, 91-107. Moorman, C., & Miner, A. S. (1998). Organizational improvisation and organizational memory. Academy of Management Review, 23(4), 698723. Nonaka, I., & Takeuchi, H. (1995). The knowledge-creating company. New York: Oxford University Press. Park, J. E., & Bunn, M. D. (2003). Organizational memory: A new perspective on the organizational buying process. Journal of Business and Industrial Marketing, 18(3), 237-257. Scalzo, N. (2006). Memory loss? Corporate knowledge and radical change. Journal of Business Strategy, 27(4), 60-69. Senge, P. (1990). The fifth discipline: The art and practice of the learning organization. London: Random House. Serving the American public: Best practices in downsizing. (1997). Retrieved. from www.npr. gov/library/papers/benchmrk.downsize.html

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Smith, M. K. (2001, December 28, 2007). Chris Argyris: Theories of action, double-loop learning and organizational learning. The encyclopedia of informal education, from www.infed.org/thinkers/argyris.htm Ulrich, D., Glinow, V., & Jick, T. D. (1993). High-impact learning: Building and diffusing learning capability. Organizational Dynamics, 22, 52-66.

Walsh, J. P., & Ungson, G. R. (1991). Organizational memory. Academy of Management Review, 16(3), 57-91. Weick, K. (1979). The social psychology of organizing. Reading: Wesley. Weick, K. (1995). Sensemaking in organizations. Thousand Oaks: Sage.

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Chapter III

Effective Stakeholder Knowledge Sharing for Effective Organizational Memory Nicholas P. Robinson McGill University, Canada Prescott C. Ensign University of Ottawa, Canada

ABSTRACT This chapter argues that a trusting corporate culture predicated on values that emphasize sharing and encourage interactions amongst stakeholders at all levels spawns knowledge sharing activities and leads to the development of robust organizational memory reserves. The authors argue that the importance of knowledge management in the information age will make it essential that competitive companies inculcate stakeholders with the values necessary to encourage the production, sharing, and storage of knowledge for the benefit of the organization and its stakeholders. The authors demonstrate that having the proper systems and processes in place and fostering a culture that values sharing should help organizations to develop and use latent knowledge reserves. An experiential learning model is used to illustrate how mere data can be transformed into commercially viable knowledge.

IN According to Hewlett-Packard CEO Lew Platt “if HP knew what HP knows, we would be three times as profitable”(Yang, 2007, p.83). This statement has been echoed and reiterated by CEOs

throughout the world that wish to optimize the use of their organization’s knowledge bases in order to better serve internal and external stakeholders. This means managing knowledge, information, and data in a manner that meets business objectives efficiently and effectively, despite the dilemmas

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Effective Stakeholder Knowledge Sharing for Effective Organizational Memory

posed by the electronic age. IBM CEO Louis Gerstner states that “one of the great conundrums of e-business is that it gives enterprises a powerful new capability to capture and analyze massive amounts of customer information so they can serve individuals more effectively” (Privacy Guru, 2001, p.1). Thus, organizations are faced with a bifurcated problem: On one hand investments in organizational memory systems offer businesses the opportunity to grow exponentially while, on the other hand, information overload challenges the modern manager. The electronic communications revolution has produced a situation that demands that companies employ better systems and practices to manage this information in order to cope with issues such as information overload while better accommodating customer and stakeholder concerns, such as privacy issues and improved corporate profitability. It is therefore imperative that all organizations aim to develop a culture that is conducive to long-term learning and supports the institutionalization of successful strategies. A static approach to managing external and internal relationships with stakeholders can lead to a business’ obsolescence, whereas an approach that emphasizes continual learning and adaptability to meet the ever changing needs of the organization and its external stakeholders can help support the organization’s endurance. It is essential that an organization’s leaders develop the institutions and culture necessary to ensure that future generations of leaders are better equipped to adapt and respond to external stakeholder needs. This means inculcating employees with values that emphasize the sharing of valuable knowledge and the implementation of systems that enable the creation of various types of organizational memory, and processes to acquire and store this memory. By developing healthy and trusting social networks, designing effective information communications systems such as electronic bulletins and intranets, and having a plan in place to capitalize on these organizational memory

systems a company can position itself to succeed in the information race. This being said, making learning and memory an important part of an organization’s relations with external stakeholders cannot be defined in static terms. Acquiring, building, and applying organizational memory in a way that strengthens the organization’s relations with external stakeholders and achieves organizational objectives should be treated as an ongoing process that will enable the organization to weather changes in stakeholder relationships—whether the change involves employee turnover or winning a new client. Irrespective, having the proper systems in place and a culture that is open and trusting should help the organization to effectively develop and use innate experiential knowledge for the benefit of the corporation and all its stakeholders. This chapter argues that all stakeholders can benefit from organizational memory systems that are predicated on a culture that values sharing and learning. It will define both the types of organizational memory that exist and provide an example of one system design that can be used to capture these memories. Additionally, research demonstrating the importance of fostering a trusting and open office environment will be provided to substantiate that trust is the cornerstone of growing healthy social networks, not to mention a prerequisite for knowledge sharing at a more basic level, and thus plays an important role in ensuring effective organizational memory systems. Finally, the chapter will discuss the benefits of these systems to all stakeholders and apply Kransdorff’s six-stage experience-based management cycle to demonstrate how experiential learning occurs and organizational memory is amassed (Kransdorff, 2006, pp.124-125). More generally, the complications faced by those who wish to successfully implement an integrated organizational memory plan will be discussed and the nuances involved when designing systems to satisfy the needs of particular stakeholders will be highlighted.

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BA Organizational memory falls under the broader topic of knowledge management, which encompasses areas of scholarly research such as organizational learning and has implications for management information systems. All of an organization’s memories must be collected, stored and made accessible in order for them to be put to effective use. These memories are either stored in a company’s systems (including databases, paper archives and other resources) or in its people, through individual and group memories. Organizational memory therefore plays an important role in every organization, as memory is a prerequisite (or occasionally a barrier) to the successful achievement of organizational goals and the implementation of the organization’s strategic plans. According to Girard (2006, p.23) organizational memories can be subdivided into data, information, and knowledge. Data, which is the most basic building block of an organization’s memory, can be defined as “as a set of discrete, objective facts about events” and is normally manifested in an organizational context as “structured records of transactions” (Davenport and Prusak, 1998, p.2, as cited in Girard, 2006, p.24). Given data’s quality as the raw material from which knowledge is derived it can be considered the “lowest level in the value chain and by itself is not very beneficial” (Girard, 2006, p.24). Data must be transformed into information, the second form of organizational memory, through one of five processes—categorization, contextualization, calculation, correction, or condensation (Girard, 2006, p.24). Information on the other hand is best described as a “message, usually in the form of a document or an audible or visible communication” (Davenport and Prusak, 1998, p.3 as cited in Girard, 2006, p.24) and must have a sender and a receiver. The last notch in the organizational memory pyramid is knowledge, which can be described as “a fluid mix of framed

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experience, values, contextual information, and expert insight that provides a framework for evaluating and incorporating new experiences and information” (Davenport and Prusak, 1998, p.5 as cited in Girard, 2006, p.24). Knowledge is the most evolved form of organizational memory and has more value, as it is normally applicable without further refinement. Knowledge itself can be described as either being explicit, meaning “formal and specific” and easily communicable (Nonaka, 1998 as cited in Girard, 2006, p.25), or tacit meaning highly personal and difficult to communicate (Takeuchi, 1995 as cited in Girard, 2006, p.25). Tacit knowledge can be analogized to the knowledge gained by the apprentice under the guidance of a master artisan (Nonaka and Takeuchi, 1995, as cited in Girard, 2006, p.26). Thus, collectively knowledge, information and data form the hierarchical system on which knowledge management generally, and organizational memory specifically, rests (Girard, 2006, p.22). In order to organize these memories and eventually make use of them an organization employs organizational memory systems, which better enable the collection, storage, and accessibility of data, information, and knowledge. According to Olivera, improved organizational memory systems “can buffer the organization from the disruptive effects of turnover (Argote et al, 1990 as cited in Olivera, 2000, p.811), facilitate coordination (Yates, 1989 as cited in Olivera, 2000, p.811), contribute to the development of innovative products (Hargadon and Sutton, 1997 as cited in Olivera, 2000, p.811; Moorman and Miner, 1997), and may even serve to rebuild an organization (Campbell-Kelly, 1996 as cited in Olivera, 2000, p.811).” Further, in the multi-unit organization, such as the multinational corporation or any government, lessons derived from experiential learning efforts that have been collected and stored in one division of the organization can be beneficial to other parts of the organization (Olivera, 2000, p.811). Using experiential learning, or lessons learned through individual

Effective Stakeholder Knowledge Sharing for Effective Organizational Memory

and organizational experiences, is promising for organizations that wish to avoid the redundancy of having to re-learn the same lessons or repeat the same mistakes. An effective organizational memory system can be generalized to benefit all parts of the organization and will necessarily be comprised of “both human and technological components” (Girard, 2006, p.25). Thus, an organizational memory system can be defined as a set of “knowledge retention devices, such as people and documents, which collect, store and provide access to the organization’s experience” (Olivera, 2000, p.815). These systems can be used to “collect solutions to problems, maintain records of exchanges between the organization and its clients, and provide links between people who need and have experiential knowledge” (Olivera, 2000, p.814). Each organizational memory systems has several constituent components, including content, structure and operating processes, all of which must function in unison in order to effectively enable the successful collection, storage, and access of information needed in the achievement of organizational goals (Olivera, 2000, p.813). The system’s structure “refers to how the knowledge it contains is organized” and is defined by the location of its content (or knowledge) (Olivera, 2000, p.816). Indexing and other organizational techniques are therefore essential to allowing internal and external stakeholders to access the information required (Olivera, 2000, p.816). If the organizational memory system consists only of electronic databases of an intranet system then the knowledge will reside wherever it is indexed within the system. If the knowledge is stored in a social network, or an individual with specific expertise, then it is located “wherever the individuals in the network are located” (Olivera, 2000, p.816). This fact makes the use of human based referential organizational memory systems, such as expertise-locator systems (or “ELS”) critical in managing knowledge. The quality of the indexing of both electronic resources and social

networks is therefore a determinant of the accessibility of the content and the overall effectiveness of the organizational memory system itself (Olivera, 2000, p.816). An effective expertise-locator system can therefore increase the accessibility of the knowledge in question. Studies have indicated that office workers generally prefer social networks over computer systems when in need of accessing organizational memory. Social networks have been evaluated as more effective given that “people have a natural preference for interacting with other people but also because they have unique features that other memory systems lack” (Olivera, 2000, p.827). According to Olivera (2000, p.827) social networks are “capable of containing multiple types of experiential knowledge and pointers to the location of knowledge in other systems, and of effectively linking dispersed knowledge” in a way that the most sophisticated computer systems have difficulty. People have a unique ability to connect remote and disparate information and explain that information in a manner that no computer can replicate. Utilizing the expertise of others in an office is therefore an important part of organizational memory, though “experts may be under-utilized as a resource if other, less costly, sources are available” (Olivera, 2000, p.827). In Olivera’s study (2000, p.823), it was discovered that an overwhelming majority of office workers rated people in their office or other offices as “as effective or very effective (88 per cent and 83 per cent, respectively)” suggesting that co-workers and social networks generally are perceived as being an effective source of knowledge. This compares to only 55% for intranet systems and 54% for electronic bulletin boards used by the survey’s respondents (Olivera, 2000, p.823). The faith that many office workers place in social networks is striking and indicates the importance of having healthy social networks to complement other IT based systems. Irrespective, social networks and computer based systems, the two most important branches of organizational

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memory systems, both function in much the same way and serve the same purpose of allowing the collection, storage and access of pertinent information used in the achievement of organizational objectives. On a general level, both social networks and computer-based systems “are similar to repositories or storage bins in that they refer to means by which organizations store experiential knowledge that can be used in decision-making” (Walsh and Ungson, 1991 as cited in Olivera, 2000, p.817). According to Yang (2007, p.87), “the efforts of knowledge sharing may facilitate greater organizational effectiveness” and an “emphasis on organizational learning should facilitate financial performance.” In this light, placing emphasis on the most effective organizational memory systems, especially social networks, may be key to an organization’s financial and operational success. Yang’s research (2007, p.88) indicates that knowledge sharing and organizational learning make a significant contribution to the overall effectiveness of the organization and that “integration and collection of shared knowledge into organizational assets or capability is necessary and important, in order to proceed to organizational learning.” Further, Yang (2007, p.89) states that “knowledge sharing implementation definitely influenced organizational learning at a certain level” in his study providing a strong incentive for organizations to foster the type of environment where this type of sharing is possible. Arguably the construction of viable social networks is a critical part of the organizational memory mix and can influence an organization’s success. Knowledge sharing and organizational learning are therefore critical to the development of a healthy organizational memory base. More strikingly, Robinson and Large (2004, p.49), and others argue that a healthy and wellmanaged base of organizational memory is a critical factor in managing external stakeholder relations. Though the implications of organizational memory on internal players, such as shareholders

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and employees, are obvious the implications for external stakeholders (like customers and those with any public interest in the organization’s activities) is less apparent. Robinson and Large (2004, p.49) argue that adequate organizational memory systems will buttress a company’s ability to meet its obligations to outsiders, such as potential customers who demand that their privacy be respected. Satisfying the needs of external stakeholders, such as customers, could then result in incidental benefits to the organization such as customer loyalty (Robinson and Large, 2004, p.49). Similarly, Girard (2006) has found that internal stakeholders can benefit from a company’s organizational memory systems. It can be argued that healthy organizational memory systems will aid in alleviating the stresses that office workers face daily. This can be achieved by using appropriate indexing techniques to improve accessibility and alleviate information anxiety. Girard (2006, p.22) found that information anxiety depends less on the type of task being performed than on the frequency of the task’s performance. Further, a weak positive relationship between tacit knowledge use and information anxiety…” was found to exist, suggesting that is more desirable for managers to operate in the explicit knowledge sphere when possible (Girard, 2006, p.22 & 36). In addition, an effective organizational memory system can reduce the amount of time wasted in locating information. Consider, for instance, that research has shown that in some organizations as much as “43 percent of managers delayed decisions because of too much information” (Wilson, 2001 as cited in Girard, 2006, p.27). An effective organizational memory system alleviates problems such as these that partly result from the existence of information that is largely unstructured or not pertinent to the manager’s needs (Girard, 2006, p.27). According to Girard (2006, p.35), “in the longer term, the implementation of a knowledge strategy that emphasizes a culture of knowledge sharing and provides the technology to find and

Effective Stakeholder Knowledge Sharing for Effective Organizational Memory

access information quickly will go some way to reducing the anxiety associated with infrequent tasks.”

MAIN Issues The importance of knowledge sharing to organizational memory cannot be underemphasized. However, creating an environment that enables the sharing of organizational knowledge for the benefit of internal and external stakeholders is often a challenge given human tendencies and competitive corporate cultures. The sharing of knowledge is a pillar for the development of a healthy base of organizational memory and is a critical factor in determining the success of social network memory systems. All social networks are reliant on the individual participants, who must be both willing and able to contribute their learned experiences for the benefit of internal and external stakeholders—including co-workers and customers. Considering the postulation that “the competitive basis of the multinational enterprises will increasingly be derived through intangible assets such as knowledge” (Markusen, 1995 as cited in Ensign, 2002, p.152), companies must strive to develop cultures that are conducive to the development of relevant organizational memory bases by encouraging knowledge exchange. Fostering this type of environment is a considerable challenge according to numerous scholars in the organizational memory sphere. Ensign (2002), among others has identified numerous barriers that can potentially inhibit knowledge sharing and the growth of an organization’s memory bases. According to research on R&D scientists working in multinational firms conducted by Ensign, the reputations of individuals and even groups play a critical role in determining the extent to which knowledge is shared. Among members of this sample group, it was “observed that past

behaviour and expected action were considerations in making the decision to provide scientific know-how to a fellow R&D employee in the firm” (Ensign, 2002, p.136). Reputation, as defined “in terms of past behaviour and expected action is developed from signals emanating from both the individual and the group” and weighs in on the knowledge source’s choice to share or withhold the knowledge in question (Ensign, 2002, p.136). The “source contemplating whether or not to share technological knowledge considers the balance of past transactions and whether the sum of these prior interactions is positive, negative, or zero” (Ensign, 2002, p.136). Other factors, such as the location of the recipient of the knowledge, were also found to have a bearing on the choice to share knowledge. Pharmaceutical R&D scientists being located in different countries were thought to discourage the flow of tacit technological knowledge (Ensign, 2002, p.136). Other factors, such as being located in the same city, the expertise of the recipient, contribution and uniqueness of sharing (or, in other words, the significance of the contribution) all had a positive impact on knowledge sharing while exchanges that involved greater time and effort, or involving those located in another country had a negative impact on knowledge sharing (Ensign, 2002, p.138). In fact, a correlation was discovered between physical distance generally and the communication of technological knowledge (Ensign, 2002, p.141). As a rule, the greater the distance the less likely it is that the source will share the knowledge with the recipient (Ensign, 2002, p.141). Further, the “technological expertise of the recipient positively impacted the source’s contemplation of whether or not to provide technological assistance” thus demonstrating that “a source may discriminate in choosing whom to help and whom to bypass” (Ensign, 2002, p.142). This factor suggests that the recipient’s reputation in the community as knowledgeable lends credence to their request and may even

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impact the extent to which the source trusts the recipient. Similarly, other researchers have found that the source’s credibility is a “key dimension” in individuals’ selection of sources of expertise (Cicourel, 1990 as cited in Olivera, 2000, p.816). In addition, the importance of the knowledge in question was found to bear on the extent to which sharing occurred. The “greater the contribution the technological knowledge was or would have been to the recipient the more frequently it was provided by the source” (Ensign, 2002, p.143). However, where the request involved a contribution that was “too close to home,” Ensign (2002, p.143) concluded that there were times when the sharing of information was perceived as a threat to the expert source’s “scientific domain.” This attitude, which Kransdorff (2000, p.124) refers to as “defensive” in nature, is both stifling to sharing and stifling to the development of a solid base of organizational memory. Sharing existing knowledge saves companies from making the same mistakes twice—it makes “processes efficient” and positively impacts the organization on the whole (Ensign, 2002, p.144). This being said, this same defensive attitude was exhibited by less senior employees to more senior employees as they were “more inclined to deny assistance to those who were senior” (Ensign, 2002, p.144). Additionally, closer personal and professional relationships were found to increase the competitiveness of R&D scientists. In fact, “it was found that as personal and professional interaction increased (and the relationships themselves became stronger) scientific know-how was less likely to be shared” (Ensign, 2002, p.139). These results are illustrative of the barriers that organizations face in getting employees to work collaboratively, share knowledge, and build trusting relationships. Sadly, “close interaction or familiarity does not promote the flow of scientific know-how…in fact it inhibits it” (Ensign, 2002, p.139). According to Ensign (2002, p.139) his research indicates that familiarity is more likely to breed contempt, not empathy or a willingness to share.

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This is further evidenced by the fact that “on average strangers are treated better than known others” and lends support to social exchange theory by “corroborating the out-for-tat strategy” – whereby “cooperative actors select members of the network that cooperate (abandoning noncooperative members)” (Ensign, 2002, p.139). In agreement with social exchange theory, Ensign (2002, p.138) also found that “past behaviour influences the sharing decision.” Thus, in order to understand the likelihood of knowledge sharing one must first understand the past behaviour of the recipient and the source and their relationship—including the recipient’s reputation, which is defined by the individual’s past behaviour and history. The two primary dimensions of interest in determining whether knowledge will be shared therefore include both the recipient’s reputation and the expected action that the recipient will take (Ensign, 2002, p.138). From the knowledge source’s perspective the recipient’s predictability, or “the source’s belief about the recipient’s future actions…was found to contribute to knowledge sharing” (Ensign, 2002, p.145). The “greater certainty with which the recipient’s future conduct could be regarded, the more likely the recipient was to receive technological assistance from the source for the R&D problem that motivated the request” (Ensign, 2002, p.145). The element of trust may be considered a factor as trusting co-workers would likely feel a greater sense of “certainty” that their colleagues would follow through with their actions. Likewise, the existence of healthy bonds between colleagues would diminish the need for predictability—trust is the firmest foundation upon which any relationship can be predicated. Similarly, reciprocity or “the expectation that the recipient would reciprocate, i.e., give help back to the source, to others in the firm, or even that others in the firm might provide help to the source, weighed in the source’s decision to share technological knowledge” (Ensign, 2002, p.140). Actions of reciprocity both increase the perceived

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benefits of sharing the knowledge in question and likely produces a more trusting relationship between the professionals. In this light, a “compelling case can be made that the dimensions of reputation, past behaviour and expected action, play a substantial role in exchanges where resources are intangible or for which contracting is costly or difficult” (Ensign, 2002, p.145). According to this analysis, the social mechanisms and psychology that comes into play when sharing knowledge allow for the evaluation of past behaviour and future expectations and may make “exchanges more efficient under certain conditions” (Ensign, 2002, p.145). Thus, an employee’s hesitance to share knowledge can be viewed as a mechanism to avoid negative outcomes, such as unbearable costs (in terms of time or energy). The existence of a trusting relationship may decrease the perceived cost of sharing information or knowledge with a colleague and result in increased utilization of the organizational memory stored in social networks and individuals. Although there are reports of knowledge sharing with acrimonious colleagues, this occurrence is the exception and runs counter to the rule that sources share knowledge with recipients with whom they have trusting relationships (Ensign, 2002, p.147). In the Ensign study, an acrimonious colleague was one who “received the highest scores for being someone who needs to be monitored (is untrustworthy) and is unpredictable and the lowest scores for personal friendship, professional relationship, freely sharing ideas, belonging to a communicative group, and likely to keep promises” (Ensign, 2002, p.147). Ulterior motivations, such as the pleasure and respect derived from sharing one’s expertise were identified as reasons for such actions (Ensign, 2002, p.147). One can conclude that the existence of a trusting relationship positively impacts information sharing by improving the perceived predictability of the recipient and adding an extra incentive to exchange information. This then begs the question, how does an organization improve information

sharing amongst individuals and units within the organization?

Solutions Though it is “not immediately apparent how one might foster such factors as predictability as reciprocity”, organizations should strive to encourage these sentiments in order to improve sharing (Ensign, 2002, p.148). Buckley and Casson (1988:38) indicate “to speed up reputation building, it may be advantageous to create…additional opportunities for agents to forbear reciprocally.” Buckley and Carter (1999) suggest that expectations deter opportunism; though monitoring is not set aside, the expectation that new knowledge will be provided leads to stable exchange relationships. In other words, by instilling the idea of reciprocity in employees and creating a social contract that values equitable exchanges the organization can encourage the trusting social networks needed to produce dynamic exchanges and build the organization’s memory bases. Furthermore, “the burden lies on the recipient to make the sharing of technological knowledge as little work for the source as possible, i.e., reducing the time and effort exerted by the source” (Ensign, 2002, p.149). Reducing the costs of sharing means reducing the cost of accessing valuable organizational memories captured by individual employees and managers. In addition to this, ensuring that organizations choose the right employees, namely those that are willing to share and are competitive at the group (not individual) level (i.e., placing the interests of the organization above incremental individual gains), the company can foster a sense of trust and spur knowledge exchanges. A trusting employee that is a team player is an employee that drives organizational learning and helps in the development of an organization’s memory bases (Vera and Crossan 2004). In fact, Adler (2001) states that economic and organization theory have shown that relative to price and authority mechanisms, trust and reputa-

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Effective Stakeholder Knowledge Sharing for Effective Organizational Memory

tion might play an important role in transactions involving knowledge-based assets. A team effort is essential given that entrepreneurial organizations, by nature, must assemble knowledge and information that is “incomplete and dispersed” (Rosen, 1997, p.140). Other authors reiterate the importance of an individual’s attachment to the organization. Wenger and Snyder (2000, p.144) state “if members don’t feel personally connected to the group’s areas of expertise and interest once it has been defined, they won’t fully commit.” In other words, issues such as trust, personal attachment and belonging may be determinative of whether sharing and learning can occur—whether in a small group or a big organization. Successful organizations will find ways to bridge individual interests and defensive tendencies in order to maximize the benefits derived from organizational memories that are innately stored in individual stakeholders’ minds. The word stakeholder includes customers and suppliers who are an extraordinary source of information that can be used to the organization’s benefit. Healthier customer relationships, resulting from the attentive management of customer needs, can yield knowledge-sharing resulting in the improved delivery of products and services (Robinson and Large, 2004, p.61). In addition, it is argued that trusting relationships with customers will also incidentally make the customer relationship more profitable for the business in the long run (Robinson and Large, 2004, p.49). In the absence of a trusting, predictable relationship, it could be postulated that sharing may occur where the knowledge in question has acquired the quality of property (Eliasson, 1992, p.253). In these circumstances, reciprocity can be viewed as a voluntary exchange of benefits that is based on the expectation of a future return, rather than a purely gratuitous exchange (which may occur in the absence of these benefits). It is plausible that by somehow “proprietizing” the knowledge in question an organization may facilitate knowledge-sharing between employees.

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This would alleviate the problem faced when a source voluntarily gives up knowledge to a recipient that cannot be expected to return the favour. By moving sharing from the realm of gratuity to the realm of opportunism the organization can circumvent the classic problem faced in knowledge exchanges. That is, knowledge’s uncanny “inalienable” quality that requires the clarification of relations between people including terms of kinship (Gregory, 1982). Given that objects of knowledge “are never completely separated from the men who exchange them” (Mauss, 1925, p.31) the sharing of knowledge will always involve a social element. Whether the organization chooses to work with this element by encouraging trusting relationships or minimize this element by proprietizing knowledge sharing, it will always pose a barrier to knowledge sharing and the growth of organizational memory banks on the whole. Sharing is therefore a critical determinant of the health of an organization’s memory systems as sharing is a prerequisite for the collection and access of information. Kransdorff (2006, p.124) has developed a six stage Experience-Based Management Cycle (or EBM Cycle) that encompasses the different processes that an organization must go through in order to collect, store, and access organizational knowledge in order to achieve organizational objectives. This chapter proposes an adapted version of this model in order to demonstrate the process through which mere data and information can be translated into relevant and commercially viable knowledge. The application of this model should be helpful in overcoming the problems associated with deficiencies in knowledge sharing amongst employees. By actively seeking out pertinent organizational knowledge and assembling this knowledge in a useful manner for the benefit of all of the organization’s units a company can avoid losing innate knowledge due to office politics. This model contrasts with the aforementioned approach that relies on employees to voluntarily divulge information and share knowledge. By systematically eliciting and assem-

Effective Stakeholder Knowledge Sharing for Effective Organizational Memory

bling a company’s knowledge and then integrating it into its organizational memory system some of the difficulties faced by individual employees in accessing knowledge from social networks can be addressed. An active approach is necessary in developing organization memory bases. The first stage in Kransdorff’s model (2006, p.124) involves a planning stage to “prune the (organization’s) potential learning opportunities down to a manageable size that harmonizes with the organization’s perceived requirements.” At this stage the organization must determine what knowledge and systems currently exist and where perceived knowledge deficiencies lie. Further, the role that this knowledge plays in the business (relative to operational elements etc.) should be determined. Kransdorff (2006, p.124) recommends the use of knowledge charts, project maps, and employee transit audits in order to achieve this. Second, the organization must work to “ensure that experiences don’t walk out of the front door and that organizational memory, when it is recalled, is not imprecise” during the knowledge capture stage (Kransdorff, 2006, p.124). This requires that the organization surveys and collects data and relevant information derived from individual and group experiences. This entails keeping accurate records of difficulties faced and any important lessons learned. Though individuals may naturally capture experiential knowledge and may even share this knowledge voluntarily, as demonstrated by the Ensign study, capturing it for the benefit of the entire workforce is an entirely different challenge. Kransdorff suggests archives (such as databases, intranet systems and electronic bulletins), oral debriefings, and keeping a corporate history to capture knowledge. Third, a reflection phase is required to “make sense of information, extract meaning and relate this to everyday organizational and wider business life” (Kransdorff, 2006, p.124). This entails using the information and data captured to produce commercially valuable knowledge that is reflective of the business’ particular goals and circumstances,

and involves organizing, adapting or editing the information in a manner that increases the information’s relevance and applicability. The reflection stage, as is suggested by its name, requires that the organization both examine itself and the information to better understand how the pieces of the puzzle fit together. Fourth, a lessons audit should be conducted to “allow for the institution-wide fertilization across the organization and down the generations so that learning becomes more corporately based” (Kransdorff, 2006, p.124). This audit should involve some sort of review of existing organizational memories and create a continuity that passes relevant lessons down to future generations and other organizational units. The audit should also filter out items that must be unlearned—namely those attitudes and solutions that are no longer helpful or are even detrimental to the organization’s goals. According to de Holan and Phillips (2004, p.1611), “if critical knowledge is forgotten, the competitiveness of the organization is lost and forgetting would have been better avoided”. However, “if the forgotten knowledge was extraneous or was actively interfering with the application of more appropriate knowledge, then forgetting was a positive occurrence” (de Holan and Phillips, 2004, p.1611). De Holan and Phillips’ (2004, p.1611) argument is that organizational forgetting is an important part of creating an effective organizational memory system given that much of the knowledge that organizations acquire is disruptive to future learning or is of inferior quality. Thus, in some cases it is reasonable for organizations to spend “considerable time…trying to forget something that (is) no longer or never had been functional” (de Holan and Phillips, 2004, p.1611). In other words, forgetting in order to filter out erroneous knowledge and make way for newer improved knowledge is a necessary step.The lessons audit performs this function by filtering and disseminating relevant knowledge across the organization. According to Cicourel (1990 as cited in Olivera, 2000, p.816), this in-

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Effective Stakeholder Knowledge Sharing for Effective Organizational Memory

creased filtering affects the recipient’s perception of the information’s credibility. Despite this, it is an important and necessary part of the entire experiential learning process. Kyriakos and de Ruyter (2004, p.1493) also touch on this subject by noting some of the pitfalls that firms who blindly rely on past knowledge face. According to these scholars, “too much reliance on prior procedures, however, reveals the classic problems as observed in the extant literature; core rigidities’ and ‘not invented here syndrome’ even in the presence of new information from external parties” (Kyriakos and de Ruyter, 2004, p.1493). This leads them to recommend that organizations use “moderate levels of procedural as well as high levels of declarative memory” in order to avoid some of the dangers of relying on old knowledge in the context of product development (Kyriakos and de Ruyter, 2004, p.1493). Kransdorff’s (2006, p.124) lessons audit works to filter out inferior memory, both procedural and declarative, and disseminate useful memories throughout the organization. Lastly, the organization must continually reassess (or reprocess) the value of the knowledge it has stored in its organizational memory systems. Further, the organization must evaluate its systems and seek to make improvements wherever possible (Kransdorff, 2006, p.124). This means adjusting organizational knowledge to new norms or conditions and assessing its role in light of these changes. According to Kransdorff, by following this process companies apply incremental learning in a way that will yield massive benefits for the entire organization. “If every manager identified just one lesson per month that was translated into a better decision, the collective impact across the organization would be considerable” (Kransdorff, 2006, p.125). More notably, actively collecting, storing, and accessing organizational memory for the benefit of the organization at large may help to deter “defensive” behavior and diminish the problems that it produces.

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F TRENDS According to Swedish management professor Jonas Ridderstrale (2003, p.27) “we are in the midst of a revolution at least as important as the industrial one” but oddly, “companies are proving slow to respond in terms of restructuring themselves to use, rather than abuse, knowledge” (Ridderstrale, 2003, p.27). Organizations, by nature, are reliant on structures and changing those structures to accommodate organizational learning and the development of organizational memory systems poses a very real challenge to many companies. Further, making the organization flexible enough to adapt when necessary to capture, store and access relevant information is an even greater challenge. Given that “the overall ratio of tangible to intangible resources has shifted”, organizations need to learn to apply the same savvy to managing people and ideas as they already do to managing balance sheets and company finances (Ridderstrale, 2003, p.27). This entails moving away from what Ridderstrale (2003, p.27) jokes is “business autopsy” toward “pre-emptive medicine.” In other words, organizations need to be proactive is managing their memory systems in order to survive in this age of multinational companies and instantaneous information exchange. The model suggested in this chapter is a good start, but formal structures cannot be success if not accompanied by the right culture and environment. In the future, developing informal social networks and other structures may prove to be critical in order to ensure the sharing of organizational knowledge and the development of memory. In fact, the facilitated growth of so-called communities of practice and other informal social networks has proven to be a defining event in the evolution of modern management practices. Companies are only as healthy as their people—including their customers, employees, managers, and other stakeholders—and must learn to adopt an approach that values and integrates the

Effective Stakeholder Knowledge Sharing for Effective Organizational Memory

knowledge gained from all these groups. In fact, even Bill Gates has admitted, “if 30 people were to leave Microsoft the company would face bankruptcy” (Ridderstrale, 2003, p.29). In this light, many scholars have advocated the development of communities of practice, social networks, and other social structures to ensure that the transmission and dissemination of knowledge occurs (see Wenger and Snyder, 2000). Though such communities normally evolve organically, without the interference of management, Wenger and Snyder (2000), amongst other scholars, advocate that companies take a more active approach by nurturing these communities. According to these scholars, managers can turn their companies into incubators for communities that spawn learning and act as fountains of organizational knowledge. Wenger and Snyder (2000, p.140) contend “successful managers bring the right people together, provide an infrastructure in which communities can thrive, and measure the communities’ value in non-traditional ways.” This means creating the precursory conditions for the growth of these communities. For instance by providing the resources and the flexibility to employees who wish to voluntarily organize themselves into communities of practice and then abstaining from interfering with the community (Wenger and Snyder, 2000, p.142-143). Communities of practice, which are already used by many companies but are greatly underutilized, “are informal—they organize themselves” and can facilitate sharing by offering employees an opportunity to discuss both “successes and frustrations” (Wenger and Snyder, 2000, p.142). For this reason communities of practice and other informal social networks will play a greater role in the future of knowledge management and organizational memory. Though they have always existed in some form, nurtured communities of practice are an important emerging trend given their potential to stimulate sharing and overcome some of the social barriers to learning (Wenger

and Snyder, 2000), and are not used nearly as often as they could be. Although Ensign (2002, p.139) concludes that a negative correlation exists between familiarity and the likelihood of sharing know-how, future research would be merited to test if this relationship changes when group members are brought together voluntarily and are bound by trusting, positive relationships. Presumably, the reputations of members of communities of practice would score higher given that these voluntary associations are created with the expectation that participants will engage in reciprocal exchanges of knowledge. Why else could communities of practice have the potential to “radically galvanize knowledge sharing, learning and change” if these factors were not in place (Wenger and Snyder, 2000, p.139). Further research into the complexities of trust in an office situation would be merited along with research into the “efficacy of the transmission” of know-how (Ensign, 2002, p.146). In addition, a number of serious questions still exist as to how a company can increase reciprocity in knowledge sharing and deter the formation of negative bonds that breed a reluctance to share information and knowledge. This being said, the use of Kransdorff’s learning cycle and taking actions that foster a sense of trust amongst employees should prove fruitful in developing robust bases of organizational memory. Finally, Ensign (2002, p.146) also notes the need for more information on the decision process that an individual goes through when deciding whom to contact for assistance. Future research in this area could be helpful in understanding whether the recipient interferes with the knowledge sharing process and the underlying psychology that is determinative of whether exchanges occur. Leaders must understand the psychology of organizational learning and knowledge sharing before they can strategize how to retain organizational memories that are relevant to organizational goals.

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Effective Stakeholder Knowledge Sharing for Effective Organizational Memory

CONCLUSION The information age and globalization has produced a situation where competitive companies can only remain competitive if they learn to manage what they know in a manner that allows them to meet organizational objectives. Given that the “economic value of knowledge is becoming much greater” this skill will become increasingly important in the coming years (Ridderstrale, 2003, p.27). Successful companies will be able to manage what they know to the benefit of all stakeholders, including customers and employees. Overcoming the challenges of knowledge sharing by building an environment that emphasizes trusting relationships and reciprocal sharing, in addition to designing structures that enable the formal elicitation of relevant information and knowledge (such as the model recommended by Kransdorff (2006)), will improve an organization’s ability to cope with these challenges. Healthy organizational memory systems, namely social networks and computer systems, are buttressed by knowledge sharing at all levels of the organization. This includes benefiting from interactions with external stakeholders, such as clients and customers, as well as internal stakeholders. More importantly, sharing can be encouraged by choosing the right employees, designing appropriate organizational memory systems, building trusting communities, and encouraging employees to reciprocate when colleagues share knowledge. As “intelligence and intangibles replace raw materials and capital as the true sources of competitive advantage” organizations will need to learn to better assimilate disparate information, shedding problematic old knowledge in favour of superior knowledge (Ridderstrale, 2003, p.27). A trusting corporate culture that values sharing and provides ample opportunities for such exchanges, as is increasingly being done through communities of practice, will go a long way in promoting the company’s efforts to develop and utilize organizational memory. Complementing

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this atmosphere with technological and social structures that assist in the collection, storage, and access of organizational knowledge will yield benefits to internal stakeholders and external stakeholders alike, who will benefit from more efficient exchanges, greater customer satisfaction, and overall improved productivity and company performance. Constructing an environment that is conducive to the development of organizational memory will prevent firms from repeating past mistakes and separate the winners from the losers in the information economy.

REFEREN Adler, P. S. (2001). Market, hierarchy, and trust: The knowledge economy and the future of capitalism. Organization Science, 12(2), 215-234. Buckley, P. J., & Carter, M. J. (1999). Managing cross-border complementary knowledge. International Studies of Management & Organization, 29(1), 80-104. Buckley, P. J., & Casson, M. (1988). A theory of cooperation in internationalbusiness. In Contractor, Farok J. & Lorange. Peter (eds.) Cooperative strategies in international business. Lexington, MA: Lexington Books. de Holan, P. M., & Phillips, N. (2004). Remembrance of things past? The dynamics of organizational forgetting. Management Science, 50(11), 1603-1613. Eliasson, G. (1992). Business competence, organizational learning, and economic growth: establishing the Smith-Schumpeter-Wicksell (SSW) connection. In Scherer, Frederic M. & Perlman, Mark (eds.) Entrepreneurship, technological innovation, and economic growth: studies in the Schumpeterian tradition. Ann Arbor, MI: University of Michigan Press.

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Ensign, P. C. (2002). Reputation and technological knowledge sharing among R&D scientists in the multidivisional, multinational firm. Montreal: Univeristy of Montreal, Unpublished Dissertation. Girard, John P. (2006). Where is the knowledge we have lost in managers? Journal of Knowledge Management, 10(6), 22-38. Girard, J. P. (2005). Taming enterprise dementia in public sector organizations. International Journal of public sector management, 18(6), 534-545.

Olivera, F. (2000). Memory systems in organizations: An empirical investigation of mechanisms for knowledge collection, storage and access. Journal of Management Studies, 37(6), 811-832. Privacy Guru Joins IBM. www.crm-forum.com, November 30, 2001, p.1. Ridderstrale, J. (2003). Cashing in on corporate competencies. Business Strategy Review, 14(1), 27-38.

Gregory, C. A. (1982). Gifts and commodities. London, UK: Harcourt Brace Jovanovich.

Robinson, N., & Large, D. (2004). PIPEDA: Impact on CRM and public-private sector interaction. Optimum Online: The Journal of Public Sector Management, 34(4), December 2004, 47-60.

Kransdorff, A. (2006). Corporate DNA: Using organizational memory to improve poor decision making. Aldershot, UK: Gower Publishing.

Rosen, S. (1997). Austrian and neoclassical economics: Any gains from trade? Journal of Economic Perspectives, 11(4), 139-152.

Kyriakos, K., & de Ruyter, K. (2004). Knowledge stocks and information flows in new product development. Journal of Management Studies, 41(8), 1469- 1498.

Vera, D. & Crossan, M. (2004). Strategic leadership and organizational learning. Academy of Management Review, 29(2), 222-240.

Mauss, M. (1925/1974). The gift: Forms and functions of exchange in archaic societies. London, UK: Routledge. Moorman, C., & Miner, A. S. (1997). The impact of organizational memory on new product performance and creativity. Journal of Marketing Research, 34(1), 91-106.

Wenger, E. C., & Snyder, W. M. (2000). Communities of practice: The organizational frontier. Harvard Business Review, 78(1), 139-145. Yang, J-te (2007). The impact of knowledge sharing on organizational learning and effectiveness. Journal of Knowledge Management, 11(2), 83-90.

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Chapter IV

Revising the SECI Model for American Organizational Culture Jerry Westfall Liberty University, USA

ABSTRACT This chapter discusses the revision of the SECI model originally based on Japanese organizational culture into a model based on American organizational culture. The argument presented is that the original SECI model was developed from a Japanese perspective that does not align well with the American perspective. The American perspective is much different than in other cultures because individualism is paramount, but when compared to the group-centric culture of Japan, the differences are made evident. The hope is that by converting the model to a culturally relevant one that it can be better used as a foundation for understanding organizational knowledge transfer thereby improving organizational memories.

IN The general perspective of this chapter is the multinational or more specifically the multicultural aspect of the knowledge management field. The multicultural aspect is found in recent years to be vital for securing global market share and economic success. The difference in cultures is explicitly examined in this chapter concerning the flow of knowledge within organizations. The difference is between Japanese and American organizational cultures pertaining to knowledge management.

Much ink has been spilt on describing knowledge. Scholars from all areas of the globe have written, presented, or spoken about knowledge. The pursuit of knowledge is one most of us can agree upon as a foundational drive inherent in humans. This drive to learn motivates us to develop cognitive theories that will guide us in our understanding of knowledge which we can then apply within the knowledge management realm. A foundational knowledge management concept that was developed in Japan by Nonaka and Takeuchi (1995) is called the SECI model (Socialization, Externalization, Combination,

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Revising the SECI Model for American Organizational Culture

and Internalization Model) which according to the authors models an organizational knowledge system based upon their observations in Japanese organizations. Their work has been used in numerous research projects and is often referenced in articles and books all around the world. Their contributions to the knowledge management field are innumerable and their theories form the basis of this chapter. The SECI model describes the theory of knowledge flow within an organization from tacit to explicit knowledge. Tacit knowledge is that knowledge which is internal and relevant to the originator of the knowledge (Polanyi, 1958). It is knowledge which is often hard to explain to others. We know what we know, and we can often give others the reasons we know it and describe to them how to obtain this knowledge. This means converting our internal or tacit knowledge into explicit forms. Explicit knowledge is that which we can make known externally and thereby the ability to give this knowledge to others (Connell, Klein, & Powell, 2003). However, tacit knowledge is sometimes difficult to reproduce for others and this is why we need to understand knowledge more thoroughly so we can make the tacit knowledge conversion process work better for knowledge generating organizations. The emphasis in this chapter on the SECI model is based on the need, as I see it, to revise the highly successful Japanese SECI model into a model that works for more western cultures, specifically the United States of America. Therefore the information contained in this chapter is to present the similarities and differences in Japanese and American cultures that obviate the need for a more specific American cultural model. The SECI model is in no way invalid, but since it was developed in Japan and based on Japanese organizations, I believe, it is most useful when applied to that country’s organizational culture. However, if we push the detail of the model to the US which, by and large, has different organizational cultures the model doesn’t fit as well.

Finally, although the fit is not quite right there is considerably much to gain from looking at the SECI model as developed by Nonaka and Takeuchi in the 1990s. This will give us the foundation we need to explore the changes given later in the chapter when an SECI model is revised for American organizational cultures.

BA Nonaka and Takeuchi (1995) developed the SECI model to describe the transfer of knowledge within an organization. The SECI model has four processes or phases that follow a logical path for tacit to explicit knowledge conversion. Their four phases are: •

•

•

Socialization: Direct interactions, over time, resulting in knowledge transfer via physical proximity. Externalization: Translation of tacit knowledge into externally comprehensible forms. Combination: Conversion of explicit knowledge into more complex forms.

Figure 1. SECI Model

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Revising the SECI Model for American Organizational Culture

•

Internalization: Converting explicit knowledge into tacit knowledge for organizational benefit which relies on action and practice as well as simulation and experimentation.

The SECI process is a spiral approach to learning within organizations (Nonaka & Toyama, 2002). Within the original SECI model there is a process of synthesis that develops making knowledge transfer acceptable to the participants in the exchange system. Knowledge creation becomes the key to processes derived from the organizations values and views which is termed knowledge vision (Nonaka & Toyama, 2002). Knowledge vision is the organizational ba which provides value and gives direction to the knowledge conversion spiral or SECI model (Nonaka & Toyama, 2002). Directly linked to these four phases are the four types of ba. Ba refers to the shared context wherein individuals share knowledge through knowledge interaction, utilization, and creation (Kothuri, 2002). Ba is the term used by Nonaka and Takeuchi (1998) to describe this relational phenomenon in organizations. In Japanese ba means place, field, or space. The four ba phases correspond to the four phases of the SECI model and are outlined below: 1.

2.

3.

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Originating ba a. Corresponds to the Socialization Phase of the SECI Model b. Sharing feelings, emotions, and mental models c. Face-to-Face interaction Interacting ba a. Corresponds to the Externalization Phase of the SECI Model b. Individual skills or “know-how” and mental models are converted into common terms and concepts Cyber ba a. Corresponds to the Combination Phase of the SECI Model

4.

b. Technology is used to represent and present the explicit knowledge derived in the interacting ba process Exercising ba a. Corresponds to the Internalization Phase of the SECI model b. Explicit knowledge is converted into tacit knowledge through training and self-refinement

Within the SECI model context then ba is the process that motivates the internalization cycle of explicit knowledge conversion into tacit knowledge. This process according to Nonaka and Takeuchi is important to understand when developing knowledge management functions within an organization. Once understood then at the minimum a knowledge conversion process can be defined, developed, and utilized. Knowledge vision is the organizational ba which provides value and gives direction to the knowledge conversion spiral of the SECI model (Nonaka & Toyama, 2002). This vision cannot be free from the organizational context it is intended to become part of (Nonaka & Toyama, 2003). The fundamental idea found within this model is that through interactions individuals absorb explicit knowledge and convert it to tacit knowledge which they use daily to fulfill their work requirements, and thereby contribute to the overall organizational goals, strategies, and outcomes. The goal of knowledge managers then is to develop methods and means to keep this cycle working and to capture knowledge whenever possible to ensure successful knowledge transactions.

ISS ContROERSIES PROBLE There are some who suggest that the SECI model is not as relevant to knowledge management research as was thought when it was introduced in 1995. Dave Snowden (2003) considers the SECI

Revising the SECI Model for American Organizational Culture

model as part of the “Second Age” of knowledge management. His belief is that the SECI model does not go far enough to encompass flow, context, and complexity of knowledge. Snowden believes we always know more than we can share or tell. Because of this failure of the SECI model Snowden postulates a third age of knowledge management involving complex, complicated, and chaotic knowledge. Snowden clearly believes that knowledge management is much more than making a knowledge transfer from one employee to another. He believes that although the model is useful in knowledge management research it should be a model only and not describe the actual processes involved in knowledge transfers. Where Nonaka and Takeuchi’s SECI model focuses on the movement between tacit and explicit knowledge states and is widely regarded as a credibly designed and postulated theory, Snowden (2003) believes that there are chaotic forces at work in organizational knowledge processes that force us to reconsider whether the SECI model is a usable model within organizations. The differences between these two theorists is striking but understandable when viewed in light of other theorists like Stacy (2001) who believes that knowledge cannot be measured, stored, or managed. Snowden and Stacy both argue that knowledge is not a thing, but a process that cannot be treated as a scientific system. Stacy (2001) goes farther and postulates that knowledge management so far has been about content management. Snowden (2000) also argues that knowledge management has been focused on the container and not the knowledge contained. They believe that this leads to a misunderstanding of knowledge and a greater emphasis on content management processes instead of on knowledge itself. Even though there are some dissenting theories refuting the SECI model as a foundation or tool for understanding knowledge conversion in organizations, the overwhelming consensus is that the SECI model is very useful and relevant

for understanding the tacit to explicit knowledge conversion processes in organizations. Regardless of the contrary theories noted here, the SECI model has proven valuable to knowledge management research. However the original model itself does not represent well other styles of organizational knowledge processes or more specifically those found in the differences between Japanese and American organizations. The current SECI model works well in the context of the Japanese organizational structure, as it was intended to do, but when applied to American organizational structure it does not define the processes as well.

The Japanese Oganization The Japanese organization style is rooted in the tradition of groupism (Hayashi, 1990). Groupism is the individual’s identity with a group to the extent that their individuality is not completely repressed, but it is submissive to the group (Graham, 2003). The group in Japanese organization is the foundation for loyalty, belonging, and family. It is the group that dictates the employee’s work life and becomes a driving force in the lives of Japanese employees. The Japanese organization cultivates the groupism within its control and lifelong employment becomes the norm where individual effort is rewarded by participation in the group. The Japanese organization relies on that sense of belonging to control employee behavior and turnover. Although individuals contribute to the group in organizations, the strong cultural sense of groupism requires the Japanese employee to give their complete loyalty to the group they belong to within the organization. Dishonor becomes a reality for the group members and acting out in a manner not supported by the group leads to dishonor and often dismissal from the organization. Dishonor is a serious proposition for the Japanese and is culturally motivated by centuries of societal development.

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Revising the SECI Model for American Organizational Culture

To be dishonored is one of the highest forms of disgrace to the Japanese. This concept has its roots in the Samurai and Bushido ways (Lang, 2003). These values have defined Japanese culture for centuries and their influence continues today. The Bushido way demands extreme loyalty to the head of the group. Honor and sacrifice are the earmarks of a good Japanese citizen. The values expressed in the ways of the Samurai and Bushido continues to influence Japanese culture and therefore Japanese organizations. The vastness of Japanese culture norms and values is beyond the scope of this chapter, however it is worth noting that there is a long and proud tradition in Japanese culture and it is a fascinating study in its own right. In summary the Japanese employee has a deep cultural system that defines their attitude toward the head of the group and to the members of the group. They display a deep sense of honor and sacrifice which is the expected normal behavior. Therefore when this cultural system is placed within Nonaka’s and Takeuchi’s SECI model it is clearly relevant to the Japanese organizational system. The SECI model defines the dynamic of the group mindset in Japan well and gives a good foundational model for the knowledge processes involved in that culture.

The SECI Model Processes in Japanese Organizations The SECI model depicts in the externalization quadrant that the individual Japanese employee contributes their tacit knowledge through externalization to the group to which they belong. The group becomes the center for knowledge transfer and is the primary unit of knowledge processes in the Japanese organization. The group is the recipient of the individual employee’s knowledge and uses this knowledge to further the goals of the group. The Japanese sense of honor and willingness to sacrifice for the group provides an ideal

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environment for knowledge transfers that might not otherwise happen within the organization. The individual is rewarded for contributions to the group (Graham, 2003) and obligations are a matter of honor to be repaid to the members of the group whenever the employee is able to do so. Obligations are thought to be essential to satisfy honor and to continually improve the group. Therefore contributing to the group satisfies both any obligations that arise and the honor code of the Japanese worker. The cultural emphasis on the group provides an ideal situation that the SECI model incorporates well. The SECI model depicts in the combination quadrant that the group provides this knowledge to the organization. The organization becomes the beneficiary of the tacit knowledge of the individual by way of the group. The group is thought of as the employee and its primary emphasis here is to disseminate the explicit knowledge to the rest of the organization. Given this process the group is then rewarded for excellence which in turn trickles down to the individuals within the group. The group however is the primary motivator of these knowledge exchanges. The organization is the beneficiary of the knowledge and because it is already in explicit form there is no need to convert it for additional organizational dissemination. This gives the group more power within the organization than the individual. Within Japanese organizations the individual is rewarded through the group, but in contrast they are criticized individually. This dichotomy of performance culture is a source of stress and anxiety for the Japanese employee. The Japanese employee will speak more readily about the individual’s failures, but not about the group’s failures. This dichotomy of Japanese work culture further reinforces groupism. Therefore the SECI model again provides an excellent peek into the Japanese organizational culture. The SECI model in the internalization phase defines the overall knowledge transfer structure defined by Nonaka and Takeuchi for the Japa-

Revising the SECI Model for American Organizational Culture

nese organization. The individual contributes to the group and the group contributes to the organization as a whole. The process flows from individual effort and knowledge to group effort and knowledge on to organization knowledge. The organization’s effort is diminished because the group has already developed the explicit knowledge content. Once the internalization process is complete the process begins again in the socialization phase where individuals work together and develop new tacit knowledge that they can then share with the group to begin the knowledge transfer process anew. What this means for the Japanese organization is that retaining knowledge is motivated by the group effort to product that knowledge. The members of the group are treated collectively and therefore any knowledge generated is attributed to the group. What one group knows other groups may learn through training, but the process involves the group. Individualism is not encouraged and the knowledge of the individual is only relevant in that it elevates the entire group status. This group status defines the Japanese employee throughout their employment history. Since the individual is less encouraged to share their knowledge with others sometimes only their group has it and the chance to convert it to explicit knowledge is reduced unless the group is committed to that knowledge sharing. The process of knowing what we knew is hampered in an organization where the group is responsible for the tacit to explicit knowledge transfer (Graham, 2003). If the group decides to retain the knowledge that was converted due to an obligation or as a matter of honor then the knowledge does not get shared to the rest of the organization and the individual cannot speak on their own behalf if the group decision is final. This then makes for a difficult time in developing the organizations memory. Building organizational memories is hampered depending on what the groups in the Japanese

organization decide to do with their tacit knowledge. Normally it would be an obligation to report to the organization, but when honor is at stake there may be a resistance or reluctance to do so. This becomes a sticking point for building organizational memories in a group-centric organization.

The Problem with the SECI Model in Aerican Organizations The problem with the SECI model for American organizations is that it does not describe the American employee work culture very well but can serve as the foundation for translation to the American work culture. This translation is discussed in the following sections. The primary revision defined here is to make the SECI model, which has been most helpful in the past for development of sound knowledge management processes, more reliable for American organizations. The reason for this change is that when we look at American work culture, described in the section below, we find that individualism is the primary force affecting employees in America (Tocqueville, 2003). In contrast to the Japanese group-centric organization the American organization is defined by the individuals’ contribution to organizational memories. Defining the American organizational culture first is important to be able to understand the revisions proposed for and to the original SECI model. Just as we have discussed the Japanese organizational culture we will examine the American organizational cultural history and then develop the revised SECI model, and finally describe the processes involved within the changed phases of the model.

The American Organization The American organization is built, just as the Japanese organization, with individuals. These individuals comprise the workforce of both

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American and Japanese organizations. However there are differences between the cultural systems of each country’s employees. These differences are what have prompted the revision of the SECI model. The revisions take into consideration the differences between American and Japanese individuals in regards to their connection to the employing organization. An American cultural trait is found in that of expectionalism. Alexis De Tocqueville stated that Americans strive for individualism because they are products of a revolution that was fought to secure liberty (Tocqueville, 2003). Liberty, once fought for, becomes a force within the culture that produces people who have a strong sense of freedom of the individual or what we call personal liberty. The American Revolutionary War was fought to secure liberty for the people in the United States and this was due to the overwhelming need for personal freedoms. The primary freedom was that of, freedom of religion, but the hard fought war caused a cultural shift to the idea of personal liberty (Shafer, 1999). Personal liberty became a focus for the early Americans and became a driving force in all aspect of life for the country. The Constitution guaranteed individual rights, and the Declaration of Independence specifically prescribed the pursuit of happiness, life, and liberty for each citizen. There was no century’s long cultural history, such as the Japanese had in the Samurai tradition, therefore Americans developed their culture based on the pursuit of liberty gained from their victory in the Revolutionary War. The American culture itself fosters individualism, which is in stark contrast to the Japanese culture of groupism. This difference has prompted the revision of the SECI model to accommodate the American organizational knowledge culture. The revisions are only minor, but they reflect the model of American organizations much better than the original model. The model’s foundations remain intact with only differences found in the details of the four phases of the model.

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Maguire and Kroliczak (1983) found through their research that Japanese and American workers had diverging attitudes about their organizations. They found that Japanese workers focused on groupism and that American workers focused on individualism. This was discovered in the differing attitudes about life-time employment, personal advancement, and systems of rewards and punishments. Their findings further suggest that the revision of the SECI model is in order to accommodate American organizational cultures. Additionally Kim, Emmett, and Sikula (2001) looked at the changing nature of the American workforce in the past decade and discovered that American employees were less loyal to the organization, more focused on their individual needs, and less committed to the organizations goals and strategies. Employee turnover is a prominent feature of the American organization landscape. This is in contrast to the Japanese attitude of life-long employment and total commitment to the organization. This research further argues in favor of a revision of the SECI model to align it to American organizational culture. In summary the SECI model as originally proposed fits Japanese organizational culture very well, but does not reflect well the American organizational culture. This has prompted the revision to the original SECI model to reflect the workforce culture in the United States. The revised model is outline in the next section.

The SE Model Process in Aerican Organizations The revisions made to the SECI model are not major changes, but are minor changes that reflect the culture of American organizations better than the original model. Since the original model was designed around Japanese organizations, it makes sense that it might not fit completely when applied to other organizational cultures. In this specific instance the culture is American organizational culture to which we apply the SECI model. As

Revising the SECI Model for American Organizational Culture

noted previously there are major differences in American and Japanese cultures in general and these differences are reflected in their respective organizations. To account for the differences in the cultures of groupism vs. individualism the SECI model was revised. In America the individual is supreme and in Japan the group is supreme. The historical evidence for both these differences are abundant, but the important aspect to keep in mind is that the SECI model works for both cultures with only minor revisions needed to better fit with American organizational culture. In the socialization phase there has been no revisions made because it is the same for both cultures, which is to say that there are always interactions between individuals within an organization whether in Japan or in America. The social exchanges may be different due to historical and cultural differences but nevertheless individuals interact daily within the organization. In the externalization phase a revision is made. This revision reflects the individualism inherent in American culture. The individual in this phase typically provides knowledge to the organiza-

Figure 2. Revised SECI model

tion. Although many American employees work in groups, there is not the sense of loyalty to the group as pervades Japanese organizations. The American worker may have a loyalty to the organization, but as previously stated there is no sense of lifetime employment expectations in American workers as there are in Japanese workers. Therefore in this revision the American employee individually contributes to the organization, maybe through a group, but not in the same way that the Japanese worker provides their contributions. The group dynamic in American organizations is one of mutual support, but only as long as the benefits to the individual out way the risks of group membership. Turnover in group membership is high in American organizations, and again the individual’s needs and desires take precedent over the group’s or even the organization’s needs (Maguire & Kroliczak, 1983). As with anything there are always exceptions to the norm in both Japanese and American organizations. Therefore the generalization of American individualism and Japanese groupism is not 100% certain. However, the evidence is sufficient to warrant that a distinction be made between the two culture’s organizations. In the combination phase the revision indicates that the organization disseminates knowledge throughout its individual members via group training. This is understandable in that American organizations spend billions of dollars annually training their employees. They do this most efficiently by training in groups. However, these are temporary groups only which are created to facilitate training at appointed times and then the groups are dismissed. The group simply becomes a way for the organization to train many people at once. Explicit knowledge therefore is not concentrated at the group level, but at the organization level. This gives the power of the knowledge to the organization. The individual is only considered important in the capture of knowledge, not in the

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control of the knowledge which is the domain of the organization. In the internalization phase of the revised SECI model the flow of knowledge from explicit to tacit is depicted in its entirety. The organization disseminates explicit knowledge through group training and each group is made up of individuals that incorporate the explicit knowledge training into their daily working lives and the cycle of knowledge transfer and conversion begins anew in the socialization phase of the SECI model and the revised SECI model. The complete SECI model revision then signifies the changes necessary to utilize the model in, this instance, American organizations. Because American organizational culture is based on individual contributions which are based on the cultural emphasis on personal liberty, the revised SECI model is more useful a tool for explaining knowledge transfers and conversions in American organizations. Therefore in American organizations the emphasis normally is placed on individual knowledge capture. This entails establishing a way to capture this knowledge so that the organization memories can be built in some manner. Without the benefit of individual knowledge capture the organization’s memories would be lost and we would never be sure we know what we knew.

FUTURE TRENDS What does the revised SECI model give us in America? The answer to this question is that in America we are concerned with keeping or maintaining our position in the global economy. This is making us think about how to capture, convert, and disseminate knowledge that is locked away in our employees minds (tacit knowledge). The revised SECI model gives us a look at the dynamics of the knowledge conversion process and should provide us a foundation for develop-

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ing plans to make our own knowledge conversion procedures better. The goal of this revision is to focus more on the individual, which is primary in American organizations. The groupism of Japan does not fit the individualist culture of America very well, and the differences this makes in organizations is significant. Whereas the Japanese capture group knowledge, Americans capture individual knowledge. The differences in the dynamics of individuals and groups are important to consider when developing a knowledge capture, conversion, and dissemination plan. For the future we must look to the individual knowledge source in America and design our knowledge capture systems to function with the individual. This brings up many questions that need to be answered in order to successfully capture and convert knowledge: 1. 2.

3. 4. 5. 6. 7. 8. 9.

How do we capture individual knowledge? What tools must we design to handle individual contributions to our knowledge base? What method do we use to illicit contributions by the individual? What is the motivation needed to ensure individual participation? How do we manage the conversion of individual contributions? What is the best method for explicit knowledge training? How do we know that we are capturing all the knowledge we wish to? How do we promote individual interactions to increase knowledge creation? How do we measure knowledge conversion from the explicit to the tacit?

These questions and many others must be answered at some point in the future by the organization if they are to succeed in their knowledge management endeavors.

Revising the SECI Model for American Organizational Culture

The result of looking at the Japanese and American SECI models is to focus attention to the differences in organizational cultures that exist between these two example countries. Therefore, once properly focused on cultural differences then other revisions of the SECI model might be in order when looking at other countries organizational cultures. In a global marketplace or marketspace (Rayport & Sviokla, 1994) there is a need to be relevant in the culture with which we engage in business. Understanding that American organizational culture is different from other organizational cultures provides a benefit in focusing attention to the source of knowledge within the organization. If the source is understood then some type of plan may be created to capture, convert, and disseminate the knowledge successfully. The tacit to explicit conversion, although not addressed in this chapter, is important in that organizational knowledge is tied up within the organization’s employees (Droege & Hoobler, 2003). The tacit knowledge if left un-captured does not benefit the organization and may lead to market disadvantages. Turnover of employees must also be considered in the future as we strive to capture relevant knowledge before the employee leaves the organization. The individualism inherent in American culture must also be considered and plans created to function successfully in this environment. Where turnover is high, there must be viable tacit knowledge capture procedures that give the organization control of the knowledge they hope to retain for future employee training. The organization then must use whatever tools, models, or theories that best fit their organizational culture to provide a good foundation for planning their knowledge management processes and procedures. As the theme of this book indicates in: ”Building Organizational Memories: Will You Know What You Knew?” the desire for the organization is to retain the best possible knowledge for use throughout the organization now and in the future.

The loss of some critical knowledge necessary for organizational success may be damaging and the results of this loss disastrous for the organization. The organizational memory therefore must be protected and made available and useful to the organization. There are no easy answers to maintaining organizational memory, but the emphasis currently is to understand how knowledge is exchanged, captured, converted, and disseminated to ensure organizational success. Foundational to understanding organizational memory is to understand the basic dynamics of the knowledge creation process. The SECI model and the revised SECI model both provide this foundation. Although it does not answer many of the questions we asked earlier, it does provide a basis for understanding knowledge flows within the organization. This is important for anyone interested in research, management, or utilization of knowledge to better guide their endeavors to achieve their knowledge concept goals. Building organizational memories involves people and understanding people is most important to this process. Understanding individualism or groupism, regardless of the prevailing culture, is beneficial to anyone concerned or interested in knowledge management concepts. Building organizational memories must be guided by the underlying principles or concepts involving individuals, groups, and organizations. These underlying principles and concepts, whatever they are, gives organizations a better foundation and framework within which to encourage, develop, capture, convert, and disseminate the organization’s memories.

FUTURE RESEARCH Future research possibilities include a look at the effectiveness of the SECI model in its original form and in its revised form. Also examining the differences between Japanese and American cultures might provide additional insight into

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creating well-developed knowledge management plans. The search to better understand cultural differences might also be undertaken in Europe, Russia, Asia, or Africa and might prove valuable in revising the SECI model to better fit the culture examined. Other research might incorporate the concepts of individualism and groupism in search of a viable method for encouraging participation and then capturing knowledge from the individual or group. Social dynamics and political concerns might also be examined with the goal of understanding these interactions to develop successful organizational memory capture, conversion, and dissemination procedures. Finally, any future research should examine the success or failure of the SECI model in whatever form it is revised into, to accurately reflect the organizational culture it is intended to reflect. This would involve examining the underlying culture, the history of the organization in that culture, and the knowledge management emphasis that is expected in that culture. If all of these research endeavors are undertaken then we will have a better understanding of the dynamics of organizational culture and knowledge management processes that leads to better models for building organizational memories.

CON First, this chapter discussed the SECI model as it pertains to Japanese organizations and the resulting revisions that were made to the model to fit American organizations. This was initiated by a brief look at the history of Japanese culture and the reasons for the groupism dynamic inherent in Japanese organizations. The original SECI model was examined and detailed as it related to the Japanese. Second, the American culture was examined and briefly described. The individualism of the American culture was examined and how it carries

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over into American organizations. The original SECI model was then modified to reflect the differences inherent in American organizations. Third, the revised SECI model was examined in light of the main theme of this book concerning organizational memories. The emphasis was on building a foundation of understanding to guide knowledge management processes and procedures. This understanding is vital to successful knowledge capture, conversion, and dissemination efforts. Fourth, the result of the revision to the original SECI model is to provide American organizations the foundation for indentifying the knowledge processes within their organization leading to better knowledge management. The organizational memories tied up in the employees of the organization must be captured in order to build organizational memories, but also captured in such a way that makes sense given the prevailing organizational culture. The resultant successful knowledge capture leads to better conversion and ultimately better dissemination throughout the organization. Without dissemination throughout the organization there would be no point in building organizational memories. Having the knowledge captured, does not provide value to the organization in and of itself. Converting the knowledge to an explicit form and then disseminating it throughout the organization does provide value. This value is difficult to quantify and qualify, but its value is nonetheless understood. Value in whatever form the organization chooses to accept is vitally important if organizational memories are to be useful and worthy of managing. Finally, given the nature of the marketspace and the global marketplace there is now and in the future an emphasis being placed on knowledge management processes. The organization of today must consider all their organizational knowledge as important and develop methods and means of building organizational memories. These organizational memories provide the basis for organiza-

Revising the SECI Model for American Organizational Culture

tional improvements in numerous forms that give the organization a chance of success. In the future there are even more reasons to indentify knowledge concepts, because the employee of the future will not be satisfied with the status quo, but seek to maximize their employment situation. If the organization does not understand how to capture, convert, and disseminate their organizational memories they may lose valuable knowledge. The employee becomes the focus in the organization, whether in Japan or America, as the knowledge that resides within the organization resides within the individual employee. Given that the SECI model has been a useful foundational concept for knowledge management in Japan, the revised SECI model is a useful foundation for knowledge management in America. The value of the original and revised models is open for further research and interpretation, but both models fit their intended organizations and provide a sound basis for understanding knowledge dynamics in their respective countries.

REFEREN Anand, G. (2006). Continuous improvement and operations strategy: Focus on Six Sigma programs. The Ohio State University, Columbus: ProQuest Digital Dissertation Database. Bogliolo, D. (2004). E-Learning in biblioteca e nei servizi di documentazione: Opportunita e criticita. Seminario AIDA. Roma: Bibliocom2004. Connell, N., Klein, J., & Powell, P. (2003). Its tacit knowledge but not as we know it: Redirecting the search for knowledge. Journal of the Operational Research Society , 140-152. Droege, S., & Hoobler, J. (2003). Employee turnover and tacit knowledge diffusion: A network perspective. Journal of Managerial Issues, 50-64.

Graham, F. (2003). Inside the Japanese Company. Routledge. Hayashi, T. (1990). The Japanese Experience in Technology. The United Nations University Press . Kim, C., Emmett, D., & Sikula, A. (2001). Employee Relations Ethics and thee Changing Nature of the American Workforce. Ethics & Behavior, 23-38. Kothuri, S. (2002). Knowledge Origins. Retrieved September 11, 2007, from Kothuri: http://www. gse.harvard.edu/~t656_web/Spring_2002_students/kothuri_smita_knowledge_in_orgs.htm Maguire, M., & Kroliczak, A. (1983). Attitudes of Japanese and American Workers: Convergence or Diversity. The Sociological Quarterly, 107-122. Nonaka, I., & Konno, N. (1998). The concept of “ba”: Building a foundation for knowledge creation. California Management Review, 40-54. Nonaka, I., & Takeuchi, H. (1995). The Knowledge Creating Company: How Japanese Companies Create the Dynamics of Innovation. New York, NY: Oxford University Press, USA. Nonaka, I., & Toyama, R. (2002). A firm as a dialectical being: Towards a dynamic theory of a firm. Industrial and Corporate Change, 995-1009. Nonaka, I., & Toyama, R. (2003). The knowledgecreating theory revisited: knowledge creation as a synthesizing process. Knowledge Management Research & Practice, 2-10. Polanyi, M. (1958). Personal Knowledge. London: Routledge and Kegan Paul. Rayport, J., & Sviokla, J. (1994, November-December). Managing in the Marketspace. Harvard Business Review, pp. 141-150. Samarah, I. (2006). Collaboration technology support for knowledge conversion in virtual teams. Southern Illinios University at Carbondale: ProQuest Digital Dissertations Database. 55

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Shafer, B. (1999). American Exceptionalism. Annual Review of Political Science, 2, 445-463, June 1999. Snowden, D. (2003). Complex acts of knowing: Paradox and Descriptive Self-Awarness. Bulletin of the American Society of Information Science and Technology, 23-28. Snowden, D. (2003). Innovation as an objective of knowledge management. Part 1: The landscape of management. Knowledge Management Research & Practice, 113-119. Stacy, R. (2001). Complex responsive processes in organizations: Learning and knowledge creation. Routledge.

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Thall, J. (2005). The role of the manager in the conversion of tacit to explicit knowledge. The George Washington University, Washington, D.C.: ProQuest Digital Dissertation Database. Tocqueville, A. d. (2003). Democracy in America and Two Essays on America. London: Penguin Books. Westfall, J. (2006). The impact of structure on explicit knowledge recall. Touro University International, Cypress: ProQuest Digital Dissertation Database.

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Chapter V

Knowledge Transfer within Multinational Corporations: An Intercultural Challenge Parissa Haghirian Sophia University, Japan

A A growing interest in the various aspects of knowledge transfer within multinational corporations has been evidenced by a recent surge in empirical research. Despite the fact that the number of empirical studies investigating various aspects of knowledge transfer within multinational corporations has significantly increased, very few insights into the influence of culture on knowledge transfer, however, have come to light. In fact, the cultural aspects and the individuals involved in the transfer and communication of corporate knowledge within multinational corporations seemed to have been overlooked by researchers. This chapter attempts to fill this gap and investigates the impact culture has upon knowledge transfer processes within multinational corporations. It presents a comprehensive intercultural knowledge transfer model and identifies which aspects of national culture hinder and which aspects foster an effective transfer of knowledge.

Knowledge and Its Relevance in the Modern Corporation As businesses globalize and thus face global competition, they come under pressure to change and renew their existing practices (Choi and Lee, 1997). Thus, it is increasingly difficult for firms to sustain competitive advantages through the

reallocation of capital (Bresman and Birkinshaw, 1999). Goods and services have become more sophisticated in content and production, which forces companies to increase their competitiveness. The foundation of competition has become increasingly knowledge-based, with the focus on developing valuable and hard-to-imitate knowledge that yields sustainable competitive advantages (Soo, 2005).

Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Knowledge Transfer within Multinational Corporations

Knowledge in an organizational context refers to the intellectual assets of an organization. Knowledge refers to “valuable information arising from reflection, synthesis, and other cognitive activities of the human mind. It is often, but not always, hard to structure, difficult to capture on machines, sometimes tacit, and hard to transfer” (Mockler 2001, p. 3673). The most relevant feature of knowledge is its division into tacit and explicit knowledge. Maasdorp (2001) considers this a distinction between focal (explicit) and background (tacit) knowledge. Explicit knowledge is the most articulable and the most context-free type of knowledge. It exhibits the highest degree of fit between the knowledge and its representation to others (Doz and Santos, 1997). It is knowledge that can be separated from its owner and expressed in a formal and systematic language (Nonaka, 2000), learned by observation and study (Doz and Santos 1997) and can be shared in the form of data, scientific formulas, specifications, manuals, (Nonaka, 2001), patents, technical blueprints, computer software, etc. (Doz and Santos, 1997). Because of its explicit form it is easily processed, transmitted and stored (Nonaka, 1994; Nonaka, Toyama et al. 2001). The role of explicit knowledge in organizations is expanding and it is considered a key factor of production within the knowledge economy (Zack, 1999). Explicit knowledge is largely characterized by the separation of the individual that holds knowledge and the known. This, however, does not mean that explicit knowledge is easy to handle. Tacit knowledge on the other hand is based on the unity of the person who knows and the object of knowledge (Scharmer, 2000). It is deeply rooted in action, commitment, and involvement in a specific context (Nonaka, 1994). Polanyi (1985) puts it like this: “We know more than we can say”. He observes that although people may be able to perform certain tasks, they may not be able to articulate the way they managed to perform them. Being able to perform an activity does not imply that it is also possible to explain the very same

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action (Polanyi, 1985). Tacit knowledge is therefore not only strongly connected to its knowledge owner, but is also located within an individual. It refers to knowledge that is not easily articulated and is defined as “non-codified, disembodied, know-how that is acquired via the informal take-up of learned behaviour and procedures” (Howells 1996). In fact, knowledge can never be fully explicit and always shows a certain degree of tacitness. Even if knowledge can be separated from its owner and put down in words or other explicit ways, there is still a part of it which stays tacit and can not be extracted and therefore can not be easily shared. Knowledge-based theory of the firm, which considers knowledge and information the core resources of a firm (Wernerfeld 1984), has helped to raise important questions about the sustainability of competitive advantages and cumulative strategic change within the organization (Choi and Lee, 1997) and deals with the importance of knowledge within the corporation. Drucker (1992) describes the importance of knowledge: Knowledge has become the primary resource for individuals and for the economy overall. Land, labour and capital – the economist traditional factors of production – do not disappear but they become secondary. They can be obtained, and they can be obtained easily, provided there is specialized knowledge. (Drucker 1992, p. 95) Knowledge-based approaches in management research consider organizations primarily to be vehicles producing, transferring and combining knowledge (Kogut and Zander, 1996, Nonaka, 1994) and basically see firms as social communities that serve as efficient mechanisms for the creation and transformation of knowledge into economically rewarded products and services (Kogut and Zander, 1993). Hence, a firm can also be understood as an organization specializing in speed and efficiency in the creation and transfer of knowledge. Through this knowledge firms

Knowledge Transfer within Multinational Corporations

evolve, partly by the generative logic of their capabilities, but also by the opportunities and influences of the external environment (Kogut and Zander, 1996). In an organizational context, knowledge is generated, codified and coordinated; it is transferred from one unit to another and is then used. Knowledge is therefore considered a strategic asset and a valuable resource of the company (Holden, 2002).

Knowledge Transfer withth Muinational Corporations During internationalization processes, the complexity of knowledge management increases, because the establishment of a subsidiary in a foreign market is strongly dependent on the corporation’s ability to access and interpret information in these markets. At the beginning of the process, many management decisions on how to perform in these new markets, however, are taken in head offices and not in the local subsidiaries. Particularly during the early stages of market entry, headquarters strongly attempt to control the expansion processes in the host market and supervise market research activities because the success of the market entry often depends on how objectively market opportunities can be recognized. Once the corporation has gained some experience in the new market and developed more confidence in dealing with its customers and their particularities, more and more decisions are made in local units. This also impinges on decision-making processes within the corporations. As market know-how develops in the local subsidiaries, their managers need more freedom to react to market requirements. Local market knowledge then gains more importance, not only for the management of the subsidiary, but also for the rest of the organization. Local units start to access and transfer knowledge from their local market to the headquarters or other subsidiaries, and relinquish their roles

as knowledge receivers. The demand for new ideas and products increases, too. Companies can strengthen their competitive advantage by importing ideas from their overseas subsidiaries or by reusing product ideas developed for other markets. In this way, knowledge and its individuality can create major competitive advantages. Knowledge transfer thus not only refers to information shared by headquarters with subsidiaries and their reaction to it. Knowledge management in multinational corporations increasingly turns into an exchange of creative ideas between all members of an organization whether they live and work in the same country or not. Not every product needs to be invented and not every project is new to members of a multinational corporation. The larger the company the higher the chances that somewhere knowledge and experience about certain tasks has been created and stored. As globalization continues product life cycles become shorter and consumers become more demanding and thus knowledge assumes a central role in multinational companies. Bringing new ideas from all over the world to market and transferring these ideas efficiently between corporate units located all over the world becomes vital for sustaining competitive positions and creating long-term advantages for global corporations. Effective knowledge transfer is therefore an increasingly pressing issue for multinational corporations, since the capability of efficiently combining knowledge from different locations around the world is vital for survival, and managing knowledge flows between subsidiaries is becoming a determinant of competitive success (Doz and Santos, 1997). Multinational corporations face various challenges with regard to internal knowledge transfer. Subsidiaries have to be motivated to access knowledge in their local market and subsequently make this knowledge accessible to other units that need it. A good example is marketing knowledge, which needs to be exchanged frequently, because it is information about development requirements

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as well as monitoring and evaluating host markets. The company faces the challenge of finding this information in the appropriate locations and establishing suitable channels of communications for all the participants involved in the processes (Buckley and Carter, 2002). Communication needs to be established between those who need and those who possess knowledge. Therefore, the organization has to choose the best instruments of control, motivation and context (Foss, 2002). Knowledge transfer mechanisms further depend on the location and the context of the potential users of knowledge in the potential market (Doz et al., 1997), and effective knowledge transfer depends on how easily knowledge can be transported, interpreted, and absorbed (Hamel et al., 1989). As a result, the company has to constantly be aware that the knowledge accumulated in various parts of the organizations needs to be localized and examined, because it may have the potential to be re-used at another location within the organization. The ability to move knowledge from one part of the organization to another becomes the basis for competitive advantages for multinational firms (Quinn, 1992).

Definition of Knowledge Transfer within Multinational Corporations Accordingly, the main focus of managing knowledge within a multinational corporation is the sharing or transferring of it in an effective way. The concept of knowledge transfer is difficult to capture, because there is no clear distinction between the transfer of knowledge and the creation of new knowledge (Bresman et al., 1999). It is customary to speak of the ‘transfer’ of knowledge between two distant units of a multinational corporation or between two different functional units at the headquarters, between a vendor and a customer, or even between countries. The use of ‘transfer’ implies an image of flow: knowledge

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‘flows’ from its primary holder to the secondary holder (Doz and Santos, 1997). Knowledge flows, or knowledge transfer, refers to the transfer of either expertise or external market information of global relevance, but not to the transfer of internal administrative information (Gupta and Govindarajan, 1991). Transferring knowledge means the operationalization of transferring knowledge. This can happen in the form of data, information, blue-prints, parts, subassemblies, machines or other means to represent knowledge. It can also happen via persons, individuals or teams (Doz and Santos, 1997). The organization has to enable communication between those individuals who need and those who own knowledge and furthermore make sure that the relevant subsidiary knowledge is actually made available to those units within the multinational corporation that need it (Foss, 2002). Knowledge flows and knowledge transfers are strategically important to organizations for several reasons. They transmit localized knowhow, which is generated in one sub-unit to other locations in the organization. Knowledge transfers also facilitate the co-ordination of work flows linking multiple, geographically dispersed subunits. Furthermore, they can enable organizations to capitalize on business opportunities requiring the collaboration of several sub-units. Knowledge flows are also crucial to the orchestrated execution of unified strategic responses to the moves of competitors, customers and suppliers. Finally, knowledge flows enable the recognition and exploitation of economies of scale and scope (Schulz and Jobe, 2001). In this chapter, knowledge transfer within multinational corporations is defined as the transfer of either expertise (e.g., skills and capabilities) or external market data of strategic value within the organization. The type of knowledge transferred could refer to input processes such as purchasing skills, throughout processes, e.g. product designs, process designs, and packaging designs, or output processes, for

Knowledge Transfer within Multinational Corporations

instance marketing know-how and distribution expertise (Gupta and Govindarajan, 1991). However, knowledge management literature gives the impression that knowledge management operates in a kind of unitary vacuum, in which diversity in terms of language, cultural and ethical background, gender and professional affiliation are compressed into one giant independent variable, which is in any case considered of marginal importance. This approach may be convenient for conceptualizing, but is very limited for practical purposes in the modern international business world with its complex forms of intercultural learning, interactive networking, and knowledge acquisition and sharing (Holden, 2002). In multinational corporations cultural differences play an extremely important role, because most company units are geographically dispersed and differ in their national culture. Accordingly, the main concern of organizations when transferring knowledge is the fact that knowledge is sent from one environment to another, which is geographically and culturally different (Holden, 2002). In most cases, organizational internal knowledge transfer takes place between organizational and sometimes dispersed units and divisions of the multinational corporation. Individuals and organizations can share several dimensions of context at the same time, e.g. climate, nationality, education, politics, justice, economics, and other systems; corporate governance; management styles and incentive schemes (Doz and Santos, 1997). However, these dimensions of knowledge may also differ greatly.

Culture and Knowledge Transfer Cultural background is an important point that needs to be discussed when talking about knowledge management within multinational corporations. Adler refers to culture as the base of management activities (Adler, 2001), which

shape all processes and operations of knowledge management. Neither knowledge nor information can be secluded from their cultural contexts. Culture shapes the idea of what knowledge management is about. It also influences who is managing knowledge and in which way and defines how knowledge is used in specific situations. Generally, we can assume that culture shapes all knowledge management operations in an organization (De Long and Fahey, 2000). We can further conclude that culture also impinges on the success of knowledge transfer processes. If the cultures of the sender and receiver differ, we speak of a intercultural knowledge transfer process. Intercultural knowledge transfer processes can happen between senders and receivers who are working in the same team or organizational unit. In today’s multinational corporations, intercultural knowledge transfer processes increasingly happen between geographically dispersed organizational units. Hofstede (1984) points out that geographical separation and cultural differences can lead to quasi-autonomous sub-organizations which may further lead to numerous problems of communication, co-ordination, control and motivation (Hofstede, 1984). Thus, cultural differences within an multinational corporation should not be neglected when discussing knowledge transfer and can be regarded as one of the barriers between company divisions and local units of the company (Davenport and Prusak, 1998; von Krogh et al., 2000). Knowledge transfer within units located in the same country may already pose a challenge, but it is clear that the problem associated with transfer increases with geographical and cultural distance (Bresman et al., 1999). So the main concern of organizations when transferring knowledge is the fact that it is sent from one environment to another, which is geographically different (Holden, 2002). Knowledge management literature often leaves us with the impression that this transfer happens between different company units, however, in this case two individuals transfer knowledge and in

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most cases this geographical distance also leads to a cultural distance between the sender and receiver unit. This cultural distance between the sender and receiver unit may strongly influence the knowledge transfer process. The main aspect of cultures in an organizational context is the fact that culture shapes the actions and the way of thinking of individuals. Hall (1990) says: “Culture can be likened to an enormous, subtle, extraordinarily complex computer. It programs the actions and responses of every person, and these programs must be mastered by anyone wishing to make the system work” (Hall and Hall, 1990). People are, whether they are aware of it or not, resistant to change (Hall and Hall, 1990). Culture influences people’s and individuals’ actions and consequently also creates the context for the managerial practices necessary to transfer knowledge, such as knowledge codification (codification style) and the selection of relevant knowledge (procedural and declarative knowledge). The intercultural knowledge transfer processes within multinational corporations differ slightly from the intercultural communication process. First, the sender is accumulating knowledge from sources inside the organization and chooses which knowledge and what type to transfer. This refers to the intention stage in the communication process. After this, the message is encoded according to cultural context and sent indirectly (e.g. email, phone, etc.) over a given physical and cultural distance. The receiver on the other end receives the message, decodes it according to his cultural context, and formulates a reaction (gives feedback). Then knowledge is potentially filtered and passed on again to other individuals in the organization. Moreover, the model illustrates that the cultural context is dependent on the agent’s home and host culture at the same time and the overall cultural setting is, in turn, subject to the interaction (acculturation and deculturation) between the two (See Figure 1) (Bargstädt 2007). The main aspect is that the cultural fields do not overlap. Sender and receiver both stay in their

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cultural fields while participating in the process. At the same time sender and receiver are also separated by a geographical distance. This geographical distance increases communication problems. Knowledge managers are required to adapt to the specific requirements of the knowledge transferring context to increase its success. In a well-known environment this may be an easy task to undertake, whereas adapting the transfer processes to the requirements of an unknown foreign subsidiary and the receivers in it may become more difficult. Accordingly, many intercultural business processes suffer from the fact that there are always gaps in understanding. Even simple activities like writing letters or greeting somebody can be culturally different. These gaps may comprise deficits in understanding the counterpart’s language correctly, reading his or her body language or understanding hidden

Figure 1. Intercultural knowledge transfer process (author) Sender In te n tio n C o d ifica tio n o f M essag e S e n d in g P rocess

F e e d ba ck

C u ltu ral F ie ld A C o u n try A

C h a n n el (N o ise )

R e ceptio n o f M e ssag e D e codifica tio n o f M essage R e a ctio n R e c eive r

C u ltu ral F ie ld B C o u n try B

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meanings. To perform efficiently one needs to manage all of these gaps. This is very difficult if participants do not have high intercultural skills as it can lead to stressful situations or culture shock. Once individuals have acquired more expertise in communicating with members of other cultures, this communication and understanding gaps narrow. In an intercultural knowledge transfer process, things get even more complicated because it is often not possible to communicate directly with a counterpart. These gaps become more obvious, when misunderstanding occurs during the process. Participants can not see one another’s reactions and therefore can not adapt their communication to ease the transfer process. Since reactions can not be seen, intercultural knowledge transfer activities can not be adapted. The individual is mostly tempted to perform his or her knowledge transfer processes in his or her culturally acceptable way. Finally, all participants in the intercultural knowledge transfer process have different cultural skills which may further influence the success of the knowledge transfer process.

CuAttes of Knowledge Sender and Knowledge Reccer Cultural Openness of Knowledge Rceiver Cultural openness is a set of abilities and cultural knowledge, primarily based on past experience, which enables a person to engage in appropriate and meaningful interactions with people of divergent national and organizational cultures. People who develop a cultural openness also improve the overall cultural interaction as may be seen in national culture adjustments over time due to the intercultural communication between relationship partners (Griffith and Harvey, 2001).

When adapting to new situations and their requirements, human beings have always found ways to deal with differences. Results are mutually beneficial, demonstrating the fact that change and adjustment are happening (Casrnir, 1999). Enhanced cultural openness helps to develop a basic insight into communication patterns and the skills necessary for intercultural communication. Thus, cultural openness leads to a more interactive communication between individuals from different cultural backgrounds and to higher communication competence. Cultural openness of the sender therefore strongly influences the fluency of intercultural communication as well as the success of knowledge transfer.

International Experience Intercultural knowledge transfer within multinational corporations can be influenced by the degree of consistency of core elements among the national cultures of its members (Fox, 1997; Li, 1999). The knowledge recipient needs to be aware of the context of the knowledge sender. The more each party understands the other’s situation, perspectives, and culture, the easier it is to use symbols that will be codified and de-codified in a similar way (Thomas, 2002). Once individuals come into prolonged contact with individuals from other cultures in a shared environment, the “other” as well as the related concepts of difference and change comes to the foreground of any individual’s perception (Casrnir, 1999) and can improve the flow of intercultural communication. Experiences of having lived in a foreign country and interacting with individuals of a different nationality and lifestyle can improve intercultural skills. Improving intercultural skills mainly takes place via experiencing intercultural communication challenges and conflicts. The greater the experience in intercultural communication, the greater the knowledge of possible misunderstandings and possible solutions. Since individual intercultural communication is the base for knowledge transfer,

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we assume that intercultural knowledge transfer is also positively influenced by a high degree of international experience.

Perceived Cultural Dstance Perceived cultural distance is another factor influencing the intercultural knowledge transfer within multinational corporations. The concept of cultural distance seeks to measure the extent to which different cultures are similar or different from one another and has been applied to a multitude of research questions, especially in the area of foreign direct investment (Shenkar, 2001). Concerning companies, it shows the degree to which the norms and the values of two firms differ because of their separate national characteristics. The degree of cultural distance is considered one of the major obstacles in successful performance in intercultural business relationships (Williams, et al. 1998). Not surprisingly, one of the main assumptions, concerning multinational corporations, is that the higher the distance between cultures, the worse the performance of foreign subsidiaries (Shenkar, 2001). Cultural distance can be defined on a country and corporate level (Makino and Beamish, 1998). In this chapter the construct of cultural distance refers to perceived cultural distance by the individual (sender) involved in the knowledge transfer process. The intercultural communication process between these interactors is strongly influenced and complicated by the cultural distance or the cultural novelty between partners (Griffith and Harvey, 2001). The reason for this is that communication competencies do vary by cultural distance and develop differently based on a person’s level and frequency of past interactions, the past success of intercultural communications, and the level of internationalization (Kim, 1988). The greater the cultural distance between people who are attempting to communicate effectively and thus the less consistent the communication environment, the less likely there will be sufficient social bonding

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among individuals to facilitate effective communication (Griffith and Harvey, 2001). When it comes to knowledge transfer, cultural distance matters, because it raises barriers for understanding other members of the corporation (Simonin, 1999). Johanson and Vahlen (1997) define cultural distance as the result of culture-based factors that impede the flow of information.

Language Ability of Knowledge Rceiver One obvious consideration in intercultural knowledge transfer is language as an instrument being used by the partners to communicate. Despite this, the aspect of language is a neglected factor in prior research on multinational corporations (Marschan-Piekkari et al., 1999). Language ability refers to the ability to speak, read, listen and understand another culture’s language and allows verbal messages to be communicated (Li, 1999). Language is man’s most important tool of communication and an instrument for transferring cognitive, affective and conative information (Rosengren, 2000). This implies the sender and receiver own a certain language ability to do so. It reflects the ability to interact and empathize with members of other cultures and, if necessary, resolve occurring communication problems. Speaking of knowledge transfer the language abilities of both the individual in the subsidiary and the individual in the head office generally have to be satisfactory, because a lack of language ability may make even well codified knowledge inaccessible (Simonin, 1999). Knowledge transfer in an environment with a common language increases the probability of understanding, but also the shared fund of knowledge and a shared system of meanings (Doz and Santos, 1997). When no shared language is available or language skills at subsidiary level are very poor these units may consciously try to avoid or resist the headquarters’ efforts to control by “hiding behind the language” or passively adopt patterns of non-confirmative

Knowledge Transfer within Multinational Corporations

behaviour (Björkman and Marschan-Piekkari, 2002). Simonin (1999) refers to language differences as a factor increasing cultural distance and Richter (1996) showed that if subsidiaries’ employees lacked a satisfactory level of English or any other appropriate language to communicate with the head office, the company was not able to learn by communicating with the headquarters and thus gain new knowledge. The language ability of the knowledge sender may also influence the way knowledge is transferred. The higher the language ability of the sender, the more likely he or she will prefer to interact verbally and talk directly to his or her counterpart. If language ability is limited, the sender or receiver prefers to communicate via means that reduce the possibility of misunderstandings. In any event, the language abilities of both sender and receiver of knowledge within a multinational corporation have to be satisfactory to guarantee knowledge transfer without losses. On issues of further research, the topic of intercultural knowledge transfer offers numerous potential research avenues. First, the detailed process of transferring knowledge between company units of differing cultural background should be investigated in greater detail. To explore this issue further more qualitative research may be adequate. Greater attention should be paid to the role of the knowledge recipient. His or her attitudes, strategies, and perceptions of knowledge and influences on knowledge transfer and sharing processes have been insufficiently investigated in management research. Secondly, the issue of language in intercultural knowledge transfer needs to be revisited. Knowledge managers in the 21st century will increasingly deal with intercultural knowledge management issues. Future research will therefore also need to investigate the knowledge management activities within the intercultural workplace, not only in a subsidiary, but in any intercultural team.

Concluu Knowledge transfer within multinational corporations is a process little investigated by scientific research, but is a process that plays a crucial role in international knowledge management processes. It is based on intercultural communication processes. Even if it occurs between two company units, knowledge is in fact communicated between two individuals with differing cultural backgrounds and communication styles who exchange messages and in doing so share knowledge and information. Both communicators are surrounded by numerous culture-related variables which may influence their knowledge choice, knowledge transfer instruments, and acceptance of new knowledge. All of these aspects influence the success of knowledge transfer processes. Different communication styles can lead to misunderstandings and interrupt communication processes. Accordingly, the process is easily interrupted by different perceptions among the communicators. This limits the ability to interact directly and to react to misunderstandings or misinterpretations.

References Adler, N. J. (2001). International Dimensions of Organisational Behavior. Cengage Learning Services. Bargstädt, A. (2007). Defining the Knowledge Agent - A Qualitative Analysis of Knowledge Transfer within Multinational Corporations. Unpublished Master Thesis. Sophia University, Japan. Björkman, A., & Marschan-Piekkari, R. (2002). Hiding Behind the Language: Language Fluency of Subsidiary Staff and Headquarter Control in Multinational Corporations, Proceedings of the 28th Annual Conference of the European International Business Academy, Athens 2002.

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Bresman, H., & Birkinshaw, J. (1999). Knowledge Transfer in International Acquisitions. Journal of International Business Studies, 30(3), 439-462. Buckley, P., & Carter, M. J. (2002). Process and Structure in Knowledge Management Practices of British and US Multinational Enterprises. Journal of International Marketing, 8, 29-48. Casrnir, F. L. (1999). Foundations for the Study of Intercultural Communication based on a Thirdculture Building Model. International Journal of Intercultural Relations, 23(1), 91-116. Choi, C. J., & Lee, S. H. (1997). A Knowledgebased View of Cooperative Interorganizational Relationships. Cooperative Strategies. P. W. Beamish and P. J. Killing. San Francisco, The New Lexington Press. Davenport, T., & Prusak, L. (1998). Wenn Ihr Unternehmen wuesste, was es alles weiss...; Das Praxisbuch zum Wissensmanagement. Landsberg/Lech, Verlag Moderne Industrie. De Long, D. W., & Fahey, L. (2000). Diagnosing Cultural Barriers to Knowledge Management. The Academy of Management Executive, 14(4), 113-127. Doz, Y., Asakawa, K., Santos, J., & Williamson P. (1997). The Metanational Corporation, Working Papers INSEAD, Fontainebleau, France. Doz, Y., & Santos, J. F. P. (1997). On the Management of Knowledge: From the Transparency of Collocation and Co-setting to the Quandary of Dispersion and Differentiation. Working Paper, Fontainebleau, France, INSEAD. Drucker, P. F. (1992). The New Society of Organizations. Harvard Business Review, 70(5), 95-104. Foss, N. J., & Pedersen, T. (2002): Transferring Knowledge in MNCs: The Role of Sources of Subsidiary Knowledge and Organizational

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Context. Journal of International Management, 8, 49-67. Fox, C. (1997). The Authenticity of Intercultural Communication. International Journal of Intercultural Relations, 21(1), 85-103. Griffith, D. A., & Harvey, M. G. (2001). Executive Insights: An Intercultural Communication Model for Use in Global Interorganizational Networks. Journal of International Marketing, 9(3), 87-103. Gupta, A. K., & Govindarajan, V. (1991). Knowledge Flows and the Structure of Control within Multinational Corporations. Academy of Management Review, 16(4), 768-792. Hall, E. T., & Hall, M. R. (1990). Understanding Cultural Differences. Maine, Intercultural Press. Hamel, G., Doz, Y., & Prahalad, C. K. (1989): Collaborate with your Competitors, and Win. Harvard Business Review, 67(2), 133-139. Hofstede, G. (1984). Culture`s Consequences; International Differences in Work-Related Values. London, Sage Publications. Holden, N. (2002). Intercultural Management; A Knowledge Management Perspective. Harlow, England, Financial Times, Prentice Hall. Howells, J. (1996). Tacit Knowledge, Innovation and Technology Transfer. Technology Analysis & Strategic Management, 8(2), 91-105. Johanson, J., & Vahlne, J.-E. (1977). The Internationalization Process of the Firm - A Model of Knowledge Development and Increasing Foreign Market Commitments. Journal of International Business Studies, 8(1), 23-32. Kim, Y. (1988). Communication and Intercultural Adaptation: An Integrative Theory. Clevedon, England, Multilingual Matters.

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Kogut, B., & Zander, U. (1993). Knowledge of the Firm and the Evolutionary Theory of the Multinational Corporation. Journal of International Business Studies, 24(4), 625-645. Kogut, B., & Zander, U. (1996). What Firms Do? Coordination, Identity, and Learning. Organization Science 7(5), 502-518. Kroeber-Riel, W. (1992). Konsumentenverhalten. Muenchen: Vahlen. Li, H. Z. (1999). Communicating Information in Conversations: A Intercultural Comparison. International Journal of Intercultural Relations, 23(3), 387-409. Marschan-Piekkari, R., Welch, D., & Welch, L. (1999): In the Shadow: The Impact of Language on Structure, Power, and Communication in the Multinational. International Business Review, 8, 421-440. Maasdorp, C. (2001). Bridging Individual and Organisational Knowledge: The Appeal to Tacit Knowledge in Knowledge Management Theory. Retrieved April, 24th 2002, 2002, from www. hds.utc.fr/~barthes/ISMICK01/papers/IS01Maasdorp.pdf. McKenzie, J., & Winkelen, C. van (2004). Understanding the Knowledgeable Organization; Nurturing Knowledge Competence. London, Thompson Publishing. Mockler, R. J. (2001). Knowledge Management. In M. Warner (Ed), International Encyclopedia of Business and Management. International Thompson Business, (pp. 3666-3673). Nonaka, I. (1994). A Dynamic Theory of Organizational Knowledge Creation. Organization Science, 5(1), 14-37. Nonaka, I., R. Toyama, et al. (2001). SECI, Ba and Leadership: a Unified Model of Dynamic Knowledge Creation. In I. Nonaka and D. Teece.(Eds.), Managing Industrial Knowledge: creation,

transfer and utilization (pp.13-34). London, SAGE Publications. Polanyi, M. (1985). Implizites Wissen. Frankfurt am Main: Surkamp Verlag. Quinn, J. B. (1992). The Intelligent Enterprise. New York: Free Press. Richter, F.-J. (1996). Organizational Learning between Subsidiaries and Headquarter: The German Experience in Japan, Working Paper. Berlin: Ostasiatisches Seminar, Freie Universität Berlin. Rosengren, K. E. (2000). Communication: An Introduction. Thousand Oaks: Sage Publications. Scharmer, C. O. (2000). Organizing Around NotYet-Embodied Knowledge. Knowledge Creation; A Source of Value. G. von Krogh,, I. Nonaka and T. Nishiguchi (Eds.). London: Macmillan Press. Scollon, R. & Wong-Scollon, S. (1995). Intercultural Communication. Oxford: Blackwell Publishers. Schulz, M., & Jobe, L. A. (2001). Codification and Tacitness as Knowledge Management Strategies: An Empirical Exploration. Journal of High Technology Management Research, 12, 139-165. Shenkar, O. (2001). Cultural Distance Revisited: Towards a More Rigorous Conceptualization and Measurement of Cultural Differences. Journal of International Business Studies, 32(3), 519-535. Simonin, B. l. (1999). Transfer of Marketing Know-How in International Strategic Alliances: An Empirical Investigation of the Role and Antecedents of Knowledge Ambiguity. Journal of International Business Studies, 30(3), 463-490. Soo, C. W., Midgley D. F., & Devinney, T. (2005). The Process of Knowledge Creation in Organizations. Academy of Management Annual Conference, Hawaii, USA, August 2005.

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Thomas, D. C. (2002). Essentials of International Management: A Intercultural Perspective. Thousand Oaks, Sage Publications. von Krogh, G., Ichijo K., & Nonaka, I. (2000). Enabling Knowledge Creation: How to Unlock the Mystery of Tacit Knowledge and Release the Power of Innovation. Oxford, University Press. Williams, J. D., Han, S.-L., & Qualls, W. J. (1998): A Conceptual Model and Study of Intercultural

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Business Relationships. Journal of Business Research, 42, 135-143. Wernerfeld, B. (1984). A Resource-based View of the Firm. Strategic Management Journal, 5(2), 171–80. Zack, M. H. (1999). Managing Codified Knowledge. Sloan Management Review, 40(4), 45-58.

Section II

The Components of Organizational Memories

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Chapter VI

Valuing a Multiplicity of Views: How to Tap Informal Networks to See the (W)hole Patrice Dunckley Mindful Connections, USA Suzanne Roff-Wexler Compass Point Consulting, USA

A This chapter provides perspective and practical techniques that individuals and organizations can use to maximize knowledge transfer efforts. It illustrates the importance of using informal sources of information sharing to create a complete picture. The authors assert that using the traditional formal channels of transfer can leave holes when attempting to share the whole. Overall, the chapter offers practical, easily executable solutions that individuals can apply and that leaders can teach to fill the gaps that often go unnoticed. Influenced by sense making, storytelling, psychology, and visual mapping, the authors offer tools and provide coaching for using the tools, contained in text boxes throughout the chapter. The intent is to both introduce concepts and make them straightforward for the reader to implement.

I This is a story all of us have heard or experienced in some form. A young professional takes a job at a Fortune 300 company. For our story, it is a diversity and inclusion professional who takes a job at a company with a 30 year legacy of practicing inclusion. The organization has an inspiring

story to share which has received much press for its accomplishments. On her first day of work, our young professional found a timeline of progress in diversity. It provided beneficial information that helped to shape the future plans of the company, but the essential or core information came from the 27-year non-exempt veteran who had witnessed it all. This person’s informal story behind the ink

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Valuing a Multiplicity of Views

and paper provided valuable context that would help shape the success of newly implemented initiatives. Learning the nature of the business and the drivers of business success put the picture into 3-D and allowed a more complete story to emerge. Effective future program execution was largely fueled by that story. Clearly, tapping informal networks to gather a multiplicity of views made a significant difference in the trajectory of the young professional new to the organization. This chapter provides the reader with tools to continue the story. Organizational memory (the body of data, information and knowledge relevant to an individual organization’s existence) can be understood as a sociotechnical system. Our observation is that organizational documentation (including written policies, email, publicity, and employee surveys) is physically or electronically stored in the complex context of people, physical space, and other technologies. This interrelationship of people and technology makes up a sociotechnical system. As a system, organizational memory is witnessed by many points of view that converge into a complete story. An individual witness cannot tell the story in a way that complete learning can take place. Documentation tells one story; the project or process manager involved tells another part; the leader has their story; the workers have theirs…add in customers, suppliers, the press, the current business climate and the possible points of view are endless. Perception of the present is related to previous experience (and its memory conscious or unconscious). We selectively remember what fits a current schema. When we have no experience, i.e., memory that fits, we attempt to fill the hole to create a whole. While an “elegant” solution, it leads to a potential distortion. We assert that this is also true of organizational memory. Clearly a distortion of the past impacts present and future understanding. Gathering a multiplicity of views indirectly and through informal networks may lessen the distortion.

It all makes sense, but now we are making things complicated. We find the idea of sensemaking useful here (Kurtz & Snowden, 2003). David Snowden of the Cognitive Edge defines sense-making as how we make sense of the world so that we can act in it. It is an approach drawing from insights from the cognitive sciences and the science of complex adaptive systems. Knowing that we have to write our knowledge bases as if someone were looking at our organization for the first time is one thing but having to capture multiple points of view and organize them into a cohesive story seems complex and daunting. Visual referencing is more prevalent in contemporary culture. Social networking online tools such as LinkedIn and Facebook; contextual and graphical search engine sites such as Silobreaker which shows the networks and relationships around a topic; and applied organizational consulting tools coming from academic settings. In particular, social network mapping is an applied tool to provide a visualization of the interaction of people and information. While a mind map, with its potential for brainstorming, depicts word ideas in a non-linear format, a social network map provides a tool to indicate informal network connections at various levels. Our minds alone cannot hold the complexity of this picture without a manual or computer-generated map. Given that picture, the beholder begins to make sense of the data. In this sense-making effort, opportunities emerge to be pursued toward organizational goals. This chapter provides best practice ideas and tools to create a knowledge system map which will help to identify the sources of the knowledge needed to capture a more complete picture of organizational culture.

INFORALWOR FOR S Information is often gathered through formal channels following organizational roles and

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Figure 1. Views 2 and 3 provide different perspectives and a more complete picture View 2 My view

Look Here

View 3

responsibilities. Expert change agents now understand that the memorable story is located in the informal channels, meaning spontaneous connections and interactions, and usually contains details that make the difference between success and stagnation or spinning wheels. When a leader takes on a new role, the focus is often on the tasks assigned and the deliverables expected. What is often overlooked is that all of these happen by, with and through professional relationships. Such relationships come in formal and informal structures and both are social in nature. When we are discussing organizational networks, we will be referring to both an organization’s formal social structure and the informal social structure that individuals choose to build based on values such as affiliation, comfort, usefulness, mutual learning, etc. In a new situation, the formal channels are evident: organizational charts, introductions to critical players, job descriptions, project plans, mission statements, visions and more. There is so much cascading information that it is counter-intuitive to believe it may be incomplete. We sort through the data, piecing it together in a way that make sense to us and ready to move enthusiastically forward unaware that the picture we have may not be the picture we need. What we actually need is discovered in informal, unwritten or overlooked channels of communication where information is shared. These channels are people connecting and communicating across affiliations: friend-

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ships, collaborations, interests, demographic commonalities, geography, and tenure….just to name a few. The formal channels begin to pale in comparison to the color and vibrancy of the informal networks at work. The ways people connect with others (channels) are in many ways universal to all new situations, but it is important to look for those that may be culturally significant to the organization. For example, in some organizations, tenure can be an important affiliation for valuable information sharing. Being new to an organization may create the need for a sponsor with sufficient tenure to provide the social capital needed to be given entry to the information flow. Coaching Action Item: Notice the affiliations in your new situation that seem to be primary. List them and assess those which you can navigate alone and those, which you should gain the trust of a sponsor. When seeking information it is important to look for all of the possible sources to view the whole and for the places where holes exist in the information that is shared. It takes time and focus to determine what defines the whole and see the holes that need to be filled, but through asking questions and natural curiosity, an openness to exploring what is not known can be accomplished.

Valuing a Multiplicity of Views

The whole and hole create a dialectic tension, that is, a contradiction of ideas that serves as the determining factor in their interaction. It is this dialectic interaction that makes it critical to seek both the whole and hole where each is needed to define the other. Stated another way, how do you know holes without some sense of a whole? Conversely, how can we know a whole without some sense of holes? Where there is one, there is the other. This duality is a key to learning. It is a predictable learning action to seek out what we don’t know. As we become more familiar and comfortable with not knowing, we can begin to seek out the things we don’t know that we should know. You may recall the Johari Window (Luft & Ingram, 1955) training exercise where four quadrants represent communication and relationship traits. Invented in the 1950’s, the Johari Window became a model for mapping personality awareness. It is a psychological tool to better understand what you and others recognize about you (arenas), what you but not others recognize about you (façade), what others but not you recognize (blind spots), and what neither you nor others recognize about you (unknown). The Johari Window can be used as an exercise to identify the holes in your self-understanding. It is based on a 2 by 2 quadrant that maps how we are known or not known to ourselves and to others. Imagine the quadrant

with the top half marked as Known to Self and Not Known to Self. The side half is marked as Known to Others and Not Known to Others. You begin by selecting several personality qualities that describe you and then mapping them on the quadrants. Others who know you select qualities about you and map them on the quadrants. What emerges is a more complete perspective on a person based on a better understanding of what we do and do not show to others. Coaching Action Item: Draw the quadrant and select several adjectives that describe you. Place the words that describe you where they belong in the quadrant. Ask people you know to do the same. Begin to notice what you do and do not show others about your personality. No one can have complete self-understanding or know someone else completely. While we may strive for a whole, at best we find a multiplicity of views by filling in the holes of how we perceive ourselves and are perceived by others. As you review the quadrants related to yourself, consider how this concept translates to organizational understanding and knowledge. The dilemma is found in the tension between what we know and what we do not. Often we will rely on others to show us what we do not know,

Figure 2. The Johari Window

Known to Self

Not Known to Self

Known to Others

Not Known to Others

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but this is rarely a complete picture. One thing that gets in the way is the difficulty to remember what it is like not to know things and explain them in a way that a person unfamiliar with them can follow. We often leave holes in our explanations simply from being so familiar with our own knowledge. As learners, it is an equally difficult task to see the holes since we rely so heavily on the knowledge transfer process. Gaps in knowledge transfer are normal human processes, and knowing this helps us to listen for them as we are sharing and/or taking in information. Coaching Action Item: Listen to yourself the next time you explain something and notice information that seems obvious to you. Consider whether you need to explain at the level of the novice listener rather than at your level of understanding. Being able to listen for the whole and the holes takes personal practice in listening and the skill of assessing when you see a “complete enough picture.” The thing that brings the needed picture into focus is context. The same information can be interpreted many different ways depending upon the context we put around it. We have all heard the adage that there are three sides to every story: mine, yours and the truth. The truth requires more context than we can determine on our own. It requires a multiplicity of views. The good news is that a multiplicity of views is available to us. Information is available for the asking. Everyone around us has a perspective on the same situation. Often in new situations only a small portion of the views are tapped as we learn. It is essential that we employ the skills of listening, observation, and curiosity to our learning process. We must also vary the sources of our learning. This is where understanding the dynamics of informal networks is invaluable. While the reasons a network forms will vary, need and affiliation are among the most common.

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ThE ElemENS OFAL NEWOR Informal networks are difficult to recognize when entering a new situation. Often the members do not even think of themselves as part of a social network. Nonetheless, formal and informal connections exist and can be mapped. The language of informal networks is an emerging lexicon that has a wide vocabulary. Rob Cross of the University of Virginia’s Network Roundtable (identifies those who are central connectors, those who broker relationships, those who are peripheral people and those who block the flow of information. An extensive resource for these ideas is the Network Roundtable website (http://www.thenetworkroundtable.org). He sees them all as important parts of an informal organizational network with specific roles and responsibilities that help to facilitate the flow of information. This language, and more like it that is being developed by others, is bringing an age old process into focus as a strategic advantage on an organizational level. Individuals can use this same information to their own strategic advantage when entering a new situation to gather the multiplicity of views needed to see the whole and the hole. Central connectors are the keepers of information because of their rank, tenure, power, expertise, political position or skill at observation. They know what you need to know, but often do not remember what it is like not to know and sometimes leave unintentional (we hope) gaps in their information. These are the people who can experience the difficulty of explaining what they know in a way that is clear to those who do not have the same level of understanding. Often the questions we ask central connectors are critical to gathering their complete view. Brokers are comfortable with diversity. They have relationships across organizational silos, age, tenure, organization, culture, gender, etc… They serve as liaisons and are able to introduce, invite and initiate relationships to find what they

Valuing a Multiplicity of Views

need. These are the people who foster innovation and collaboration. In some organizations, brokers operate out in the open; in other organizations they work below the surface. They are often sponsors across social capital affiliations. In evaluating the players in a network, it is important to apply questions that allow a multiplicity of views. In Rob Cross’ work he shows that peripheral people may appear to be unimportant to the network at first glance, but knowing why they are on the outskirts is the key to an accurate assessment of their value to the information flow. Cultural misfits and disconnected contributors can often provide a view of the organization that others are unwilling to voice but is still essential to future success. Remember the boy who cried out that the Emperor was naked? Niche experts can bring focus to a view that is unique. When we look at people, position and performance in a simplistic way, we can miss the value they add. Poor performers can be a result of subjectivity or indicate a talent that is not needed in the organization. Artful questions will get at the heart of these situations so that the information you need can be culled from the edge of the network. This reminds us of how complexity

theorists often pay attention to changes occurring at the boundary (“edge”) of the system. It is at this edge of chaos where innovation and creativity may occur. So to, peripheral people may hold critical information to view a (w)hole. Only exploration will show us the value. Since each of these “nodes” in a network view the organization from a different perspective, only their collective sharing fills in the details of an accurate picture. Not only is it essential to gather view points from many, it is also important to listen to their answers and for the information that might lead to the next essential question or probe. Coaching Action Item: Create a sketch of the informal networks you have observed. Ask yourself who connects others, who do people go to for information, who is needed to accomplish critical tasks, who seems isolated from any network, what levels (departments, areas, geographies, etc…) of the organization are tapped most often for your role, which of these seem untapped? Next assess which areas of the network you have gathered information from and which are still to be mined. You should come back to this sketch periodically

Figure 3. The Network of Nodes You Sales & Mktg

Mail Carrier

R&D Big Cheese

BC’s Admin

Supply Chain

You are managing your boss and relying o n her for all your i nformation. Some nodes are well connected, but only the mail carrier witnesses the whole.

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to add to it and look for additional opportunities for learning.

Elements of Comfort The lubricant that makes a network of information flow includes comfort, trust and openness. Interpersonal issues that block the flow include fear, power concerns, familiarity, and other discomforts. Flow and blocking factors are present in any situation that involves people; it is normal and common. Remembering that human beings are all at various stages of comfort and emotional intelligence will help you in learning from both formal and informal networks. People share more when they are comfortable than they do when they are uncomfortable. Each of us must begin by managing our own comforts and discomforts and build skills that will enable increased comfort in others. There are certain things that most people respond well to in human interactions. They like to be listened to; dislike being judged; admire humility and enjoy the respect of being valued for their knowledge. Building skills that foster these feelings will go a long way to gathering the information that will build the whole and expose the holes.

Creating Comfort Listening has two dimensions: listening to and listening for. Explicit words provide what must be listened to; tones, inflections, pauses, delivery and silence are listened for. Vital information is found in practicing both at the same time. Again the issue is context. Listening to words provides raw information. Listening for fills in context and provides a glimpse of what might be unsaid or understated and essential for seeing the whole and the holes. As we practice both, questions we should be asking begin to unfold as we read the moment.

Coaching Action Item: When listening, feel free to jot down a question that comes to mind so that you might remove it as a distraction to your listening. No one will mind if you refer to your notes later and ask the question at the appropriate time. While listening, it is also important to make observations. Observations are different than conclusions and judgments. They are things we see or intuit without assigning any meaning or taking any action. If you are unfamiliar with this process, it will take practice to obtain the skill. Begin practicing on small things outside of your new situation and then transfer the skill after you have become competent. Observations without judgment help you to identify questions or statements that keep a dialogue open and comfortable. People respond well to observations and poorly to judgments and conclusions. Coaching Action Item: Driving often provides wonderful opportunities for practicing observation and suspending judgment. If you listen to what goes through your mind about other drivers, you may find yourself assigning meaning to their actions or even using colorful language to describe the content of other drivers’ character. If someone cuts in front of you without turning on their signal, you may call them an insulting name, but the only fact you have is that they cut you off. If they do it many times, you can then begin to observe that they are a danger to other drivers, but still will not know the content of their character. Take note throughout your day of how often your mind jumps from observing an action to judging. Next begin to practice naming the observation and suspending the judgment by listing the many possibilities that explain the observation. The more possible explanations, the more obvious it is that you would need to ask many questions to determine which were accurate. A useful concept is the Fundamental Attribution Error (Ross, 1977) which suggests that we

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tend to attribute positive events to qualities in ourselves but only to luck in others. Conversely, if something bad happens, we view that as bad luck for us but as a character flaw in someone else. Begin to notice how you attribute others’ behavior either to their own personality qualities or to external circumstances. The skill of practicing humility and honoring the knowledge of others complement each other. Even if you have a PhD in the subject you are assigned to execute, have been with an organization for many years and are in a new assignment, or have known the person you are learning from for years, you can usually learn something new. Remembering to be open to being a learner rather than having to demonstrate expertise allows you to show humility and revere the knowledge of others. It is obvious in our actions as well as our words, so be sure they match and demonstrate authenticity. There are concepts from the discipline of psychology that can be extremely helpful in obtaining the outcome of learning that we desire. Complexity theory is one of them, it teaches us how to notice all aspects of a complex situation are important, helps us find the whole and the hole. Initial conditions, those small behaviors that unpredictably impact the outcome of a system, help to put ourselves into a space that will make it possible to contribute to a comfortable exchange of ideas. This phenomenon “sensitivity to initial conditions,” discovered by Lorenz (1963), has been labeled the Butterfly Effect because it suggests that a butterfly, that beats its wings in Tokyo today, can transform a storm system next month in New York. Acknowledged to have some validity, initial conditions are factored into weather prediction. In a human system, this means that even a small initial behavior, engaging in a spontaneous hello, can have unpredictable results. For example, you go to a new restaurant only to discover they do not have your reservation and then you sit down to a table that is only partially set. Suppose you are a restaurant critic and you write a harsh review

which leads to a loss of potential patrons. In this example, a few incidences of inattention to details lead to an unexpected but significant outcome. Initial conditions make predictability in organizational behavior imperfect, given that small changes can impact actions. For example, even a strong intention to informally network with a co-worker at a critical time can be affected by other work demands, absenteeism, transportation problems, or a bad headache. Anyone trying to manage a new employee’s first impression of a workplace recognizes that it cannot be controlled with any accuracy. Conditions such as a personal crisis can influence a supervisor’s motivation or availability to help onboard someone into the system of networks. Coaching Action Item: Become aware of where you are right now. Recall what conditions, intentional or accidental, that brought you to the point of reading these words in terms of time and space. Now think about your networks. How would a smile or friendly eye contact impact your entry into a new connection? Remember that a seemingly small event can impact the sharing of knowledge and the deepening of your networks. Try to discover how initial conditions can set a human system into motion.

KNOWLEDGEaring Through S Every culture shares its history and learning through anecdotes and stories. Prehistoric people probably initiated this behavior around a fire. Storytelling as information sharing leads to knowledge sharing. We view knowledge as information in context. The context is subject to multiple psychological dimensions related to how we know what we know, how we share what we know, and how we forget, repress, and recall emotional and cognitive material. Stories are a natural way of communicating memorable,

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emotional, and powerful learning particularly in an informal network. Office gossip, founding stories, and anecdotes about a successful project or pitch are narrative examples in the service of sharing knowledge about the organization. Formal stories are often prepared by HR or marketing professionals in the service of presenting the “whole” story in a positive light. They include the rag to riches stories of a leader, stories of the social consciousness of an organization, as well as stories of the founders. Corporate brands, including logos and slogans, create consumer reactions about a product or service. The brand serves as a collection of images and ideas that create associations and expectations. Formal stories can contribute to the employment brand of an organization, that is, its desirability, and attract new employees and customers. But formal stories provide an incomplete picture with holes. Informal stories, on the other hand, can begin to complete the picture by providing alternative perspectives that are not formally recognized or known. It is important to gather a multiplicity of views to gain a fuller sense of the organization. Seek out more informal information or anecdotes to fill in the holes. Coaching Action Item: Identify the formal stories in your organization, favorite sports team, or community. Ask yourself what is missing from these accounts. Begin to mine for informal stories through conversations and anecdotes that can fill in the holes in your understanding. Compare the formal story itself to the one you have after you have supplemented it with informal stories. Think about how to listen to and share informal stories to discover a multiplicity of views.

TOOLSFORINGA Multiplicity oOFIEWS This part of the chapter will discuss how we locate leaders, regardless of title or tenure. It will also

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describe how organizations can share anecdotes and stories about how leaders do what they do, how they solve problems, and how they contribute to innovation. Here we introduce anecdote circles; organizational and social network analysis; and self-coaching guidelines.

Anecdote Circles A useful technique to get at the stories is a facilitation process known as anecdote circles. Guidelines can be found at the websites for the Cognitive Edge, Anecdote, and The Gurteen Knowledge Website (http://www.cognitiveedge.com; http://anecdote.com.au; http://www. gurteen.com ). An anecdote circle, in contrast to a focus group that seeks opinion, is used to elicit naturally occurring stories (anecdotes) and to gain insight into emergent, unplanned themes. Anecdote circles allow for spontaneous sharing that is free of expectation and therefore a more authentic expression of a selected topic. When used in organizations, an anecdote circle leads to discovery because the topic is indirect to what is actually trying to be understood. For example, the facilitator wants to discover how employees experience a rapid change in executive leadership. Asking directly will lead to politically correct opinions that hide underlying sentiments. Conversely, eliciting anecdotes about the best and worst workplace surprise can potentially yield rich insights. Once the anecdotes are collected in the facilitator’s memory or transcription, there is an opportunity to make sense of the data regarding the change in leadership.

Organizational and Social Network Aalysis We note a growing interest in software applications of organizational network analysis as well as social network analysis (Anklam, 2007; Cross, 2004). These tools generate a visual map of relationships among participants who may fill out a

Valuing a Multiplicity of Views

questionnaire. They are useful tools to discover the connections among people and how they exchange tangible and intangible information and resources. But as tools, they are primarily of benefit when they generate questions, insight, and action. We believe they offer the potential to see the hole and the whole in multiplicity of relationships both inside and outside and organization. There are strong opportunities for organizational consultants to partner with organization to reap the benefits of these tools.

Self-Coaching Guidelines Throughout this chapter we have provided a variety of coaching tips that can be used immediately as action items for building the skill needed to see the hole and uncover the whole. Here we go deeper with guidelines that you can put into practice and adapt to your needs.

Using Questions and Observations to Create an Organizational Network Setch Earlier we suggested you create a sketch that would show who serves as connecting, brokering, blocking and peripheral nodes in the interactions between people. Flushing out the sketch can be a great way to put the mechanics of tapping networks into action. The essential elements are to ask, watch and learn to find information and context. Use the sketch to identify the areas, people and subjects that should be explored: • • •

Ask people who they go to for information when they need it and why. Watch to see who is being tapped for information by others. Assess the sketch and analyze interactions on a number of levels: people as nodes, environments of sharing, silos that create peripheries and/or block information flow, geographies that are helped or hindered by

•

•

•

time or technology differences, and any other affiliation that identifies layers of information complexities. Identify where there might be holes of information to explore and wholes you can create by sharing. Assess which areas you have a direct connection to use the network to learn and which will require a broker. Identify the brokers and connectors; set up a time to meet with each of them; consider the questions you might ask ahead of time. When choosing your questions consider those that uncover information, those that create leads for more and those that encourage a dialogue. Listen for questions that might arise from the dialogue.

Every interaction with people is an opportunity to learn. Being mindful about your opportunity to learn allows you to create “deliberate happenstances” throughout your day. Deliberate happenstances are times when you choose to ask, watch or learn without a special appointment or formal setting. It is an inner experience that you use to learn to listen for important information, be aware of observations and behaviors and gather clues as to the context in which you find yourself. Sometimes just using an informal situation, such as time in line or at a lunch table to ask a question or to test an observation can give us a chance to learn something important or solve a problem. Be observant to see where the best physical spaces are for deliberate happenstances to be initiated. It will likely be necessary to find many spaces to ensure you are mining the whole. There is also an opportunity to deliberately decide what type of node you are going to be. First, create your own network sketch to figure out your role in the personal and professional informal networks you are a part of. Determine whether you are a connector, broker, blocker or peripheral node. Assess whether your typical status as a node will serve the goals of the in-

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formation flow needed to create the whole. Add to your skills and action plans to ensure that the information flow you need can be attained from your position as a node.

CONCLUSION The Johari Window described earlier is a good tool to begin with in terms of knowledge sharing and network building. By identifying how you perceive your networks and how they perceive you begin to turn holes of contextual information into a new kind of knowledge or wisdom. We believe that it is only through an immersion into a multiplicity of views that the story begins to write itself. In organizations, that means you are in a more beneficial position to take advantage of opportunities that increase the connections within your growing networks. The more you use techniques which provide a multiplicity of views, the better poised you are to create strategic plans, manage change, create solutions and navigate complexity. We predict the outcome will be a prosperous future for your organization created by honoring the past and fully engaging the present moment’s potential.

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REFEREN Anklam, P. (2007). Net Work: A practical guide to creating and sustaining networks at work and in the world of work. Burlington, MA: Elsevier. Cross, R., & Parker, A., (2004). The hidden power of social networks: How work really gets done in organizations. Boston, MA: Harvard Business School Press. Kurtz, C., & Snowden, D., (2003). The new dynamics of strategy: Sense making in a complex complicated world. IBM Systems Journal, 42(3), 462-483. Lorenz, E. N. (1963). Deterministic nonperiodic flow. Journal of Atmospheric Science, 20(2), 130-141. Luft, J., & Ingram, H. (1955). The Johari Window: A graphic model for interpersonal awareness. Proceedings of the Western Training Laboratory in Group Development. Los Angeles: University

of California.

Ross, L. (1977). The intuitive psychologist and his shortcomings: Distortions in the attribution process. In L. Berkowitz (Ed.), Advances in experimental social psychology, 10, 173–220. New York: Academic Press.

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Chapter VII

Organizational Knowledge Sharing Networks Haris Papoutsakis Technological Education Institute (TEI) of Crete, Greece

ABSTRACT This chapter explores the ways that Knowledge Sharing Networks support the flow of organizational knowledge within a firm. Based on the assumption that tools people need to work with others are different from the ones they need to work alone; it demonstrates how the use of groupware permits “anytime, anyplace” collaboration within the organization. Furthermore, it takes a close look at information technology tools that enable leaders not only to encourage their employees to share knowledge personally, but also to put their knowledge in a form that others can easily access it now or in the future. In doing so, Knowledge Sharing Networks play an important role in preserving organizational memory.

“In the end, the location of the new economy is not in the technology, be it the microchip or the global telecommunications network. It is in the human mind.” Alan Webber (1993, p. 27)

IN In the course of this book, the term organizational memory is used to describe the preservation of organizational knowledge. The following definition, proposed by the Editor in his call for chapters for this book, has served as a starting point:

Organizational memory is the body of knowledge, past, present, and future, required to achieve the strategic objectives of an organization. Enabled by technology, leadership, and culture, organizational memories include repositories of artefacts, communities of people, and organizational knowledge sharing processes, which focus on achieving the organizational vision. The key objectives of this chapter are to explore how knowledge repositories, as part of a Knowledge Sharing Network, may best support the flow of organizational knowledge within a

Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Organizational Knowledge Sharing Networks

firm, and to describe ways, through which, in the future, they will best serve for preserving organizational memory. The chapter is organized as following. In the following section we examine two different approaches that are utilized for the flow of information and the organizational knowledge transactions within organizations; namely internal knowledge markets and internal knowledge communities. The section sub headed Supporting Collaboration starts with the assumption that tools people need to work with others are different from the ones they need to work alone. Everyday activities like communication and interaction, or decision making and problem solving are examined under all possible same/different time or same/different place conditions. We demonstrate how the use of groupware permits ‘anytime, anyplace’ collaboration within the organization. In the following section, under the title Supporting Organizational Memory, we consider organizational knowledge as an intellectual capital asset under the knowledge-based theory of the firm. We take a close look at IT-tools that enable leaders not only to encourage their employees to share knowledge personally, but also to put their knowledge in a form that others can easily access it now or in the future. In the section sub headed Knowledge Sharing Networks, knowledge repositories are presented as the most important element of a Knowledge Sharing Network (KSN) and their contribution in both Integrative and Interactive Knowledge Management (KM) applications is presented. KSNs and their architecture are weighed against codification and personalization strategies, which certain researchers, departing from different perspectives, consider appropriate for a number of organizations. Closing this core section of the chapter, we focus on problems related to the effective use of KSNs, as we consider them the KM and IT-tools that mostly affect organizational performance. Finally, our conclusions are presented in an effort to assist managers in the difficult task of

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successfully managing and sharing organizational knowledge.

ORGANIZAIONALnowledge FLOW For the purpose of our investigation it is important to examine the channels that permit and facilitate organizational knowledge to flow inside and within an organization. Two are the main types of information-handling activities: The procedure-based ones (related to the procedures that employees are involved in their every day practice) and the knowledge-based informationhandling activities. We shall focus our interest on the Information Systems (IS) aiming on supporting knowledge-based activities. IS that support employees in performing information-handling activities in order to work together, share expertise and knowledge, and solve problems. As of their nature, these IS must support activities that do not follow the same or similar process every time and that deal with information and knowledge that cannot be easily captured. There is more than one pattern that allows this flow of information and knowledge in organizations. Cohen (1998), in his well documented Report on the First Annual U.C. Berkeley Forum on Knowledge and the Firm, distinguishes among two different approaches to knowledge transactions in organizations: Internal knowledge markets and internal knowledge communities. It is obvious that the choice of one of the two viewpoints is of significant importance, as it affects action. According to Cohen, the proponents of knowledge markets are mainly talking about knowledge interactions between individuals and may emphasize on incentives as they tend to consider that knowledge is a ‘thing’ that can be transferred. The devotees of knowledge communities focus on the group and give more attention to encouraging connections between people, which may lead to more exploration of the process of knowing.

Organizational Knowledge Sharing Networks

Supporters of the two approaches can be found in the scientific literature and they also made themselves obvious in the Berkeley Forum. Prusak (1997, and during the Forum) stated that there are knowledge buyers, sellers and brokers in firms, each of whom expects to gain something in a knowledge transaction. The main price mechanism governing the knowledge market is reciprocity, the expectation that one will get valuable knowledge in return for giving it. Or, to put it in another way, one needs to contribute knowledge to become part of the knowledge networks on which his success depends. Gilmour (2003) goes one step further and proposes that organizations should focus on collaboration management based on a brokering model that forces people to share knowledge when there is something in it for them. Let us consider, for example, two managers (i.e. the Manufacturing and Quality managers of a company) evaluating the same vendor; wouldn’t they want to talk to each other and compare their notes and experiences? The brokering model is there to connect people who should be connected. One IT-based solution, proposed by Gilmour (2003), is to continually survey the flood of electronic information that flows through the company in order to find out who is likely to know what. Then, when somebody needs information, those who have it can be asked privately whether they are willing to share. Supporters of the knowledge community approach, suggest more emphasis on personal connection and commitment to shared success –but also risks and benefits– and less on knowledge transactions, which von Krogh (1998) associates with ‘low care’ social situations. Collaborators worry about themselves and their partners; buyers and sellers don’t. Trust and good will influence action much more powerfully in a community or collaboration world than they do in the relatively impersonal market environment. The knowledge market approach driven by pure self-interest and that of the knowledge community characterized by sharing, trust and

generosity represent the two extremes, with reallife situations somewhere in between. In practice, many individuals care about their colleagues and knowledge markets do depend on trust and reciprocity, as the value of exchanged knowledge cannot be precisely defined and ‘payment’ for it is usually intangible and delayed. In the same way, knowledge community members are individuals who are better prepared to contribute to the group effort when they expect a share of the benefits of the group success. In their way, they also make a ‘market’ calculation of what they will get in exchange for the knowledge they offer.

Supporting COLLABORAION In a prophetic article Drucker (1988) stated that organizations are becoming information based, and that in the future they will be organized not like manufacturing organizations, but more like a symphony orchestra, a hospital or a university. Each organization will be composed mainly of specialists who direct their own performance through feedback from others: colleagues, customers and headquarters. Three are the factors driving this move, according to Drucker. One, knowledge workers are becoming the dominant portion of labor, and they resist Taylor’s command-and-control form of organization. Two, all companies, even the largest ones, need to find ways to be more innovative and entrepreneurial. Three, information technology is forcing a shift. Once companies use IT to handle information rather than data, their decision processes, management structure and work patterns change. Both in industrial and business environments, work is done mainly in task-focused teams, where specialists from various departments (i.e. manufacturing, quality and R&D) work together as a team for the duration of a project (i.e. the development of a new product) based on a variety of IT tools for their collaboration. Drucker had long ago foreseen that getting value out of knowledge

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sharing requires more than technology, and we were at the beginning of the third evolution in the structure of organizations: the organization of knowledge specialists. Expecting information and knowledge simply to flow through organizations is unrealistic, because people’s time and energy are limited and they will choose to do what they believe will give them a worthwhile return on those scarce resources. Robert Johansen, in the web site of the Institute for the Future (IFTF), notes that systems that support groups are important because most people spend 60 to 80 percent of their time working with others. At the same time, from informal polls he has taken, people seem to feel they are most productive when they are working alone, or to put it in another way, they are not happy about how they work with others. These findings reveal a need for systems that support groups. The tools people need to work with others are different from the ones they need to work alone. So groupware (electronic tools that support teams of collaborators) is different from past software. In many organizations groupware represents a fundamental change in the way people think about using computers. Taking full advantage of existing IT platforms (e-mail systems, LANs, departmental systems and public network services such as the telephone or the Internet) groupware is not just another part of corporate information systems. Successful firms have discovered the right mix of people, process, and technology elements in order to use their groupware systems as the backbone of their knowledge sharing infrastructure. Supporting collaboration has lately been a main effort in organizations as it is commonly accepted that it is conductive to both organizational knowledge generation and sharing. Making available the wealth of knowledge that exists throughout the organization is of real benefit to firms that wish to improve the ability of employees to make decisions. For the past 25 years, Group Decision Support Systems (GDSS) have been used in order to help more than one person work together to

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reach a decision. McNurlin and Sprague (2004) note that GDSSs traditionally support ‘pooledinterdependent’ decision making (several people to reach a decision jointly by working together simultaneously and interacting) or ‘sequential interdependent’ decision making (one person makes a decision –or part of a decision- and passes it on to another person). As it has been increasingly difficult to tell when decision making starts and when supplementary activities (such as data gathering, communicating and interacting) the ‘D’ has disappeared and we now talk about Group Support Systems (GSS). The activities of groups can be divided into two generic categories: •

•

Communication and interaction, where communication is conceived as transmitting information from one person to another or to several others and interaction means back-and-forth communication over time. (Example: Office systems and in particular e-mail.) Decision making and problem solving, where members of the groups reach a decision or form a consensus. (Example: The evolution of Group DSSs from the already existing DSSs.)

Both types of group activities are needed in collaboration and, historically, systems supporting group work have originated from one or the other of these two major functions. Johansen (1991) and his colleagues of the IFTF are categorizing the work of groups using a variation of the DeSantis and Gallupe (1985) matrix, by having time on one dimension (same time/different time) and place on the other (same place/different place). The time/place framework they propose in their search for ways in which technology can be utilized to support ‘anytime, anyplace’ collaboration is shown in Figure 1. The two options (same or different) of the parameters time and place designate the way the group mem-

Organizational Knowledge Sharing Networks

Figure 1. Groupware options

Sam e P la ce

S a m e T ime

Differen t T ime s

F a c e-to -F a c e Me etin gs

T e a ms in P lac e

E le ctro n ic c o p y b o ard s E le ctro n ic d e cisio n su p p o rt T e a m -b u ild in g to o ls

T e a m r o o m to o ls

P la tforms Loca l a re a n e tw o rks A d vanced w o rksta tio n s O p e ra tin g enviro n m e n ts In te g ra te d o ffice su its

D iffe re nt P la c es

On g oing C oo rd in atio n V o ice m a il E -m a il F a csim ile G ro u p e d itin g P ro je ct m a n a g e rs /schedule rs W o rk flo w

C ro s s -D is ta n c e Me etin gs A u d io c o nfe re n cin g V ideoconfe rencin g S cre e n s h a rin g

bers are communicating and interacting over time and/or distance. The ‘same time/same place’ cell, for example, includes electronic meeting support systems. The ‘different time/different place’ cell incorporates such communication-oriented systems as e-mail, computer conferencing and use of Lotus Notes or more modern software. In the following two subsections we shall further comment on some particular situations where the use of IS in support of collaboration is important. Until recently there has been little integration among the systems in the four cells, even though it is clear to investigators and system developers that supporting collaboration must aim to permit anytime, anyplace group working.

Sme Time / Same Place Collaboration Supporting same time/same place collaboration has generally meant supporting meetings. Team members from the groups involved meet faceto- face in order to develop the basic plan and objectives and finally reach a decision. Meetings are part of the daily schedule of any staff member

and McNurlin and Sprague (2004) mention the results of a US study that have found that the average executive in a US company spends more than 800 hours a year in meetings. The number alone represents an approximate 30 percent of total work hours, but in addition, the executives reported that they considered about 240 of those hours to have been wasted in useless meetings. Here is a short list of the main problems with meetings: •

•

•

Often there is no agenda, participants do not study the documentation provided before the meeting and expect to be briefed during the meeting. Key people arrive late or do not attend at all, time may be spent on briefing attendees or on routine matters, and due to a poor job of the chairperson a few people –very often the same ones– dominate the discussion and others do not speak up. Many meetings are wasteful from a cost standpoint (consider cost per hour in salaries, travel expenses, etc) not to mention the unavailability of the participants at their place of duty. 85

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The goals of systems used for improving meetings are to (a) eliminate some meetings, (b) encourage better planning and better preparation for those meetings that must be held, and (c) improve the effectiveness of meetings that are finally held. The following measures can be taken and it is here that information technology can help: •

•

•

Eliminate some meetings. Use of e-mail or the company intranet can eliminate all meetings that do not call for a group decision or action (i.e. progress report meetings). Electronic and voice mail systems allow meetings to be cancelled at the last moment (when key people can not attend or essential information is not yet available). Better preparation for meetings. Computer conferencing can play a significant role in improving preparation for meetings. A computer conferencing system is actually a form of enhanced e-mail, allowing participants to log on at their convenience, read all entries made by others since they last logged on, and make their contributions. The chairperson can use the system to obtain reactions to the proposed agenda and even for handling routine actions (like approval of previous meeting minutes and voting on routine issues) as well as for providing a written record of pre- and post- meeting communications. Improve the effectiveness of meetings. The major benefit of using meeting support systems is improved meeting efficiency and effectiveness. Meetings are more effective when the ideas generated by the group are more creative and the group commitments materialize more quickly.

Another ‘same time/same place’ situation that can benefit from the use of group support systems is the traditional presentation and discussion sessions usually applied in conferences and in business meetings of a certain importance.

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Dfferent Place Collaboration Collaboration of groups that work in different places and probably at different times is another promising use of information systems, and mainly groupware. In the global economy era multinational companies can use the three main regions of the globe (Asia, Europe and the Americas) to extend their workday to round-the-clock by passing work from groups in one region to the next at the end of each one’s workday. Imagine the following situation: Two scientists collaborate on writing a report. The one based in Europe, e-mails his thoughts and questions on the topic to his US based colleague at the end of his workday. During his workday –and while his EU partner is sleeping– the US scientist does some thinking and research on the topic, and e-mails his thoughts and findings back to Europe at the end of his day. Now, when the US scientists sleeps, the EU one can work again and this may continue for, let’s say, a week. At the end of the week, they will have accomplished at least two weeks’ worth of work, without either of them having to work long hours. In an extreme case (of a company having a third person involved in the project and working in Asia) the result could have been even three weeks’ worth of work done. One of the results of using IT to support collaboration is the formation of the so called virtual teams; they exist in a space but not in one place. Some of them never meet face-to-face. They are formed to handle a project and then disband after the project is completed. Virtual teams tend to operate in three cells of the matrix presented in Figure 1: • •

Same time/same place: The team meets face-to-face probably once, at the beginning, to develop the basic plan and objectives. Different time/different place: Team members then communicate by e-mail and do data gathering and analysis separately.

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•

Same time/different place: If the company possesses strong enough technology, team members may have audio or video conferences to discuss developments and progress towards goals.

It is obvious that there is a spectrum of group working situations and many types of IT-based systems that support collaboration. These systems have been around for at least 30 years, becoming increasingly sophisticated over that time. They permit more discussion, more evenly spread participation, more high-level companywide discussion, and involvement by more people than a traditional planning meeting would allow. Other tools allow real-time collaboration among distributed team members who not only need to hear each other’s voices, but also need to simultaneously see their hand-drawn changes to an engineering drawing in real time. Still other collaboration tools help team members located around the globe ‘converse’, not in real-time but at different times of the day. In all these, and many other cases, use of ITbased collaboration tools changes the collaboration process, revolutionize who can participate, how they participate and even the kind of work they do. Collaboration is at the heart of the business world today. Use of collaboration software can change the structure within one enterprise, working relationships between enterprises, and working relationships between people in different parts of the world.

SrtINGORGANIZAIONAL KNOWLEDGE Supporting organizational knowledge, and the information systems used for this purpose, is an issue very closely related to managing knowledge. We have addressed the subject in the previous section of this chapter from a general perspective. Here, we shall do it from a practical point

of view, emphasizing on particular IT-based tools and techniques that facilitate the flow of organizational knowledge within the company. In doing so, we bear in mind that organizations create and exchange knowledge to achieve a competitive advantage. Leaders of knowledge creating organizations must create value today and, at the same time, have to take all necessary measures, in real time, in order to ensure that the next generations of organizational leaders know what they knew. That means not only encouraging people to share knowledge personally, but also to put their knowledge in a form that others can easily access it now or in the future. Because knowledge originates from both inside and outside the company, practical issues on knowledge management deal with customer knowledge and researcher knowledge and how to embed this outside knowledge in a real-time system. It is under this umbrella that we are examining knowledge as an intellectual capital asset and in particular the usage and sharing of organizational knowledge. The challenge is to recognize where IT fits in the overall knowledge management and knowledge sharing arena.

Theoretical Background Knowledge management has been an enduring subject in the IT field since the mid 1990s. Many attempts have been made to capture knowledge in computer systems, but soon top management realized that their greatest assets (their employees) walk out the door every evening, taking with them another crucial asset, knowledge. Many researchers in the field (Grant, 1997 and 2000; Sveiby, 2001, and von Krogh, 1998 among them) believe that knowledge is not something that can be captured in a machine; it only exists inside a person’s head. Information can be captured in computers, knowledge cannot. Some of them feel that the term knowledge management creates the wrong impression, as knowledge cannot be controlled or engineered. It can only be leveraged

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through processes and culture. The more people are connected, and the more they exchange ideas, the more their knowledge spreads and can thus be leveraged. The fundamental problem in traditional management theory is how to align the objectives of workers with those of managers and the stakeholders. Only when executives view knowledge in this light will they manage it for most effective use. Grant (1997, p. 452) affirms that “… if knowledge is the preeminent productive resource, and most knowledge is created by and stored within individuals, then employees are the primary stakeholders”. According to Grant, the knowledge-based theory of the firm is the most adequate framework for these objectives to be fulfilled. Under this perspective, management’s principal challenge is to establish the mechanisms for collaborating individuals and groups to coordinate their activities in order to best integrate their knowledge into productive activity. Sveiby (2001, p. 346) believes that people can use their competences to create value in two directions: by transferring and converting knowledge externally or internally to the organization they belong to. •

•

When the managers of an industrial company direct the efforts of their employees internally, they create tangible goods and intangible structures such as better processes and new designs for products. When they direct their attention outwards, in addition to delivery of goods and money they also create intangible structures, such as customer relationships, brand awareness, reputation and new experiences for the customers.

In both these above transactions, shared knowledge within an organization becomes a critical factor for its performance and this is exactly the way sharing knowledge is conceptualized in this chapter.

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The above view has not been generally accepted. Brewer (1995) researched the topic and tried to answer the question: If we cannot disembody knowledge, how do we better manage the knowledge within people to leverage this asset? He notes that as we move from a service economy to a knowledge economy, companies move towards more effective knowledge management by transferring knowledge between the two states it exists. From tacit knowledge (within a person’s mind and thus private) to explicit knowledge (articulated, codified and thus public) and vise versa. According to Brewer, knowledge is not a physical asset, and as such it is not effectively described in terms of manufacturing analogies such as storing it in inventories. The process of transferring tacit knowledge to others is a key part in managing knowledge. Emphasizing on this aspect, some companies have stopped talking about knowledge management and only use the term knowledge sharing. Under this perspective, IT is seen as one enabler, but not the only one. Getting people together faceto-face to explain how they do things, is still very important in organizational knowledge sharing. Talking about what they do and why, barriers fall, knowledge flows, and sharing increases. Unfortunately, free time for sharing knowledge is not yet seen as important by the majority of top and senior management executives.

Manage or ‘Sare’ Knowledge At its first stages, knowledge management focused on sharing knowledge related to industrial world applications. The two dominant and mostly cited examples of the 1990s refer to new product design and development, and industrial innovation. The first one, by Nonaka (1991), relates to the development of new product lines (like Matshusita’s bread making machine, the Honda City car, and Canon’s revolutionary mini-copier) and persuades researchers, product designers, manufacturing and sales personnel to work together across

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departmental boundaries. With these examples Nonaka has made Matshusita’s software developer Ikuko Tanaka with her ‘twist dough’ identical to his SECI model, Honda’s project team leader Hiroo Watanabe with his ‘Tall Boy’ concept and Canon’s task-force leader Hiroshi Tanaka with his beer can analogy, identical to terms like ‘metaphor’, ‘analogy’ or ‘model’. The analogy to the knowledge sharing situation that our research is focused on is very strong. The second example refers to the sharing of what Seely Brown (1991) and the researchers of the Xerox Palo Alto Research Center (PARC) call ‘local innovation’ in the design of usable technology by sharing the knowledge that endusers have of the products under consideration. PARC research is focused on new work practices, in parallel to new products, and recognizes the customer as the research department’s ultimate innovation partner. In both these classic examples, the emphasis is on the way large organizations (namely Matsushita, Honda, Canon and Xerox) used brainstorming methods and software systems for co-designing and cross-leveling the knowledge within the organizations. Recently, sharing of organizational knowledge emphasizes more on indirect interactions between members of different groups in an organization or members of a community, that are not always working at the same geographic location. Davenport and Probst (2002), in their Siemens Best Practices case book, refer to a number of organizations devoted on their staff sharing ‘best practices’ using document repositories (such as reports of past successful or failed projects, employee, product and service profiles, known as Yellow Pages) and IT-based tools for inputting and extracting knowledge from the repositories. The range of such knowledge sharing systems includes from simple document management systems that help in the storage, annotation and retrieval of documents (Gibbert et al 2000; Kalpers et al 2002) to Group Support Systems and Expert Systems that help in problem solving and decision making

(McNurlin & Sprague 2004), as we have already seen in the previous section. Classical knowledge sharing models suggest that the knowledge transfer and/or sharing process involves the conversion of tacit knowledge into explicit and vice versa. At the same time, there are processes that help share tacit and explicit knowledge without conversion, despite the fact that for Nonaka and Takeuchi (1995) the conversion of knowledge from tacit to explicit and finally tacit is the basis of knowledge creation. The knowledge conversion process involves close interaction between and complete understanding amongst key employees, the so called knowledge group of an organization. This team includes employees and staff (from manufacturing, quality, R&D, marketing, supplies and sales) and in most cases the end-users of the products or services created by the organization.

KNOWLEDGEaring NEWOR For knowledge to be shared effectively between, within and across organizations and persons, those who possess knowledge should make it available in an accessible place and manner and with a focus on its application. Those who seek knowledge should first be aware of the knowledge locus and, second, be capable of interpreting the knowledge within their own context, prior to applying it. In recent literature, a number of scientists have successfully addressed the topic of inter-organizational networks. Based mainly on the work of von Krogh and Roos (1996), Zack (1999), and Dyer and Nobeoka (2000), we consider Knowledge Sharing Networks (KSN) as those types of networks among individuals, communities, organizations (or even between groups of organizations), which have as main common characteristic the sharing of both tacit and explicit knowledge. Dyer and Nobeoka (2000) consider that a KSN serves as a

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locus for facilitating knowledge sharing and effective knowledge work, since it makes knowledge permanent, accessible and portable to those who need it, both inside and outside organizations. Zack (1999) proposes a framework that he calls Knowledge Management Architecture, in order to manage mainly explicit knowledge, based on two KSN elements: • •

Repositories of explicit knowledge Refineries for accumulating, refining, managing and distributing explicit knowledge

He also recognizes the new organization roles needed in order to execute and manage the refining process, and the importance of IT in supporting the repositories and processes. We shall briefly explain these two KSN elements, building mainly upon Zack (1999) and Ruggles (1998).

Knowledge Repositories Knowledge repositories capture explicit, codified information wrapped in varying levels of context. They are used to store and make accessible ‘what the organization knows’. They include data warehouses, which are useful in knowledge management when the mining and interpretation of their content allows employees to become better informed. More sophisticated repository approaches attempt to enfold more context around information as it is captured. According to Zack (1999) the basic structural element of a repository is the Knowledge Unit, a formally defined atomic package of knowledge content (labeled, indexed, stored, retrieved and manipulated). The repository structure also includes schemes for linking and cross-referencing the different knowledge units. A Knowledge Platform may consist of several repositories, each one with a structure appropriate to a particular type of knowledge or content. The most common types of knowledge repositories are those accumulating:

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•

•

•

Structured internal knowledge or knowledge embodied in documents such as memos, reports, product oriented material, etc. Informal internal knowledge, a less structured form of accumulated knowledge, such as discussion databases containing knowhow, usually referred to as ‘best practices’ or ‘lessons learned’. External knowledge, such as competitive intelligence knowledge encompassing analyst reports, trade journal articles and external market research on competitors.

Repositories may be linked to form a ‘virtual’ repository (i.e. product literature, best-sales practices and competitor intelligence might be stored separately but viewed as though contained in one repository).

Knowledge Refineries The refinery represents the process for creating and distributing the knowledge contained in a repository. This process includes five stages: • •

•

• •

Acquisition: Firms either create or acquire knowledge. Refinement: A value-adding process, including cleansing, labeling, indexing, sorting, abstracting, standardizing, integrating and recategorizing. Storage and retrieval: Bridges upstream repository creation and downstream knowledge distribution. Distribution: The mechanisms used to make repository content accessible. Presentation: Firms develop capabilities in selecting, arranging, and integrating knowledge content.

Acquisition, refinement and storage create and update the knowledge platform, whereas retrieval, distribution, and presentation generate various views of that knowledge.

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For KSNs –and knowledge projects in general– to succeed, organizations must create a set of roles and skills to do the work of capturing, distributing and using knowledge. The majority of researchers (Earl & Scott 1999; Zack 1999; Davenport & Prusak 2000, among others) coincide with the need of a Chief Knowledge Officer (CKO), responsible for the overall organization’s knowledge management. As Davenport and Prusac (2000) point out, many firms in the United States and a few in Europe have already appointed CKOs, although in some of them the title may vary. It may be Chief Learning Officer (CLO), Director of Intellectual Capital, or Director of Knowledge Transfer, just to mention a few. We have already emphasized on the role of IT in section 3. The IT infrastructure provides a ‘pipeline’ for the flow of explicit knowledge through the five stages of the refinery process. Using IT (i.e. the World Wide Web and Groupware) a firm can build a multimedia repository with knowledge units indexed and linked by categories. In this way, the organization’s explicit knowledge will be displayed as flexible subsets via dynamically customizable views. Effective use of IT allows knowledge communication via electronically mediated channels. Explicit, factual knowledge may be disseminated by means of an electronic repository. When the exchanged knowledge is less explicit, e-mail or discussion databases are more appropriate and when knowledge is primarily tacit, most interactive modes, such as videoconferencing or face-to-face conversation are the best answers.

Knowledge Repositories and Knowledge Processes According to Zack (1999) and under the concept of his Knowledge Management Architecture, knowledge processing is segmented into two broad classes: integrative and interactive. These two approaches support well-structured knowledge repositories, for managing explicit knowledge,

while enabling interaction to integrate tacit knowledge. Integrative applications exhibit a sequential flow of explicit knowledge into and out of a repository. Producers and consumers of knowledge interact with the repository rather than with each other directly. The focal point tends to be the repository and the explicit knowledge it contains, rather than the contributors, users and the tacit knowledge they may possess. Zack (1999) distinguishes two extreme situations, based on the extent to which knowledge producers and consumers come from the same or different knowledge communities. •

•

At one extreme, which the author names Electronic Publishing, the consumers (readers) neither directly engage into the same work nor belong to the same community as the producers (authors). For example: The organization produces newsletters, or its Human Resources department publishes its policies or a directory of employee skills. At the other extreme, producers and consumers are members of the same practice community or organizational unit, and the repository provides a means to integrate and build their collective knowledge. Zack names this an Integrated Knowledge Base and he provides the following example: A best-practices database, where practices are collected integrated and shared among people confronting similar problems.

Zack (1999) gives a detailed scheme of the organizational roles required for successfully managing integrative applications that includes knowledge creators, finders, collectors, and others such as organizational ‘reporters’, analysts, classifiers and integrators. Finally, he proposes that a librarian or ‘knowledge curator’ should manage the repository. Interactive applications focus primarily on supporting interaction among those people who

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possess tacit knowledge. Here the repository is a by-product of interaction and collaboration, rather than the primary focus of the application. According to Zack (1999) they also vary regarding the expertise level of producers and consumers and the degree of structure imposed on the interaction: •

•

When formal training or knowledge transfer is the objective, (interaction between instructor and student) Zack refers to these applications as Distributed Learning. Interaction among those performing common practices or tasks tends to be more aid hoc or emergent. These applications are referred by Zack as Forums. Highly interactive forums, support ongoing, collaborative discussions among producers and consumers as one group.

Interactive Applications play a major role in supporting Integrative Applications. For example, a forum may be linked to an electronic publishing application so that editors discuss directly with readers. Best-practices databases typically require some degree of forum interaction, so that adopters can discuss reapplication with the creators. Zack (1999) gives a detailed scheme of the organizational roles required for successfully managing interactive applications that includes recruiters and facilitators to encourage and manage participation in forums; communicators, who often refine, structure and index the content. Finally, a Conference Moderator who shall manage the conference repository throughout its life cycle may also be needed, as well as Quality Assurance personnel, in order to assure the quality of the knowledge stored in the repository.

KSN and Knowledge Management Despite the fact that many companies today consider knowledge as an asset (Drucker 1988 and 2002; Davenport & Prusak 2000), it is treated

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differently from the traditional assets of land, labor and capital. Knowledge is a resource locked in the human mind, consequently creating and sharing knowledge are intangible activities that can neither be supervised nor forced out of people. Active cooperation of the individual possessing the knowledge is absolutely necessary for knowledge to be shared. A common language among all the participants –not just English, French or Spanish, but also ‘industrial engineering’ or ‘field sales’– is a major factor in the success of any knowledge transfer. Individuals who do not share a common language will neither understand nor trust one another. When they are brought together to collaborate, they will spar or simply not connect. Over the same perspective Nonaka and Takeuchi (1995) emphasize on ‘redundancy’ when people from overlapping areas of expertise are working together, while other researchers simply refer to ‘cultural mismatch’ as a barrier to knowledge or technology transfers. We are summarizing here below some reasons that make sharing knowledge a complicated task: •

• •

•

•

Knowledge is not simple and should not be simplified to be made to fit into a KSN, because doing so lessens sharing and exchange. People do not easily share knowledge, even if its value grows as it is shared. Culture often blocks sharing, especially in highly competitive environments. A sharing culture is a prerequisite for the existing disincentives not to prevent the use of the KSN. Technical solutions do not address the sharing issue, or to put it in another way, technology does not change the culture. Sharing is not cure-all; neither it is good in all cases. Unlimited knowledge sharing does not work, either. Managers (and especially the CKO, wherever one exists) must be aware of that and take the necessary measures.

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•

Even hiring and promotion practices may affect knowledge sharing. If not rewarded, sharing may be seen as an anathema.

Barriers to generating and sharing knowledge do exist even in cases where management has taken all necessary steps to encourage it. Most of those barriers have to do with either the stimulation of divergent thinking among the knowledge workers, or the distribution of that thinking among the collaborating group members. We shall briefly present some of the most typical ones: •

•

•

Individuals who possess knowledge – especially tacit knowledge – may be actively discouraged from participating, or even worse, could sensor themselves. In order to avoid this, companies must first reward knowledge sharing, mentoring and assisting others, and second, provide the required time for personal contacts. Inequality in status among group members is also a strong inhibitor to sharing knowledge, especially when worsen by differences in accessing information. Technicians often hesitate to propose solutions, not only because engineers have higher status, but because technicians base their recommendations on different knowledge bases. Distance –both physical and time– makes sharing of knowledge, and especially its tacit dimension, difficult. Technology may offer a partial solution, despite the fact that much knowledge is generated and transferred through body language, physical skill demonstration, and very often requires the use of three-dimensional prototypes.

Increasing productivity is one of the challenges for KSNs in a manufacturing environment. Product and manufacturing process life cycles are becoming shorter as we move from traditional to more high-technology based engineering. As a consequence, the available time for recovering

the expenses related with developing and manufacturing new products, is also compressed. This places a reward on the ability of KSNs to capture knowledge created during the process and re-use it in the next generation of products, thus reducing the development and manufacturing time. This “capture-reuse” cycle is a key enabler for performance improvements. The fact that the challenges associated with capturing and reusing knowledge, are basically knowledge management challenges is underlining KM’s key role. KM responses to this challenge may range from the above presented Knowledge Management Architecture, as proposed by Zack (1999), to the alternatives of a Knowledge Codification Strategy (a people-to-document approach to codify, store and reuse knowledge) or a Knowledge Personalization Strategy (based on networks of people and dialogue between individuals) as clearly distinguished by Hansen et al (1999). Companies using codification strategies or approaches rely primarily on repositories of explicit knowledge. Personalization strategies or approaches imply that the primary mode of knowledge transfer is direct interaction among people. Based on a study of KM practices of companies in several industrial sectors (Consulting Firms, Health Care and High Tech Industry) Hansen et al (1999) note that although in every sector managers had chosen a distinct knowledge management strategy, there is a common pattern among them. “Those that pursued an assemble-to-order product or service strategy emphasized the codification and reuse of knowledge. Those that pursued highly customized service offerings, or a product innovation strategy, invested mainly in person-to-person knowledge sharing.” (p. 112). They also note that many companies that use knowledge effectively have chosen one strategy predominantly and use the second one to support the first, on an 80-20 split: 80% of their knowledge sharing follows the predominant strategy and 20% the supporting one. They advise managers not to straddle as they may find themselves with an unmanageable mix

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of people and expertise. Grover and Davenport (2001) seem to be in complete agreement, when they state: “Both [codification and personalization approaches] are necessary in most organizations, but an increased focus on one approach or the other at any given time within a specific organization may be appropriate” (p. 8). It is noteworthy that they add ‘time’, as a new parameter affecting the company’s decision. It has already been noted that effective knowledge sharing strongly affects the organization’s performance. It is for this reason that we shall close this section by taking a closer look into the issue.

KSNs and Performance Some organizations believe that they have internal customers; manufacturing is marketing’s customer, for example. By doing so they lose sight of what they are trying to accomplish as an organization. Others are organized around multifunctional processes that are directly focused on serving the end user. They form ‘product business teams’ that behave completely differently to the way departments behaved in the past over relevant functions. In this way a lot of dumb decisions in manufacturing –made only for the sake of manufacturing– can be avoided. The ‘product business teams’ are meant to divert the focus from the function to the customer. There are particular aspects in the manufacturing process that create difficult situations for both the Knowledge Sharing Networks (KSNs), and the knowledge management system in use. We are listing here below some of the most common ones: • •

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Lack of shared understanding, mainly due to the fact that they do not all use a common language. Discrepancies among the various versions of information stored in different locations of the KSN.

•

• •

•

Extensive use of personal (or group) information stores and the absence of easy-to-use indexing systems. Over-dependence upon sharing explicit knowledge and information, as the tacit one is more difficult to flow. Loss of skills developed due to collaboration, as they are not transferable through the KSN. Over-dependence on the KSN, and thus minimization of face-to-face contacts.

In industrial environments where these situations are not overcome, they may result in inefficiencies in the manufacturing process, which may, in their turn, produce a negative influence on the performance of the organization. Thus the effort is to make available infrastructures supporting knowledge management applications and introduce management initiatives promoting knowledge sharing activities throughout the entire manufacturing environment.

CON It has been made clear, in this chapter, that getting value out of knowledge sharing requires more than technology. Knowledge is inherently hard to control as it is ever expanding and unpredictable. Only when executives view organizational knowledge under this light will they manage it for most effective use. Starting on the assumption that tools people need to work with others are different from the ones they need to work alone, we demonstrated how the use of groupware permits ‘anytime, anyplace’ collaboration within the organization and for the benefit of the organization. Further on in this chapter, we examined organizational knowledge as an intellectual capital asset and focused on the effect that IT has on its management. We also recognized where IT –and particular groupware and knowledge

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repositories– fit in the usage and sharing of organizational knowledge. Under this perspective, we demonstrated that management’s principal challenge is to establish the mechanisms for collaborating individuals and groups to coordinate their activities in order to best support the flow of organizational knowledge within a firm, and to define ways, through which, the same mechanisms will preserve organizational memory in the future. That means not only to encourage their employees to share knowledge personally, but also to store their knowledge in a form that others can easily access it now or in the future. Thus, we may conclude that successful management or sharing of organizational knowledge provides a competitive advantage by adopting a knowledge management perspective assisted by information technology, leadership and culture, while, at the same time, it preserves organizational memory.

REFEREN Brewer, T. (1995). Managing Knowledge. Wentworth Research Program, November. Gartner Executive Programs, Stamford, CT. Retrieved January 21, 2005, from www.gartner.com Cohen, D. (1998). Toward a Knowledge Context: Report on the First Annual U.C. Berkeley Forum on Knowledge and the Firm. California Management Review, 40(3), 22-39. Davenport, T. H., & Prusak, L. (2000). Working Knowledge: How Organizations Manage what they Know. USA: Harvard Business School Press. Davenport, T. H., & Probst, G. (2002). Knowledge Management Case Book: Siemens Best Practices. 2nd Ed., Berlin and Munich: Publicis Corporate Publishing, and John Wiley & Sons, Inc. DeSantis, G., & Gallupe, B. (1985). Group Decision Support Systems: A New Frontier. Data Base, winter, 10-15.

Drucker, P. F. (1988). The Coming of the New Organization. Harvard Business Review, 66(1), 45-53. Re-published in The Harvard Business Review on Knowledge Management, (1998) Boston, MA: Harvard Business Review Series, Harvard University Press. Drucker, P. F. (2002). They’re Not Employees, They’re People. Harvard Business Review, 80(2), 70-77. Dyer, J. H., & Nobeoka, K. (2000). Creating and Managing a High-Performance Knowledgesharing Network: The Toyota Case. Strategic Management Journal, 21, 345-367. Earl, M. J., & Scott, I. A. (1999). What is a Chief Knowledge Officer? Sloan Management Review, 40(2), 29-38. Gibbert, M., Jonczyk, C., & Volpel, S. (2000). ShareNet – The Next Generation Knowledge Management. In Davenport, T.H. and Probst, G., (Eds), Knowledge Management Case Book: Siemens Best Practices, 2nd Ed. 2002, (pp. 2239). Munich: Publicis Corporate Pub., and John Wiley and Sons. Gilmour, D. (2003). How to Fix Knowledge Management. Harvard Business Review, 81(10), 16-17. Grant, R. M. (1997). Knowledge–based View of the Firm: Implications for Management Practice. Long Range Planning, 30(3), 450-454. Grant, R. M. (2000). Shifts in the World Economy: The Drivers of Knowledge Management. In C. Despres & D. Chauvel, (Eds), Knowledge Horizons: The Present and the Promise of Knowledge Management (pp. 27-55). Boston, MA: Butterworth-Heinemann. Grover, V., & Davenport, T.H. (2001). General Perspective on Knowledge Management: Fostering a Research Agenda. Journal of Management Information Systems, Special Issue on Knowledge Management, 18(1), 5-21.

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Hansen, M. T., Nohria N., & Tierney, T. (1999). What’s your Strategy for Managing Knowledge? Harvard Business Review, 77(2), 106-116. Johansen, R. (1991). Leading Business Teams: How Teams Can Use Technology and Group Process Tools to Enhance Performance. Reading, MA: Addison-Wesley. More on his work on the site of the Institute for the Future www.iftf.org Johansen, R., & O’Hara-Devereaux, M. (1994). Bridging Distance, Culture and Time. San Francisco, CA: Jossey-Bass Publishers. Kalpers, S., Kastin, K., Petrikat, K., Scheon, S., & Spath, J. (2002). How to Manage Company Dynamics: An Approach for Mergers and Acquisitions Knowledge Exchange. In Davenport, T.H. and Probst, G., (Eds), Knowledge Management Case Book: Siemens Best Practices”, 2nd Ed. 2002, (pp. 187-206). Munich: Publicis Corporate Pub., and John Wiley & Sons, Inc. McNurlin, B. C., & Sprague, R. H. Jr. (2004). Information Systems Management in Practice. Sixth Ed. New Jersey: Pearson Educational Inc. Nonaka, I. (1991). The Knowledge-Creating Company. Harvard Business Review, 69(6), 96-104. Nonaka, I., & Takeuchi, H. (1995). The Knowledge-Creating Company. Boston, MA: Oxford University Press.

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Prusak, L. (1997). Knowledge in Organizations. USA: Butterworth-Heinemann. Ruggles, R. (1998). The State of the Notion: Knowledge Management in Practice. California Management Review, 40(3), 80-89. Seely, B. J. (1991). Research that Reinvents the Corporation. Harvard Business Review, 69(1), 102-111. Re-published (1998) Harvard Business Review on Knowledge Management. Boston: Harvard Business Scholl Press, (pp. 153-180), and again (2002) as a Best of Harvard Business Review, 80(8), 105-114. Sveiby, K. E. (2001). A Knowledge-based Theory of the Firm To Guide Strategy Formulation. Journal of Intellectual Capital, 2(4), 344-358. von Krogh, G. (1998). Care in Knowledge Creation. California Management Review, 40(3), 133-153. von Krogh, G., & Roos, J. (Eds) (1996). Managing Knowledge: Perspectives on Cooperation and Competition. London: Sage Publications Ltd. Webber, A. (1993). What’s So New About the New Economy? Harvard Business Review, 71(1), 24-42. Zack, M. H. (1999). Managing Codified Knowledge. Sloan Management Review, 40(4), 45-58.

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Chapter VIII

Lessons Learned as Organizational Project Memories Raul M. Abril Universitat Pompeu i Fabra, Spain Ralf Müller Umeå University, Sweden and Norwegian School of Management BI, Norway

ABSTRACT This chapter suggests established research approaches to capture and validate project lessons learned. Past research indicates that due to the temporal nature of projects, improper management of knowledge, especially lessons learned, constitutes a risk for present and future projects. The authors argue that case study research is appropriate for developing lessons learned and that an inductive methodology can be used to generate hypotheses. These hypotheses are validated through an analysis of their Goodness of Fit into learning related business questions. Quality assurance in a lessons learned process should include a formalism to avoid loosing knowledge in the coding process, a formalism to avoid equivocality in the knowledge transfer to third parties, and validation techniques for the identified knowledge items. Furthermore, the authors argue that a common understanding should be achieved before organizational learning influences decisions and/or actions.

I Projects are intrinsically of temporal nature, they exist for a limited period of time and are characterized by frequent change of team members, depending on the skills needed at any particular point in time in the project (Turner & Müller, 2003). Continuous dispersion and re-formation of project

teams causes brain-drain problems through people leaving projects and simultaneously integration problems by people joining projects. Improper management of knowledge, especially lessons learned, constitutes a risk for present and future projects (Reich, 2007). Under the term “organizational project memories” we include any organization that is project

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Lessons Learned as Organizational Project Memories

driven including its higher order organizational structures like programs and portfolios. Therefore, for the purpose of this chapter, when we talk on organizational memories, we also consider organizational program memories and organizational portfolio memories. Project lessons learned demand two sets of knowledge to be externalized in order to reduce equivocality (i.e. different understandings after reading them). These are (1) knowledge of the ex-post mortem project life cycle like knowledge about the performance, deliverables and resources (e.g. Kasvi, Vartiainen & Hailikari, 2003), and (2) knowledge of the ex-ante contract like knowledge on the situation and context (e.g. Abril, 2005). Project lessons learned are thereby a subset of the organizational memory. This, in its most basic and traditional sense, can be defined as stored information from an organizations’ history that can be brought to bear on present decisions and/or actions (e.g. Huber, 1991; Walsh & Ungson, 1991). Anecdotal experience (e.g. Senge, Kleiner, Roberts, Ross, Roth, & Smith, 1999 ) and past research (e.g. Darr, Argote & Epple, 1995; Eskerod & Skriver, 2007) indicates that if action is not taken then knowledge from experiential learning (e.g. Kolb, 1984) is not preserved in the organizational memory (e.g. Cooper, Lyneis & Bryant, 2002). On the other hand, capturing lessons learned and reusing them has a positive impact (e.g. avoiding known mistakes) on the performance of other projects (e.g. Gulliver, 1987; Kotnour & Kurstedt, 2000; Karlsen & Gottschalk, 2003). An important limitation has to be noted here that exceeds the scope of this chapter, knowledge will only be considered successfully transferred when it is reused (e.g. shaping or guiding subsequent behavior). Unfortunately, you can have an excellent organizational memory that is not being used (e.g. Newell, Bresnen, Edelman, Scarbrough & Swan, 2006). This last observation brings up an interesting debate about the term “learned” from the

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behavioral and cognitive perspectives of the organizational learning literature. In the behavior perspective of the organizational learning literature (e.g. Huber, 1991) an entity learns if, through its processing of information, the range of behaviors is changed. This means that the members involved in the project influence their decisions and/or actions influenced by others’ prior knowledge captured in lessons learned. On the other hand, in the cognitive perspective of the organizational literature (e.g. Weick, 1995) an entity learns if, through a sense making process which is an attempt to reduce multiple meanings, it reaches a common interpretation of a state of affairs. This means that the members involved in the project have reached a common understanding on the whereabouts of the project which can be externalized (in the sense of Nonaka & Takeuchi, 1995) in the form of lessons learned. We argue that for an organization there is no conflict between both perspectives in organizational project memories and, furthermore, that a common understanding should be achieved before organizational learning influences decisions and/or actions.

BACKGROUND The economic and cognitive impacts are frequently neglected in the traditional literature on lessons learned. Traditional literature frequently targets practitioners. It describes the utilitarian value of lessons learned as being overwhelmingly associated with the reuse of knowledge (e.g. risk reduction by avoiding known issues). However, rarely it is mentioned that the utilitarian value of lessons learned enhances common understanding and project performance. For example, Ball, Evans, Dennis & Ormerod (1997) provided empirical evidence supporting the hypothesis that the time engineers spend understanding information is highly correlated with the time they spend acquiring it. They follow monotonically decreasing

Lessons Learned as Organizational Project Memories

functions that decrease at a decreasing rate such that they approach asymptotically the horizontal line representing the project lifecycle (see Figure 1). In another words, the early phases require an intense dedication to understanding and acquiring project information (see also Andersson & Müller, 2007). Of course, there are many project life cycle paradigms. However, most of them - including paradigms that are labeled with the terms “rapid” and “agile” - share the concept of phases and require handling of more abstract concepts in the earlier phases. Therefore, we argue that these earlier phases represent the best opportunities for optimizing the value of “good” lessons learned in terms of (i) enhancing common understanding and (ii) improving project performance. The term “good” applied to lessons learned can be controversial as it might suggest (unintended) the presence of a qualitative scale (e.g. “poor”, “mediocre”, “excellent”) when we talk about lessons learned. Being thorough, we cannot accept any lessons learned as such if it does not code true knowledge. We use the term “good” as a

qualification of the extent that the true knowledge coded in the lessons learned enhances common understanding. Likewise, the “common” term addresses a potential criticism on the relativism of the utilitarian value of lessons learned. If we omit the term “common” we would shift our unit of analysis from organization to individuals. If we omit the term “common” the utilitarian value of lessons learned enhancing understanding would be dependent on the ex-ante knowledge of a person. However, we are interested in the value from an organizational learning perspective where the organization (e.g. the project team) is the unit of analysis and a common understanding is needed. Summarizing, if the ex-ante lessons learned project team’s common understanding was Ka and the ex-post lessons learned project team’s common understanding was Kp , and Kp > Ka (i.e. there was enhancement in the common understanding) then the project team had a “good” lessons learned. This chapter addresses the question of how to codify explicit knowledge from project experiences in lessons learned. From a learning

Figure 1. Best opportunities for enhancements via lessons learned

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Figure 2. Constructs and relationships considered

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perspective the objectives of this chapter are (1) to provide a comprehensive literature review on how to produce good Lessons Learned in a project environment, and (2) to facilitate the internalization of the explicit knowledge coded in this chapter by practitioners for future use. The mind map in Figure 2 describes the main constructs that are presented.

Main Thrust of the Chapter Our approach considers lessons learned as a business research outcome. Therefore, thorough research concepts should be considered (see Figure 2). The structure of the chapter will follow the categories of concepts that need to be considered for a research design in the social sciences and the presentation of the sections in the charter will follow the flow of decisions that business researchers have to make in conducting research. We will pay extra attention to making the chapter understandable and reusable for practitioners.

Ontologies as Representations of Explicit Knowledge A Realism ontology (see Easterby-Smith, Thorpe & Lowe, 1997 for other ontologies) is the set of formal declarative representations of some elements of reality (e.g. entities, events) and of

their relationships that both exist according to a theory (e.g. Jurisica, Mylopoulos & Yu, 2004). Therefore, the amount and/or quality of explicit knowledge is influenced by a person’s ontology. In other words, the knowledge explicited through ontology might be a part of the explicit knowledge in the knowledge domain, Figure 3. The externalization of the explicit knowledge will require a formalism (e.g. words, charts, equations) in order to code the lesson learned. And again, it will be relevant that such formalism avoids knowledge lost in the coding process and equivocality in the knowledge transfer to third parties. Jurisica et al. (2004) claim that, in most cases, there are four broad ontological categories that will explicit knowledge. Their four broad ontological categories deal with static, dynamic, intentional and social aspects of the world. For example, if we want to explicit ex-ante contract knowledge, we may choose a theory/ontology that covers the four above aspects. However, if we want to explicit ex-post mortem project life cycle knowledge, we may choose a theory/ontology that covers only the static and dynamic aspects. Althoff, Birk, Hartkopf, Müller, Nick, Surmann & Tautz (1999) use logical data modeling graphic formalism in their grounded theory/ontology for the reusability of software development knowledge (see Figure 4).

Figure 3. Explicit knowledge vs. Ontology vs. Knowledge domain

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Figure 4. Ontology for reusability of software development knowledge, inspired through Althoff et al. (1999)

Research as a Process for Acquiring Eplicit Knowledge

• •

Research is a discerning pursuit of knowledge (e.g. Hair, Babin, Money & Samouel, 2003). The pursued knowledge in this chapter is ex-ante contract knowledge and ex-post mortem project life cycle knowledge. For the purposes of this chapter the terms research, inquiry, enquiry and investigation are exchangeable constructs. Any research, as a process of making knowledge explicit, should be consistent with the philosophical bases of the knowledge that is pursued. So, if we select a Realism ontology then the research process should be inductive. Among the different research designs, exploratory research is especially appropriate in the following knowledge demand situations (Churchill, 1991):

• •

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Formulating a problem statement Developing explanations in the form of hypotheses Establishing priorities for further research Increasing understanding on issues

The pursued knowledge will be based on facts (i.e. observable evidences). Information on facts will be found in different sources like files, texts, observations and people’s knowledge (see Figure 5). Additional key research decisions need to be made by the researcher. For the purposes of producing project lessons learned, we propose the following research decisions: • • • •

Research approach (also method of inquiry in the literature): Inductive Research strategy: Case study Time horizon: Longitudinal Data collection method: Interviews, questionnaires, secondary data

Lessons Learned as Organizational Project Memories

Figure 5. Project lessons learned as a business research outcome

We argue that an exploratory research in the above terms is appropriate for acquiring ex-ante contract knowledge and ex-post mortem project life cycle knowledge due to the good means-ends fit in the procedural rationality framework (e.g. Abril, 2002) between the epistemological bases of the above research decisions (i.e. the means) and the ontological choice for representing the acquired knowledge (i.e. the template of the end state). Figure 5 intents to illustrate the Lessons Learned as the “dependent variable” of a business research process. Obviously, forward extensions of a value chain having Lessons Learned as the independent variable (e.g. of project risk reduction) are out of the scope of this chapter.

Ex-Ante Contract Knowledge Project life cycles are not isolated from the scenario and environment within which they are defined and executed. There are reciprocal inter-relationships influencing each other. Therefore, such in-

fluences, from a comprehensiveness perspective, would justify by themselves to understand them if we pretend to understand in a holistic way the conditions under which the project is going to be implemented. However, such influences are not the only reason for acquiring ex-ante contract knowledge on the scenic and environmental factors. In our opinion, and based on past research, the main reason is that scenic and environmental factors impact the meaning attributed to coded symbols and data (e.g. lessons learned) when knowledge is acquired and transferred (e.g. Tyler, McGirr & Stanley, 1998; Weick, 1995; Thomas, Shankster & Mathieu, 1994; Brannick, 2000). Therefore, removing knowledge on the scenario and environment favors the risk of equivocality, that is, the risk of more than one interpretation of the lessons learned. Equivocality is negatively associated to common understanding and therefore it is not at all supporting the desired goal of enhancing common understanding for “good” lessons learned.

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Ex-ante contract knowledge involves knowledge before the closing of the project contract. It includes all the influential factors, like scenic factors, environmental factors, and project scope. Therefore, the ideal time for coding ex-ante contract knowledge is just before the contract is going to be signed. Otherwise, such knowledge could be “corrupted” with knowledge that is not really available ex-ante contract. Searching the literature on ontology of scenic factors, Burke (1969) suggested an ontology of five constructs for scenario descriptions. Burke’s constructs are act, agent, agency, purpose, and scene. Taking as a reference Burke’s ontology, we identify the following core scenic factors of a project life cycle: •

•

Context: A process or set of processes in a client’s functional area (e.g. CRM processes in the marketing function), the industry to which the organization belongs to (e.g. financial), the firm resources considered (e.g. technology, data, individuals) or a combination of the above constructs. Situation: A considered state of relevant business affairs characterized by a discriminant criteria. As an illustration, “product launch” and “market test” are examples of different situations which phase the discriminant criteria of both situations.

At a minimum, the scenario is the aggregation of a context and a situation. Additional scenic factors are stakeholders (both external to the project team and members of the project team), culture, location (e.g. off-shore development), problem that the project should address, and challenges. Searching the literature on ontology of environmental factors Porter (1980) suggested a well known ontology of five competitive forces for describing the firm’s environment: Supplier’s power, barriers to entry, customer’s power, threats of substitutes and competitors. Porter’s model provides a suitable ontology.

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Past research (e.g. Turner & Müller, 2004) has recognized the application and convenience of Agency theory to project management, identifying the project owner as principal and the project manager as agent. Project scope and scope change management are two situations where the following categories of the ontology implied in agency theory can be considered: •

• •

Problem to be solved with the project, goals and requirements of the project, as a formalization of the interest of project owner Terms and conditions of the contract between project owner and project manager Project estimates as a formalization of the delivery capacity of the project manager

Ex-Post Mortem Project Life Cycle Knowledge Ex-post mortem project life cycle knowledge involves knowledge from the contract up until the project is formally considered closed. We argue that ex-post mortem project life cycle knowledge should be coded in an incremental way after any of the following events: A major phase has concluded, a project milestone has been achieved, a major goal has been met, a major deliverable has been produced, a crisis has happened. Additionally, just before the project is formally to be closed (i.e. as part of the project life cycle) all the already coded pieces of the ex-post mortem project life cycle knowledge should be reviewed in order to produce a consistent and comprehensive document. If this incremental approach is not done, experience indicates that the availability of the sources of information about the facts during the implementation is very low. With a sense of humor…”they are gone with the wind”. Interestingly, project management seems to have been a praxis in search of a theoretical support (e.g. Söderlund, 2002; Koskela & Howell, 2002). In fact, it could be argued that well known standards

Lessons Learned as Organizational Project Memories

like the Guide to the Project Management Body of Knowledge (PMBOK) (PMI 2004) were in its origin a set of best practices, rather than a set of scientifically supported knowledge. However, empirically grounded theory (e.g. Easterby-Smith et al. 1991) is developed bottom-up, that is, from the longitudinal observations of successful experiences in managing projects. Accordingly, related ontologies developed and led to multiple research paradigms, as outlined, for example, in the nine schools of project management (Bredillet 2007a, 2007b, 2008). Through that comparative methods emerged (e.g. by looking at other theories in other knowledge domains) allowing for the development of (grounded) theories of project management (see Turner, 2006a-d). As suggested by Kuhn (1996) this incremental paradigm shift has contributed to a better understanding of a phenomena, in this case Project Management. The following ontological high order categories (partial view) for ex-post mortem project life cycle knowledge are suggested in the PMBOK (PMI, 2004): • • • • • • • •

Project management plan Deliverables Requested changes Implemented change requests Implemented corrective actions Implemented preventive actions Implemented defect repair Work performance information

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The method of inquiry will be induction. The classical methods of inquiry are described in terms of observations, facts and rules. The induction method of inquiry consists of the following basic steps: •

•

Case Study as a Research Strategy for Producing Lessons Learned We argue that case study is the best research technique (e.g. Yin, 2002) for acquiring ex-ante contract knowledge and ex-post mortem project life cycle knowledge due to the following reasons: •

Good fit between the requirements for conducting case study research and the

conditions in a project (e.g. single instance, real-life environment, in-depth analysis, fact oriented, different perspectives). From this research perspective a project is a case. Good fit between the research outcomes (i.e. the lessons learned) and the expected value as a case for knowledge transfer to third parties.

•

First, the project manager makes observations of the form X  Y. The observations are formulated as propositions involving an entity/property X and an entity/property Y. For example, being X= “team member John Perez” and Y= “level of knowledge/experience in new technology T1” we make an observation  =“meeting competence requirement” as it follows “team member John Perez does not meet competence required for knowledge/experience in new technology T1”. Second, the project manager matches observations with facts of the form X  Z. A fact is a validated proposition as true statement involving an entity/property X and an entity/ property Z. For example, being X= “team knowledge/experience”, Z= “number of P1 problems” and  = “negative association”, it is known the fact “team knowledge/experience is negatively associated to number of P1 problems”. The project manager engages a case study research finding enough evidence of the fit between the observation and the fact. Third, the project manager infers a rule of the form Y  Z. Rules are hypotheses that provide an explanation about a research/ business question and that until they are not

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falsified are considered as acceptable. For example, “level of knowledge/experience in new technology T1 is a risk because of number of P1 problems”. These basic steps give us relevant clues on the focus of case study research making observations and searching for information about facts in the available sources in order to generate hypotheses (see Figure 5). The basic steps for conducting case study research for the production of project lessons learned will include: •

Designing case study research Formulating learning related business questions  Identifying unit(s) of analysis  Identifying sources of observations  Literature review on facts  Selecting the data collection techniques  Identifying the analysis techniques  Designing triangulation steps  Designing the Lessons Learned Template Conducting case study research Analyzing case study evidence and facts Generating hypotheses Analyzing Goodness of Fit of the Lessons Learned Writing lessons learned 

• • • • •

Learning Related Business Questions In the introduction we have mentioned that in the traditional literature on lessons learned the utilitarian value of lessons learned is overwhelmingly associated with the reuse of knowledge. In essence, this main stream literature posits an “undirected” organizational memory. This proposition implies the following logic “capture as much lessons learned as possible and hopefully when someone will access them there will be a fit between the knowledge demands and the knowledge supply

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(in the Lessons Learned)”. We see this as a very narrow logic and recommend that “good” lessons learned, in addition to comprehensiveness and low equivocality, should support a fit with a set of defined knowledge demands. We define a learning related business question (e.g. Schank, 1988) as a sentence worded or expressed in such a form so as to express a demand of knowledge. In theory, the set of learning related business questions should not influence the lessons learned. That is, the lessons learned are not coded only or mainly for responding to the stated learning related business questions. If this would be the case, then additional learning related business questions would be hard to answer through lessons learned. We recommend that once the lessons learned have been coded, a test of their utilitarian value as organizational memory should be done by checking their goodness of fit with the learning related business questions. From a research perspective there is no difference between a learning related business question and a research question. In research, the researcher formulates a set of research questions that he/she wants to respond. For such purposes, adopts some epistemological premises and designs a research process. Here, the person leading the effort of coding lessons learned formulates a set of learning related business questions with the same intention that a researcher has with the research questions. Let’s see a few examples of learning related business questions that could be of interest to answer looking at a project lessons learned: • • • •

Was the ex-ante contract knowledge appropriate for scoping the project? Which factors contributed to the risk level in each phase of the project? What actions were executed to correct deviations of the plan? What are the recommendations to replicate the good things that happened in future projects?

Lessons Learned as Organizational Project Memories

•

• •

•

What are the recommendations to avoid/ mitigate/divert the bad things that happened in future projects? What knowledge assets (e.g. project deliverables) can be reused? How to secure accessibility to knowledge that was not possible to code for the lessons learned? Are there any recommendations (e.g. the value chain) about the project environment?

Unit of Analysis The unit of analysis acquiring ex-ante contract knowledge should be the project. However, acquiring ex-post mortem project life cycle knowledge, the recommendation is to take all the relevant units of analyses that will provide different perspectives to the lessons learned. For example, the project manager might select as units of analyses type of deliverable and implementation phases as he/she might want to gain lessons learned at the level of specific deliverables and specific phases.

Lessons Learned Templates Observations on the ex-ante contract knowledge can be coded in the template illustrated in Figure 6. Hypotheses, contributing factors, and recommendations on the ex-post mortem project life cycle knowledge can be coded in the template illustrated in Figure 7. It is highly recommendable to assign a unique code to each hypothesis, contributing factor, recommendation and observation. The templates suggested follow a format table of the involved ontology. We also recommend producing a mind map (see Figure 8) where all the lessons learned and business questions are visible. We recommend using the identifiers and a short descriptor of the lessons learned components:

• Observations in the ex-ante contract knowledge • Hypotheses, contributing factors, recommendations in the ex-post mortem project life cycle knowledge • Learning related business questions

Analyzing Goodness of Fit of the Lssons Learned We recommend that once the lessons learned have been coded, a test of their utilitarian value as organizational memory should be done by checking their goodness of fit with the learning related business questions. A similar situation is found in the data modeling literature for analyzing if a query (i.e. business question) can intentionally (i.e. independently of the actual data) be answered by a logical data model. Graph Theory and Mathematical Logic (e.g. Cohen & Nagel, 1961; Ullman, 1988) analyze query answerability in a given model. In summary, a query is answerable if it can be successfully mapped into the logical Query Normal Form (e.g. Spiegler & Elata, 1988) which can be done if the used formalism for the query and the logical data model is the same by finding a logical proposition (e.g. a well formulated formula (wff)) for the query that uses symbols of the wffs that describe the logical data model. Unfortunately, in our experience the thoroughness of first-order logic, as a formalism with well-defined model-theoretic and proof-theoretic semantics for inference (e.g. Liu, 1999), is not very popular among the average project manager. However, formalisms based on graphs like entity relationship (ER) models are more affordable to the average practitioner and can be mapped to an extended variant of first-order predicate logic (e.g. Chen, Thalheim & Won, 1998). Nevertheless, graph formalism still has to follow thorough rules which might be difficult to apply. With the mind map formalism there is no way that we can prove the answerability of a learning

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Figure 6. Template for project ex-ante contract knowledge

related business question by the lessons learned because the mind map formalism does not meet the requirements of having well-defined modeltheoretic and proof-theoretic semantics for inference. So, what can we do? We can increase our level of confidence in that the lessons learned provide a response to the business question. We can do it by using table (Fernandez, 1987) as an explanatory technique of the goodness of fit between a business question and the lessons learned. Again, the table in itself does not prove

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anything; it is just a technique for expressing the information clues in the business question with respect to the information clues provided by the lessons learned. The table technique goes as it follows (see Figure 9): 1.

Construct a table with a header row with the aggregated intension of the information clues intervening in the business question.

Lessons Learned as Organizational Project Memories

Figure 7. Template for project ex-post mortem life cycle knowledge

Figure 8. Template for mind map of project lessons learned

2.

Add a row to the table writing in the left hand side of each row an information clue in the business question and search for such information clue in the lessons learned both in the ex-ante contract knowledge and ex-

post mortem life cycle knowledge. If you find a fit add a column header (if it does not exist already) with the lessons learned information clues and in the intersection cell put a check mark and if needed a comment.

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3.

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Application_A1 AND Budgeted _Cost_of_Work_Performed

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Application_A1 AND Budgeted _Cost_of_Work_Performed AND Budgeted _Cost_of_Work_ Scheduled

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√

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Application_A1 AND Budgeted _Cost_of_Work_Performed AND Budgeted _Cost_of_Work_ Scheduled AND Causes

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√

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If you find a fit, then you can increase your level of confidence in that this information clue required in your learning related business question can be answered by the lessons learned. If you do not find a fit, then you can decrease your level of confidence in that this information clue required in your learning related business question can be answered by the lessons learned. Repeat step 2 for all the information clues in the learning related business question.

{Application_A1, Budgeted _Cost_of_Work_Performed, Budgeted _Cost_of_Work_Scheduled, Causes}. We would expect to find information clues related to Application_A1 in the went wrong expost mortem project life cycle knowledge and in

Ex-ante Went Wrong: Factor Fk

Ex-ante Project estimates PEj

Application_A1

For example, let’s assume that we have the business question BQ01: What were the causes of the delay delivering application A1? We identify the following information clues:

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Ex-post Went Wrong: Factor Fi

BQ01 : “What where the causes of the delay delivering application A1? ”

Ex-post Unit of Analysis: Application 1 A1

Figure 9. Analyzing the goodness of fit business question vs. lessons learned (table example)

√

the project ex-ante contract knowledge on project estimates (see Figure 9). In case that there is confidence in that the lessons learned provide answer to a learning related business question, it is recommendable to illustrate it with a link in the mind map between the business question and the clues in the lessons learned providing an answer. We argue that the table technique has more value identifying missing lessons learned as it tries to answer the stated business questions.

Futu Lessons learned as organizational project memories is a popular and important subject in project-based organizations. However, if not neglected at all, Lessons Learned are often reduced to capturing of individuals “top of mind” items at project end in a utilitarian approach to the re-use of experiential learning, The present chapter suggested a broader, scientific approach by making use of past research in social sciences and the development of associated research processes. To that end a process and techniques are

Lessons Learned as Organizational Project Memories

provided for capturing and validating valuable Lessons Learned. The relative newness of this approach implies a need for future research and development to advance processes, as well as foster acceptability by practitioners. That implies two directions of future research, a) research for advancing current understanding, and b) development for advancing sophistication and application. The former requires: • Further empirical studies on the impact of lessons learned on enhancement of team understanding. This includes studies on the reduction of equivocality through the proposed approaches, as well as the overall impact of Lessons Learned activities on project results. • Further research on possible ontological frameworks for project lessons learned. This implies a move from singular paradigms, such as those mentioned above, to frameworks encompassing ontological differences by project types, industries, geographies or stakeholder groups. Here guidelines could be developed to help practitioners to determine their idiosyncratic types of lessons to capture or reuse. These two sets of studies would allow for better understanding of the value of lessons learned as organizational project memories, and foster their practical application in project work. Advancing sophistication and application of Lessons Learned requires: • Development of dedicated research strategies for project lessons learned. That includes methodological approaches and their process steps consistent with the different entries in the ontological framework mentioned above. • Development of knowledge-based systems as repositories of project lessons learned

for better project estimates and better risk assessments. These integrate management of risk, knowledge, and planning into an overall learning system of organizational memory, to be used for project and operational work. • Development of formalisms and appropriate semantics that are well-defined model-theoretic and proof-theoretic. • Development of interactive tools and techniques which are user friendly, based on visual graphic user interfaces and allow for easy capturing and representing of lessons learned. These developments will increase acceptance, usage and importance of lessons learned for the benefit of organizational memories.

CONCLUSION This chapter identified practices of capturing project lessons learned as being limited to utilitarian approaches and lacking validation of items captured for the context within which they evolve. To develop a rigorous and methodologically stable approach to capturing project lessons learned we took a social science perspective and took advantage of its inherent research processes. To that end we suggest to use established research approaches to capture and validate project lessons learned. Two sets of knowledge were identified as being required for project lessons learned: •

•

ex-ante contract knowledge, captured through observation just before contract signature. This encompasses the project’s original intention and scope. ex-post mortem project life cycle knowledge, captured over the course of the project and readily available at the end of the project in form of hypotheses about what happened in

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the project, contributing factors, and recommendations. Development of the lessons learned will follow a six step process, which uses a case study research approach and an inductive methodology to generate hypotheses. These hypotheses are validated through an analysis of their Goodness of Fit into learning related business questions. That constitutes the minimal requirement for assessing lessons learned. A lessons learned process should meet a number of criteria ensuring quality in the outcome by using: • A formalism to avoid loosing knowledge in the coding process. This is achieved through the interaction between hypotheses and learning related business questions. Only those lessons learned relevant for the intended type of learning are created. • A formalism to avoid equivocality in the knowledge transfer to third parties. This is ensured by use of templates, such as those shown in Figure 6 and 7. • Enhancing the common understanding by adding “good” knowledge to the existing level of knowledge, achieved through the six step process. • Validation techniques for the identified knowledge items. This is ensured through cross tabulation of knowledge items with the identified learning related business questions. Notwithstanding potential implications for policies and procedures governing project and organizational knowledge management, we addressed project lessons learned as a business research activity, with the project manager executing a process adapted from the social sciences. Just as a social scientist, the project manager should be aware of the different ontological stances and associated worldviews in order to identify an ap-

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propriate perspective towards the lessons learned in a project. We suggested realism ontology with a case study approach as a typically appropriate ontological and epistemological perspective to capture the facts accumulated over the project’s life cycle and interpret them in the context of the project and its situation. To that end we suggest to use social science findings to build organizational memories from today’s projects. This paradigm shift may contribute to better project results and to the benefit of project stakeholders.

REFERENCES Abril, R. M. (2002). Procedural rationality as a framework for assessing case research methods. In R. Hackney (Ed), International Symposium on Research Methods, Barcelona, Spain. Abril, R. M. (2005). A methodological framework for gaining research focus. The case of problem sense making in CRM using a data warehouse (Henley Working Papers). Henley Management College, UK. Althoff, K-D., Birk, A., Hartkopf, S., Müller, W., Nick, M., Surmann, D., & Tautz, C. (1999). Systematic population, utilization, and maintenance of a repository for comprehensive reuse (Tech. IESE Rep. No 001.99/E), Fraunhofer IESE, Kaiserslauten, Germany. Andersson, A., & Müller, R. (2007). Containing transaction costs in ERP implementation through identification of strategic learning projects. Project Management Journal, 38(2). Ball, L. J., Evans J., St. B. T., Dennis, I., & Ormerod, T. C. (1997). Problem-solving strategies and expertise in engineering design. Thinking and Reasoning, 3(4), 247–270. Brannick, T. (2000). The enigma of marketing information. IBAR- Journal of the Irish Academy of Management, 21(2), 81-106.

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Bredillet, C. (2007a). From the Editor. Project Management Journal, 38(3), 3-5, Bredillet, C. (2007b). From the Editor. Project Management Journal, 38(4), 2-4, Bredillet, C. (2008). From the Editor. Project Management Journal, 39(1), 2-4, Burke, K. (1969). A grammar of motives. Berkeley, CA: University of California Press. Chen, P. P-S., Thalheim, B., & Wong, L. Y. (1998). Future directions of conceptual modeling. In P. P. Chen, J. Akoka, H. Kangassalo, & B. Thalheim (Eds.) Conceptual modeling: Current issues and future directions. Lecturing Notes in Computer Sciences (pp 294-308). Springer-Verlag. Churchill Jr., G.A. (1991). Marketing research. Methodological foundations. The Dryden Press. Cohen, M., & Nagel, E. (1961) An introduction to logic and scientific method, 1 & 2. Harcourt, Brace & World. Cooper, K. G., Lyneis, J. M., & Bryant, B. J. (2002). Learning to learn, from past to future. International Journal of Project Management, 20. Fernandez, C. (1987). El modelo relacional de datos: De los fundamentos a los modelos deductivos. Diaz de Santos. Darr, E. D., Argote, L., & Epple, D. (1995). The acquisition, transfer, and depreciation of knowledge in service organizations: Productivity in franchises. Management Science, 41(11). Eskerod, P., & Skriver, H. J. (2007). Organizational culture restraining in-house knowledge transfer between project managers. A case study. Project Management Journal, 38(1). Easterby-Smith, M., Thorpe, R., & Lowe, A. (1991). Management research. An introduction. SAGE. Gulliver, F. R. (1987). Post-project appraisals pay. Harvard Business Review, 65(2).

Hair Jr., J. F., Babin, B., Money, A. H., & Samouel, P. (2003). Essentials of business research methods. Wiley. Huber, G. P. (1991). Organizational learning: The contributing processes and the literatures. Organization Science, 2(1). Jurisica, I, Mylopoulos, J., & Yu, E. (2004). Ontologies for knowledge management: An information systems perspective. Knowledge and Information Systems, 6(4). Karlsen, J. T., & Gottschalk, P. (2003). An empirical evaluation of knowledge transfer mechanisms for IT projects. Journal of Computer Information Systems, Fall. Kasvi, J., Vartiainen, M., & Hailikari, M. (2003). Managing knowledge and knowledge competences in projects and project organizations. International Journal of Project Management, 21(8). Kolb, D. A. (1984). Experiential learning. Experience as the source of learning and development. Prentice-Hall. Koskela, L., & Howell, G. (2002). The Underlying Theory of Project Management is Obsolete. In Proceedings of the PMI Research Conference (pp. 293-302). Kotnour, T. G. & Kurstedt, H. A. (2000). Understanding the lessons-learned process. International Journal of Cognitive Ergonomics. 4(4). Kuhn, T. (1996). The structure of scientific revolutions, 3rd ed., University of Chicago Press, London, UK. Liu, M. (1999). Deductive database languages: Problems and solutions. ACM Computing Surveys, 37(12). Newell, S., Bresnen, M., Edelman, L., Scarbrough, H., & Swan, J. (2006). Sharing knowledge across projects: Limits to ICT-led project review practices. Management Learning, 37(2).

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Nonaka, I., & Takeuchi, H. (1995). The knowledge creating company. Oxford University Press. Porter, M. E. (1980). Competitive strategy: Techniques for analyzing industries and competitors. NY: Free Press. Project Management Institute PMI (2004). A Guide to the Project Management Body of Knowledge PMBOK, 3rd edition. Reich, B. H. (2007). Managing knowledge and learning in IT projects: A conceptual framework and guidelines for practice. Project Management Journal, 38(2). Schank, R. C. (1988). Creativity as a mechanical process. In R. J. Sternberg (Ed), The nature of creativity: Contemporary psychological perspectives (pp 220-38). Cambridge, UK: Cambridge University Press. Senge, P. M., Kleiner, A., Roberts, C., Ross, R., Roth, G., & Smith, B. (1999). The Dance of Change. Doubleday. Soderlund, J. (2002). On the development of project management research: Schools of thought and critique. Project Management, 8(1). Spiegler, I., & Elata, S. (1988). A priori analysis of natural language queries. Information Processing & Management, 24(6). Thomas, J. B., Shankster, L. J., & Mathieu, J. E. (1994). Antecedents to organizational issue interpretation: The roles of single-level, cross level, and content cues. Academy of Management Journal, 37(5). Turner, J. R. (2006a). Towards a theory of project management: The nature of the project. International Journal of Project Management, 24(1), 1-3.

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Turner, J. R. (2006b). Towards a theory of project management: The nature of the project governance and project management. International Journal of Project Management, 24(2), 93-95. Turner, J. R. (2006c). Towards a theory of project management: The functions of project management. International Journal of Project Management, 24(3), 187-189. Turner, J. R. (2006d). Towards a theory of project management: The nature of the functions of project management. International Journal of Project Management, 24(4), 277-279. Turner, J. R., & Müller, R. (2003). On the nature of the project as a temporary organization. International Journal of Project Management, 21(1). Turner, J. R., & Müller, R. (2004). Communication and co-operation on projects between the project owner as principal and the project manager as agent. European Management Journal, 22(3). Tyler, K., McGirr, D., & Stanley, E. (1998). Contextualising: Technology, relationships and time in a financial services virtual organisation. Service Industries Journal, 18(3). Ullman, J. (1988). Principles of database and knowledge-base systems (vol. I and vol. II) Computer Science Press. Yin, R. K. (2002). Case Study Research. Design and Methods. Applied social research method series Vol. 5. Sage. Walsh, J. P. & Ungson, G. R. (1991). Organizational memory. The Academy of Management Review, 16(1). Weick, K. E. (1995). Sensemaking in Organizations. Sage.

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Chapter IX

Will You Recall What You Knew? Jerry Westfall Liberty University, USA

A This chapter discusses employee recall due to training presentations. Recall is an employee’s ability to remember what they knew or have learned via a training activity. This recall is improved when one utilizes structured training material. This eliminates selective scanning and provides program control for the training material. This chapter is specifically concerned with the transition from the externalization phase to the combination phase of the SECI model where the authors turn organizational tacit knowledge into explicit knowledge. They use these explicit knowledge materials to train employees for the purpose of organizational improvement. Research into employee recall is somewhat limited at this point, but the economic and personal impact for the employee and the organization are considerable when compared to the over US$2 trillion dollars spent annually by organizations on employee training worldwide. The motivation then is to design our explicit training materials so that we receive maximum benefit from improved employee recall leading to overall improvement of our organizations.

IN Today we live in a “knowledge society” characterized by “knowledge workers” (Heath, 2003) who use the knowledge they have of their organization to interact with each other and change organizational outcomes. Organizational outcomes might be profits, customer retention, customer service improvements or goodwill. Whatever the outcome there are employees in the organization that have the knowledge to make these outcomes success-

ful. Since the employee knowledge concept has become increasingly understood it has caused organizations to realize that knowledge is critical to their continued success (Wild, Griggs, & Downing, 2002). The critical part becomes the need to retain business knowledge within the organizations for future use and integration. The trend becomes one of movement by organizations from exclusive physical asset management to dual physical and knowledge asset management.

Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

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Evidence of the change from exclusively physical asset management to knowledge asset management becomes clear in that organizations worldwide are spending upwards of $2 trillion dollars on employee training and education each year. The knowledge industry has become larger each year as organizations continue to leverage their knowledge assets to produce some type of positive organizational outcome. Training and education becomes integral for an organization to remain competitive. There has been a move to expand competitiveness and positive organizational outcomes by investing in human capital (knowledge) and technology (Paye, 1996). Because knowledge management has become a real concern for organizations it has prompted much research about knowledge capture, storage, and training systems. The knowledge residing within the employee has become an important asset for the organization to manage, usually with some type of technology system. Not only has the capture and storage of employee knowledge become important, but also the training of other employees on this newly captured knowledge. In addition to training, improving employee recall has become a concern for organizations wishing to maximize their knowledge assets because it is in employee recall of the trained knowledge where the organization benefits the most from their knowledge asset endeavors. Worth examining in this realm specifically is the relationship between training employees and the resultant recall of the employees of the knowledge they were trained upon. The employee must recall the knowledge they were trained upon in order to develop cognitive, or brain function, processes that convert this knowledge into useful tacit knowledge (Herbig & Bussing, 2004). Tacit knowledge is know-how knowledge (Nonaka & Konno, The concept of “ba”: Building a foundation for knowledge creation., 1998) or knowledge that is intuitive, sometimes difficult to express, gained through experience, and shared through personal inter-

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actions (Droege & Hoobler, 2003) and is tied up in the cognitive process of the employees mind. However, for tacit knowledge to become useful it has to be converted to explicit knowledge. This makes the converted knowledge (explicit knowledge) flexible or easy to use within the organization. When a business organization can successfully capture tacit knowledge explicitly they have then made it potentially available to everyone else in the organization. They have captured important knowledge from one or more employees with the intention then of distributing that captured knowledge, explicitly, to others who can benefit from it (Westfall, 2006). Explicit knowledge is the result of some type of conversion process driven by the tacit knowledge captured from employees. Tacit knowledge is converted into some form that is readily accessible by other employees and can be used in training situations. Explicit knowledge is simply tacit knowledge put into some physical or electronic form that others may review, train upon, or access. The explicit knowledge material does not provide benefits in itself to the company other than dissemination, but it is the employees’ later recall of the explicit knowledge material that drives positive organizational outcomes. There is no benefit to the explicit material itself because it is simply the conduit through which employee training is formalized. Employees at all levels of an organization are in constant contact with other employees thereby spreading knowledge through these personal interactions. However, since every employee does not usually have access to every other employee the knowledge exchanges may be limited. Therefore the explicit knowledge material provides the means to disseminate knowledge to everyone in the organization. The benefit is therefore derived from the use of the knowledge distributed throughout an organization but this is not possible if the employee does not recall what they have learned during an organizational training session. These sessions

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may be in group settings, web based, CD/DVD based, or through individual apprenticeships or internships. Regardless of the method of training the result must be the employee recall of what they have learned. To attain a successful conclusion to a knowledge management initiative an employee must be able to recall what they have learned and though interactions in their daily work life utilize this new knowledge thereby developing more knowledge. This knowledge then again becomes tacit or internal knowledge, and the knowledge management processes used previously must continually be applied to capture this newly developed knowledge. The emphasis in this chapter is to develop an understanding of knowledge recall and the resultant solutions for improving recall once employees have received training on an explicit knowledge concept. Although recall abilities may be different in each employee it is still necessary to increase employee recall whenever possible and through whatever means possible. Therefore we will examine knowledge processes and current research into knowledge recall and discover what makes recall so important to knowledge management activities.

and procedures. Our knowledge management processes and procedures will be dictated by what quadrant of the model we desire to work within. This then helps us divide our knowledge management initiatives into workable sections. While this is most helpful to us in knowledge management especially with capturing and storing knowledge, it does not specifically address improving employee recall. This approach examined the social interactions of employees thereby creating new tacit knowledge. The tacit to explicit and back to tacit knowledge process provides a good way for us to view our knowledge management strategies. However, when we begin to incorporate our desire to improve recall into the model we step outside the model’s parameters. What we do have is a way to compartmentalize our processes to ensure that we are working toward improving recall within the SECI model processes. In the SECI model processes there is in the socialization phase an exchange of tacit knowledge between individuals. In the externalization phase the individual’s tacit knowledge is transferred to

Figure 1. SECI Model

BA Nonaka and Takeuchi (1995) developed a model to describe the transfer of knowledge within an organization. This is a spiral approach to knowledge creation and conversion within an organization. This approach considered the interpersonal relationships of employees within an organization, and their relationships to the working group and to the whole organization to which they belong. This spiral approach moves from tacit knowledge to explicit knowledge and then back again. This spiral approach gives us a foundational approach when trying to understand and formulate our knowledge management processes

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the group which is the primary knowledge force in the organization. In the combination phase the group makes their tacit knowledge explicit so that the whole organization can benefit from that knowledge. In the internalization phase the explicit knowledge is internalized and the process begins anew. Specifically relevant to our topic in this chapter is that we find a tacit to explicit to tacit process that gives us a way to track our knowledge capture, storage, and training endeavors within the organization. However, the model does not describe the specifics of how to train nor the results once training has happened. Knowing the process of the tacit to explicit to tacit exchange described in the SECI model does provide an excellent framework for understanding knowledge processes within an organization. What is missing, and what we talk about in this chapter is the results of the training activities and how that relates to the recall of the knowledge an employee receives during the training.

KNOWLEDGE TRANSFERS Making successful knowledge transfers have been shown to provide channels to problem solving, goal achievement, and competitive advantage (Smith, 2001). The goal of the knowledge transfer is to generate action by the receiving employee thus making the actions they take based on the received knowledge more effective (Connell, Klein, & Powell, 2003). The key is to make the emphasis of a knowledge transfer the employee’s recall and not just the knowledge itself (Connell, Klein, & Powell, 2003). Emphasis should now be placed on the employee’s ability to recall, transform, and utilize the new knowledge for positive organizational outcomes. Positive organizational outcomes are becoming increasingly important as most organizations move into global markets. The outcome associated with improving employee memory recall is

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important to examine and may have the most impact on the success or failure of the organizations strategies and goals. If we want our organizational memories to remain viable we have an obligation to seek methods of improving recall throughout the organization. Will our employees know what they knew? Yes, they will if we do everything in our power as knowledge management professionals to help them recall or remember what they have learned.

Issues, Controversies, Problems The problem dealing with recall is one of discovering how to train employees in such a way that we improve their recall after the training event. Evidence seems to indicate that the training event presentation methods we use may have an impact on how much an employee will recall. Examination of presentation methods has had some limited research, but the problem is that more research is needed in order to find the best method of training. The lack of research in this area of employee training recall prevents us from developing a complete picture when dealing with human memory and recall and discovering the best training methods to ensure satisfactory recall of the training by the employee. There may not be one, best, method of training to improve recall, but research has indicated that there are differences in recall ability when different training methods are utilized. At issue in this chapter is the focus on the type of training presentation which might potentially lead to improved recall. Research into creating training presentations so that a difference may be observed statistically leading to conclusions being developed to explain the differences. Prior research has shown that different presentations methods produce differences in recall. One research project found that by structuring a training presentation recall was improved (Herschel, Nemati, & Steiger, 2001). Structure was

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defined as creating a training presentation in an orderly manner such as hierarchical, or outline, or etc. It was found that the structure of the training presentation made a difference, at least statistically, in improving employee recall. Additional research conducted in 2006 utilizing structure, quasi-structure, and non-structure training presentations resulted in a difference statistically between the methods used (Westfall, 2006). A structure presentation (using PowerPoint) was developed in a hierarchal manner whereas the non-structure was created in paragraph form, and the quasi-structure presentation was a combination of the two previous styles. The results of this research suggested that differences in recall are statistically observable due to the differences in the training presentations. Given several objective statistical factors the indication was that other factors like age, education level, employment status, gender, and income did not make a difference statistically. However, when the three presentation styles were looked at statistically a difference was observed. This observation, although not conclusive, seems to indicate that a training presentation style may influence recall in employees. Furthermore, in both research efforts outline above, the training was autonomous where there was not a lecturer, or speaker conducting the training session. The employees where trained electronically via videos or automatic PowerPoint presentations. This was done to eliminate outside influences on the training session and resultant recall. As with any research there are many factors to consider and this non-human participation factor will need further examination. Additionally it must be noted that in both these previous research efforts, the employees were tested for recall very soon after the training exercise which provided for some statistical corroboration or proof that structuring training presentations improve recall. Future research would need to examine recall at later time inter-

vals to distinguish between immediate recall and normal recall over time. Regardless of the time interval involved in the previous research there seems to be a connection between the style of training presentation used and the successful recall of that training after the training event. This gives researchers additional areas of research in which to prove or disprove that recall can be improved by using different training styles. Further at issue is that the majority of knowledge management research and development today is geared toward capturing and storing knowledge. The use of networks and relational databases to capture and store knowledge is a burgeoning area of interest. Practitioners involved in researching and creating these knowledge reservoirs continue to have success in improving our capture and storage abilities. Also many researchers create and develop multiple ways to convert stored knowledge into explicit forms with varying degrees of success. The success of capture, storage, and conversion methodologies while continually improving, usually do not consider in any statistically meaningful way the results of these processes. Thus the recall of training is not researched significantly and this may limit the usefulness of making knowledge available to employees. Research into employee recall becomes one of finding the best way to create our training presentations in such a way that we know with some certainty that improved recall results from our efforts.

Structure, Cognition, and Recall The methods examined in this chapter are those of organizing knowledge in our training presentations so that we produce some type of improvement in employee recall. In past research it was discovered that organizing knowledge within a training presentation improved recall (Caillies, Denhiere, & Jhean-Larose, 1999). This research

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found that simply organizing knowledge explicitly improved employee recall at a later time. Further it was postulated that organization of knowledge created five unique levels which were: 1.

2. 3.

4.

5.

Generalization a. Main ideas clarified with additional details or examples Enumeration a. Lists the ideas one after another Classification a. Groups or segregate ideas into categories Sequence a. A continuous and connected series of events or steps Compare/Contrast a. Compares relationships between two or more ideas

Each of these levels gave some type of organization or structure to the training presentations. This finding was significant because a step was made in determining the best way to create explicit knowledge presentations for employee training. Additionally in other research it was found that recall was better when concepts were organized in a hierarchy within the experimental media (Wolfe, 2005).

Slective Scanning A characteristic of previous research endeavors into employee recall was the concept of selective scanning. Selective scanning was expressed as the process whereby employees determine selectively what was important or not important to them when viewing some type of training presentation. Employees tended to look through non-linear (sequenced) media for clues about what was important to the idea or thought presented. This selective scanning was done to make sense of the material and to help employees remember

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or recall what they had viewed or read at a later time. They weeded out what was not important to their understanding of the material as they perceived it. Non-selective scanning occurred when the training material was presented in a structured (hierarchal) way which meant that employees did not need to weed out unnecessary material (Eveland, Cortese, Park, & Dunwoody, 2004). Unstructured material encouraged selective scanning and defeated the purpose for having structure applied to the media in use. Therefore it was argued that structure seemed to improve recall because non-selective scanning was part of the cognitive ability of each employee to begin with. Selective scanning in viewing some type of media has been a skill that has been applied to other types of tasks. Using their ears, for example, employees listened to a presentation and scanned it for relevant clues as to the important points or ideas presented (Eveland, Cortese, Park, & Dunwoody, 2004). If the presentation was structured then selective scanning was not as important for the employee to perform when listening. Also for a visual task that was structured, the need to selectively scan was not necessary. The structure gave clues to the employee as to what was important about the material being presented. However if the same task was presented without structure (sequence or paragraph form) then selective scanning became necessary for the employee to make sense of what they were learning. The whole idea of selective scanning is important to consider because we all tend to do this daily. We look for clues within the material presented until we have formed some mental process to handle absorption of the material and to facilitate later recall. Since it is common for us to selectively scan, it is appropriate that we consider this process when designing our training presentations. What this means for the knowledge management professional is that we have to take into consideration selective scanning when we design

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our training materials. Are we going to make the employee scan for the relevant material or are we going to give them the important material already outlined and indentified? This question is of utmost importance if we wish to make sure our training is recalled at a later time. Recent studies have examined learning in relation to using training materials that elicit user control and program control methods. User control (Jonassen, 1988) says that each individual is different in their learning capabilities and that no one training presentation is best for a training activity. User control gives the user the control of their own learning abilities and relates to selective scanning in that the user controls the methods and processes in scanning training materials for relevant ideas and concepts. However, some studies have shown some benefit for recall from user control (Kinzie, Sullivan, & Berdel, 1988) while other studies have shown little benefit to user control (Yang & Chin, 1996-1997). In contrast, program control, places the control with the training material itself. It leaves little control to the user and therefore selective scanning is less important to the user. Eveland and Dunwoody (2001) found that selective scanning was useful in non-structured training material. They specifically used the web as their non-structured material source, but the results indicated that there was selective scanning utilization when the user was not given specific clues to important aspects of the training material. Selective scanning therefore creates associative connections within the learner as to the important clues or items about the training material. Because the web is based on hyperlinks and hypermedia the thought is that this mimics the associate and selective scanning processes in the human mind (Churcher, 1989). Selective scanning therefore is performed by individuals when there are no distinct clues to the important items in training materials. All of this means that we as knowledge management professionals must consider selective

scanning in the context of our training material development. We must choose to make our training materials in such a way that we either encourage or discourage selective scanning. This chapter makes a case for non-selective scanning training materials because previous research has shown that there is a noticeable difference in recall when structure is used in training materials. Reducing selective scanning seems to improve recall in employees and this then leads to a better assurance that our organizational memories are correct and remain useful throughout the organization. Additionally we have to ensure that we consider the types of knowledge exchanges we encourage so that we are sure our knowledge exchange endeavors are successful.

KnowledgeNOWLEDGE From prior research it was discovered that knowledge was transferred most frequently between individuals that were “homophilious” or alike. This is important because individuals within an organization are typically more alike than different when given adequate time for organizational acclimatization. This transferred knowledge however was typically more tacit than explicit given the acclimatization process (Rogers, 1995). It is more tacit because it is knowledge gained through observation, interactions, and individual training. This knowledge is not explicit but instead is given from one employee to another directly or indirectly. To make the knowledge more transferable to “heterophilious” or dissimilar individuals, knowledge needs to be converted into explicit knowledge. This is where knowledge is converted from employee tacit knowledge to some explicit form that is then transferred to others within or without the organization. Communicating employee knowledge has always been vital to organizational goals and processes and when done in a way consistent with socialization factors,

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cognition factors, and scanning factors previously mentioned the resultant improvement to recall is confirmed. As prior research has shown there is a consistent statistical improvement in recall when explicit training presentations are structured in some way to help employees retain knowledge and latter recall that knowledge for use in their normal work environments. The study of how humans learn, remember, and recall is far beyond this chapter, but as noted we can improve employee recall at least in some measureable way leading to improved employee performance. Structuring a training presentation therefore seems to reduce selective scanning which leads to improved recall. The next section deals with how to create a training presentation that improves recall.

Create Training Presentations That Wrk The goal of training should be to facilitate learning in employees and improve knowledge recall. This obviously is an important component to any knowledge management strategy. Once we capture the knowledge we wish to retain within the organization we must also be sure to develop that knowledge into useful explicit forms contributing to our employee training initiatives. Since previous research has not formally defined what type of training presentation is the best, the motivation for us is to prepare a variety of presentations to evaluate which improves recall the best. The trainer must look for clues to which presentation provides the best training style so that it can be copied to other training initiatives within the organization. The evidence, so far, suggests that structuring a training presentation in some manner improves recall in employees and therefore our task is to find that best training style and use it to drive improvements in employee training recall. This gives us our best shot at improving employee recall and making a difference within the organization.

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For an employee to “recall what they knew” we as business leaders, trainers, teachers, and training professionals must strive to provide the best possible training to our employees. We must ensure that we are motivated to seek out and find the best methods for training. This includes current research that tells us that structuring our training presentations in a way that reduces selectivescanning and thereby leading to better recall is important for the organizations we represent. Since every trainer has a particular style they usually prefer, it is critical for recall improvement success to be flexible enough to consider other means of training. Changing our methods is sometimes difficult, but in light of our commitment to improve employee recall we should endeavor to become as flexible as we can be until we find the best training methods. It is vital to be able to give our employees the best possible conditions whereby they are improving their training knowledge recall. We may not presently know the optimum style when creating explicit training presentations, but we do know that presentations that are hierarchal or outline in form tend to reduce selective scanning and improve recall. Prior research has indicated this to be the case and we should attempt to reproduce our own training materials to elicit, at the minimum, a statistically verifiable improvement in employee recall. As indicated in Figure 2 there is every indication that as we reduce selective-scanning within in our training presentations we can measure an improvement in recall. This means we have gone from total selective scanning to non-selective scanning along our recall percentage scale. This chart is not statistically accurate, but only represents our goal of reducing selective scanning and the resultant improved employee recall. The training materials that present the needed information in hierarchal or outline way produces an increase in employee recall of the material. Therefore if we give our employees the required clues to the importance of the needed information

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Figure 2. Selective vs. non-selective scanning (non-statistical)

we can be sure we are giving them a chance to assimilate the information in a meaningful way so that they can recall it when needed. We reduce selective scanning so that we do not force the employee to make assumptions about the information we wish to convey. We take program control of the training presentation so that user control is eliminated as much as possible. The most important thing to remember here is to provide the required clues and emphasize the relevant or important information within the training material. Be sure to include the information that gives the employee the best possible information scenario so that they can have all the advantages they need once they recall the information for use in their daily work.

FUTURE TRENDS What does all of this do for us as we are moving through the 21st century? The answer is that we are just now trying to research and discover more about how training affects recall and what best methods are needed to ensure we are successful trainers. Successful trainers are those that

become initiators of discovery into finding the best methods for structuring explicit knowledge training materials and presentations. As more and more employees seek better paying and more fulfilling jobs, especially in the United States where employee turn-over rates are high, we must not only learn how to capture knowledge before those employees leave, but we must also learn how to convert that knowledge into useful training materials. With our organizational success being tied up within the minds of our employees we should be motivated to develop better training initiatives and encourage training successes. As more and more organizations enter or expand into the global market the potential for lost knowledge becomes greater. The mobility of the workforce worldwide, in most cases, will increase and the magnitude of losing valuable organizational knowledge is increased. When an employee can move easily between organizations they may take valuable knowledge with them that if not captured is lost to the previous organization. So not only is capture of knowledge critical, once the knowledge is captured it must be made available to incoming or existing employees so

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that the knowledge may be used to continue successful operation of the organization. At some point in the future we will inevitably understand knowledge, knowledge capture, knowledge conversion, and knowledge training much better. We will have hopefully maximized our knowledge management strategies so that we encourage and expect improved employee recall. The economic impact of the $2 trillion dollars spent yearly on training cannot be ignored. With this much money spent on training employees we should be sure we are making the most of the dollars spent. This means that we are not only encouraged, but often mandated by our organizations to spend our training dollars wisely. The results of our conscious efforts to improve employee recall will be noticed when employees are able to make the organization’s performance better due to being able to recall key and important information because of our training practices.

FUTURE RESEARCH Future research conducted formally in academia or in business should seek to discover the best way to train an employee that leads to the best recall capability within that employee. Without recall the employee has only benefited temporarily from the training and the organization cannot be sure they will reap the rewards of the knowledge training. If the employee does not recall what they have learned the organization will not see the results reflected in productivity, profits, or moral. Additionally in the future there needs to be an effort exerted to find out the connections between successful recall, moral, and motivation of the employee. The research must consider all of these factors when looking at recall success or not. If an employee recalls the training well, but it does not provide any benefit to them or to the organization this needs to be discovered quickly

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so that changes can be made to our knowledge training strategies and tactics. Furthermore future research might look at the reasons and causes of employee turnover. These causes or reasons might be eliminated which would improve the longevity of the employee and the time we have available to capture, store, and convert knowledge leading to successful training. When a global market is available for employees to move from one organization to another at will, there will be huge losses of knowledge which benefits no one. Since the knowledge moves with the employee there must be a concerted effort to figure this situation out so that we may learn to reduce knowledge losses due to turnover. Finally we must strive as knowledge trainers to be vigilant and aware of our responsibilities to the organizations we work for and to the employees we train. We should be motivated to improve our training methods when needed and to ensure successful employee recall so that our trainees will truly “recall what they knew”.

CONCLUSION As previously stated, we want our employees to “recall what they knew” and this involved looking at past and present research into employee knowledge recall. We found that this type of research is much more limited than other types of knowledge management research. We emphasized the importance of knowledge recall research and the benefits it brings to an organization. Finally we examined the future research possibilities to seek better understanding of how to improve employee recall. As with any research process there is always room for improvement and this situation is no different. Researchers must be prepared to test many and varied methods and styles of training to be able to draw conclusions and make recommendations to organizational trainers and training managers. The goal of the research is to, at the least, find

Will You Recall What You Knew?

a way to statistically prove that we can improve employee recall after training events. At the most we wish to provide a basis of understanding for trainers and managers that allow them to capture, maintain, and utilize organizational memories. The question asked in this book is: “Building organizational memories: Will you know what you knew?” and the answer is yes we can know what we knew by ensuring that we recall what we have learned. The organizational memories contained within our employees minds must be captured, stored, and then disseminated explicitly to other employees. This ensures that we are maintaining our collective knowledge pool and providing positive organizational outcomes well into the future. Lastly, as we learn more about knowledge and its impact upon our organizations, we will find that we have contributed to the success of our respective organizations when we have trained our employees well. Well trained employees contribute more to the organization and they do this by utilizing what they knew or what they have recalled from all the training they have received. If we can improve recall we can improve our organizations and truly; “Know What We Knew”.

REFEREN Caillies, S., Denhiere, G., & Jhean-Larose, S. (1999). The intermediate effect: Interaction between prior knowledge and text structures. Lawerence Erlbaum Associates. Churcher, P. R. (1989). A common notation for knowledge representation, cognitive models, learning and hypertext. Hypermedia, 1, 235254. Connell, N., Klein, J., & Powell, P. (2003). Its tacit knowledge but not as we know it: Redirecting the search for knowledge. Journal of the Operational Research Society, 140-152.

Droege, S., & Hoobler, J. (2003). Employee turnover and tacit knowledge diffusion: A network perspective. Journal of Managerial Issues, 50-64. Eveland, W. P. (2001). Applying research on the uses and cognitive effects of hypermedia to the study of the World Wide Web. Mahwah, NJ: Erlbaum. Eveland, W., Cortese, J., Park, H., & Dunwoody, S. (2004). How web site organization influences free recall, factual knowledge, and knowledge structure density. Human Communications Research, 30(2), 208-233. Heath, J. (2003). Harvesting and using corporate knowledge. Work Study, 184-189. Herbig, B., & Bussing, A. (2004). The role of explicit and implicit knowledge in work performance. Psychology Science, 408-432. Herschel, R., Nemati, H., & Steiger, D. (2001). Tacit to explicit knowledge conversion: Knowledge exchange protocols. Journal of Knowledge Management, 5(1), 107-116. Jonassen, D. H. (1988). Designing structured hypertext and structuring access to hypertext. Educational Technology, 28(11), 13-16. Kinzie, M. B. (1988). Learner control and achievement in science computer-assisted instruction. Journal of Educational Psychology, 80, 299303. Nonaka, I., & Konno, N. (1998). The concept of “ba”: Building a foundation for knowledge creation. California Management Review, 40-54. Nonaka, I., & Takeuchi, H. (1995). The Knowledge Creating Company: How Japanese Companies Create the Dynamics of Innovation. New York, NY: Oxford University Press, USA. Paye, J. (1996). Organization for Economic Cooperation and Development. The Ecd Observer, 4-6.

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Rogers, E. (1995). Diffusion of Innovations. New York: The Free Press. Westfall, J. (2006). The impact of structure on explicit knowledge recall. Touro University International, Cypress: ProQuest Digital Dissertation Database. Wild, R., Griggs, K., & Downing, T. (2002). A framework for e-learning as a tool for knowledge management. Industrial Management +Data Systems, 371-380.

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Wolfe, M. (2005). Memory for Narrative and Expository Text: Independent Influences of Semantic Associations and Text Organization. Journal of Experimental Psychology Learning, Memory, and Cognition, 31(2), 359-364. Yang, Y. C. (1996-1997). Motivational analyses on the effects of type of instructional control on learning from computer-based instruction. Journal of Educational Technology Systems, 25, 25-35.

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Chapter X

Added Value of Ontologies for Modeling an Organizational Memory Maria de los Angeles Martin National University of La Pampa, Argentina Luis Olsina National University of La Pampa, Argentina

ABSTRACT With the aim to manage and retrieve the organizational knowledge, in the last years numerous proposals of models and tools for knowledge management and knowledge representation have arisen. However, most of them store knowledge in a non-structured or semi-structured way, hindering the semantic and automatic processing of this knowledge. In this chapter the authors specify a case-based organizational memory ontology, which aims at contributing to the design of an organizational memory based on cases so that it can be used to support better decision-making. One ontology goal is to serve as a base for the organizational knowledge exchange with semantic power, which can facilitate the reuse, interoperability, and automatic processing by agents. In addition, the ontology aims to be at a high level from which other more specific representations can be formulated. In order to illustrate its utility a practical case is shown.

IN The organizational knowledge management represents a key asset to support decision-making processes by different organizational stakehold-

ers. The main aim of knowledge management systems is to manage, store and retrieve the organizational knowledge, so that it can be used later to learn, share knowledge, solve problems, and ultimately to support better decision-making

Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Added Value of Ontologies for Modeling an Organizational Memory

processes (Conklin, 1996; Dogson, 1993). Therefore by having a well-developed organizational memory that supports the structuring, reusing and processing of organizational knowledge is a primary decision (and likely a success factor) to achieve such an effective management. Nonaka and Takeuchi have said that an organization cannot create knowledge itself. Conversely, the knowledge creation basis for an organization is the individual’s tacit knowledge; and tacit knowledge is shared through interpersonal interactions (Nonaka & Takeuchi, 1995). In the same direction, Hedberg (1981) has said that an organization does not have brain, but it has cognitive systems and memories. The organizational stakeholders act as the agents of organizational learning, and a link between them and organizational learning systems have to be established. Therefore, in order to reach and maintain the organizational effectiveness and competitiveness, an organization needs to learn from past and present experiences and lessons learnt and to formalize organizational memories for enabling to make explicit the individual’s tacit knowledge -and why not community’s tacit knowledge as well. It is worth mentioning that one of the possible classifications of organizational knowledge can be, namely: public/private, explicit/implicit (or tacit), and formal (syntactically and semantically structured)/informal (unstructured). One of the main goals of an organizational knowledge management strategy is to make explicit the individuals’ implicit knowledge, to try to formalize the informal knowledge in order to allow machine-processable semantic inferences, and to make the knowledge public or private depending on the strategic policy at different organization levels. So far most of the current knowledge management systems capture and store the knowledge in repositories of documents like manuals, memos, and text files systems, and the knowledge transfer is made by means of meetings, courses or by documented manuals and guides. This traditional form of storing and transferring knowledge

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causes loss of time and high investment in human resources, since it does not consider powerful mechanisms of semantic and automatic processing of knowledge. A way of alleviating this problem from the IT-based knowledge representation standpoint is to store the knowledge in a more structured and formal way. We have followed this approach by using the case-based organizational memory strategy. It combines organizational knowledge storage technology with case-based reasoning (CBR) to represent each item of informal knowledge. In general organizational memories are intended to store the partial formal and informal knowledge (Conklin, 1996) present in an organization with automatic processing capabilities. In particular, by structuring an organizational memory in cases can also facilitate the automatic capture, recovery, transfer and reuse of knowledge for problem solving. Although the benefits of applying the knowledge management systems are well known, and the idea of applying case-based reasoning methods to lessons learned and best practices are not new in the knowledge representation area (Weber et al., 2001; Yang & Chen, 2006), there is almost no consensus yet on many of the concepts and terminology used in both knowledge management and case-based reasoning areas. Despite the efforts made in new research developments and international standardization during the last decade, knowledge management is currently in the stage in which terminology are still being defined, consolidated, and agreed upon. In particular, as we know, there is no full-fledged specified ontology on case-based organizational memory. In order to reach this aim we have started to construct a common conceptualization for casebased organizational memory where concepts, attributes and their relationships should be explicitly specified; such an explicit specification of a conceptualization is one of the core steps for building an ontology. In this chapter we argue in general about the added value of ontologies for

Added Value of Ontologies for Modeling an Organizational Memory

modeling organizational memories. Knowledge can be made explicit, shared, formalized, and processed semantically and automatically by machines. As a matter of fact, in the present work we will focus particularly on the specification of a case-based organizational memory ontology and on its benefits for an effective organizational knowledge management. The sources of knowledge for the proposed case-based organizational memory ontology come from an Australian related standard (AS5037, 2005), from recognized research articles in the area (Aamodt & Plaza, 1994; Kemp et al., 2001; Kolodner, 1993; among others), and from meetings among members of our research group in order to reach a consensus for this terminology. In addition, some concepts were taken from the WordNet (WordNet, 2007) ontology. It is worth mentioning that so far there exists no international standard (like ISO –International Standard Organization) in the knowledge management area (Ferguson, 2006). The main contributions of this research can be summarized in the following items: • •

•

The use of the case-based reasoning approach and vocabulary to develop a casebased organizational memory ontology. The integration of the organizational memory and case-based reasoning related concepts by means of a common ontology framework (i.e., a domain ontology, a context ontology, and an organizational memory ontology), which can be useful as conceptual foundation for any organizational knowledge management and knowledge representation systems. Lastly, the discussion about the added value of ontologies for modeling organizational memories. Thus, data, information, and knowledge from heterogeneous and distributed sources can be automatically and semantically processable by web-based applications, for instance, an ‘intelligent’

recommendation system to support a more effective decision-making process. The structure of the rest of this chapter is as follows. The next section thoroughly analyses the case-based organizational memory ontology using the Methontology (Fernandez et al., 1997) steps to building it, and UML (Unified Modeling Language) as an intermediate language for the specification of the conceptualization; in addition some implementation issues are also addressed. To illustrate the main ontology concepts, we then elaborate on a practical example of case-based knowledge base, and its similarity assessment model for an specific domain, viz. for the software measurement and evaluation domain. A discussion about related work in the area is then addressed and finally future trends and concluding remarks are drawn in the last two sections.

Aase-BBASEDORGANIZAIONAL MemOR OONOLOG Let us start this section with these often cited quotes in the ontology engineering and Semantic Web literature: A body of formally represented knowledge is based on a conceptualization … An ontology is an explicit specification of a conceptualization. The term is borrowed from philosophy, where an ontology is a systematic account of Existence. For knowledge-based systems, what “exists” is exactly that which can be represented. (Gruber, 1993, p. 199) An ontology may take a variety of forms, but necessarily it will include a vocabulary of terms, and some specification of their meaning. This includes definitions and an indication of how concepts are inter-related which collectively impose a structure on the domain and constrain the possible interpretations of terms. An ontology is virtually always

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the manifestation of a shared understanding of a domain that is agreed between a number of agents. Such agreement facilitates accurate and effective communication of meaning, which in turn leads to other benefits such as inter-operability, reuse, and sharing. (Uschold, 1998, p. 8) In other authors’ words an ontology is a shared, formal conceptualization of a given domain, which lead to the following two factors with straightforward implications to knowledge management and knowledge representation. First, it is built upon a shared understanding on a given domain within a community; this understanding represents an agreement or consensus of the community (often domain experts) about the concepts, attributes and their relationships. This feature has therefore an individual, social and cultural ground thus implying a human factor. Second, an ontology is a formal conceptualization which entails some kind of computer-understandable knowledge representation for automatic processing and reasoning thus implying a technological factor. These two factors make possible to create the semblance of intelligence in knowledge management applications by incorporating domain knowledge in the form of ontologies. Note that the two factors carry different weights in this respect. While machines can manipulate and reason about domain knowledge based on the ontology, knowing what the symbols and rules stand for remains a human function. Therefore no ontology may exist without a community supporting it”(Mika & Akkermans, 2004, p.14). In addition, they say: the application of ontologies is limited to explicit knowledge. Nevertheless, once we have some kind of knowledge described in an explicit, formal way, we can trust our computers to work with this knowledge. This not only means an increase in the size of the knowledge we can handle, but more importantly gives us the opportunity to use 130

our computer networks (intranets, extranets and the internet) to significantly extend the reach of this knowledge. (p.14) Generally, the main goals were to build ontologies –with direct implications to knowledge representation and knowledge management areas- can be manifold, for instance: to sharing a common understanding and then facilitating the communication among people; to integrating the disparate and heterogeneous representations; to formalizing the representation of a domain problem or theory; ultimately as the basis to supporting semantic reasoning to full-fledged knowledge-based applications, among others. In the sequel we describe the used methodology to construct the case-based organizational memory ontology and the employed steps, as for example the specification step, the conceptualization step, and the implementation step.

The Used Strategy A bunch of methodologies have been published to build ontologies, where different principles, design criteria, and steps for ontology development were reported. One of the well-known methods is the Methontology strategy, which provides guidelines for specifying ontologies at the knowledge level, particularly, how to deal with the specification for conceptualizations. It proposes an effective, generally applicable method for domain knowledge model construction and validation as well. This methodology was developed by Fernandez et al. (1997) and includes a set of stages and strategies, namely: identification of the ontology development process where the main activities are represented (e.g. planning, evaluation, configuration management, integration, documentation, implementation, etc.); a life cycle based on evolving prototypes; and the methodology itself, which specifies at least the following steps: •

Step 1: Specification. The ontology specification’s goal is to put together a document

Added Value of Ontologies for Modeling an Organizational Memory

•

•

•

that covers the ontology primary purpose, level and scope. The aim is to identify the terms to be represented, their characteristics, and their granularity. Step 2: Conceptualization. When most of the knowledge has been adquired, the ontologist has a lot of unstructured knowledge that must be organized. Conceptualisation helps to organize and structure the adquired knowledge using an external representation language that are independent of implementation languages and environments. Specifically, an informally perceived view of a domain into a semiformal specification is organized and structured using a set of intermediate representations (e.g., tables, UML diagrams, or other schemata) that the domain expert and ontologist can understand. Step 3: Implementation. It consists in implementing the conceptual model into a formal language like RDF/S (Resource Description Framework/Schema), or OWL (Ontology Web Language) (W3C, 2002), among others. Step 4: Evaluation. It means to perform a technical judgment of the ontology, its software environment and the documentation with respect to a frame of reference (e.g. the requirements specification document).

For the case-based organizational memory ontology we have employed for the conceptualization step a mixture of tables as suggested by the Methontology strategy and the well-known UML language, which was previously used for this end (Wang & Chan, 2001; Martin & Olsina, 2003).

The Specification Step The proposed ontology specification’s goal is to contribute to the integration of the organizational memory and case-based reasoning related concepts, which can be useful as a conceptual base for any organizational knowledge management system. Specifically, we will integrate the knowledge acquired and stored in a case knowledge base from lessons learnt in measurement and evaluation projects (Olsina et al., 2005) with a recommendation system to support the decisionmaking process. The organizational memory ontology aims to be at a generic level from which other representations for specific domain applications can be formulated (see Figure 1). On one hand, the case-based organizational memory ontology is defined at a generic organizational memory level, and, on the other hand, to characterize the cases according to the specific knowledge domain and

Figure 1. The relationship between ontologies at the specific domain level and at the generic organizational memory level A pos s ible i ns tanc e of Contex t O ntology i s the C-INCA M I C ontex t O ntology

A pos s ible i ns tanc e of Dom ain O ntology is the M etric & Indic ator O ntology

Contex t O ntology

Dom ain O ntology

O rganiz ational M em ory O ntology

Domain Level

Generic OM Level

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its context (Molina & Olsina, 2007), a domain and context ontologies should also be provided. Ultimately, the objective of our ontology is to serve as a foundation for the organizational knowledge exchange with semantic power, which in turn facilitates the reuse, the interoperability and the automatic processing by agents (Fensel, 2003).

The Conceptualization Sep In this section we describe the main concepts of the ontology which are illustrated in the UML diagram of the Figure 2. Notice that in the following text, the main terms are highlighted in italic and defined also in Table 1. An organizational memory is the way in which an organization stores and keeps track of what

Table 1. Case-based organizational memory ontology: Glossary of concepts Concept Name

Description

Case

A case is a contextualised knowledge item representing an experience by means of a problem and its solution.

Case Knowledge Base

A specific knowledge base where each knowledge item is represented through a case.

Complex

A similarity function type that keeps the similarity measure to each pair of possible values of a feature.

Context

The properties that characterize the situation of an entity relevant for a particular information need. Note 1: The situation of an entity is composed of the task, the purpose of that task, and the interaction of the entity with other entities as for that task and purpose. (see the definition of the terms Entity and Information Need in Table 4)

Difference

A similarity function type that is inversely proportional to the difference between a feature values.

Exact

A similarity function type that returns 1 if two feature values are the same and 0 otherwise.

Feature (syno Property, Attribute)

A measurable physical or abstract property of an entity category Note: It is synonym for the attribute term defined in (ISO 14598-1, 1999).

Knowledge Base

An organized body of related knowledge. (AS5037, 2005). Note: Knowledge is a body of understanding and/or lessons learnt from skills and experiences that is constructed by people.

Knowledge Item

An atomic piece of knowledge.

Organisational Memory

The way an organization stores and keeps track of what it knows.

Problem

A state of difficulty that needs to be resolved (WordNet, 2007).

Problem Feature (syno Problem Property, Attribute)

Feature that characterizes a problem.

Result (syno Outcome)

Satisfaction level achieved by the application of a solution to a problem.

Similarity Assessment Model

Algorithm or function with associated similarity elements that models the similarity assessment of cases.

Similarity Criterion

Assessment pattern used to determine the semantic similarities between two feature values.

Similarity Model Element Algorithm or function with associated similarity criterion that models the similarity assessment of a feature. Similarity Type Solution Solution Feature (syno Solution Property, Attribute)

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Specifies the similarity function type, which can be exact, difference or complex. A statement that solves a problem or explains how to solve a problem (WordNet, 2007). Feature that characterizes a solution.

Added Value of Ontologies for Modeling an Organizational Memory

it knows, i.e., about the past, present and future knowledge. An organizational memory can have one or more knowledge bases which are intended to achieve different information needs of an organization –recalling that data, information and

knowledge are useful assets for decision making. In addition, an organizational memory may be seen as a repository that stores and retrieves the whole specified, explicit, formal and informal knowledge present in an organization.

Figure 2. UML diagram that specifies the main terms, attributes and relationships to the Case-based Organizational Memory Ontology. O rganis ationalM em ory nam e c orporationN am e des c ription

K now ledgeB as e na me de s c ript ion 1..* s u bjec tA re a

has 1

includes

1

1..* K now ledgeItem

C as eK now ledgeB as e

1 des c ribes

contains

1

C as e

S im ilarity A s s es s m entM odel

nam e des c ription 1..* author tim eS tam p

as s ociated_with

C ontex t

(fro m C o n te xtO n to l o g y)

1

nam e des c ription

combines

1

s pecified_by 1

1

has _res ult S olution P roblem is _s olved_by nam e nam e 1 0..1 des c ription 1 1..* des c ription 1 caracteriz ed_by 1..*

1

P robl em F eature

(f ro m D o m a in O n to lo g y)

R es ult

0..1 refers _to 1..*

E valuationIns tanc e (fro m IN C A M I)

1..* S olutionF eature

P riority

D om ai nC onc ept

0..1

is _of_type 1

1

S im ilarity Ty pe

1

1.. *

Si m il arit y Mo delE l em ent nam e des c ription w eight upperThres hold low erThres hold compous ed_of

1..* 0.. *

S im ilarity C riterion < < ins tanc eO f> > :E x ac t

F eature nam e value 1..*

:D ifferenc e

:C om plex

firs tV alue s ec o ndV alue s im ilarity

defined_by

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Added Value of Ontologies for Modeling an Organizational Memory

Table 2. Case-based organizational memory ontology: Attribute description Concept

Case

Feature

Knowledge Base

Organisational Memory

Problem Problem feature

Attribute

Description

name

Name of the case to be identified.

description

An unambiguous description of the case.

author

The person, group or agent name responsible for creating a case.

timestamp

Instant when the case is created.

name

Name of the feature to be identified.

value

Numerical o categorical data assigned to the feature.

name

Name of the knowledge base to be identified.

subjectArea

The area to which the related body of knowledge belongs

description

A description of the knowledge base content.

name

Name of the organizational memory to be identified.

corporationName

Name of the corporation which owns the organizational memory.

description

A description of the organizational memory content.

name

Name of the problem to be identified.

description

An unambiguous description of the problem.

priority

Numerical value that model a problem feature priority.

Similarity Assessment name Model description

Similarity Criterion

Similarity Model Element

Solution

Name of the similarity assessment model to be identified. A description of the similarity assessment model meaning.

firstValue

First numerical or categorical data value by which the semantic similarity is compared.

secondValue

Second numerical or categorical data value by which the semantic similarity is compared.

similarity

Numeric data (between 0 and 1) representing the semantic similarity between two feature values.

name

Name of the similarity model element to be identified.

description

An unambiguous description of the similarity model element.

weight

Numerical value that model the relative importance of a feature element in a given similarity assessment model.

upperThreshold

Numerical constant specifying the upper threshold for a given similarity model element.

lowerThreshold

Numerical constant specifying the lower threshold for a given similarity model element.

name

Name of the solution to be identified.

description

An unambiguous description of the solution.

On the other hand, a knowledge base is an organized body of related knowledge, taking into account that knowledge is a body of understanding and/or lessons learnt from skills and experiences that is constructed by people. A type of knowledge base is a case knowledge base which stores the acquired knowledge in past experiences, good

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practices, lessons learnt, heuristics, etc. to different domains; that is, it stores cases. A case is a contextualized knowledge item (i.e., an atomic piece of knowledge) representing an experience by means of a problem and its solution. Looking at the previous statement for an organizational memory is of paramount importance keeping

Added Value of Ontologies for Modeling an Organizational Memory

Table 3. Case-based organizational memory ontology: Relationship description Name

Description

associated_with

One or more cases are associated with one context.

characterised_by

One problem or one solution are characterised by one or more features.

combines

A similarity assessment model combines (associates) one or more similarity model elements.

compounded_of

One or more similarity model elements are compounded of zero or more similarity criteria.

contains

One knowledge base contains many cases.

defined_by

One or more feature are defined by one domain concept in a domain ontology.

describes

One similarity assessment model is defined in order to specify the case structure and the case similarity model. So a similarity assessment model describes a concrete case-based knowledge base.

has

One organizational memory has one or more knowledge base.

has_result

One solution has one or more result dimension

includes

A knowledge base includes one or more knowledge items.

is_of_type

A similarity model element is of one specific type (Exact, Difference or Complex).

is_solved_by

One problem is solved by one or more solutions

refers_to

One or more similarity model elements refer to one or more domain concepts.

specified_by

One case is specified by a specific problem, a solution, and a result.

the context information where each case happens -see for example (Molina & Olsina, 2007) for the modeling of context information. The representation of the knowledge through cases facilitates the reuse of the knowledge acquired in past problems to be applied to a new problem in similar situations (Aamodt & Plaza, 1994). Traditionally, there are several types of methods for representing cases that range from natural language and non-structured representations to completely structured and automatically processable ones (Chen & Wu, 2003). We have chosen the latter strategy, where the meaning of concepts can formally be specified and machine processed by using domain ontologies. A case can be seen as an ordered pair < P, S >, where P is the problem space, and S is the solution space. Because a problem can have several solutions not all with the same result, for a better selection and recommendation of a solution in decision making, it can also be relevant to store the result achieved in the application of a solution to a problem. Notice that any result can be yielded and interpreted by following the WebQEM (Web

Quality Evaluation Method) evaluation methodology (Olsina & Rossi, 2002). There exists a general description of problems as P(x1, x2, ... , xn), where each individual problem is an instance P(a1, a2,..., an); also a general description of solutions as S(y1, y2, ... , yn), and every individual solution S(b1, b2, ... , bn) is an instance of that general description. The xi are variables that characterize the problem (problem feature), and the yi are variables that characterize the solution (solution feature), where both are features. A feature or attribute is a measurable physical or abstract property of an entity category. Since the stored cases refer to a specific knowledge domain, the features that characterize the problems and solutions are defined by a domain concept term; for example, the concepts coming from the metric and indicator domain ontology that intervene in actual measurement and evaluation projects, as we see later on. The case-based reasoning process consists in assigning values to problem variables and finding the adequate instances for solution variables. To find the appropriate values for the instances of a

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Added Value of Ontologies for Modeling an Organizational Memory

solution, the similarity assessment of cases should be performed, so that for each case knowledge base a similarity assessment model should be specified.

Similarity Assessment Model Rpresentation Most of the case-based reasoning applications have been focused on problems of specific domains (Kolodner, 1993). However, in order to be useful to an organization, a case-based reasoning system should be fitted in with the main knowledge sources that can stem from diverse domains, and so the similarity functions appropriate to each case knowledge base. As we can see in Figure 2, each case knowledge base has a similarity assessment model that specifies it. The similarity assessment model class represents, on one hand, the general description of problems as P(x1, x2, ... , xn), i.e. the problem structure, by combining several similarity model elements -one per each problem feature xi. On the other hand, it is a function with associated similarity elements that models the similarity assessment of cases. In turn the similarity model element is a function with associated similarity criterion that models the similarity assessment of a feature. In the following subsection, we propose a model to define the case structure indicating the features that characterize it and the possible similarity models.

Similarity Measurement Usually, the similarity between a recovered case R and a new case C is defined as the sum of the similarities among its constituent feature values multiplied by their weights, i.e. the so-called Nearest Neighbor formula: Similarity (R, C) = Σ wf simf ( fR , fC ) (1) f∈F

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where wf is the weight of the feature f, and simf is the similarity measurement function to the feature. Therefore, in order to provide an appropriate representation of the similarity model, it is necessary to represent the weights that model the relative relevance, and the similarity function type for each specific feature. The weights are represented as an attribute inside each similarity element (see Figure 2), and the similarity type is restricted to be one out of three general types, namely: Exact, Difference and Complex. The inclusion of these three types of functions is based on the analysis of numerous investigation works in the case-based reasoning area (Aamodt & Plaza, 1994; Coyle et al., 2004), as well as taking into account they cover the similarity representation needs of most cases in the Software and Web Engineering area. Particularly: •

•

•

The Exact similarity function returns 1 if two feature values are the same and 0 otherwise. The Difference similarity function is inversely proportional to the difference between a feature values. It can only be applied when it is possible to define the value difference; for instance, between numerical values the difference is the mathematical difference (i.e. the Euclidian distance). The Complex similarity function solves the similarity for all those situations where the two previous functions are not applicable; for example, the semantic difference between two synonymous terms that is neither completely the same nor completely different. If the number of a feature values is finite, it is feasible to have beforehand the similarity measure values for all possible values’ pairs. In our model, these parameters are represented in the Similarity Criterion class, which is defined as the assessment pattern used to determine the semantic similarities between two feature values.

Added Value of Ontologies for Modeling an Organizational Memory

Ultimately, an exhaustive glossary of terms, attributes and relationships are shown in Tables 1, 2 and 3 respectively, where the terminology for the case-based organizational memory ontology is explicitly described. We have used an adaptation of tables proposed by the Methontology method, for instance, we do not show a column of antonyms.

The Iep To make the ontology machine processable it is necessary to implement it in a formal language. For this purpose we have used RDFS and OWL (W3C, 2002) since are the associated languages for ontology implementation with Semantic Web capabilities (Berners-Lee et al., 2001). Figure 3 shows an excerpt of the OWL/XML serialization code, which implements some concepts and relationships of the above ontology. The reader can observe how concepts in the used intermediate language (UML) are mapped into the OWL code.

A PRAI In order to illustrate the above main concepts, attributes and relationships, we will elaborate on an example of case-based knowledge base and its similarity assessment model for an specific domain: the measurement and evaluation domain for software products. This case base stores a body of related knowledge to measurement and evaluation projects so that it serves as the basis to a recommendation system that support the design process of a new project regarding similar past ones. The way in which cases are characterized and evaluated with regard to their similarities depends on a specific application domain; therefore, it is necessary to establish a domain ontology that provides the feature types that characterize to a problem and its solution. In our example, we use the metric and indicator ontology (Olsina &

Martin, 2004) as domain ontology (see Figure 1) employed also in the INCAMI framework.

Wat is INCAMII The INCAMI framework, which stands for Information Need, Concept model, Attribute, Metric and Indicator (Olsina et al., 2005; Olsina et al., 2007) is made up of a set of components and concepts involved in the measurement and evaluation of non-functional requirements to software and web projects, as part of an organization’s quality assurance activities. It is based on the cited ontology which explicitly defines those concepts, and also on the underlying process of the WebQEM methodology (Olsina & Rossi, 2002). The main framework components are, namely: •

•

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The non-functional requirement specification component, which deals with the definition of the Information Need and the specification of requirements by means of one or more Concept Models -see Figure 4. (Note that a concept model can be instantiated in external quality, quality in use models, among many others). The measurement design and execution component, which deals with the specification of concrete entities to be measured, the metrics selection to quantify the attributes of the quality model, and the recording of the gathered measures; this component is centered in the Metric concept. The evaluation design and execution component, which deals with the definition of indicators both elementary and global ones, decision criteria and aggregation models that will help to enact and interpret the selected concept model; this component is centered in the Indicator concept –see (Olsina et. al., 2007) for more details. The recommendation component to be used for the decision-making support.

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Added Value of Ontologies for Modeling an Organizational Memory

Figure 3. An excerpt of the case-based organizational memory ontology implemented in OWL