Tuomi, Ilkka: Corporate Knowledge: Theory and Practice of Intelligent Organization. Helsinki, Metaxis, 1999. 453 p.
This work develops theory of organizational knowing and learning, and shows how the theory can be applied in organizational practice. It integrates theoretical disciplines into a theory of knowledge management, proposes a novel model of organizational knowledge creation, a framework for knowledge management, and a new way to organize for learning and competence utilization.
Part I introduces the topic of knowledge management, describes the research problems, and discusses research methodology for knowledge management.
Part II describes current views on knowledge in organizations, and compares two alternative conceptualizations of knowledge and knowing. The first is the prominent empiristic and positivistic view, here represented by Bertrand Russell. The second is a constructivistic and phenomenological view, introduced through Henri Bergson.
Bergson’s epistemology was based on evolutionary considerations. Lev Vygotsky, in turn, studied the interactions between the three different lines of development: phylogenetic evolution, socio-cultural development, and individual ontogenic development. Vygotsky also described the ways cognition is distributed within social beings and embodied in technologies. Part III introduces Vygotsky’s ideas and, based on these, presents a model of conceptual development.
This thread is elaborated using Maturana and Varela’s theory of Autopoietic Systems, and Niklas Luhmann’s theory of social systems. Part III describes these theoretical approaches and shows how advanced forms of thinking and knowing rest on communication, meaning processing, and the creation of collective meaning. Some conceptual problems of autopoietic theory are discussed and a modified version of the theory is introduced that better adapts to social phenomena. Part III finishes by discussing alternative views on organizations as foci for knowing. The various types of knowledge communities are compared, and a new way to conceptualize organizations, the fractal organization, is introduced.
Part IV develops the foundations for knowledge management practice. A novel typology of knowledge is presented, and the communicative, productive, and activity dimensions of organizations are discussed. Several models of learning are described, focusing on the model proposed by Nonaka, which is analyzed in detail. To address the limitations of extant models, a new model of knowledge creation, the 5-A model, is developed.
Part IV then moves on to describe a practical framework for managing knowledge in organizations. Two dimensions of this framework are studied in detail. First, measurement of knowledge-based organizations is discussed. Second, organizing for knowledge creation and organizational learning is discussed. A novel organizational form that supports innovation and knowledge creation is described. This community-based organizational form is compared with an alternative form proposed by Nonaka and Takeuchi, and practical implications of the different models are discussed.
The work ends with a brief discussion of the results and some suggestions for future research.
Keywords: organizational learning; social learning; knowledge creation; organizational cognition; knowledge management; knowledge measurement; organization theory; social systems; autopoietic systems; activity theory; intelligence
During the several years this book has been in preparation, many people have helped in shaping and reshaping the ideas presented. Only very few people saw the manuscript, but many of its ideas were extensively discussed in conferences, meetings, and over dinner. It is impossible to list all those who contributed to this work. I would, however, like to thank especially John Seely Brown, Andy Burnett, Paul Cole, Kathy Curley, Tom Davenport, Michael Earl, Leif Edvinsson, Omar El-Sawy, Natalie Glance, Kuan-Tsae Huang, Raimo Hämäläinen, Barbara Kivowitz, Sirkka L. Jarvenpaa, Bipin Junnarkar, Esko Kilpi, Georg von Krogh, Marjatta Maula, Reijo Miettinen, Ikujiro Nonaka, Lorne Olfman, Larry Prusak, Nicol Rupolo, Ian Scott, Syed Shariq, Riitta Smeds, Barbara Smith, Karl-Erik Sveiby, Rob van der Spek, Victoria Ward, Jack Whalen, Karl Wiig, Liisa Varjokallio, Liisa Välikangas, and Michael Zack.
During the last two years, I have greatly enjoyed the intensive and highly informative discussions at the European Industrial Research Management Association (EIRMA) working group on Corporate Knowledge Management. My own sub-group focused on the problem of measurement and valuation of knowledge, and I would like to thank John Bailey, Joost Moonen, Mark Shaddick, Mark Young, Andrea Buttle, Stefan Buchholz, Bas Sajik, and Daan van Zanten for their important contributions and feedback. The editorial board provided a great opportunity to test many of the concepts presented in this work in a highly competent group of knowledge management practitioners. I would like to thank Hans König, Kevin Gordon, Peter Kallas, Paul Warren, Ed Damant, Wilfried Koppens, Gill Drage, and Wolf Gehrisch. Some of the ideas presented in the current work were developed in discussions in an earlier working group on Long-Term Planning in a Continuously Changing World. I would like to thank especially Maurice Campagne, Ed Lorch, and Dante Casati for inspiring discussions.
Taina Schakir helped me a lot by pointing out some key theoretical sources, and in locating some difficult to find articles. Yrjö Engeström and Seppo Kontiainen provided invaluable guidance and advise. Antti Hautamäki and Jaakko Virkkunen read the entire manuscript, and their extensive and extremely competent comments played a critical role in the final revision. During the final phase of the project, Teija Löytönen helped me to clarify my thoughts and provided unfailing support when I had difficult times.
Many colleagues at Nokia played an important role by providing ideas, inspiration, guidance, and support. I would especially like to thank Petri Aaltio, Tuomo Alamäki, Kari Alppisara, J.T. Bergqvist, Timo Hannukainen, Tuomo Huhtanen, Visa Huuskonen, Chris Jackson, Hilkka Javanainen, Kaisa Kautto-Koivula, Matti Kilpi, Risto Lehtinen, James Menzies, Salla Myllylä, Kimmo Myllymäki, Harri Männistö, Esa Pylkkänen, Markku Rajaniemi, Petteri Saarinen, Simo Salminen, Ahti Salo, Tytti Varmavuo, Taina Vuorio, Riitta Weiste, and Håkan West. Pertti Lounamaa helped in many ways during the years, and created an inspiring environment for new ideas and solutions. Juhani Kuusi generously arranged funding for the final phase of the project.
I believe that new knowledge emerges most effectively in an intensive dialogue where several minds create a space for new meaning. It is a fascinating process. It is also a great privilege to be part of such a process, and to be able to observe how new ideas are created, transformed, and enriched until suddenly there is the feeling that “now we got it.” I was proud to mentor such a great team. Without the support from the Knowledge Management Group at Nokia Research Center I couldn’t have done it. I am happy to acknowledge my debt to Otso Auterinen, Jaakko Hattula, Jouni Meriluoto, Timo Partanen, and Jukka-Pekka Salmenkaita. With Petri Kasper I probably spent hundreds of hours in developing and formulating the ideas underlying the present work.
Sara Heinämaa read and commented carefully many early drafts that eventually became this book. Her expertise in phenomenology and clear thinking, and unfailing support and friendship helped a lot.
In a turbulent business environment, long-term research requires vision and commitment. I have been lucky to have many visionary leaders as my colleagues. Without the support and encouragement from Mikko Kosonen, however, I believe this work could not have been completed.
I gratefully thank them all, and dedicate this work to my parents, Aira and Paavo Tuomi.
Helsinki, May 1999
Part I: Background... 1
1 Introduction 3
1.1 Outline and Contributions 10
2 Introduction to Knowledge Management 16
2.1 Knowledge management disciplines 21
2.1.1 Organizational intelligence 22
2.1.2 Organizational development 26
2.1.3 Organizational information processing 28
2.1.4 Summary of the knowledge management disciplines 31
3 Research Problems 34
3.1 Failing with Future Watch 34
4 Methodological considerations 45
4.1 Five paradigms of research 46
4.2 Research methodology for knowledge management 58
4.3 Selection of theoretical sources 68
4.4 Validation.. 72
Part II: Toward Knowledge-Intensive Organizations 75
5 Traditional answers: the coming of the information age 77
6 Two epistemologies 87
6.1 Beyond common sense conceptions on knowledge 94
6.1.1 The construction of knowledge 97
Part III: Theory of Intelligent Organizations.................. 105
7 Intelligence and meaning processing systems 107
7.1 Intelligence redefined 114
7.1.1 The emergence of phenomenal worlds 119
7.1.2 Intelligence, knowledge, and competence 121
7.2 Intelligence and instinct: the Bergsonian view 128
7.3 Thought, speech and the development of intelligence 136
7.3.1 Development of conceptual thinking 142
7.4 Autopoietic systems and social coordination 149
7.4.1 Autonomy, autopoiesis, and operational closure 149
7.4.2 Structural determination 151
7.4.3 Ontogeny and structural coupling 153
7.4.4 Social systems, communication, languaging 155
7.5 Meaning processing in social systems 159
7.5.1 Meaning dimensions 165
7.5.2 The emergence of social systems 168
7.5.3 Communication as a three-part process 171
7.5.4 Expectations, reflexivity, and shared worlds 176
7.5.5 Communicative themes and contributions 179
7.5.6 The emergence of media 182
8 Almost autopoietic systems 192
8.1 Generalized autopoietic systems 196
8.1.1 Self-maintaining systems 197
8.1.2 Effective boundaries 200
8.2 Time in higher-order systems 203
8.3 Cognitive and social systems 208
8.3.1 Domains of behavior 215
8.3.2 Summary of self-maintaining social systems 217
9 Organizations and organizational information processing 220
9.1 Organizations as information processors 233
9.2 Organizational cognition 239
9.2.1 Mental models 244
9.3 Organizations as communicative commitments 247
9.4 Organizations as reproduced structures 251
9.5 Organizations as autopoietic systems 256
9.5.1 Structural couplings and organizational adaptation 258
9.6 Organizations as fractal communities 261
9.6.1 Knowledge creation communities 263
9.7 Practical implications of organizational ontologies 276
Part IV: Knowledge Management.................. 283
10 Theoretical constructs for knowledge management 285
10.1 Cognition and the four basic types of knowledge 290
10.2 Knowledge as product, constraint, and competence 294
10.2.1 Reproduction and expansion of social activity 297
10.3 Learning and knowledge creation 301
10.3.1 Process models for learning 306
10.3.2 Social learning 313
10.3.3 Sources of learning 319
10.4 The Nonaka-Takeuchi knowledge creation model 323
10.4.1 Analysis of the Nonaka-Takeuchi model 326
11 A model for organizational knowledge creation 341
11.1 The 5-A model of knowledge generation 341
11.2 Knowledge production at the various levels of analysis 347
11.3 Integrating the 5-A model across units of analysis 352
11.3.1 Cycles of meaning processing within the 5-A model 354
11.4 Knowledge processes at the organizational level 357
12 A framework for knowledge management 365
13 Measurement in the intelligent organization 372
13.1 The value of knowledge 372
13.2 Intangible assets and knowledge capital 377
13.3 Measuring knowledge 384
13.3.1 Types of measurement 387
13.3.2 Measuring knowledge processes 392
14 Organizing for strategic knowledge creation 396
14.1 Team-based communities 398
14.2 Community based core competence development 403
14.2.1 Implications for skill management and organizational design 405
15 Conclusion 411
16 References 419
List of Figures
Figure 1. Disciplines of Knowledge Management................ 33
Figure 2. The basic architecture of Information Refinery.. 37
Figure 3. The basic architecture of Nokia Future Watch..... 41
Figure 4. Intelligence as generator for selective action.... 122
Figure 5. Anderson's minimum cognitive architecture................ 123
Figure 6. Vygotskian model on the development of thinking. 147
Figure 7. Autopoietic unity interacting with its environment............... 154
Figure 8. Structural coupling between to autopoietic units...... 155
Figure 9. Three primary distinctions................ 168
Figure 10. Theme as emergent order in collective cognitive systems. 181
Figure 11. Models of symbolic communication by Vygotsky and Luhmann................ 188
Figure 12. Three improbabilities of communication.......... 190
Figure 13. Hierarchy of self-maintaining systems. 198
Figure 14. Three interaction time-scales................ 205
Figure 15. System types and resulting behaviors................ 210
Figure 16. Higher-order constructs and domains of behavior................ 212
Figure 17. Generative principles and the emergence of cognition................ 214
Figure 18. Three behavioral dimensions................ 216
Figure 19. Basic constructs of activity theory... 231
Figure 20. The structure of activity according to Engeström............... 270
Figure 21. Different types of knowledge creation communities............... 273
Figure 22. Four basic types of knowledge................ 293
Figure 23. Three perspectives on knowledge................ 294
Figure 24. Knowledge between stability and change.. 300
Figure 25. The five types of learning. 304
Figure 26. Organizational learning as correction of system error....... 307
Figure 27. Kolb's learning model.... 308
Figure 28. Learning cycle according to Dewey... 309
Figure 29. Engeström's learning cycle...... 311
Figure 30. Trajectory of learning in a community of practice................ 317
Figure 31. Nonaka-Takeuchi learning cycle...... 325
Figure 32. A reconstructed Nonaka-Takeuchi model.... 331
Figure 33. Three sources of ontogenic knowledge................ 342
Figure 34. The "5-A model" of knowledge generation................ 343
Figure 35. Detail structure of the 5-A model.... 345
Figure 36. Knowledge processes at the different levels of analysis. 351
Figure 37. Interactions between individual and community levels..... 352
Figure 38. Phases of the SECI model within the 5-A model................ 355
Figure 39. Knowledge processes within an organization............... 358
Figure 40. Three dimensions of organizational activity................ 363
Figure 41. Framework dimensions................ 370
Figure 42. Components of the value creation system.. 373
Figure 43. Market and book values of some companies................ 379
Figure 44. Three components of knowledge capital... 381
Figure 45. The components of knowledge capital... 383
Figure 46. Three areas of measurement.............. 388
Figure 47. Three knowledge management strategies................ 390
Figure 48. Some example areas of measurement in the 5-A model.... 394
Figure 49. Levels of engagement and the development of expertise................ 395
Figure 50. Combining the community of practice and team constructs................ 400
Figure 51. Internalization of a competence community................ 404
Figure 52. A community-based hypertext organization............... 408
List of Tables
Table 1. Disciplines of organizational intelligence.................. 25
Table 2. Disciplines of organizational development................ 27
Table 3. Disciplines of organizational information processing.................. 30
Table 4. Levels of articulation of knowledge................ 100
Table 5. Four common perspectives on organizations............. 224
Table 6. Traditional foci in organization studies.. 225
Table 7. Seven characteristics of sensemaking............. 243
Table 8. Levels of analysis and bounded and open units...... 261
Table 9. Definitions of cognition, knowledge, and intelligence................ 291
Table 10. Levels of activity and types of knowledge constraints................ 297
Table 11. Modes, sources and processes of ontogenic learning. 322
Table 12. Two complementary perspectives on organization............... 361
Table 13. Interpretation of the framework dimensions................ 371
Table 14. Reasons to measure knowledge (EIRMA, 1999)...... 385
Table 15. Three types of measurement.............. 391
Table 16. Possible standard community types in an organization............... 402
Future historians will certainly look back to the end of the 20th century as an era of information. This was the time when information was everywhere. It made machines and people work; it permeated everyday life, redefined industries and transformed societies. It propagated in nanometer-wide wires, electromagnetic fields, and in all media. Everything was becoming dependent on information and everyone thought that, somehow, information is important.
The point of view of future sociologists and historians of knowledge may, however, be quite different from the one adopted by their historical subjects. They may wonder, for example, why so many people were so exited about the idea of information. Why so few critical discussions on the nature of information were to be found? Why was it that almost everyone seemed to agree that information is important, that we need it, and that more of it is better?
One of the possible explanations could be, of course, that just because information was such a general concept, it become a symbol, a central concept in the 20th century world-view, carrying with it many of the ideological overtones from enlightenment, belief in technological and scientific progress, and echoes of 19th century philosophical discourse.
Indeed, I have argued elsewhere that the theoretical work of such information technology pioneers as Turing, Shannon and Weaver, Wiener, von Neumann and others did not launch the information age (Heinämaa & Tuomi, 1989). On the contrary, those researchers crystallized the prevailing expectations of well-educated 20th century common sense. Most importantly, they combined theoretically fascinating formulations with practical applications, showing how theory can make a difference.
Common sense, however, is continuously being checked by reality. Suddenly, one of the major questions in the information society is how we can avoid information. Only when the dream of perfect information becomes true, we start to realize that this was a more complicated matter. It becomes possible to ask why do we need information, what kind of information we need, and what this information actually is supposed to be.
A common answer to these questions has been that information is not enough. Instead, information has to be transformed into knowledge. Yet a question remains. Why do we need knowledge, what kind of knowledge we need, and what is this knowledge, after all?
Knowledge management is a new area of research and as such it necessarily is interdisciplinary. But it is interdisciplinary on a more fundamental level, as well. It deals with questions that have been addressed in research on business strategy, organization theory and information systems. But, as is claimed in the present work, it also needs to revisit basic concepts of cognitive science, epistemology and systems theory. Indeed, I shall claim that many common conceptions on managerial work, organizational design, and the role of information and knowledge in organizations are misleading. Without better conceptual foundations, the information and knowledge management systems we build will be of limited use.
Once again, we need to go beyond appearances, to search for the essences. If knowledge and information would remain as obvious as they were commonly understood to be in the 1990’s, we could build a science of knowledge management on common sense. But, first, we should look where we stand. What do we understand of the limitations and problems of common sense concepts of information and knowledge, and do these limitations have practical implications in everyday organizational life? If knowledge is power, when does such power stifle organizational innovation and change? If knowledge makes simple truths complex, when will it help organizations survive? Indeed, what is the role of knowledge in intelligent action?
In organization and management science it has been a sign of good taste to make a note on the misleading nature of anthropomorphic analogies. When researchers talk about “organizational memory” or “organizational cognition” they are quick to point out that, of course, organizations don’t have memory or cognition in the same sense as humans do. The early literature on organizations and management used such analogies quite freely, making workers the hands and managers the rational brain of the firm. The analogy was misleading. However, sometimes it seems that the critique on this analogy is misplaced. Indeed, I shall argue that researchers often have been too quick in pointing out that organizations don’t have real memory, sensemaking capability and intelligence, and that, of course, human beings are the unique hosts of these cognitive faculties.
I will argue that if we consider organizations as collective entities where autonomous knowledgeable agents coordinate their activities, we can find interesting similarities in intelligence as manifested in animals and humans, and in the intelligence of collective systems. Indeed, I will claim that when we better understand what intelligence and cognitive faculties are, it becomes clear that organizations can be intelligent. When we understand the nature of intelligence better, it also becomes possible to intentionally create organizational structures and processes that increase organizational intelligence. This, to me, is the main challenge of knowledge management.
My ultimate goal is practical and simple: how to conceptualize knowledge in an organization so that it can be managed and mobilized well. It is clear that we have a long history of conceptual discussions about the nature of knowledge. Similarly, we have many assumptions and beliefs about intelligence, organizations, and knowledge work. It should be understood right at the start that the road I shall travel is not a familiar one, and not as short as one would expect. In my navigation I rely on cartographers who have tried to map some of the most difficult terrains of thought, and some of my guides are notoriously difficult to follow. At times, it may feel that in their worlds nothing is as it should be; that their flora and fauna has never been seen before, and that, indeed, dragons wait for the unwary step.
I wouldn’t have gone there, either, were it not important, useful, and, in my opinion, necessary.
My goal is inherently multi-disciplinary. To get there, I shall combine conceptual analysis of biological intelligence, studies of learning and language acquisition, theories of social systems and organizations, and practical proposals for organizational and information system development. I hope I have been able to avoid unnecessary side-tracks, at the same time providing sufficient background so that the text is accessible on its own. This, however, means that to fully grasp the practical ideas of managing knowledge that are presented at the latter parts of the book, the reader probably has to be willing to go through some of the rather theoretical and conceptual parts at the beginning of the book.
The present work combines some threads that run through my earlier work. As a young student of theoretical physics in the late 1970’s, my main area of interest was the emerging science of complex non-equilibrium systems. This was the time when theoretical physics started to have a major impact on our understanding on self-organizing phenomena and biological systems. This lead me to study the emergence of living systems, and later, physics of cognition and of nervous systems. As computers became increasingly sophisticated and available, the natural drift took me to the areas of computational cognition and artificial intelligence.
Just below its obviously technical surface, artificial intelligence is a very philosophy-intensive domain of inquiry. It implements some of the most fundamental assumptions of the nature of knowledge, perception and thinking. Indeed, it implements many philosophical and common sense beliefs about what it is to know and what it is to be a thinking being.
As has been pointed out almost since the birth of the discipline of artificial intelligence, there are alternative ways to understand the questions of cognition, knowledge and intelligent action. Until very recently, these alternative views have been little understood, and somewhat esoteric in the Anglo-American mainstream thought. Indeed, even today some of the most interesting literature on cognition is almost totally unknown to majority of researchers in artificial intelligence and cognitive science. For example, critical conceptual work such as Bergson’s Matière et Mémoire, Merleau-Ponty’s Phénoménologie de la perception, Rosen’s Anticipatory Systems, and Maturana’s and Varela’s discussions on autopoietic systems have rarely been referenced.
When developing knowledge-based expert systems, I found such philosophical and conceptual discussions quite illuminating and useful. Instead of the original goal of artificial intelligence, the creation of autonomous intelligent machines, it seemed that knowledge-based systems could be used to augment human intelligence. Although there are both theoretical and practical reasons why human intelligence can not be programmed in digital machines (c.f. Tuomi, 1988; Heinämaa & Tuomi, 1989), it seemed possible that digital computers can be used to help humans in their cognitive tasks. One practical area where such use of computers had a potentially high impact, was that of strategic management of complex organizations. Instead of developing computer systems that would make optimal decisions, computers could be used to develop conceptual models that would make it easier for top management to make sense of their business alternatives. Indeed, following the lead given by Rosen, I claimed that it could be possible to increase organizational anticipatory capability by using object-oriented organizational modeling and software that supports such modeling (Tuomi, 1992a). In practice, I was involved in implementing several such strategic planning models, as well as a generic tool for computer supported strategic planning. This tool, Stratex, was developed at the Nokia Research Center. Although commercialization of Stratex never really succeeded due to a change in Nokia’s business focus, it had some interesting capabilities that made it possible to test novel strategic planning concepts.
The present work goes one step further on this line. If individual human intelligence can be supported using information systems, the natural question is how could we use technology to increase the intelligence of organizations. This leads to a study of collective aspects of intelligence. The traditional goal of artificial intelligence research was to build rational decision-making machines that would make intelligent choices. If we start from a system, an organization, that already has intelligent humans as its components, the role of computers can be different, however. Instead of being calculation or inference machines, computers become a medium of communication and coordination. We may then ask how computers and communication networks change individual abilities to perceive and make sense of the environment, and how computer-mediated communication technologies can be used to improve organizational cognition and intelligence.
During the time that this book has been in preparation, management of corporate knowledge has become one of the hot topics in several areas of organizational studies, information systems, human resource development, and strategy. My guess has been that much of this hype goes away after we begin to have a reasonably sophisticated understanding of the domain of knowledge management. I think we have to go further in two areas, simultaneously: develop theory that lies on a reasonably robust foundation, and develop practices that can have real impact on real organizations. I will address both these issues.
Often, it appears as if the underlying motive in management literature would be simplification until thinking is replaced with few practical steps to whatever heaven there at that point of time happens to be. In my view, we should be able to require that effective managers are not only fast “decision-makers” and actors, but that their decisions and actions are based on high-quality thinking. I believe that visionary managers have always been philosophers, and that they will be even more so in the knowledge based economy.
As Einstein put it, we should make things as simple as possible, but not simpler. In a study like this, we don’t know in advance what those concepts will be that make organizational knowledge and intelligence appear simple and easily managed. Many of those concepts that we though were obvious are shown to problematic and difficult in this work. Therefore, I assume that it may take some time to assimilate some of the ideas discussed in this book. This, of course, depends on the reader’s background. But as the present work tries to combine several relatively little-known and more or less separately developed lines of thought, I think there will be not very many readers who are well familiar with all of them. Instead of being a book that puts in well-formed slogans something that the reader already has thought and recognized as important, this book tries to provide a novel view to organizations, knowledge, and knowledge management.
All our practical activity and thinking rests on implicit or explicit theory. All our theories, in turn, rest on conceptual foundations that implicitly or explicitly structure our experience into constructs that form the building blocks of our world. It is rather exceptional that we have to change our theories, and even more exceptional that we have to change our common sense philosophies. Most of the time world is what we expect it to be, and we can go on with our practice, relying on our assumptions, concepts, and models.
In knowledge management, I don’t believe this to be the case. We can not just keep on doing what we used to do. Neither can we hold on to our implicit and explicit theories about organizations, information, and knowledge. This means that we have to reconsider those conceptual starting points that underlie our current theories. Indeed, we have to sit back, think, and try to find better ways forward.
In what follows, I shall try to rewrite some of the most prominent theories underlying the current discussions on organizational learning, organizational information processing, and knowledge management. As a result, I propose, for example, new ways to organize work in knowledge intensive organizations, new views on organizational competencies and competence based strategies, and new tools to support knowledge generation.
I shall argue that one problem with many discussions on “knowledge sharing” and “knowledge dissemination” is that they are based on models that dissect intelligent cognitive agents into two unrelated roles: the knowledgeable “source” and the “receiver,” who is the subject that learns. In most cases, the problem of knowledge dissemination, in its conventional form, arises as a result of an overly individualistic focus on knowledge and learning. This individualistic focus neglects the social and collective nature of knowledge and learning, and therefore becomes inadequate when we try to understand organizational learning. What we need, instead, is a unified model of knowledge generation where the cognitive units engaged in learning are not two of a different kind, but where these artificially separated roles are explicitly related.
Another reason for research on organizational learning to conceptualize its subject as a problem of dissemination, diffusion, and sharing of knowledge has been that most extant models on learning do not sufficiently separate two different levels of analysis: an individual cognitive system, and a collective system that comprises such cognitive units as its elements. I shall argue that—although dissemination and diffusion are relevant when knowledge is articulated as a product—in most cases these constructs are based on a fundamentally misleading interpretation of the process of knowledge generation and the units of analysis involved in organizational knowledge generation. I also develop and present a new model of knowledge generation that addresses these problems.
This work tries to answer the following question: how can we make organizations more effective users and producers of knowledge? As knowledge underlies all organizational activity, the answer to this question is not straightforward. Indeed, we have to rethink what an organization is, what is knowledge, and how knowing relates to effective action. My answer will be that, yes, we can make organizations more effective in their use of knowledge. This may look a rather obvious result. In the process of answering the question, however, I shall show that we have to reconsider those very basic conceptual foundations which make the answer look obvious, and that this reconceptualization has important practical implications.
The goal of this work is to create understanding of the role of knowledge in organizations, so that we could understand how knowledge-intensive organizations should be managed. I shall try to make more clear what knowledge is and what it does in organized activity. If parts of the present work appear complex and theoretical, it is not because the ideas presented would be exceedingly complex, but because we usually have to do only minor corrections to our way of thinking when we try to understand something new. Sometimes, however, we have to organize our thinking from a new point of view, in a process where old concepts acquire new meaning, and where old answers seem to call for new questions. This process we could call learning. It is easy when we make minor additions to our existing conceptual structures, but it is difficult when we have to re-organize key elements in this structure.
I shall define intelligence below as a process that creates effective action. Therefore my research problem can be restated as the question how can we make organizations more intelligent. I shall show that there is a novel way of seeing this question that is coherent, theoretically justified, and which leads to interesting theoretical and practical consequences.
The present work is a combination of theory construction and theory-based proposals for practical management of knowledge-intensive organizations. From a methodological point of view, this work creates new theory by synthesizing several theoretical traditions within a practical domain of application. I shall discuss the methodology in more detail in a subsequent chapter. At this point we may simply note that the criterion for the success of the method is whether it leads to novel insights, understanding, and interventions.
The contributions of this work are, roughly, as follows. First, Part I introduces the topic of knowledge management. There are several different disciplines and research traditions that have tried to address those problems that are currently becoming the focus of knowledge management. I shall describe these, and introduce the research problems by describing an attempt to develop world-class knowledge management systems and processes in Nokia. This section also summarizes some of my own experiences on what knowledge management is and what it is not.
As this is an interdisciplinary and conceptual work, it is important to clarify the methodological assumptions that underlie it. In Part I, I shall describe five different research paradigms. In the process, I propose that we can overcome some of the problems of phenomenology and radical constructivist epistemology by combining these with the theory of activity. I shall also point out that research on knowledge management needs to be located by analyzing the relation between theory, research, and practice. Knowledge management, as a socio-practical field of inquiry, therefore shares many characteristics with adult education.
After these preparations, Part II provides some relevant background and motivation for a new conceptualization of knowledge, intelligence and organizations. Part II is intended to clarify the starting point for the further development. It describes a new classification of levels of knowledge articulation. The current discussion in knowledge management has emphasized that much organizational knowledge is tacit. I shall show that there are several different types of tacit and articulated knowledge.
Part III develops theory of intelligent organizations. This involves two threads: theory of intelligence, and theory of organizations. In discussing the nature of intelligence, I shall combine several relevant areas of study. First, I shall present some extant views on intelligence and show that they need revision. I shall approach the revised view introducing some ideas that can be characterized as biological phenomenology. After these preparations, I move on to discuss the social and mediated character of cognition using the theory of cognitive development by Lev Vygotsky. Then I discuss the nature of living systems using the autopoietic systems theory of Humberto Maturana and Francisco Varela. At this point, I simply introduce the main constructs of autopoietic theory. After this we have three complementary views on intelligence; one of intelligent biological behavior, another that emphasizes intelligence as a product of historical and individual development, and a third one from systems perspective. I shall then proceed to discuss in more detail collective meaning processing using Luhmann’s theory of social systems. With these theoretical foundations, I discuss the nature of intelligence, knowledge, communication, meaning processing, and learning.
Although the theory of autopoietic systems is one of the most carefully developed and interesting accounts on the nature of cognition and living systems, it has some fundamental limitations. I shall present these, and extend the theory of autopoietic systems so that it can better be used in social and organizational contexts. From the point of view of autopoietic theory, this represents major rewriting of the theory, and it also provides novel conceptualizations on cognitive systems and cognitive processes.
I shall then introduce some prominent contemporary views on organizations and organizational information processing. Most important, I shall argue that the extant views are inadequate, and unable to address important practical and theoretical questions concerning organizational knowledge generation and organizational learning. I shall show that the information processing view on organizations can be extended in five different but compatible ways: by viewing organizations as systems of collective sensemaking, as networks of communicative commitments, as social systems within Giddens’ theory of structuration, using the concept of structural coupling from the theory of autopoietic systems, and, finally, as communities of communities. The last view is closely related to Brown and Duguid’s (1991) proposal of viewing organizations as communities of practice, but it is presented here within a more developed conceptual framework. I describe several alternative conceptualizations of the idea of community of practice, and show how Nonaka’s concept of ba may be understood as a specific type of thought community.
In summary, Part III argues that by looking organizations as intelligent developing social systems, we can have a better conceptual view on organizations than the traditional views could provide, as they typically focused on the division of labor, or decision-making and information processing. Most important, this new conceptualization has direct implications for the management of organizational learning and knowledge, and it can also be used to create design requirements for information systems that support intelligent organizations. I shall use these conceptualizations extensively in the subsequent parts of the book.
In Part III, I also make a short digression to a topic of major relevance for organizational theory and strategic management: that of organizational adaptation and fit. Within the theoretical framework presented in the previous sections, the concept of organizational fit is shown to be conceptually unfounded, and in some practical cases also misleading.
Whereas Part III is theoretical in the sense of developing constructs needed to understand intelligence in organizations, Part IV focuses on developing a practical framework for knowledge management. To do this, however, it makes some major theoretical contributions, for example, by developing a typology of organizational knowledge, and by introducing a novel model of knowledge generation.
One of the practically most interesting areas of knowledge management is that which relates to innovation and knowledge creation in organizations. Part IV therefore describes current views on organizational learning and knowledge creation. Using the presented constructs it analyzes one of the most prominent conceptual frameworks of knowledge creation, developed by Nonaka and Takeuchi (1995). As a result of this analysis, I suggest that this state-of-the-art model could be augmented by considering in more detail the collective and extended aspects of cognition, the nature of communication and meaning processing, the various types of knowledge presented in the course of this work, the units of analysis that form the basis of organizational knowledge generation, and the processes of learning and ontogenic development. I shall do this, and propose an alternative model of knowledge creation that I shall call “the 5-A model.”
Part IV then formulates a practical framework for knowledge management. The view here will be that of implementation of the above developed concepts in practical organizational settings.
Based on the framework developed, two areas of knowledge management will be elaborated: those of measuring and organizing knowledge work. I shall discuss some theory on valuation of knowledge and knowledge-related processes, and present some practical suggestions for implementing knowledge measurement systems in organizations. In discussing the ways to organize knowledge work, I shall specifically address the problem of combining strategic development of organizational core-competences with knowledge management. Indeed, I shall show that the extant views on core competencies can be conceptualized in new ways that make their development and management possible in practice. I shall also propose new ways to organize knowledge-based organizations. To show that the theory developed in the course of this work has practical implications, I briefly outline its implications for competence management. I also show how the ”hypertext” organizational model proposed by Nonaka and Takeuchi can be re-interpreted in the developed theoretical context.
It is obvious that no single individual can adequately master all those areas of study that will be touched in the course of this work. I am well aware of several important contributions that would add considerable substance to my argument and probably even change some of its conclusions. I also know that there are many important contributions that I am not aware of. On the other hand, I see this work as one contribution among a vast body of scientific literature; not a final word, of course, but hopefully giving some indications on where research and practice could be going.
I do, however, believe that a relatively bold approach to the problems of organizational knowledge is useful to uncover some relevant issues for research and practice on organizational intelligence. During the last eleven years, I have been lucky to be able to test and develop many of the ideas presented in real organizational settings in Nokia Research Center, and in the various business units of Nokia. I have gained a lot from the extremely fruitful opportunity to live in the midst of every-day business challenges, and access to brilliant executives and many world-class researchers. I know that such an opportunity is quite unique, and this position is certainly one of the reasons why I have tried to maintain a rather bold attitude. In Nokia I have learned that there is a very simple heuristic rule for the generation of new knowledge: fail faster and more systematically than your competition. Only if the attempt is bold enough, there is opportunity for substantial learning.
Finally, a stylistic comment. There are great differences in the various traditions of scientific literature, and, for example, the European and American ways of writing also have some conventions that differ. In general, it seems to me that the European style tends to emphasize historical and conceptual roots of ideas whereas the American way of writing often emphasizes novelty of ideas and empirical methods. My stylistic goal has been to make the text accessible and emphasize the points that I make. Sometimes this means that I contrast my points with those presented by other current authors. As the main argument of this book should make clear, I believe that culture and science are collective enterprises where individual contributions play a major role. I have great respect for all those who engage in this enterprise, to the extent that I often forget to mention it separately.
 References to Bergson and Rosen have been almost non-existent. Merleau-Ponty appears in Dreyfus (1979), and mainly indirectly through Maturana and Varela in Winograd and Flores (1986).
 Some of these concepts were presented in international conferences (Tuomi, 1991; 1992b; 1992c; 1993c; 1993a; 1993b; 1995; Paajanen & Tuomi, 1992). Stratex also received an award for “the outstanding new product of 1991,” when it was demonstrated at the DSS ‘91 conference at Manhattan Beach, California. The orginal concept of Stratex was based on (Bergqvist, 1987).