Measuring knowledge management in the business sector 1 steps

MEASURING KNOWLEDGE MANAGEMENT IN THE BUSINESS SECTOR – ISBN 92-64-10026-1 – © OECD/MINISTER OF INDUSTRY, CANADA, 2003 3 Foreword At the start of the 21st century, there is a recognition

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Knowledge Management

Measuring Knowledge Management

in the Business Sector FIRST STEPS

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Knowledge management involves any activity related to the capture, use and sharing ofknowledge by an organisation Evidence shows that these practices are being used moreand more frequently and that their impact on innovation and other aspects of corporateperformance is far from negligible Today, there is a recognition of the need to understandand to measure the activity of knowledge management so that organisations can be moreefficient and governments can develop policies to promote these benefits

This book offers a synthetic view of the results of the first systematic international survey

on knowledge management carried out by national statistical offices in Canada, Denmark,France and Germany

Co-published with Statistics Canada

Visit www.statcan.ca for more information about Statistics Canada.

Knowledge Management Measuring Knowledge Management

in the Business Sector FIRST STEPS

ISBN 92-64-10026-1

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ORGANISATION FOR ECONOMIC CO-OPERATION AND DEVELOPMENT

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ORGANISATION FOR ECONOMIC CO-OPERATION AND DEVELOPMENT

Pursuant to Article 1 of the Convention signed in Paris on 14th December 1960, and whichcame into force on 30th September 1961, the Organisation for Economic Co-operation andDevelopment (OECD) shall promote policies designed:

– to achieve the highest sustainable economic growth and employment and a rising standard

of living in member countries, while maintaining financial stability, and thus to contribute

to the development of the world economy;

– to contribute to sound economic expansion in member as well as non-member countries inthe process of economic development; and

– to contribute to the expansion of world trade on a multilateral, non-discriminatory basis inaccordance with international obligations

The original member countries of the OECD are Austria, Belgium, Canada, Denmark, France,Germany, Greece, Iceland, Ireland, Italy, Luxembourg, the Netherlands, Norway, Portugal, Spain,Sweden, Switzerland, Turkey, the United Kingdom and the United States The following countriesbecame members subsequently through accession at the dates indicated hereafter: Japan(28th April 1964), Finland (28th January 1969), Australia (7th June 1971), New Zealand(29th May 1973), Mexico (18th May 1994), the Czech Republic (21st December 1995), Hungary (7thMay 1996), Poland (22nd November 1996), Korea (12th December 1996) and the Slovak Republic (14thDecember 2000) The Commission of the European Communities takes part in the work of theOECD (Article 13 of the OECD Convention)

STATISTICS CANADA

Statistics Canada, Canada's central statistical agency, has the mandate to "collect, compile,analyse, and publish statistical information relating to the commercial, industrial, financial, social,economic and general activities and condition of the people of Canada." The organisation, a federalgovernment agency, is headed by the Chief Statistician of Canada and reports to Parliament through theMinister of Industry

Statistics Canada provides information to governments at every level and is a source of statisticalinformation for business, labour, academic and social institutions, professional associations, theinternational statistical community, and the general public This information is produced at thenational and provincial levels and, in some cases, for major population centres and other sub-provincial

or "small" areas

The Agency fosters relations not only within Canada but also throughout the world, byparticipating in a number of international meetings and professional exchanges Statistics Canadaconducted the pilot survey on Knowledge Management Practices as part of an international initiativeheaded by the Centre for Educational Research and Innovation (Organisation for EconomicCo-operation and Development) Canada was the lead country piloting the survey Other countries that

in 2001 undertook pilot surveys or questions based on the contents of the Knowledge ManagementPractices' questionnaire were Denmark, Germany and France

Publié en français sous le titre :

Mesurer la gestion des connaissances dans le secteur commercial : premiers résultats

© Organisation for Economic Cooperation and Development (OECD), Paris and Minister of Industry, Canada, 2003 Permission to reproduce a portion of this work for non-commercial purposes or classroom use should be obtained through the Centre français d’exploitation du droit de copie (CFC), 20, rue des Grands-Augustins, 75006 Paris, France, tel (33-1) 44 07 47 70,

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MEASURING KNOWLEDGE MANAGEMENT IN THE BUSINESS SECTOR – ISBN 92-64-10026-1 – © OECD/MINISTER OF INDUSTRY, CANADA, 2003 3

Foreword

At the start of the 21st century, there is a recognition of the need to understand and

to measure the activity of knowledge management (KM) so that organisations, and systems of organisations, can do what they do better and so that governments can develop policies to promote these benefits Facing such new emerging practices, economists, management scientists and statisticians have not yet much systematic evidence Among the various categories of knowledge-related investments (education, training, software, R&D, etc.), KM is one of the less known, both from a quantitative and qualitative point of view, as well as in terms of costs and economic returns Thus, there is certainly a need to know more on this new knowledge-based activities; on the current state of KM as an organisational process within various kinds of companies and sectors; on the variety of methods and tools that are developed; and on the economic effects of KM practices that are actually observed.

To achieve those objectives, the Center for Educational Research and Innovation (OECD) and Statistics Canada have set up a working group comprising representatives from the statistical offices of Canada, France, Italy, the Netherlands and Sweden and representatives from research bodies in Australia, Denmark, Germany and Ireland The working group has met four times since February 2001, in Copenhagen, Ottawa, Paris and Karlsruhe A questionnaire was devised during the course of the four meetings and the information deriving from the first pilot studies was discussed.

This questionnaire includes a survey on the use of 23 KM practices and is complemented with questions on incentives for using KM practices, results, responsibilities, etc The questionnaire includes many informal management practices

in order to accommodate how micro-firms are managing knowledge

For countries willing to carry out their own national surveys, two kinds of strategies were possible: either implementing the whole survey as a pilot study or lodging few questions on KM in an existing and regular questionnaire, such as the Community Innovation Survey While the first option gives the opportunity to really test the KM questionnaire and to collect information related to a large range of issues and problems, the second option has proven to be very useful for countries where starting a new survey is a difficult task for administrative, political or technical reasons.

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This book presents a synthetic view of the results of the surveys carried out in Canada, Denmark, France and Germany, as well as statistical analysis about various issues dealing with KM and a policy discussion.

This foreword cannot be closed without stressing the extent to which producing this book has itself been a successful experiment in knowledge management Especially involved were two teams that were geographically very far apart: the OECD team (D Foray, K Larsen, S Vincent-Lancrin) and the Statistics Canada team (M Bordt,

L Earl and F Gault) The teams built up an impetus which was greatly aided by

E Kremp, S Lhuillery and J Mairesse (France), J Edler and F Meyer-Krahmer (Germany), W Strømsnes (Denmark), C Noonan (Ireland), G Perani (Italy), S Nousala (Australia), S Pronk (Netherlands), L Prusak (United States), J Morgan and P Quintas (United Kingdom) and A Sundström (Sweden) All of them deserve thanks.

The book is published on the responsibility of the Secretary-General of the OECD.

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TABLE OF CONTENTS

Table of Contents

Part I

Frameworks

Chapter 1. Measurement of Knowledge Management Practices

Dominique Foray and Fred Gault 11

1.1 Introduction 12

1.2 Knowledge Management: What is New? 13

1.3 Knowledge Management as a Topic for Empirical Studies: Opening another Black Box 16

1.4 From Good Case Studies to Systematic Surveys 18

1.5 Why, How and So What? 19

1.6 Knowledge Management Surveys 21

1.7 Three Main Tasks of a Knowledge Management Survey 22

1.8 A Brief History of the OECD-Statistics Canada Project and a First Look at the Results 23

1.9 Outline of the Book 24

Bibliography 26

Chapter 2. Managing Knowledge in Practice Paul Quintas 29

2.1 Introduction 30

2.2 Key Knowledge Processes 34

2.3 Getting Knowledge Management Started 35

2.4 Limits and Potentials of Technological Solutions 36

2.5 Knowledge Capture 38

2.6 Knowledge Sharing 40

2.7 Auditing and Exploiting Intellectual Capital 42

2.8 Cross-boundary Knowledge Acquisition and Integration 44

2.9 Conclusions 48

Bibliography 50

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TABLE OF CONTENTS

Part II

Country Reports

Chapter 3. Are we Managing our Knowledge?

The Canadian Experience

Louise Earl 55

3.1 Highlights 56

3.2 Introduction 57

3.3 Survey Background/Overview 57

3.4 Definition of Knowledge Management 58

3.5 Knowledge Management Practices in Use 59

3.6 Reasons Why Knowledge Management Practices Were Adopted 64

3.7 Knowledge Management Practices Most Effective for Improving Workers’ Skills and Knowledge 67

3.8 One Quarter of Firms Had Dedicated Budgets for Knowledge Management 69

3.9 Knowledge Management – Important Business Practices 72

Annexes 76

Bibliography 85

Chapter 4. The Management of Knowledge in German Industry Jakob Edler 89

4.1 Introduction: Filling Knowledge Gaps on Industrial Knowledge Management in Germany 90

4.2 Methodology: The Sample 92

4.3 The Employment of KM Practices in German Industry 94

4.4 What Kind of KM Practices 95

4.5 The Driving Forces of Knowledge Management: Motivation Patterns in German Industry 98

4.6 Effects of Knowledge Management 104

4.7 The Institutionalisation of KM and its Meaning for the Use of Knowledge Management 108

4.8 Knowledge Management and its Role within Innovation Management 109

4.9 Concluding Summary: Only First Steps towards Filled Gaps 112

Annexes 116

Bibliography 118

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TABLE OF CONTENTS

Chapter 5. The Promotion and Implementation of Knowledge

Management – A Danish Contribution

Anja Baastrup and Wenche Strømsnes 119

5.1 Introduction 120

5.2 Some Overall Results 121

5.3 Measuring, Controlling and Documenting Effectiveness 125

5.4 Inspiration for Top Managers – Content and Process 127

5.5 What can Top Management Expect from the Environment? 130

5.6 Further Research 131

Annexes 134

Bibliography 141

Chapter 6. Knowledge Management, Innovation and Productivity: A Firm Level Exploration Based on French Manufacturing CIS3 Data Elizabeth Kremp and Jacques Mairesse 143

6.2 Diffusion of Knowledge Management 146

6.3 Complementarity of Knowledge Management Practices 151

6.4 Knowledge Management and Innovation 152

6.5 Knowledge Management and Productivity 159

6.6 Conclusion 161

Annex 164

Bibliography 168

Chapter 7. Knowledge Management: Size Matters Louise Earl and Fred Gault 169

7.2 Practices 172

7.3 Reasons for Using KM Practices 174

7.4 Results of Using KM Practices 176

7.5 Incentives to Use KM 177

7.6 Moving from Micro to Large 178

7.7 Intensity of KM Use 178

7.8 Specific KM Applications 178

7.9 What was Learned? 181

7.10 Where Next? 181

Annex 183

Bibliography 186

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TABLE OF CONTENTS

Part III

Methodological Aspects

Chapter 8. A Word to the Wise – Advice for Conducting the OECD

Knowledge Management Survey

Louise Earl and Michael Bordt 189

8.2 Questionnaire Content 190

8.3 The Questions 191

8.4 Conducting the Survey 196

8.5 Analysing and Reporting the Results 199

8.6 Conclusions 201

Bibliography 203

Chapter 9. Knowledge Management Practices Questionnaire OECD . 205

Conclusion D Foray and F Gault 213

List of Authors 219

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PART I

Frameworks

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Measuring Knowledge Management in the Business Sector

PART I

Chapter 1

Measurement of Knowledge Management Practices

by

Dominique Foray and Fred Gault

This chapter puts this survey on knowledge management practices

in the historical perspective of surveys in the domain of R&D,

technology and innovation It shows to what extent this survey is

of a different nature as compared with the available surveys on

knowledge management and it highlights the value added of this

new one Finally it provides a brief history of the OECD-Statistics

Canada project at the origin of the survey.

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I.1 MEASUREMENT OF KNOWLEDGE MANAGEMENT PRACTICES

However, the book is not just about surveys and data, it is aboutunderstanding a set of practices that are being used by firms and publicinstitutions, especially the larger ones, to do better what they do The use ofknowledge management practices in the first decade of the 21st century isbeginning to attract the same interest in the international policy community

as did the use of advanced technologies in the 1980s, and the engagement ofthe firm in the activity of innovation in the 1990s Of course, the reason for thisinterest is the identification of best practices, and their economic and socialcontext, with a view to sharing them, and making more organisations workbetter, as separate organisational units, and as part of an economic and socialsystem Th e discussion begins with wh at is meant by ‘knowledg emanagement’

Knowledge management (KM) covers any intentional and systematicprocess or practice of acquiring, capturing, sharing and using productiveknowledge, wherever it resides, to enhance learning and performance inorganisations.1These investments in the creation of “organisationalcapability” aim at supporting – through various tools and methods – theidentification, documentation, memorization and circulation of the cognitiveresources, learning capacities and competencies that individuals andcommunities generate and use in their professional contexts Practices, likeformal mentoring, monetary, or non monetary, reward for knowledge sharingand the allocation of resources to detect and capture external knowledge, areexamples of knowledge management

Knowledge management is, therefore, a matter of using a category ofpractices which are difficult to observe and manipulate and sometimes areeven unknown to those who possess them This is a challenge for firms, morefamiliar with the management and accounting for fixed capital However,evidence shows that these practices are being used more and more frequentlyand that their effect on innovation and other aspects of corporate

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performance is far from negligible (de la Mothe and Foray, 2001) The adoptionand implementation of knowledge management practices may be seen as acritical stage in the corporate move towards corporate integration into what ismore and more a knowledge-based economy

At the start of the 21st century, there is a recognition of the need tounderstand and to measure the activity of KM so that organisations, andsystems of organisations, can do what they do better and so that governmentscan develop policies to promote these benefits Facing such new emergingpractices, economists, management scientists and statisticians have littlesystematic evidence on which to base analysis Among the various categories

of knowledge-related investments (education, training, software, R&D, etc.),

KM is one of the less well known, both from a quantitative and qualitativepoint of view, as well as in terms of costs and economic returns As a result,there is certainly a need to know more about: these new knowledge-basedactivities; the current state of KM as an organisational process within variouskinds of companies and sectors; the variety of methods and tools that arebeing developed; and, the economic effects of KM practices that are actuallyobserved

1.2 Knowledge Management: What is New?

Larry Prusak – a world expert on knowledge management – likes to saythat like Monsieur Jourdain who spoke in prose, and was not even aware ofthat, companies have always managed knowledge But the need forknowledge management as a systematic strategy is becoming far more urgentfor the following reasons

Firstly, some of the older practices buried in human resources andemployment policies, which helped in knowledge management, no longerwork For example, the memorisation and transmission of tacit knowledgehas always been ensured by internal institutions (the craft guild, the internallabour market) and external organisations (professional networks), in whichthis was an essential function However, these institutions have largelydisappeared or find themselves in profound crisis For instance, in some largecompanies, a new engineer was hired a year before the old one retired in order

to ensure that knowledge was passed on in the context of an extendedmaster-student relationship In such cases, the conditions were propitious forensuring that the professional community itself ensured the memorisationand transmission of knowledge from one generation to the next However, thesystem was so costly that it is rarely used These days, a young engineerarrives a few weeks before the old one passes on the reins Naturally, thetransmission of knowledge is partial As a result, the old system fortransmitting new knowledge management practices has to be replaced by

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one, which might, for instance, be based on a codification of knowledge thatwould enable a new arrival to use this written memory as a learning program(instruction manuals, maintenance documents, expert systems)

Other practices no longer work The principle of lifelong careers and term attachment to the company led to a kind of common destiny betweenthe employee and his/her company From that point on, the individual’sknowledge was an almost integral part of the company’s intellectual heritage.Here again, recent developments in terms of turnover, mobility and flexibilitymake it necessary to invent new forms of knowledge retention – again,through either codification or the implementation of strong legal mechanisms

long-to protect the company’s intellectual heritage, or through human resourcespolicies that are better suited to maintaining skills

Secondly, the imperative of innovation as a condition of business survivalhas forced the introduction of explicit forms of knowledge management Thecost of missing the boat on an innovation (bypassing and ignoring a “goodidea”) becomes enormous We no longer have the luxury of missing out on one

or two innovations Thus, it becomes essential to introduce planned strategiesfor the collection and documentation of ideas and suggestions by employees

In addition to this type of knowledge management, processes for stimulatingcreativity become essential

Thirdly, the extension of knowledge markets, the dissemination ofinformation technologies and new methods for the evaluation of intangibleassets are three characteristics of the new economy which require theintroduction of explicit knowledge management methods

The expansion of markets for knowledge The increase in the rate of patent

applications, the impressive growth in revenues arising from the granting oflicences and the explosion in costs associated with intellectual propertysettlements are all indicators of the current development of the “knowledge-based market economy” (Arora, Fosfuri and Gambardella 2001) Yet,knowledge markets are, by definition, inefficient markets (Teece 1998).Buyers and sellers are not well informed about the commercial opportunities(no one knows who has what or who wants what) There are problemsassociated with revealing the characteristics of the product Intellectualproperty rights, even though they can reduce the first two difficulties, arefragile, uncertain and heterogeneous The product (or consumption) unit isnot clear Knowledge is sold neither by weight nor by size! At this point,knowledge management can be interpreted as an effort to create lessinefficient market conditions From this point of view, intellectual propertypolicies clearly form part of knowledge management

The use of ICTs as an opportunity to increase productivity The productivity

paradox can be expressed very simply as the delay between the appearance of

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new knowledge tools and instruments and the persistence of old forms oforganisation It then becomes a matter of moving to a higher level ofsystematising organisational skills and procedures The management ofknowledge, particularly in terms of the codification of procedures, is central tothese changes (Steinmueller 2000)

The importance of intellectual capital measurement and evaluation (to attract

venture capital or to build a partnership) It appears that the stock marketvaluation of a company increasingly depends on the value of its intangibles.Here again, the management of knowledge involves techniques for theidentification and quantification of intangibles in terms of the company’sknowledge base (Masoulas 2000)

Fourthly, the understanding of the phenomena pertaining to learning andthe transmission of knowledge is increasing; this, in turn, provides anopportunity to forge new tools an d new techniques of kn owledg emanagement The management of knowledge, as an activity, requires projectengineering in the form of tried and true tools and techniques which havethemselves been built on the basis of general advances in the economics andmanagement of knowledge, as a discipline Yet, since the work of Nonaka,Prusak, Teece, von Hippel and many others, there has been significantprogress in these disciplines, which has provided an opportunity tounderstand better the field and, thereby, the possibility of new tools Just asprogress in scientific instrumentation makes it possible to observe

phenomena that were previously invisible, progress in the innovation sciences

introduces a world that had previously been ignored The exploration of thisuniverse makes it possible to improve our understanding of the process ofknowledge production, transmission and use and, in the end, provides newoperational opportunities

Finally, beyond this economic and managerial line, some sociologistsargue that each age of capitalism has to provide those who participate in theeconomic activity (specifically for senior managers and engineers) reasons toget excited and motivated Thus, the knowledge management argument iscertainly a central part of the new system of argument and representation,capable of renewing the grounds for motivation for those who participate inthe capitalist enterprise (Boltanski and Chiapello 1999)

All these reasons are discussed in a recent book on knowledgemanagement in the innovation process (de la Mothe and Foray 2001) and inthe next Chapter by Paul Quintas

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1.3 Knowledge Management as a Topic for Empirical Studies:

Opening another Black Box

The production of detailed data on innovation-related activities and theimprovement of the economic analysis of innovation are parallel trends,which have always been in mutual reinforcement and dependence The OECDhas been centrally involved in both trends, particularly playing a key role inthe design of new indicators, as the theory of innovation has developed, andthen in the systematic collection, interpretation and use of data at aninternational level

This process – dealing with theoretical and empirical advances – consists

of opening one black box …after another!2Thus, the first generation of indicators

[see, for instance, the works by Mansfield (1968) and Griliches (1957)], focused

on the visible inputs to innovation – such as the expenditure on, and humanresources devoted to, R&D as well as the patents and publications resultingfrom the R&D The OECD has been engaged in this work, playing a key role inproducing and revising the Frascati family of manuals These manuals are allworks in progress, introducing new indicators and developing those already inuse

The second generation of indicators addressed the activity of innovation, or

the introduction to the market of a new or significantly improved product, or

of a new or significantly improved process to production As well as theactivity, there were also linkage measure (sources of innovation) and measure

of economic and social outcomes Such set of indicators and analysis permitsentry to the black box of the innovation process It is related to the

“interactive” model of innovation [see Kline and Rosenberg (1986), Teece (1989)and von Hippel (1988)] that emphasises the diversity of possible innovationpaths within an organisation, the importance of the various design activitiesand the predominance of feedback loops It is also related to the observation

of a diversity of sectoral patterns of technical change (Pavitt 1984) and to theincreasing interest of economists in the appropriation strategies of companies(“patent or trade secret?”) as well as to the interest for the detailed analysis ofthe links between the scientific knowledge base and the innovation process.Surveys on technological appropriation – followed by the surveys onuniversity & industry relations – and then surveys on innovation, based on theOslo Manual, are expressing a fine and detailed representation of theinnovation processes and aim at providing data for supporting systematicanalysis at a high level of detail and complexity Again, the OECD plays, incollaboration with Eurostat, a significant role However the first and secondgeneration indicators are largely influenced by a strong “science andtechnology” focus The light that these indicators shed on innovation istherefore more relevant for some enterprises and sectors than for others In

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certain cases they are satisfactory – the cases of sectors characterised by acentrality of science and technology – but in others these indicators illuminate

an almost empty stage

However, a second black box appears within the process of innovation

showing the need for a third generation of indicators Innovation consists

obviously in the production of new (theoretical or practical) knowledge, which

is generated intentionally (R&D) or non intentionally (learning by doing), andwhich is shared, modified, recombined and introduced to the market Theseminal references are probably Nonaka (1994) and Davenport & Prusak (1998)

in the field of management science and David (1993), Nelson (1992), von Hippel(1994) in the field of economics Such a new representation of innovation – as

a process of knowledge production, mediation and use (OECD 2000a) – openssuddenly an extremely broad field of investigation by moving the emphasisaway from technological change towards organisational change What kinds

of stylised facts are to be discovered in this new black box?

Firstly, people learn within their professional context They carry outexperiments during the regular production of goods and services Theygenerate knowledge, while it is not the main motivation of the activity

“Innovation without R&D” is, thus, an activity with considerable impacts.These impacts, however, are likely to vary depending on whether theknowledge generated remains invisible and ignored, or is articulated and

shared (Adler and Clarke 1991, Argote et al 1990, Cantley and Sahal 1980,

Pisano 1996, von Hippel and Tyre 1995)

Secondly, learning processes are “situated” and knowledge is “sticky”.The development of a situated perspective highlights the importance of thephysical context of learning This context is an essential component in theprocess This is why an engineer will pay frequent visits to a user in order tosettle a technical problem Such an understanding of the situational nature oflearning provides an opportunity to design principles of location and “optimalmobility” for experts as a function of the operational stages (Tyre and vonHippel 1997)

Thirdly, establishing an “organisational memory” is a critical factor forinnovation and learning It can be properly developed through efficientmethods of documentation, codification, storage and search or through theimplementation and maintenance of strong inter-personal networks of

knowledge (Hansen et al 1999, Steinmueller 2000).

Fourthly, the absorption capabilities as well as the strategies ofconnection to external networks of knowledge and external sources ofinnovation (users, suppliers, science and technology) are key factors(Cockburn and Henderson 1994, Hicks 1995) At this level there are conflictsbetween the requirements of searching for information (for which there

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would be an advantage in building a system of weak ties, i.e distant and

infrequent connections) and transferring knowledge [for which it is necessary

to build a system of strong ties (Hansen 1999)]

Fifthly, there is a strong relation at the firm level between economicperformances stemming from the use of new ICTs and the evolution ofworkplace practices and training (Brynjolfsson and Hitt 2000)

Finally, an efficient intellectual property policy is not only a matter ofpatent application and of infringement prevention IP also concerns protectedcommercial secrets and codified know how (often called proprietaryinformation), such as technical drawings, training, maintenance andoperating manuals Managing this part of intellectual property is difficult andoften this information has not been collected or combined and remains poorlyidentified in the firm (Arora 1995)

In short, the management of knowledge is now a key factor in promotinginnovations in organisations both by private companies and to some extent bypublic authorities

1.4 From Good Case Studies to Systematic Surveys

In opening this new black box, one can observe a quite depressingsituation: the main item – knowledge – is not observable and thus notmeasurable (Carter 1996, Henderson and Cockburn 1994, Jaffe 1999) Questionscould be raised about the meaning of the direct measurement of a stock ofknowledge (say of IBM to be compared with the stock of knowledge ofMonsanto) Several obstacles hinder, or even prevent, undertaking suchmeasurements (Machlup 1984) There is the difference between knowledge of

"that which is known" and knowledge as “the state of knowing” There are,moreover, the difference between knowledge of enduring significance andknowledge of merely temporary, quickly vanishing relevance; the differencebetween knowledge important for many and knowledge of interest to only afew Thus as soon as one goes beyond a single mind or memory, the problem

of additivity arises While measuring the stock of physical capital is a colossaltask, measuring the stock of knowledge capital seems, thus, virtuallyimpossible Even limited to current science and technology indicators, thismeasurement will be introduced only if techniques for dealing with thequestion of obsolescence are developed Moreover, does the measurement of astock of knowledge have any meaning if problems pertaining to its locationand access are not taken into account? An even more difficult task would be tomeasure flows of knowledge or the share of the stock of knowledge that entersinto the economy during a given period Measurement of embodied diffusion

(i.e the introduction into production processes of elements incorporating a new technology) and of dis-embodied diffusion (i.e transmission of

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knowledge in the form of patents licenses or know-how) are the two aspectsthat today are relatively well under control But here again, they cover only asmall part of the knowledge flows

The building of “proxies” will, thus, be at the centre of any investigation.But building good proxies requires fine and detailed case studies, providingthe basis for future and systematic works The good news is that such casestudies are happening A few examples have already been mentioned

All these works encourage the launching of programs to developindicators and to collect data about learning processes and knowledgemanagement

It is fair to mention that empirical studies are far more advanced in oneportion of the new black box, and these advances deal with organisationalchanges, the adoption of new workplace practices and impacts of thesechanges on performance (OECD 2000b) Such works have been stronglypushed by the discussions dealing with the so-called “productivity paradox”problem (raising the argument that the potential of the new ICTs forproductivity gains is great but there are many factors impeding, at least in themedium term, the productivity growth)

1.5 Why, How and So What?

The why type of question deals with the various rationales that private

companies are showing to explain the (costly) implementation of a KM policy.These rationales are the following:

● Making better use of what already exists within the organisation andoutside This is a static efficiency principle aiming at not “re-inventing thewheel”, improving corporate memory and knowledge sharing, evaluatingcompetencies in order to create best practices, and capturing externalknowledge;

● Solving co-ordination problems which arise because of the increasingcomplexity and modularity of products and systems;

● Increasing opportunities for innovation (through recombination, synergy, ortransfer);

● Transforming the stock of knowledge into a direct source of value (throughthe use of intellectual property management, licensing, and other means oftransfer);

● Attracting talents

While the two first objectives are of particular relevance for largecompanies and organisations, the three others are of value for any entity inthe modern economy

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The how type of question deals with the issue of creating and

implementing a coherent KM strategy, meaning that a main logic has to bedecided and a set of compatible practices have to implemented in thisframework It is useful to differentiate between two main knowledgemanagement strategies (Hansen, Norhia and Tierney 1999):

● Personalization: knowledge remains in its tacit form and is closely bound tothe person who developed it; it is shared primarily through person-to-person contact To make this strategy work, companies invest heavily innetworks of people (mobility, culture of bilateral interaction) In a sense,this strategy is simply another form of the traditional “internal labourmarket” as a powerful mechanism for capitalizing on, transferring andsharing knowledge It relies on the logic of expert economics Both theproblem and the knowledge are unique, and the service is expensive andtime-consuming;

● Codification: knowledge is transformed so that it can be stored in databasesand then easily accessed and used by anyone in the company; whilecodification involves high fixed costs, it enables agents to perform a number

of operations at a very low marginal cost This model is appropriate for firms

or organisations that deal repeatedly with similar problems For them, theefficient reuse of codified knowledge is essential, because their businessmodel is based on fast and cost-effective service, which an efficient system

of knowledge reuse provides Firms or organisations that follow acodification strategy rely on this Once a knowledge asset – software ormanual – is developed and paid for, it can be used many times by manypeople at very low cost, provided it does not have to be substantiallymodified at each use Re-use of knowledge saves work, reducescommunication costs and makes it possible to take on more projects;

Of course, all firms and organisations use both strategies, but thehypothesis is that those that excel focus on one and use the other in support.Hansen, Norhia and Tierney (1999) see an 80-20 split: 80% of their knowledgemanagement follows one strategy, 20% the other Those that try to excel atboth risk failing at both The argument is that the selection of a particularknowledge management strategy must reflect the firm’s or organisation’sbusiness model, which relies either on knowledge reuse or on uniqueproblems and expertise Interesting for a survey is that various dimensions ofknowledge management will differ, depending on the firm’s main strategy.There is thus an issue to identify consistent set of practices based on adominant KM logic

The so what type of question deals with the fundamental problem of the

benefits to be expected: active price competitiveness (process innovation,productivity), technological competitiveness (product innovation) and market

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power It is also a matter of identifying what are the most important

“intangibles” to show up for a company Those most important intangiblesbeing closely related to the KM strategy (personalisation and social network orcodification and ICT systems) selected

1.6 Knowledge Management Surveys

The lack of systematic evidence for KM activities is due to the fact thatvery few large scale surveys have been carried out.3Surveys that have beendone have the following attributes:

● they are multi-sectoral and international;

● they are mainly addressed to large companies; and;

● they do not make any data linking with existing data bases of R&D,innovation, employment, and so forth

While providing useful insights on KM practices,4the results are difficult

to interpret for several major reasons

Firstly, there is still considerable instability and ambiguity in the meaning

of the various concepts dealing with knowledge (consider for example theinstability of the notions of tacit and codified knowledge, knowledge andinformation, knowledge and competence, and expert systems) Researchers,experts and statisticians are nowadays in the same position as researchersand statisticians interested in working on R&D over fourty years ago Thehistorical analogy with the emergence of statistical works on R&D has,however, some limitations: R&D expenditures (and personnel) are easilyquantifiable, while we have no clearly defined equivalents for knowledgemanagement

The absence of a systematic terminology based on clear and widelyshared category increases dramatically the sensitivity of responses tosubjective perceptions and idiosyncratic understanding of “what is KM?” Theeffect of such ambiguity and lack of stable categories is amplified by the factthat KM methods and processes are not yet (and perhaps will never be)associated with the same departmental or functional budget throughout firmsand organisations KM strategies can be implemented and funded by the R&D,ICT, human resource & training or customer service sales department within

a company Thus, people with different “cultural background” can have ahighly different representation of “what is KM?” and “what are the KM issues

in the company?” We can note that this is a problem, which is minimised inthe case of a R&D survey, which is addressed in principle to R&D people

Secondly, because there was no previous experience in nationalstatistical offices in OECD countries of doing KM surveys, the existing surveysdone by other organisations cannot make the link between data on

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KM practices and the common economic performance and innovationindicators These surveys limit, thus, the scope of questions aboutperformance to subjective perceptions of the benefits (expected and “actuallyrealised”) Works on these issues tend, therefore, to be “self referential” in thesense that they are not validated by external economic criteria, such asrevenues or profits

There is, thus, a need for various tasks that could be achieved through thedesign, implementation and exploitation of an international survey carriedout by national statistical offices or in close co-operation with them

1.7 Three Main Tasks of a Knowledge Management Survey

The first task is to build a systematic database on KM practices Such a

database should ideally include information on six broad classes of questions:

● Adoption and implementation of KM practices;

● Reasons for using/non using KM practices;

● The sources which prompted the development of these practices;

● The actual benefits and consequences;

● The financing of a KM policy;

● General indicators

The second task should be to use the unique opportunity offered by

“official surveys” carried out at the national level to link the KM databases with data coming from other sources (R&D, innovation, enterprise surveys) This task

covers not only the technical aspect but also the analytical one There will be,for example, hypotheses about the types of linkage that could be trackedbetween R&D data, innovation data, and KM data At a first glance, it could beconsidered that variations in:

The third task should be to exploit an indirect effect of the survey, which

is to contribute to the stabilisation of meanings and to the standardisation of the terminology of KM strategies and practices through an international exercise The

design of a questionnaire achieved by an international group of

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well-I.1 MEASUREMENT OF KNOWLEDGE MANAGEMENT PRACTICES

recognised experts and the use of this questionnaire in various contexts(national, sectoral) can have substantial spill-over elements as it cancontribute largely to the stabilisation of basic categories and to thedevelopment of a common language on knowledge practices This follows thepractice of the OECD R&D and innovation

1.8 A Brief History of the OECD-Statistics Canada Project

and a First Look at the Results

Following the OECD High-Level Forum on knowledge management inOttawa in September 2000, a working group was set up, comprisingrepresentatives from the statistical offices of Canada, France, Italy, theNetherlands and Sweden and representatives from research bodies inAustralia, Denmark, Germany and Ireland The working group met four times

in 2001, in Copenhagen, Ottawa, Paris and Karlsruhe A questionnaire wasdevised during the course of the four meetings and the information emergingfrom the first pilot studies was discussed

This questionnaire includes a survey on the use of 23 KM practices and iscomplemented with questions on incentives for using KM practices, results,responsibilities, etc The questionnaire includes many informal managementpractices in order to accommodate how micro-firms are managing knowledge

On the other hand, it does not focus very much on the ICT infrastructure

For countries willing to carry out their own national surveys, two kinds ofstrategies were possible: either implementing the whole survey as a pilotstudy or lodging a few questions on KM in an existing and regularquestionnaire, such as the Community Innovation Survey While the firstoption gives the opportunity to really test the KM questionnaire and to collectinformation related to a large range of issues and problems, the second optionhas proven to be very useful for countries where starting a new survey is adifficult task for administrative, political or technical reasons

To date, four pilot studies have been carried out, to which this book islargely devoted The Canadian study (by Statistics Canada) covered

348 respondent firms of varying size (from 9 employees upwards), belonging

to 7 different sectors The German study (Fraunhofer ISI) covered 497 firms ofvarying size (from 1 employee upwards), belonging to 7 different sectors TheDanish study (CFL) covered 61 firms of varying size (from 1 employeeupwards), belonging to all sectors of the economy The French study (SESSI)adopted the second strategy, which was to merge four questions onknowledge management in the CIS3 survey This allowed a very large number

of firms to be covered (5100 firms with a response rate of 85%) It is to benoticed that Japan adopted more recently the same strategy – lodging fourquestions on KM in the Japanese National Innovation Survey 2003 Results will

be available in Autumn 2003

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Some of the most interesting findings to emerge from these pilot studiesare the following:

● KM practices have spread across the economy, just as technology diffuses;

● KM practices are implemented to deal with a great variety of objectives(static efficiency, innovation, co-ordination);

● Size matters: firms manage their knowledge resources differently,depending upon their size, and with little regard to industrial classification;

● KM practices matter for innovation and productivity performance;

● Cluster of practices: although this is a bit premature to make this kind ofstatement, cluster of practices makes it possible to see the two mainstrategies: codification and personalisation;

● Survey respondents showed a high level of interest, which in fact increases

as the size of the firm grows

All of these results show that the measurement process is possible andthis is both good news and an exciting challenge for statistical offices andeconometricians

1.9 Outline of the Book

In the next chapter knowledge management in practice is presented withexamples from case studies

Chapters 3 to 6 deal with country reports The Canadian, German, Danishand French cases are successively developed The data collected in eachnational survey are not presented using the same structure On the contraryeach Chapter is built on a specific structure, which best related the data to thenational circumstances and particularities The reader will also note thedifferences between the Canadian, German and Danish surveys based on apilot study (full use of the questionnaire on a limited sample of companies)and the French survey based on the introduction of few questions about KM in

a large scale survey (CIS3) Chapter 7 addresses the relation between scale and

KM practices on the basis of the Canadian data

Chapter 8 provides some “best practices” insights for those consideringconducting the OECD survey Rather than providing a manual that specifiesthe exact process required to conduct, analyse and report the survey, thischapter aims at advising the prospective KM survey manager Chapter 9presents the most recent version of the basic questionnaire

The concluding chapter is devoted to a first look at the policyimplications of the survey results as well as some indications about the nextsteps

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Notes

1 This definition is drawn from Scarbrough, Swan and Preston (1999)

2 Although this metaphor is, perhaps, not fully appropriate because the next blackbox discovered within the one that is being explored is not necessarily smallerthan the one that “contains” it

3 There was a French official survey “Les compétences pour innover”, carried out

in 1997 by the statistical office of the Ministère de l’Economie This survey,however, does not strictly focus on KM practices (SESSI 1998, Lhuillery 2001)

4 For instance, the survey undertaken by KPMG consulting provides manyinteresting results on the current state of KM It covers 423 organisations, inseveral OECD countries, which belong to 9 different sectors KPMG (2000) Seealso Arthur Andersen (2000), Cranfield School of Management (2000) and XEROX(2000)

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Measuring Knowledge Management in the Business Sector

This chapter draws on case studies and real-world examples to

illustrate knowledge management in practice We relate current

knowledge management (KM) practice to the wider context of

existing knowledge processes in organisations We note that the

processes of knowledge creation, sharing and application have been

central to organisational activity for centuries, and that there are

differences in perceptions of knowledge management between

different cultural traditions Key issues addressed include the social

nature of knowledge processes, start-up strategies for KM initiatives,

the role of technology, knowledge capture and sharing, intellectual

capital measurement, and cross-boundary processes Some lessons

are drawn from organisations’ experiences to date.

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I.2 MANAGING KNOWLEDGE IN PRACTICE

2.1 Introduction

The surge of interest in “knowledge management” (KM) in the West from

the mid 1990s is even more evident in organisational practice than it is in the

plethora of academic articles, books and conferences on the subject Profoundchanges in the economy and business environment at the end of thetwentieth century prompted organisations of all types to rethink the nature ofthe resources and capabilities that generate advantage.1Resources might now

include intellectual capital and enhanced consideration of intangible assets,

as well as knowledge itself Focus on capabilities prompted interest in key

processes such as knowledge creation, knowledge sharing, learning, and theexploitation of intellectual property Pre-1995 “knowledge management”initiatives in firms such as BP, Chevron, Shell, Hewlett Packard, Buckman Labsand Xerox, and the pioneering of intellectual capital reporting in Skandia(1994), pre-date the academic KM publishing boom (see Figure 2.1)

Figure 2.1 Growth in Knowledge Management Literature

Source: Gordon and Grant (2002)

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We should of course acknowledge that the literature on knowledge,viewed from an economics and organisational perspective, has a rather longerhistory than this “KM” phenomenon suggests From Adam Smith in the

18thcentury to Alfred Marshall in the 19thand Frederick Heyek and EdithPenrose in the early and mid 20th, the awareness of the economic importance

of knowledge and its centrality to organisations has been emphasised, if notfully articulated As Penrose wrote:

Economists have, of course, always recognized the dominant role thatincreasingly knowledge plays in economic processes but have, for themost part, found the whole subject of knowledge too slippery to handle.(Penrose, 1959, p 77)

Nevertheless it is undeniably the case that, in practice, people haveeffectively managed knowledge from the earliest incarnations of the

organisation There is a serious issue here as to what is the new subject of

interest in real-world organisations Much of the previous “managing ofknowledge processes” has been informal and unremarked, and certainly notlabelled as “knowledge management” The case studies of Honda, Matsushita

and other firms in Nonaka and Takeuchi’s influential book The Knowledge Creating Company (1995) were not examples of designated “knowledge

management” initiatives but rather descriptions of actual knowledgeprocesses of knowledge sharing, knowledge combination, and so on These

were identified post hoc as examples of knowledge being managed Similarly,

story-telling has recently been “discovered” as being alive and well andproviding knowledge sharing in many organisations Conversely (andironically) many so-called “knowledge management” initiatives and tools thatemerged in the late 1990s were less concerned with real knowledge issuesthan the informal or existing processes that are not so labelled

The example of communities of practice illustrates real management of

knowledge without the “KM label” As has been pointed out by Spender,Brown, Wenger, Baumard and others, knowledge has a social dimension – itmay be created and held collectively People who share work experiences,problem agendas and have similar learning opportunities form communities

of practice (Lave and Wenger 1991) Wenger (2000) defines a community ofpractice (CoP) as a social learning system, united by joint enterprise, mutuallyrecognised norms and competence, with shared language, routines andstories

Crucially, a community of practice is most often an informal grouping Itmay be unrecognised (Scarbrough 1996) or ignored or taken for granted(Baumard 1999) in the organisation So too it may transcend organisationalboundaries, including people in several organisations who hold experiences incommon CoP members act as resources for each other, “exchanging

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information, making sense of situations, sharing new tricks and ideas”(Wenger, 1998, p 47) In Xerox, photocopier engineers were observed workingtogether on a problem machine, communicating like jazz musicians,exchanging truncated phrases and able to communicate non-verbally because

of shared experience, shared learning, shared understandings (Brown andDuguid 1991) CoPs therefore represent oasis within which knowledgeprocesses function naturally

Formal management styles may be at odds with the informality of CoPprocesses, and indeed attempts to formally manage CoPs from outside mayundermine them Baumard (1999) identifies three CoPs in the Australianairline Qantas: the pilots and their retinue, the financial group, and themarketing group Each of these communities has their own language, which

as Baumard emphasises, indicates different interpretations of reality Qantas’top-down management style favours documents, manuals and computerisedinformation, whereas the CoPs favour less explicit circulation of knowledge:

“ communities of practice, conjectural knowledge and repertories of thoughtinscribed in practice are all tacit.” (Baumard, 1999, p 135) The Qantascommunities refused to use a new computer-based “knowledge managementsystem” introduced from outside the CoPs

The CoPs examples show that, unsurprisingly, knowledge processesfunction and work well without the “KM” label, and indeed attempts toformally introduce KM may adversely affect these more natural processes.Also, formal KM may be less concerned with knowledge than it is withinformation A key point here is that the concept of knowledge invites us tomove beyond the rather safer and certainly easier ground of data andinformation management As Spender (1996) has pointed out, there is littlepoint in introducing such a complex concept as knowledge into managementthought and practice if we do not take seriously the characteristics ofknowledge that make it special, and distinguishable from information Thisrealisation calls into question so-called “knowledge management” practicethat focuses wholly on technology, codification or commodified off-the-shelf

“solutions” Prusak makes a similar point when he says, “if you spend morethan one-third of your knowledge budget of technology … then it becomes atechnology project and not a knowledge project” (Prusak 2001, p 156)

T h e a dva ntag e of an en hanc ed focu s on kn owle dg e p rov ide sopportunities for new thinking, both about and within organisations Toignore the transformational potential of a knowledge perspective is to miss an

opportunity In this regard it is valuable to emphasise knowing as a process.

This counters the tendency, as is common in the West, to think aboutknowledge as a “thing” or commodity that can easily be moved around,managed and traded An alternative approach, focused on knowing as

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process, is more practical than it might at first appear, as this definition ofknowledge management from the Xerox Corporation illustrates:

Knowledge management is the discipline of creating a thriving work andlearning environment that fosters the continuous creation, aggregation,use and re-use of both organisational and personal knowledge in thepursuit of new business value (Cross, 1998, p 11)

The Xerox definition is strongly process and action oriented It does notemphasize knowledge resources and assets, as many definitions and indeedinitiatives do Rather, it focuses on the processes of creating new knowledgeand actively doing things with it

It is not surprising that perceptions of knowledge differ between cultures.Grossly simplifying a more complex geographical and epistemologicalvariation, Western and Eastern traditions differ in their views of the extent towhich knowledge can be separated from the knower Even within Europeancultures there are differences in conceptualisations of knowledge, as isreflected in the language we use to discuss it For example, the Englishlanguage may be accused of being deficient in having only the one word –

knowledge – when, for example, French makes a distinction between connaître and savoir, and German between kennen and wissen.

Differences in language reflect the fact that knowledge itself isconceptualised differently in different contexts, and we should notunderestimate the challenges of seeking universal definitions andvocabularies (Cohen, 1998) Nevertheless, managers and organisationsincreasingly have to operate across cultural and other boundaries, and anawareness of difference is essential

A European survey of knowledge management among 100 Europeanbusiness leaders (Murray and Myers, 1997) revealed some interesting culturaldifferences In France, more than anywhere else in Europe, nearly a quarter of

business leaders believed you can’t create any processes to help you manage

knowledge It is simply a matter of “management ability” In Germany, morethan four out of five respondents already considered their organisation to begood at encouraging staff to share knowledge and to bring forward new ideas

In the UK the main knowledge management focus was to exploit and controlthe knowledge that companies believe they already have Most remarkably,

almost a quarter of UK respondents said that creating new knowledge was not a

key priority, compared with only 1% in Germany

The international and multi-cultural approach adopted in this book is anattempt to begin to develop a comprehensive account of knowledgemanagement that goes beyond the limitations of a mono-culture perspective

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2.2 Key Knowledge Processes

Some would argue that having knowledge is a defining characteristic of

human beings and therefore it is inconceivable that we could have humanactivity without knowing and knowledge Perhaps, then, all organisationalprocesses involving humans are knowledge processes Certainly it may beargued that all activity in organisations is “knowledge based” to some extent,and therefore all workers are “knowledge workers”, up to a point, and all tasksperformed by humans is essentially “knowledge work” The counter view isthat certain types of work are more knowledge intensive than others Machlup(1962) demarcated the “knowledge economy” from the rest, Drucker (1969)coined the phrase “knowledge workers” and Reich (1991) refers to the rise of

“symbolic analysts” – distinguishing those who deal with concepts from thosewho work with physical materials In all of these post-industrial accountsknowledge processes are argued to be intensifying

Here we will focus on a number of key processes that are central to themanagement of knowledge in organisations Generic processes, especiallycommunication and learning, underpin many of the more focused processes,such as knowledge sharing, acquiring, integrating, mapping, and capturingetc It is revealing that arguably the most important process – that ofknowledge creation – is often ignored or forgotten by the “KM” professionals

We can see differing priorities in the variety of ways that firms approachtheir knowledge management initiatives For the majority of firms in theWest, the priorities are the “capture” of employees' knowledge, exploitation of

existing knowledge resources or assets, improved access to expertise (i.e.

improved “know-who”), transferring knowledge between projects, andbuilding and mining knowledge stores

Examples of early initiatives include Nat West Markets’ knowledgedirectory, and Teltech's mapping networks of experts (Davenport 1997) Ernst

& Young, Andersen Consulting, and other companies developed firm-wide ITsystems for document sharing with the aim of sharing codified best practice

and increasing re-use (Hansen et al., 1999) McKinsey consultants and Bain &

Company put greater effort into support for networking and people-to-people

links (ibid.) Skandia focused on measuring and auditing intellectual capital

and intangible assets (Skandia, 1996) Dow Chemical, Glaxo Welcome(pharmaceuticals) and Integra Life Sciences (health care) target the improvedmanagement and exploitation of intellectual property rights (IPR) Like manyorganisations, UK Post Office Consulting (POC) launched a cluster ofknowledge management projects in the late 1990s, including:

● knowledge sharing (targeted on communicating, learning, reviewing,capturing and sharing knowledge);

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● use of stories to communicate experience (targeted on transferring learning);

● after-action reviews (capturing learning from experience);

● intelligent agents (identifying specific and tailored information or contacts);

● people database (providing access to expertise);

● expert interviews (capturing expertise);

● learning from mistakes (surfacing and capturing learning in a non-blameculture, avoiding costly repetition); and

● expert masterclasses (sharing expertise)

(Quintas et al 1999)

Adopting a knowledge focus also generates new business models andopportunities Consultancy firms realise their business is entirely a knowledgebusiness and seek to commodify their knowledge as a product New businessopportunities spring up for knowledge brokers and for “talent” agents whorepresent knowledge workers in sectors where expertise is in great demand.The software services company ICL found that their knowledge managementexpertise generated a new line of business and revenue stream

2.3 Getting Knowledge Management Started

In this section we focus on how new initiatives labelled “knowledge

management” or KM (i.e espoused KM) are started within organisations The

beginnings of formal KM may be located anywhere in the organisation and

may be bottom-up or top-down Often the formal starting point was the

appointment of a chief knowledge officer IT professionals predominate inleading many early KM initiatives Who is driving an initiative matters, as ithas been demonstrated in relation to organisational learning programmes

in 3M and Coca-Cola Different groups championing and steering theprogramme (in these cases the HR department, and the technical experts inR&D) have different priorities and objectives, and the programmes may bemarkedly different

However, the realisation that there are serious people-management andcultural challenges associated with “capturing” the knowledge of employees,

or influencing the ways people deal with or share knowledge, has led togreater involvement of HR professionals Time and time again we hear therealisation dawning that it is the “soft issues” that determine knowledgeprocesses

Knowledge management was not adopted in a vacuum, and mostorganisations in the early 1990s already had ongoing initiatives in areas such

as continuous improvement, quality management and business process engineering Some early adopters of the KM label re-badged existinginitiatives, and consultancy firms re-labelled management consultancy

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re-I.2 MANAGING KNOWLEDGE IN PRACTICE

methods Some KM programmes were explicitly developed out of existingprogrammes, such as Texas Instruments best-practice knowledge sharingprogramme which emerged from their quality programme TI-BEST, and DowChemical’s knowledge programme developed out of their Intellectual AssetManagement programme BP’s KM programme began with a project calledVirtual Teamworking

Many KM initiatives are driven by board-level and CEO interest, and acommon approach is to set up a centralised office to coordinate KMdevelopments, usually accompanied by the appointment of a KM champion,titled “chief knowledge officer” (CKO) or similar The software and systemscompany ICL’s CEO appointed Elizabeth Lank as Director of ICL’s KnowledgeManagement Programme in 1996 In this case the KM champion’s role was tohead-up a programme with finite duration The task was to embed knowledgemanagement practice within all parts of the organisation, after which thecentral role would be superfluous

Bottom-up KM often starts with a small core of interested and activeenthusiasts, as is the case in both Siemens and BT Pilot projects are valuablelow-cost / low risk ways of proving the viability of a KM approach and gainingexperience, and they provide a demonstrator to be evaluated and replicated

2.4 Limits and Potentials of Technological Solutions

“It is worth remembering that the music is in the pianist, not the piano.”(Jim Marsh, Knowledge Director, Post Office Consulting)

By the early 1990s there was growing awareness that businessinformation systems were not capturing the knowledge that managers use intheir work, as noted by the former head of Information Technology (IT)research for Ernst & Young:

evidence from research conducted since the mid-1960s shows thatmost managers don’t rely on computer-based information to makedecisions … managers get two-thirds of their information from face-to-face or telephone conversations; they acquire the remaining third fromdocuments, most of which come from outside the organisation and aren’t

on the computer system (Davenport, 1994, p 121)

It is ironic that many subsequent so-called KM approaches have been

based on information technology While codified knowledge is also

information, much human knowledge cannot be codified and remainsinaccessible to information technology You cannot share a violinist’s

knowledge (i.e learn to play the violin) by listening to a CD or to a lengthy

verbal explanation of the technique Practice is required Also, availability ofinformation does not mean knowledge is being communicated (if a text is inJapanese it is information that is meaningless to a non-Japanese speaker)

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Certainly information and communications technologies (ICT)s have potential

to support communication and information flows, and the vast expansion ofinformation available via the internet is an undeniable resource Howeverstudies of organisations that have adopted an IT-driven approach to KM showthat the use of ICTs must be framed within a strategy that addresses other,fundamental factors

Many organisations introduced new IT systems as part of, and in somecases the totality of, their “knowledge management” initiative One such wasthe UK Defence Evaluation and Research Agency (DERA), an organisation ofsome 10 000 engineers, scientists and strategists.2DERA had a KM programfrom 1994 The initial KM strategy was devised by IT professionals andessentially IT-driven The four themes of the strategy were (1) technology,(2) processes, (3) people & behaviour and (4) content, prioritised in that order.DERA had an intranet in place in 1995 By 1998 the lack of success with thisprompted the introduction of “culture & behaviour” initiatives in 1998, and asecond knowledge management strategy – this time devised by a teamincluding librarians as well as IT specialists, was published in February 1999 DERA introduced KNet, a database intended to help DERA staff networkmore easily It aimed to provide information on who in DERA has expertise on

a given topic, and details about them and how to contact them KNet wasaccessible by all staff, who could update their own records on-line It was alsodesigned to hold information on expert contacts outside DERA Thoughrecognised externally as a model system of its type, it has emerged that KNetdid not work well The database categories were found inappropriate by users,who were also reluctant to enter their own data Only 10% of staff entered anydata, until management mandated this with financial incentives, causingfriction

A further major KM system, the Knowledge Store, introduced in 2001,intended to provide easy access to all types of explicit knowledge orinformation It included intuitive navigation maps, search tools, softwareagent support, cross-linking between content libraries, and integration ofexisting web sites and applications Anyone in DERA could publish almost anytype or for mat of informatio n Th e Knowledge Store was a majordevelopment, reportedly employing 80% of UK Oracle developers at one time.The problem in practice was that people would not publish and share theirinformation, principally because the organisational culture was resistant andprotective, not least because DERA was divided into business units that were

in competition to make profits Additionally, the organisational cultureinstilled an aversion to sharing knowledge – it was simply not the way peoplehad learned to behave In the words on one insider: “people don’t share - soeverything collapses” (Thornton 2001) Similar cultural barriers wereexperienced in other organisations, such as IT company ICL (Mackay 2001)

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Following the break-up of DERA a new KM strategy emerged within theemergent Defence Science & Technology Laboratory (Dstl, which employedaround 3000 people) Drawing on the DERA KM experience the Dstl strategywas based on reversed priorities: (1) people, behaviour, culture, (2) content,(3) processes and (4) technology & tools

The DERA experience had shown a KM initiative requires the enthusiasticco-operation and input of all staff within a supportive culture DERA had aculture of secrecy, internal competition and lack of trust This had to bechanged to an environment that encourages and rewards the sharing ofinformation, knowledge and skills, including successes and failures We cansummarise the lessons that emerge from DERA and the many organisationswith similar experiences as suggesting that:

● technology should not drive knowledge management practice, it has asupporting role;

● ICTs can only deal with knowledge in so far as it can be represented orcodified – this does not include tacit experiential human knowledge;

● social, cultural and process issues, and in some cases structural barriers,constrain the contribution of technology to any KM programme

For organisations seeking to better manage their knowledge, it seemsthat the use of ICTs should be focused on connectivity – providing

co mmun ication systems that link humans together – rather thanconcentrating on the capture and representation of human knowledge There

is therefore significant potential in “groupware” and other innovativecommunications technologies, but organisations must also create conditions

of trust where individuals feel encouraged to share their ideas, opinions andknowledge

2.5 Knowledge Capture

Realisation that people in organisations possess knowledge that is notcodified has prompted formal “knowledge capture” initiatives in manyorganisations Codified knowledge is information, which may be stored andre-used by others, providing they can understand its meaning Whereas sometypes of knowledge may be readily captured and codified, other forms ofknowledge are less amenable All organisations possess a great deal ofexperience-based knowledge which is learned implicitly and internalized byindividuals Much of this experiential knowledge is tacit knowledge

Almost a century ago Frederick Taylor not only recognised the presence ofindividual experiential knowledge, but also the potential value in attempting

to capture this knowledge and make it available to the organisation A centralpart of Taylor’s “scientific management” was concerned with identification of

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