Tải bản đầy đủ

Measuring knowledge management in the business sector 1 steps

«

Knowledge Management

Measuring Knowledge Management
in the Business Sector
FIRST STEPS

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.

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

OECD’s books, periodicals and statistical databases are now available via www.SourceOECD.org,
our online library.
This book is available to subscribers to the following SourceOECD themes:
Education and Skills
Science and Information Technology
Statistics Sources and Methods
Ask your librarian for more details of how to access OECD books on line, or write to us at


SourceOECD@oecd.org

Measuring Knowledge Management in the Business Sector

Co-published with Statistics Canada.

Knowledge Management

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

FIRST STEPS

w w w. o e c d . o rg

-:HSTCQE=VUUW[]:

ISBN 92-64-10026-1
96 2003 02 1 P

Knowledge Management

Measuring Knowledge
Management
in the Business Sector
FIRST STEPS


© OECD, 2003.
© Software: 1987-1996, Acrobat is a trademark of ADOBE.
All rights reserved. OECD grants you the right to use one copy of this Program for your personal use only.
Unauthorised reproduction, lending, hiring, transmission or distribution of any data or software is
prohibited. You must treat the Program and associated materials and any elements thereof like any other
copyrighted material.
All requests should be made to:

Head of Publications Service,
OECD Publications Service,
2, rue André-Pascal,
75775 Paris Cedex 16, France.


Measuring Knowledge
Management
in the Business Sector:
First Steps

ORGANISATION FOR ECONOMIC CO-OPERATION AND DEVELOPMENT
STATISTICS CANADA


ORGANISATION FOR ECONOMIC CO-OPERATION AND DEVELOPMENT
Pursuant to Article 1 of the Convention signed in Paris on 14th December 1960, and which
came into force on 30th September 1961, the Organisation for Economic Co-operation and
Development (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 in
the process of economic development; and
– to contribute to the expansion of world trade on a multilateral, non-discriminatory basis in
accordance 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 countries
became 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 (7th
May 1996), Poland (22nd November 1996), Korea (12th December 1996) and the Slovak Republic (14th
December 2000). The Commission of the European Communities takes part in the work of the
OECD (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 federal
government agency, is headed by the Chief Statistician of Canada and reports to Parliament through the
Minister of Industry.
Statistics Canada provides information to governments at every level and is a source of statistical
information for business, labour, academic and social institutions, professional associations, the
international statistical community, and the general public. This information is produced at the
national 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, by
participating in a number of international meetings and professional exchanges. Statistics Canada
conducted the pilot survey on Knowledge Management Practices as part of an international initiative
headed by the Centre for Educational Research and Innovation (Organisation for Economic
Co-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 Management
Practices' 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,
fax (33-1) 46 34 67 19, for every country except the United States. In the United States permission should be obtained
through the Copyright Clearance Center, Customer Service, (508)750-8400, 222 Rosewood Drive, Danvers, MA 01923 USA,
or CCC Online: www.copyright.com. All other applications for permission to reproduce or translate all or part of this book
should be made to OECD Publications, 2, rue André-Pascal, 75775 Paris Cedex 16, France.


FOREWORD

Foreword

A

t 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 com prising
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.

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

3


FOREWORD

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.

4

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


TABLE OF CONTENTS

Table of Contents
Part I
Frameworks
Chapter 1.

Measurement of Knowledge Management Practices
Dominique Foray and Fred Gault ....................................................
1.1. Introduction .....................................................................................
1.2. Knowledge Management: What is New?......................................
1.3. Knowledge Management as a Topic for Empirical Studies:
Opening another Black Box ...........................................................
1.4. From Good Case Studies to Systematic Surveys ........................
1.5. Why, How and So What? ................................................................
1.6. Knowledge Management Surveys ................................................
1.7. Three Main Tasks of a Knowledge Management Survey ...........
1.8. A Brief History of the OECD-Statistics Canada Project
and a First Look at the Results ......................................................
1.9. Outline of the Book .........................................................................
Bibliography ...............................................................................................

Managing Knowledge in Practice
Paul Quintas .....................................................................................
2.1. Introduction......................................................................................
2.2. Key Knowledge Processes ...............................................................
2.3. Getting Knowledge Management Started ....................................
2.4. Limits and Potentials of Technological Solutions .......................
2.5. Knowledge Capture .........................................................................
2.6. Knowledge Sharing..........................................................................
2.7. Auditing and Exploiting Intellectual Capital................................
2.8. Cross-boundary Knowledge Acquisition and Integration..........
2.9. Conclusions ......................................................................................
Bibliography ...............................................................................................

11
12
13
16
18
19
21
22
23
24
26

Chapter 2.

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

29
30
34
35
36
38
40
42
44
48
50

5


TABLE OF CONTENTS

Part II
Country Reports
Chapter 3.

Are we Managing our Knowledge?
The Canadian Experience
Louise Earl .......................................................................................
3.1. Highlights .........................................................................................
3.2. Introduction .....................................................................................
3.3. Survey Background/Overview ........................................................
3.4. Definition of Knowledge Management ........................................
3.5. Knowledge Management Practices in Use ...................................
3.6. Reasons Why Knowledge Management Practices
Were Adopted ..................................................................................
3.7. Knowledge Management Practices Most Effective
for Improving Workers’ Skills and Knowledge ............................
3.8. One Quarter of Firms Had Dedicated Budgets
for Knowledge Management .........................................................
3.9. Knowledge Management – Important Business Practices ........
Annexes ......................................................................................................
Bibliography ..............................................................................................
The Management of Knowledge in German Industry
Jakob Edler .......................................................................................
4.1. Introduction: Filling Knowledge Gaps on Industrial
Knowledge Management in Germany ..........................................
4.2. Methodology: The Sample ..............................................................
4.3. The Employment of KM Practices in German Industry .............
4.4. What Kind of KM Practices ............................................................
4.5. The Driving Forces of Knowledge Management:
Motivation Patterns in German Industry......................................
4.6. Effects of Knowledge Management ..............................................
4.7. The Institutionalisation of KM and its Meaning for
the Use of Knowledge Management ............................................
4.8. Knowledge Management and its Role within
Innovation Management ................................................................
4.9. Concluding Summary: Only First Steps towards Filled Gaps ...
Annexes ......................................................................................................
Bibliography ..............................................................................................

55
56
57
57
58
59
64
67
69
72
76
85

Chapter 4.

6

89
90
92
94
95
98
104
108
109
112
116
118

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


TABLE OF CONTENTS

Chapter 5.

The Promotion and Implementation of Knowledge
Management – A Danish Contribution
Anja Baastrup and Wenche Strømsnes ...........................................
5.1. Introduction .....................................................................................
5.2. Some Overall Results ......................................................................
5.3. Measuring, Controlling and Documenting Effectiveness ..........
5.4. Inspiration for Top Managers – Content and Process ................
5.5. What can Top Management Expect from the Environment? ...
5.6. Further Research .............................................................................
Annexes .....................................................................................................
Bibliography ..............................................................................................

Knowledge Management, Innovation and Productivity:
A Firm Level Exploration Based on French
Manufacturing CIS3 Data
Elizabeth Kremp and Jacques Mairesse ...........................................
6.1. Introduction .....................................................................................
6.2. Diffusion of Knowledge Management .........................................
6.3. Complementarity of Knowledge Management Practices ..........
6.4. Knowledge Management and Innovation ...................................
6.5. Knowledge Management and Productivity .................................
6.6. Conclusion .......................................................................................
Annex .........................................................................................................
Bibliography ..............................................................................................

119
120
121
125
127
130
131
134
141

Chapter 6.

Knowledge Management: Size Matters
Louise Earl and Fred Gault ...............................................................
7.1. Introduction .....................................................................................
7.2. Practices ...........................................................................................
7.3. Reasons for Using KM Practices ....................................................
7.4. Results of Using KM Practices .......................................................
7.5. Incentives to Use KM ......................................................................
7.6. Moving from Micro to Large ..........................................................
7.7. Intensity of KM Use ........................................................................
7.8. Specific KM Applications ...............................................................
7.9. What was Learned? ........................................................................
7.10. Where Next? ....................................................................................
Annex .........................................................................................................
Bibliography ..............................................................................................

143
144
146
151
152
159
161
164
168

Chapter 7.

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

169
170
172
174
176
177
178
178
178
181
181
183
186

7


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 .........................................................
8.1. Introduction .....................................................................................
8.2. Questionnaire Content ...................................................................
8.3. The Questions .................................................................................
8.4. Conducting the Survey ...................................................................
8.5. Analysing and Reporting the Results ...........................................
8.6. Conclusions .....................................................................................
Bibliography ...............................................................................................

Chapter 9.

Knowledge Management Practices Questionnaire
OECD ...............................................................................................

189
190
190
191
196
199
201
203

205

Conclusion

8

D. Foray and F. Gault ............................................................................................

213

List of Authors ....................................................................................................

219

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



PART I

Frameworks

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


ISBN 92-64-10026-1
Measuring Knowledge Management in the Business Sector
© OECD/MINISTER OF INDUSTRY, CANADA, 2003

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.

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

11


I.1. MEASUREMENT OF KNOWLEDGE MANAGEMENT PRACTICES

1.1. Introduction
This is a book about measuring the practices associated with knowledge
management and interpreting the findings. It is new empirical work and one
of the objectives of bringing together and publishing contributions from a
number of OECD member countries, now, is to set the stage for improved
measurements and more comprehensive findings that can be compared
across national and cultural boundaries. This is a work in progress.
However, the book is not just about surveys and data, it is about
understanding a set of practices that are being used by firms and public
institutions, especially the larger ones, to do better what they do. The use of
knowledge management practices in the first decade of the 21st century is
beginning to attract the same interest in the international policy community
as did the use of advanced technologies in the 1980s, and the engagement of
the firm in the activity of innovation in the 1990s. Of course, the reason for this
interest is the identification of best practices, and their economic and social
context, with a view to sharing them, and making more organisations work
better, as separate organisational units, and as part of an economic and social
system. Th e discussion beg ins w ith wh at is meant by ‘knowl edg e
management’.
Knowledge management (KM) covers any intentional and systematic
process or practice of acquiring, capturing, sharing and using productive
knowledge, wherever it resides, to enhance learning and performance in
organisations. 1 These investments in the creation of “organisational
capability” aim at supporting – through various tools and methods – the
identification, documentation, memorization and circulation of the cognitive
resources, learning capacities and competencies that individuals and
communities generate and use in their professional contexts. Practices, like
formal mentoring, monetary, or non monetary, reward for knowledge sharing
and the allocation of resources to detect and capture external knowledge, are
examples of knowledge management.
Knowledge management is, therefore, a matter of using a category of
practices which are difficult to observe and manipulate and sometimes are
even unknown to those who possess them. This is a challenge for firms, more
familiar with the management and accounting for fixed capital. However,
evidence shows that these practices are being used more and more frequently
and that their effect on innovation and other aspects of corporate

12

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


I.1. MEASUREMENT OF KNOWLEDGE MANAGEMENT PRACTICES

performance is far from negligible (de la Mothe and Foray, 2001). The adoption
and implementation of knowledge management practices may be seen as a
critical stage in the corporate move towards corporate integration into what is
more and more a knowledge-based economy.
At the start of the 21st century, there is a recognition of the need to
understand and to measure the activity of 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 little
systematic 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 qualitative
point 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-based
activities; the current state of KM as an organisational process within various
kinds of companies and sectors; the variety of methods and tools that are
being developed; and, the economic effects of KM practices that are actually
observed.

1.2. Knowledge Management: What is New?
Larry Prusak – a world expert on knowledge management – likes to say
that like Monsieur Jourdain who spoke in prose, and was not even aware of
that, companies have always managed knowledge. But the need for
knowledge management as a systematic strategy is becoming far more urgent
for the following reasons.
Firstly, some of the older practices buried in human resources and
employment policies, which helped in knowledge management, no longer
work. For example, the memorisation and transmission of tacit knowledge
has always been ensured by internal institutions (the craft guild, the internal
labour market) and external organisations (professional networks), in which
this was an essential function. However, these institutions have largely
disappeared or find themselves in profound crisis. For instance, in some large
companies, 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 extended
master-student relationship. In such cases, the conditions were propitious for
ensuring that the professional community itself ensured the memorisation
and transmission of knowledge from one generation to the next. However, the
system was so costly that it is rarely used. These days, a young engineer
arrives a few weeks before the old one passes on the reins. Naturally, the
transmission of knowledge is partial. As a result, the old system for
transmitting new knowledge management practices has to be replaced by

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

13


I.1. MEASUREMENT OF KNOWLEDGE MANAGEMENT PRACTICES

one, which might, for instance, be based on a codification of knowledge that
would 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 longterm attachment to the company led to a kind of common destiny between
the employee and his/her company. From that point on, the individual’s
knowledge was an almost integral part of the company’s intellectual heritage.
Here again, recent developments in terms of turnover, mobility and flexibility
make it necessary to invent new forms of knowledge retention – again,
through either codification or the implementation of strong legal mechanisms
to protect the company’s intellectual heritage, or through human resources
policies that are better suited to maintaining skills.
Secondly, the imperative of innovation as a condition of business survival
has forced the introduction of explicit forms of knowledge management. The
cost of missing the boat on an innovation (bypassing and ignoring a “good
idea”) becomes enormous. We no longer have the luxury of missing out on one
or two innovations. Thus, it becomes essential to introduce planned strategies
for the collection and documentation of ideas and suggestions by employees.
In addition to this type of knowledge management, processes for stimulating
creativity become essential.
Thirdly, the extension of knowledge markets, the dissemination of
information technologies and new methods for the evaluation of intangible
assets are three characteristics of the new economy which require the
introduction 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 of
licences and the explosion in costs associated with intellectual property
settlements are all indicators of the current development of the “knowledgebased 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 problems
associated with revealing the characteristics of the product. Intellectual
property rights, even though they can reduce the first two difficulties, are
fragile, uncertain and heterogeneous. The product (or consumption) unit is
not clear. Knowledge is sold neither by weight nor by size! At this point,
knowledge management can be interpreted as an effort to create less
inefficient market conditions. From this point of view, intellectual property
policies 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

14

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


I.1. MEASUREMENT OF KNOWLEDGE MANAGEMENT PRACTICES

new knowledge tools and instruments and the persistence of old forms of
organisation. It then becomes a matter of moving to a higher level of
systematising organisational skills and procedures. The management of
knowledge, particularly in terms of the codification of procedures, is central to
these 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 market
valuation of a company increasingly depends on the value of its intangibles.
Here again, the management of knowledge involves techniques for the
identification and quantification of intangibles in terms of the company’s
knowledge base (Masoulas 2000).
Fourthly, the understanding of the phenomena pertaining to learning and
the transmission of knowledge is increasing; this, in turn, provides an
op p ortuni ty t o f org e new t ool s an d new t e ch niq ue s o f kn ow le dg e
management. The management of knowledge, as an activity, requires project
engineering in the form of tried and true tools and techniques which have
themselves been built on the basis of general advances in the economics and
management of knowledge, as a discipline. Yet, since the work of Nonaka,
Prusak, Teece, von Hippel and many others, there has been significant
progress in these disciplines, which has provided an opportunity to
understand better the field and, thereby, the possibility of new tools. Just as
progress 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 this
universe makes it possible to improve our understanding of the process of
knowledge production, transmission and use and, in the end, provides new
operational opportunities.
Finally, beyond this economic and managerial line, some sociologists
argue that each age of capitalism has to provide those who participate in the
economic activity (specifically for senior managers and engineers) reasons to
get excited and motivated. Thus, the knowledge management argument is
certainly a central part of the new system of argument and representation,
capable of renewing the grounds for motivation for those who participate in
the capitalist enterprise (Boltanski and Chiapello 1999).
All these reasons are discussed in a recent book on knowledge
management in the innovation process (de la Mothe and Foray 2001) and in
the next Chapter by Paul Quintas.

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

15


I.1. MEASUREMENT OF KNOWLEDGE MANAGEMENT PRACTICES

1.3. Knowledge Management as a Topic for Empirical Studies:
Opening another Black Box
The production of detailed data on innovation-related activities and the
improvement of the economic analysis of innovation are parallel trends,
which have always been in mutual reinforcement and dependence. The OECD
has been centrally involved in both trends, particularly playing a key role in
the design of new indicators, as the theory of innovation has developed, and
then in the systematic collection, interpretation and use of data at an
international level.
This process – dealing with theoretical and empirical advances – consists
of opening one black box …after another!2 Thus, 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 human
resources devoted to, R&D as well as the patents and publications resulting
from the R&D. The OECD has been engaged in this work, playing a key role in
producing and revising the Frascati family of manuals. These manuals are all
works in progress, introducing new indicators and developing those already in
use.
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 the
activity, there were also linkage measure (sources of innovation) and measure
of economic and social outcomes. Such set of indicators and analysis permits
entry 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 innovation
paths within an organisation, the importance of the various design activities
and 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 the
increasing interest of economists in the appropriation strategies of companies
(“patent or trade secret?”) as well as to the interest for the detailed analysis of
the links between the scientific knowledge base and the innovation process.
Surveys on technological appropriation – followed by the surveys on
university & industry relations – and then surveys on innovation, based on the
Oslo Manual, are expressing a fine and detailed representation of the
innovation processes and aim at providing data for supporting systematic
analysis at a high level of detail and complexity. Again, the OECD plays, in
collaboration with Eurostat, a significant role. However the first and second
generation indicators are largely influenced by a strong “science and
technology” focus. The light that these indicators shed on innovation is
therefore more relevant for some enterprises and sectors than for others. In

16

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


I.1. MEASUREMENT OF KNOWLEDGE MANAGEMENT PRACTICES

certain cases they are satisfactory – the cases of sectors characterised by a
centrality 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), and
which is shared, modified, recombined and introduced to the market. The
seminal 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) – opens
suddenly an extremely broad field of investigation by moving the emphasis
away 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 out
experiments during the regular production of goods and services. They
generate 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 the
knowledge 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 the
physical context of learning. This context is an essential component in the
process. This is why an engineer will pay frequent visits to a user in order to
settle a technical problem. Such an understanding of the situational nature of
learning provides an opportunity to design principles of location and “optimal
mobility” for experts as a function of the operational stages (Tyre and von
Hippel 1997).
Thirdly, establishing an “organisational memory” is a critical factor for
innovation and learning. It can be properly developed through efficient
methods of documentation, codification, storage and search or through the
implementation and maintenance of strong inter-personal networks of
knowledge (Hansen et al. 1999, Steinmueller 2000).
Fourthly, the absorption capabilities as well as the strategies of
connection to external networks of knowledge and external sources of
innovation (users, suppliers, science and technology) are key factors
(Cockburn and Henderson 1994, Hicks 1995). At this level there are conflicts
between the requirements of searching for information (for which there

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

17


I.1. MEASUREMENT OF KNOWLEDGE MANAGEMENT PRACTICES

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 economic
performances stemming from the use of new ICTs and the evolution of
workplace practices and training (Brynjolfsson and Hitt 2000).
Finally, an efficient intellectual property policy is not only a matter of
patent application and of infringement prevention. IP also concerns protected
commercial secrets and codified know how (often called proprietary
information), such as technical drawings, training, maintenance and
operating manuals. Managing this part of intellectual property is difficult and
often this information has not been collected or combined and remains poorly
identified in the firm (Arora 1995).
In short, the management of knowledge is now a key factor in promoting
innovations in organisations both by private companies and to some extent by
public authorities.

1.4. From Good Case Studies to Systematic Surveys
In opening this new black box, one can observe a quite depressing
situation: the main item – knowledge – is not observable and thus not
measurable (Carter 1996, Henderson and Cockburn 1994, Jaffe 1999). Questions
could be raised about the meaning of the direct measurement of a stock of
knowledge (say of IBM to be compared with the stock of knowledge of
Monsanto). Several obstacles hinder, or even prevent, undertaking such
measurements (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 and
knowledge of merely temporary, quickly vanishing relevance; the difference
between knowledge important for many and knowledge of interest to only a
few. 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 colossal
task, measuring the stock of knowledge capital seems, thus, virtually
impossible. Even limited to current science and technology indicators, this
measurement will be introduced only if techniques for dealing with the
question of obsolescence are developed. Moreover, does the measurement of a
stock of knowledge have any meaning if problems pertaining to its location
and access are not taken into account? An even more difficult task would be to
measure flows of knowledge or the share of the stock of knowledge that enters
into 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

18

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


I.1. MEASUREMENT OF KNOWLEDGE MANAGEMENT PRACTICES

knowledge in the form of patents licenses or know-how) are the two aspects
that today are relatively well under control. But here again, they cover only a
small 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, providing
the basis for future and systematic works. The good news is that such case
studies are happening. A few examples have already been mentioned.
All these works encourage the launching of programs to develop
indicators and to collect data about learning processes and knowledge
management.
It is fair to mention that empirical studies are far more advanced in one
portion of the new black box, and these advances deal with organisational
changes, the adoption of new workplace practices and impacts of these
changes on performance (OECD 2000b). Such works have been strongly
pushed by the discussions dealing with the so-called “productivity paradox”
problem (raising the argument that the potential of the new ICTs for
productivity gains is great but there are many factors impeding, at least in the
medium 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 and
outside. This is a static efficiency principle aiming at not “re-inventing the
wheel”, improving corporate memory and knowledge sharing, evaluating
competencies in order to create best practices, and capturing external
knowledge;



Solving co-ordination problems which arise because of the increasing
complexity and modularity of products and systems;



Increasing opportunities for innovation (through recombination, synergy, or
transfer);



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



Attracting talents.

While the two first objectives are of particular relevance for large
companies and organisations, the three others are of value for any entity in
the modern economy.

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

19


I.1. MEASUREMENT OF KNOWLEDGE MANAGEMENT PRACTICES

The how type of question deals with the issue of creating and
implementing a coherent KM strategy, meaning that a main logic has to be
decided and a set of compatible practices have to implemented in this
framework. It is useful to differentiate between two main knowledge
management strategies (Hansen, Norhia and Tierney 1999):


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



Codification: knowledge is transformed so that it can be stored in databases
and then easily accessed and used by anyone in the company; while
codification 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, the
efficient reuse of codified knowledge is essential, because their business
model is based on fast and cost-effective service, which an efficient system
of knowledge reuse provides. Firms or organisations that follow a
codification strategy rely on this. Once a knowledge asset – software or
manual – is developed and paid for, it can be used many times by many
people at very low cost, provided it does not have to be substantially
modi fied at each use. Re-use of know ledg e s aves work, reduces
communication costs and makes it possible to take on more projects;

Of course, all firms and organisations use both strategies, but the
hypothesis 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 knowledge
management follows one strategy, 20% the other. Those that try to excel at
both risk failing at both. The argument is that the selection of a particular
knowledge management strategy must reflect the firm’s or organisation’s
business model, which relies either on knowledge reuse or on unique
problems and expertise. Interesting for a survey is that various dimensions of
knowledge management will differ, depending on the firm’s main strategy.
There is thus an issue to identify consistent set of practices based on a
dominant 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

20

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


I.1. MEASUREMENT OF KNOWLEDGE MANAGEMENT PRACTICES

power. It is also a matter of identifying what are the most important
“intangibles” to show up for a company. Those most important intangibles
being closely related to the KM strategy (personalisation and social network or
codification and ICT systems) selected.

1.6. Knowledge Management Surveys
The lack of systematic evidence for KM activities is due to the fact that
very few large scale surveys have been carried out.3 Surveys that have been
done 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,4 the 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 the
instability of the notions of tacit and codified knowledge, knowledge and
information, knowledge and competence, and expert systems). Researchers,
experts and statisticians are nowadays in the same position as researchers
and statisticians interested in working on R&D over fourty years ago. The
historical analogy with the emergence of statistical works on R&D has,
however, some limitations: R&D expenditures (and personnel) are easily
quantifiable, while we have no clearly defined equivalents for knowledge
management.
The absence of a systematic terminology based on clear and widely
shared category increases dramatically the sensitivity of responses to
subjective perceptions and idiosyncratic understanding of “what is KM?” The
effect of such ambiguity and lack of stable categories is amplified by the fact
that KM methods and processes are not yet (and perhaps will never be)
associated with the same departmental or functional budget throughout firms
and 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 a
highly 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 in
the case of a R&D survey, which is addressed in principle to R&D people.
Secondly, because there was no previous experience in national
statistical offices in OECD countries of doing KM surveys, the existing surveys
done by other organisations cannot make the link between data on

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

21


I.1. MEASUREMENT OF KNOWLEDGE MANAGEMENT PRACTICES

KM practices and the common economic performance and innovation
indicators. These surveys limit, thus, the scope of questions about
performance to subjective perceptions of the benefits (expected and “actually
realised”). Works on these issues tend, therefore, to be “self referential” in the
sense that they are not validated by external economic criteria, such as
revenues or profits.
There is, thus, a need for various tasks that could be achieved through the
design, implementation and exploitation of an international survey carried
out 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 tracked
between R&D data, innovation data, and KM data. At a first glance, it could be
considered that variations in:


R&D intensity;



innovation intensity;



types of innovation;



appropriation strategies (patent, secrecy, lead time, complementary asset);
and,



sources of innovation and information (internal, users, universities,
suppliers) should be related to various KM strategies and practices. This is,
however, a rather uncertain conjecture which is discussed in the Chapter by
Elizabeth Kremp and Jacques Mairesse.

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 well-

22

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


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 can
contribute largely to the stabilisation of basic categories and to the
development of a common language on knowledge practices. This follows the
practice 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 in
Ottawa in September 2000, a working group was set up, 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 met four times
in 2001, in Copenhagen, Ottawa, Paris and Karlsruhe. A questionnaire was
devised during the course of the four meetings and the information emerging
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.
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 of
strategies were possible: either implementing the whole survey as a pilot
study or lodging a 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.
To date, four pilot studies have been carried out, to which this book is
largely 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 of
varying size (from 1 employee upwards), belonging to 7 different sectors. The
Danish study (CFL) covered 61 firms of varying size (from 1 employee
upwards), belonging to all sectors of the economy. The French study (SESSI)
adopted the second strategy, which was to merge four questions on
knowledge 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 be
noticed that Japan adopted more recently the same strategy – lodging four
questions on KM in the Japanese National Innovation Survey 2003. Results will
be available in Autumn 2003.

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

23


Tài liệu bạn tìm kiếm đã sẵn sàng tải về

Tải bản đầy đủ ngay

×