i
PRAISE FOR
THE KNOWLEDGE
MANAGER’S HANDBOOK
‘I’ve been working in knowledge management for over 20 years and I still picked
up some new ideas from The Knowledge Manager’s Handbook that will make my
work easier. Knowledge managers will find themselves returning to this book
again and again.’
Nancy Dixon, Common Knowledge Associates
‘A brilliant book with practical and grounded approaches, believable case studies
and fabulous tips that made me want to revisit my entire KM programme.’
Murni Shariff, former Senior Manager, Knowledge Management and
Institutional Capability, PETRONAS, Malaysia
‘If you are new to KM, this will be the book to help you get started quickly and
surely. If you are already an experienced knowledge manager, you’ll be surprised
how this book can help you check your blind spots and show you how to move
forward.’
Mavis Lee, former Head of Knowledge Management, Singapore Army,
Training and Doctrine Command
‘This is the most comprehensive book I have ever read on the implementation of
KM. Whether you are just starting out or a seasoned professional, it is all here.
An absolutely first-rate reference.’
Robert H Buckman, retired Chairman and CEO, Bulab Holdings, Inc
‘A long-awaited knowledge manager’s handbook based on a simple,
comprehensive and pragmatic roadmap on how to successfully implement KM in
an organization. The tips and real case studies provided throughout the book
nicely illustrate the concepts presented. A must-have in your KM book
collection!’
Professor Vincent Ribière, Managing Director and Co-founder, Institute for
Knowledge and Innovation Southeast Asia (IKI-SEA)
ii
‘Exploiting knowledge management for business gain or competitive advantage
is a broad, multifaceted affair that brings with it many questions; this book not
only identifies them, but gives sensible answers to them too.’
Colin Cadas, former Associate Fellow KM, Rolls-Royce plc
‘For knowledge practitioners, no other KM book comes close. Milton and Lambe
cover a comprehensive set of topics and challenges spanning the conception of
KM to post-implementation, as well as treatments on change management and
sustainability, two of the hardest problems in any KM journey. Valuable in-depth
case studies further enhance the value of this practitioner’s bible.’
Eric Tsui, Professor and Associate Director, KM and Innovation Research
Centre, The Hong Kong Polytechnic University
iii
Second Edition
The Knowledge
Manager’s
Handbook
A step-by-step guide to embedding
effective knowledge management
in your organization
Nick Milton
Patrick Lambe
iv
Publisher’s note
Every possible effort has been made to ensure that the information contained in this book is
accurate at the time of going to press, and the publishers and authors cannot accept responsibility for any errors or omissions, however caused. No responsibility for loss or damage
occasioned to any person acting, or refraining from action, as a result of the material in this
publication can be accepted by the editor, the publisher or the authors.
First published in Great Britain and the United States in 2016 by Kogan Page Limited
Second edition published in 2020
Apart from any fair dealing for the purposes of research or private study, or criticism or review, as
permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of
the publishers, or in the case of reprographic reproduction in accordance with the terms and licences issued by the CLA. Enquiries concerning reproduction outside these terms should be sent
to the publishers at the undermentioned addresses:
2nd Floor, 45 Gee Street
London
EC1V 3RS
United Kingdom
www.koganpage.com
122 W 27th St, 10th Floor
New York, NY 10001
USA
4737/23 Ansari Road
Daryaganj
New Delhi 110002
India
© Nick Milton and Patrick Lambe, 2016, 2020
The right of Nick Milton and Patrick Lambe to be identified as the authors of this work has been
asserted by them in accordance with the Copyright, Designs and Patents Act 1988.
ISBNs
Hardback 978 1 78966 035 7
Paperback 978 0 7494 8460 6
eBook
978 0 7494 8461 3
British Library Cataloguing-in-Publication Data
A CIP record for this book is available from the British Library.
Library of Congress Cataloging-in-Publication Data
Names: Milton, N. J. (Nick J.), author. | Lambe, Patrick, 1960 author.
Title: The knowledge manager's handbook : a step-by-step guide to embedding
effective knowledge management in your organization / Nick Milton,
Patrick Lambe.
Description: Second edition. | New York, NY : Kogan Page, 2020. | Includes
bibliographical references and index. |
Identifiers: LCCN 2019031191 (print) | LCCN 2019031192 (ebook) | ISBN
9781789660357 (hardback) | ISBN 9780749484606 (paperback) | ISBN
9780749484613 (ebook)
Subjects: LCSH: Knowledge management.
Classification: LCC HD30.2 .M5465 2020 (print) | LCC HD30.2 (ebook) | DDC
658.4/038--dc23
Typeset by Integra Software Services, Pondicherry
Print production managed by Jellyfish
Printed and bound by CPI Group (UK) Ltd, Croydon CR0 4YY
v
We dedicate this book to the knowledge managers around the
world from whom we have learned so much, to our colleagues
with whom we have learned, and to our families, for their
patience and understanding in supporting the often
challenging life of a professional knowledge manager.
We also thank Linda Davies, Barbara Fillip, Hank Malik,
Suleiman Al Toubi, Dan Ranta, Tan Xinde, Doreen Tan and
Roznita Othman, whose real-life KM stories are included as
Chapters 30 through 36. Your willingness to share the lessons
from your journeys is a beacon to knowledge managers
everywhere.
vi
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vii
CONTENTS
About the authors xviii
Foreword by Laurence Prusak xx
Introduction
1
PA R T O N E Orientation to knowledge
management implementation
01
What is knowledge management?
5
7
Introduction 7
Definition 7
The seven main components of knowledge management 9
Translating KM into business terms 11
The supply chain analogy 14
The essential elements of knowledge management 14
Knowledge management as orchestration 18
Summary 20
References 20
02
The stages of KM implementation
22
The different implementation approaches 22
Our recommended approach 22
The parallel opportunity-led programme 28
Escalating levels of management decision 29
Summary 30
Reference 30
03
Barriers and pitfalls
31
Survey evidence 32
Lessons from the field 34
Summary 43
References 44
viii
Contents
PA R T T WO Preparation and resources
04
Knowledge management strategy
45
47
Deciding the strategic principles 47
Identifying the business drivers 48
Defining the knowledge management vision 49
Agreeing the knowledge management scope 50
Defining the strategic knowledge areas 50
Assessing the current state of knowledge management 51
Creating a draft knowledge management framework 52
Deciding how to handle change management 52
Creating a business case 53
Summary 53
References 54
05
The role, skills and characteristics of the
knowledge management leader 55
The role of the knowledge management leader 56
Should the knowledge management leader be an internal or
external appointment? 57
The most important characteristic for an external
appointment 58
What competencies does the knowledge management
leader need? 59
The personality trap 60
A metaphor 61
Summary 63
References 63
06
The KM team members
64
How big should your KM team be? 64
What skillsets will you need on your team? 66
Attitude and values 68
Team roles 68
Summary 69
Reference 70
Contents
07
The role of senior management
71
The role of the sponsor 71
The risks to effective sponsorship 73
The knowledge management steering team 74
Working with the other senior managers 75
Summary 76
08
Budget and timescale
77
The need for a budget 77
How big will the budget need to be? 78
Assigning your budget among the four KM enablers 78
Benchmarking your budget 80
How long will it take to implement knowledge management? 81
Beware the self-funding trap 83
Summary 84
Reference 84
09
Aims and objectives for the KM implementation
programme 85
Benefits mapping 85
The interim objectives 89
Making the objectives SMART 90
Impact metrics for knowledge management 91
Setting the value targets and estimating ROI 95
Dealing with imposed targets 96
What if you can’t measure value in monetary terms? 97
Not all measures should be targets 97
Summary 98
References 99
10
Finding partners to help you
100
Who should be responsible for KM? 100
KM as partnering 103
Initiating a partnership 105
Transitioning the partnerships 107
Identifying non-obvious partners 108
Summary 111
References 111
ix
x
Contents
PA R T T H R E E Assessment and planning
11
Conducting the knowledge resources audit
113
115
What is a knowledge resources audit? 116
How does the audit help a KM implementation? 117
What are we auditing? 117
What are the steps in a knowledge resources audit? 120
Analysing the results of the audit 121
Summary 124
References 125
12
The knowledge management framework
126
What is a management framework? 126
Why we need a framework for KM 128
A template for your KM framework 129
When you might need more than one framework 132
Summary 133
Reference 133
13
The knowledge discussion elements of the KM
framework 134
Dialogue as the preferred form of discussion 134
Roles for knowledge discussion 135
Processes for knowledge discussion 139
Technologies for knowledge discussion 142
Governance for knowledge discussion 143
Summary 144
References 144
14
The knowledge capture and documentation
elements of the KM framework 145
The difference between documented knowledge
and information 145
Roles for knowledge documentation 146
Processes for knowledge documentation 148
Technology for knowledge documentation 153
Governance for knowledge documentation 155
Summary 156
References 156
Contents
15
The knowledge synthesis elements of the KM
framework 157
What is knowledge synthesis? 157
What does synthesized knowledge look like? 158
Roles for knowledge synthesis 160
Processes for knowledge synthesis 161
Technologies for knowledge synthesis 163
Governance for knowledge synthesis 165
Summary 166
References 166
16
The knowledge-finding and re-use elements
of the KM framework 167
The challenges of knowledge re-use 168
Incentivizing knowledge seeking 168
The importance of making knowledge findable and accessible 169
Roles for knowledge finding and re-use 170
Processes for knowledge finding and re-use 172
Technologies for knowledge finding and re-use 174
Governance for knowledge finding and re-use 176
Summary 177
References 178
17
Knowledge organization
179
Grounding knowledge organization in the business drivers 179
The three components of knowledge organization 180
Taking an evidence-based approach to knowledge
organization 184
Using the knowledge resources audit to focus on what counts 185
Testing and validating your knowledge organization system 186
Summary 187
Reference 188
18
Influencing the stakeholders
189
The steps of the buy-in ladder 189
The knowledge manager as salesperson 191
Segmenting your audience 192
Influencing tactics 194
xi
xii
Contents
When to use the influencing techniques 198
Summary 198
References 199
19
Culture, communications and change
200
KM as an agent of culture change 200
Mapping the current culture 201
Understanding the cultural drivers 205
The KM paradigm shift 206
Communication and change 207
The communication plan 209
Summary 210
References 210
20
Preparing the KM implementation plan
212
How to create the implementation plan 212
Potential elements of the KM plan 216
Summary 223
PA R T FO U R The implementation activity
21
Building the KM champion network
227
What is a KM champion? 227
What KM champions do 228
How to identify potential KM champions 229
Maintaining the motivation of the KM champions 231
Supporting the KM champions 234
Summary 237
References 237
22
Trials and pilots
238
Proof-of-concept trials 238
Where to look for quick wins 241
Selecting KM pilot projects 241
225
Contents
The ‘minimum viable KM framework’ 243
Delivering KM pilots 244
Reaching the organizational decision point 248
Summary 249
Reference 249
23
Roll-out, embedding and governance
250
What does embedding mean? 250
Examples of embedded KM 251
Finalizing the KM framework 254
The governance elements of the KM framework 254
The KM policy 255
KM roll-out 258
Celebrating the successes 259
Tracking the roll-out phase 261
Summary 262
References 262
24
Setting up the KM metrics and reporting system
The different kinds of metrics and their purposes 263
Examples of KM metrics 267
KM performance management 270
KM metrics reporting 271
KM metrics as a learning opportunity 272
Summary 273
References 273
25
Dealing with bumps in the road
274
Dealing with common objections 274
Challenge scenario 1: over-enthusiastic support 276
Challenge scenario 2: death by a thousand cuts 278
Challenge scenario 3: perpetual reset mode 279
Challenge scenario 4: the showstopper 281
Summary 282
Reference 283
263
xiii
xiv
Contents
26
Transition to the operational team
284
The decision to close the implementation programme 285
The role of the KM team after implementation 286
Knowledge management refresh and update 287
Summary 289
References 289
PA R T F I V E Deepening and extending your KM
programme
27
291
Working with external frameworks and standards
293
The benefits and limitations of generic KM frameworks 294
KM maturity models – opportunities and dangers 295
KM awards – benefits and limitations 298
Standards development in KM 300
Using the ISO 30401:2018 KM standard 303
Self-audit or external audit? 304
Summary 308
References 308
28
Working externally
310
Building your KM peer networks 310
Working with trusted consultants 312
Working with technology vendors 316
Scoping and issuing tenders for KM projects 317
Summary 324
Reference 324
29
Knowledge management and digital transformation
The relationship between KM and digital transformation 325
The core technologies of digital transformation 327
The limitations of artificial intelligence (AI) 329
KM implications of digital transformation and AI 331
Summary 337
References 337
325
Contents
PA R T S I X Case histories
30
Implementing KM at Mars
339
341
By Linda Davies, former Knowledge
Management Director, Mars, Incorporated
Know why you’re doing what you are doing 341
Focus on critical activities that help deliver strategy 342
Plan the roll-out to build the KM story 344
Go where there is ‘pull’ and keep all activities relevant
to the business and to associates 344
Measure the business impact of KM activities 345
Be consistent 346
Select the team members carefully 346
Build top-down support 347
Embed critical knowledge via existing business processes 348
When is it over? 348
Summary 349
31
NASA – emergence, evolution and resilience
of a KM programme 350
By Barbara Fillip, former KM lead within the Flight Projects
Directorate, Goddard Space Center
Building a resilient KM programme 351
The NASA KM Community 351
KM at NASA Headquarters: a tight bond
with internal training 352
KM at a NASA Center: Goddard Space Flight Center 354
Evolution of KM at headquarters and at the Centers 355
Strengthening of the programme at the Agency
and Center levels 356
A new beginning for a resilient KM programme
and a focus on continuous improvement 359
Summary 360
References 361
xv
xvi
Contents
32
Using the ISO KM standard 30401:2018 to sense-check
KM at Petroleum Development Oman 363
By Hank Malik and Suleiman Al Toubi, Hank Malik is KM
Programme Lead, PDO and Dr Suleiman Al Toubi is former Asset
Oil Director, PDO and visiting industry academic, Muscat
University, Oman
Introduction 364
The standard’s key requirements and PDO KM reflections 364
Conclusions 373
Summary 373
33
KM implementation in a global oil and gas company
374
By Dan Ranta, KM Leader at GE
A focus on collaboration 374
Connecting sharing to the business – a bold approach 375
The link between knowledge networks and business results 376
Connecting people and governance 377
Visible leadership led to knowledge network growth 378
Building sustainability 378
Knowledge discussions and lesson learning 379
Promoting knowledge re-use 379
Knowledge synthesis: closed discussions
and an enterprise wiki 380
Measuring knowledge network activity 381
Summary 381
Reference 382
34
KM implementation at Huawei
383
By Tan Xinde, former leader of the Huawei KM programme
The value of KM to Huawei 384
The start of Huawei’s KM journey 385
Going from the HQ to the frontline 388
Explicit vs tacit knowledge management 389
The current state of KM in Huawei 389
Summary 391
Contents
35
KM implementation at the Singapore Youth
Olympics 392
By Doreen Tan, former Head Knowledge Management, Singapore
Youth Olympic Games Organizing Committee
Facilitating the smooth flow and exchange of information 393
Cultivating a learn-as-you-go culture 394
Retaining and transferring Games know-how 396
Summary 397
36
Implementing and sustaining KM in the
Public Works Department Malaysia 398
By Roznita Othman, former Knowledge Management
Director, PWD
PWD Malaysia is a knowledge-intensive organization 399
The beginning of the KM journey 399
KM initiatives 401
Key challenges for KM 405
How KM was sustained 406
Areas of future improvement 407
Summary 408
Summary
409
Glossary 410
Index 421
xvii
xviii
ABOUT THE AUTHORS
Dr Nick Milton
Dr Nick Milton is director and co-founder of Knoco Ltd (www.knoco.com)
and has worked in the knowledge management field since 1992.
Working with Knoco Ltd, Nick has helped develop and deliver KM strategies, implementation plans and services in a wide range of different organizations around the globe. He has a particular interest in Lessons Learned
programmes, managing major lessons capture programmes in fields such as
mergers and acquisitions and high-technology engineering, and also specializes in the development of KM Frameworks. Prior to founding Knoco, Nick
spent two years at the centre of the team that made BP the leading KM
company in the world at the time, acting as the team Knowledge Manager,
developing and implementing BP’s knowledge of KM development and implementation, and coordinating the BP KM Community of Practice. Prior to
this he acted as Knowledge Manager for BP Norway for five years.
Nick is the author of The Lessons Learned Handbook and Knowledge
Management for Teams and Projects, co-author of Knowledge Management
for Sales and Marketing, Performance through Learning: Knowledge management in practice and Designing a Successful KM Strategy: A guide for the
knowledge management professional. He is a member of the ISO working
group that authored ISO 30401:2018, the KM standard. Nick blogs most
days at www.nickmilton.com and can be found on Twitter at @nickknoco.
Patrick Lambe
Patrick Lambe is founding partner of Straits Knowledge, a knowledge management consulting and research company headquartered in Singapore
(www.straitsknowledge.com). He divides his time between Singapore, Kuala
Lumpur, and Dublin, Ireland. He has been working in knowledge management since 1998.
With Straits Knowledge, Patrick has conducted knowledge audits and
supported clients in developing and implementing knowledge management
strategies across Asia and the Middle East. He has a particular specialization
About the authors
in knowledge organization and taxonomy development, with clients in the
United States, Europe, the Middle East and Asia. Before working in KM,
Patrick’s background was in Library Science and learning and development.
Patrick is two-term former president of the Information and Knowledge
Management Society, and founding President of the International Society
for Knowledge Organization Singapore Chapter. He is a Visiting Professor
in KM at Bangkok University, and a member of the Editorial Advisory Board
of the top-ranked Journal of Knowledge Management.
Patrick is the author of Organising Knowledge: Taxonomies, knowledge
and organisational effectiveness and The Blind Tour Guide: Surviving and
prospering in the new economy, and co-author of KM Approaches, Methods
and Tools: A guidebook and Knowledge Management Competencies: A
framework for knowledge managers. Patrick blogs at www.greenchameleon.
com and can be found on Twitter at @plambesg.
xix
xx
FOREWORD
Although humans of a speculative nature have been thinking about knowledge since there has been written language (and most likely before that), it
is only recently that anybody has tried to think about how to ‘manage’
knowledge in an effective manner within organizations and governments.
The reasons for this are varied, and it would be presumptuous of me to
try to list them here. Suffice to say there wasn’t much need or incentive to do
so until it was acknowledged and widely understood that knowledge has
serious economic potential – maybe even more than the traditional sources
of wealth: land, labour and capital.
The confluence of several economic forces spurring on this revelation led
such thinkers as Peter Drucker, Ikujiro Nonaka and others to begin writing
in the late 1980s on knowledge, knowledge work and, most importantly,
how one could realistically manage knowledge with the existing tools and
models.
This led pioneer organizations across many industries to attempt to do
just this – somehow to figure out what knowledge they had, or had potential
to acquire, and try to manage it effectively, efficiently and with measures to
judge how well they were doing.
Many of these early attempts failed, mainly because there was no agreement even within organizations as to what knowledge actually was, and
how it might be different from data, information, judgment, etc. To this
problem was added a powerful techno-utopian fantasy (especially in the
Anglophone countries) that an organization’s knowledge could somehow be
digitized and easily made accessible to whomever needed it.
However, the subject has survived all this – and much more – because of
the very apparent need for any organization to actually know what it knows,
use what it knows, and to know new things. Anyone with even a modicum
of sense cannot fail to think this is worth doing in the 21st century.
And here are two very experienced knowledge practitioners and thinkers
to help all of us get through the difficulties of bringing forth a desperately
needed new practice – still not taught much in business schools or recognized by economists – with clarity, insight, many good examples and good
writing. Hooray for them!!!
Laurence Prusak
consultant and teacher
1
Introduction
There is nothing more difficult to take in hand, more perilous to conduct,
or more uncertain in its success, than to take the lead in the introduction
of a new order of things, because the innovator has for enemies all those
who have done well under the old conditions, and lukewarm defenders in
those who may do well under the new.
machiavelli (1532)
Machiavelli was writing about political change, but he could equally well
have been writing about knowledge management (KM).
For many organizations, knowledge management is something new, and
implementing KM can be extremely difficult and politically challenging.
Recent history is littered with failed attempts to introduce programmes of
change into organizations, and KM is no exception. However, despite the
challenges, some organizations have succeeded in introducing KM, embedding it into the way they work, and delivering considerable value as a result.
Implementing and sustaining KM can be done, and has been done.
The book is intended as a practical guide for the working knowledge management professional, and for anyone else who wishes to get an overview of
what is involved in introducing KM to an organization in a sustainable,
value-adding way. Although we provide references where further reading
might be useful, this is not an academic treatise on KM – there are many of
those on the market already. Instead we have constructed this book as a practical roadmap, based on our own experiences and on numerous examples of
successful, and some less successful, KM implementations. This second edition of the book builds on the first edition, adding elements that have increased in importance in the past four years, including KM’s role in digital
transformation, stronger links with artificial intelligence and machine learning, and the publication of ISO 30401:2018, the ISO management system
standard for knowledge management.
The book contains several sections, as shown in Figure 0.1. You can either
start reading from the beginning, or jump to the implementation step most
relevant for you.
2
Figure 0.1
Orientation to KM
implementation
Preparation and
resources
Assessment and
planning
Assessment and
planning (cont’d)
Implementation
The structure of this book
1. WHAT IS KNOWLEDGE
MANAGEMENT?
4.
KM
STRATEGY
11.
K RESOURCES
AUDIT
21.
KM CHAMPION
NETWORK
6.
KM
TEAM
12.
KM
FRAMEWORK
17.
KNOWLEDGE
ORGANIZATION
30.
MARS
18.
INFLUENCING THE
STAKEHOLDERS
22.
TRIALS AND
PILOTS
31.
NASA
7.
SENIOR
MANAGEMENT
13.
DISCUSSION
23.
ROLL-OUT
27.
FRAMEWORKS
AND STANDARDS
Deepening and
extending
Case histories
5.
KM
LEADER
2. THE STAGES OF
IMPLEMENTATION
3. BARRIERS AND PITFALLS
8.
BUDGET &
TIMESCALE
14.
CAPTURE
15.
SYNTHESIS
19.
CULTURE,
COMMUNICATIONS
AND CHANGE
24.
METRICS
33.
OIL
COMPANY
10.
PARTNERS
16.
RE-USE
20.
THE KM
IMPLEMENTATION
PLAN
25.
BUMPS IN THE
ROAD
28.
WORKING
EXTERNALLY
32.
PDO
9.
AIMS AND
OBJECTIVES
26.
TRANSITION TO
OPERATIONAL
TEAM
29.
KM AND DIGITAL
TRANSFORMATION
34.
HUAWEI
35.
SINGAPORE
YOUTH
OLYMPICS
36.
PUBLIC
WORKS DEPT
MALAYSIA
Introduction
The first section of the book, Chapters 1 through 3, gives a general introduction, including an orientation to KM and what it covers, an overview of the
implementation steps, outlining our recommended approach, and the top
ten barriers and pitfalls you will face.
This is followed by a section on preparation (Chapters 4 through 10),
covering the resources you need to have in place before you begin – the
overall strategy, the people, the budget, the objectives, the partners.
The longest section of the book (Chapters 11 through 20) covers assessment and planning, as this is where most of the critical decisions are made.
We introduce the audit process, and the concept and potential components
of a KM framework. Then we address the issues of stakeholder management, communication, culture and detailed planning.
Part Four (Chapters 21 through 26) covers the process of implementation
itself; the creation of the KM champions network, the ‘trials and pilots’
stage, the roll-out programme, the system of metrics and reporting, the ‘road
bumps’ you may encounter, and the transition to operational KM.
Part Five (Chapters 27 to 29) is mostly new material. These chapters deal
with the opportunities and challenges of working with frameworks and
standards and the use of external audits, the use and value of external support in the form of consultants, vendors, peer networks and consortia, and
the increasingly close links between KM and digital transformation.
We round off the book in Part Six with a series of case studies (three of
them new to this edition) describing how KM was implemented in a multinational food products company, a national aerospace body, two different
kinds of oil company, a Chinese telecoms giant, a public-sector sports organization, and a Malaysian government department..
We have been pleased and honoured by the response to the first edition
of this book. We are always happy to receive feedback and suggestions for
how our book might better serve as a reliable and valuable companion to
your KM implementation journey. In many ways, this is the book we wish
had been available when we began our own KM journeys over 25 years ago;
it might have saved us a few pitfalls along the way!
May it do so for you.
Reference
Machiavelli, N (1532) The Prince [online] https://www.constitution.org/mac/
prince00.htm (archived at https://perma.cc/R27V-AF7R) [accessed 26 January
2019]
3
4
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5
PART ONE
Orientation
to knowledge
management
implementation
Executive summary
Chapter 1 will give you a rapid overview of how to define KM in practical
terms for your organization. It stresses the importance of taking a holistic,
balanced approach to KM, and will help you figure out when the KM implementation is out of balance. Chapter 2 sketches out the pros and cons of
different KM approaches, and identifies the main phases of KM implementation. This chapter provides a roadmap to the rest of this book. Chapter 3
identifies the most common implementation pitfalls to avoid.
6
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7
What is
knowledge
management?
01
Introduction
This chapter tackles, as best it can, the thorny topic of what knowledge
management (KM) actually is, and what it entails. It contains the following
elements:
●●
a definition of KM, and a comparison with other disciplines;
●●
the six main components of KM;
●●
a translation of KM into business terms;
●●
the supply chain as an analogy for KM;
●●
the essential elements of KM;
●●
KM as orchestration.
Definition
There’s a saying that if you put five knowledge managers in a room, they
will come up with seven definitions of what KM is. This is apocryphal, but
it reflects reality. There is a lot of debate and confusion about the nature of
KM, none of which is helpful to you as you attempt to implement it within
your organization. Hence, your first step, together with your line manager
and the steering group for the KM implementation programme, should be
to come to a common definition and understanding of what ‘knowledge
management’ means in your organizational context.
Our view is that KM is the latest in a range of management disciplines,
and is the discipline with knowledge as its focus. The ISO Knowledge
Management Standard, ISO 30401:2018 defines KM as ‘management with
8
Orientation to Knowledge Management Implementation
regard to knowledge’ (ISO, 2018). So ‘knowledge management’ (or KM)
represents a way of managing work, paying due attention to the value and
effect of an intangible asset, namely, knowledge.
Knowledge is one organizational resource among many. For centuries,
organizations have managed their visible assets and resources, such as
money, people, property and equipment. More recently organizations have
been addressing their intangible assets, such as information, reputation, intellectual property, customer relationships, the diversity and talent of their
staff, their ability to work safely and sustainably, and now their knowledge.
Knowledge management is therefore just the latest management discipline dealing with intangibles. Risk management, quality management,
­customer relationship management, brand management, reputation management, talent management, safety management – all deal with intangibles,
and the implementation programmes for these analogous disciplines can all
provide a model for implementing KM. Look at the discipline closest to KM
that is already embedded in your organization and ask, ‘How did we implement this? How are we sustaining this? What lessons are there for the KM
programme?’
In the industrial sector, probably the closest analogue disciplines for KM
are safety management and risk management. Neither of these disciplines
involve the management of tangibles – neither safety nor risk are things you
can pick up, weigh and put in your pocket. They are about how you manage your organization so that safety and risk are given priority, and so that
people’s safety behaviours and risk behaviours change. This is exactly what
we are looking for from KM. So if your organization has, in the past, successfully introduced risk management and safety management, then you
should be greatly encouraged, as KM can then follow a proven implementation path.
KM can also be placed within the same governance framework as the
other disciplines. You can position it within the same structures and expectations, and you can review it using the same review processes; the stage
reviews of the project management framework, for example. In other
words, you can (and should) embed KM within ‘normal work’. How are
the other disciplines sustained? Do they have a company policy? Support
staff? Roles embedded in the business? KM will probably need something
similar. This does not mean that you reproduce the frameworks from other
disciplines, but it does mean you can learn from them. Any analogue
­discipline that has successfully been embedded is a learning opportunity for
your KM ­implementation.
What is Knowledge Management?
Tip
Find the people who were responsible for implementing the latest new
management framework in your organization (eg risk management, quality
management, diversity management, or safety management) and conduct a
learning session with them. Probe for the things they did that were
successful and ask for their advice. Find out the things they tried that did
not work, work out why they did not work, and discuss how you might avoid
these pitfalls yourself. Focus on what was needed to fully embed the
framework.
The seven main components of knowledge
management
Looking at KM as ‘intangible asset management with knowledge as a focus’
may help us align it with other management disciplines, but does not particularly help us understand in detail what KM entails, and what it could
look like in your organization.
Surveys conducted by Knoco in 2014 and 2017, with responses from
over 700 knowledge managers from around the world, explored this issue
by asking the respondents to prioritize, from a list of 11 potential KM approaches, the ones that they focused on as part of their KM implementation
(Knoco, 2017). Table 1.1 shows which elements were given highest priority.
Table 1.1
Survey results showing the priority given to different elements of KM
Knowledge management
element
Percentage of respondents that
judged this element to be the highest
priority for their KM programme
Connecting people through
communities and networks
19%
Improved access to documents
(including search and portals)
17%
Knowledge retention
13%
(continued)
9
10
Orientation to Knowledge Management Implementation
Table 1.1
(Continued)
Knowledge management
element
Percentage of respondents that
judged this element to be the highest
priority for their KM programme
Learning from experience
12%
Creation and provision of Best
Practices
10%
Innovation
6%
Provision of knowledge to
customer-facing staff (support/
sales)
6%
Improved management of
documents
5%
Accessing external knowledge
and intelligence
4%
Knowledge-based engineering
3%
Big Data
1%
SOURCE Knoco Ltd
In this book, we focus mainly on the top seven items, which together represent the primary focus for over 80 per cent of respondents:
●●
connecting people;
●●
improved access to documents;
●●
retention of knowledge;
●●
learning from experience;
●●
creation of best practices;
●●
innovation;
●●
provision of knowledge to customer-facing staff.
Different industries and markets may favour different components, and
­priorities will shift depending on circumstance and need, but in combination
these seven seem to pretty much map out the mainstream field of KM as it
is currently understood.
What is Knowledge Management?
Tip
Use Table 1.1 as a discussion point with your manager. Decide how you will,
in your organization, prioritize the seven core components of KM. Avoid the
temptation to ignore any of these seven completely (unless, of course, you
have no customers, or have no need for innovation or documents), but they
will not all be of equal priority for you. As you attempt to rank them, you will
find yourself discussing important distinctions for your business.
Translating KM into business terms
All of the seven KM components above are expressed in KM terms. When
we communicate to the business about KM, we need to avoid using KM
terminology and instead talk about business issues. We need to identify the
business problems or issues that the KM solutions will address, and talk
about KM in business language.
We can think of an organization as a large-scale entity that needs to solve
three broad types of business problem in order to function effectively. Each
of these problem types generates specific business problems that KM solutions can address.
Coordination
The different parts of the organization need to be able to coordinate their
activities, maintain shared objectives, avoid mistakes in handoffs, and keep
track of how they are making progress on common tasks. Business issues
here include:
Collaboration – bringing together knowledge from different parts of the
business to develop better ways of working, using the knowledge you
already have, but which is scattered and siloed. Here you use KM
approaches from the ‘connecting people’ component, such as communities
of practice.
Hand-offs and situational awareness – ensuring effective communication of
knowledge between teams and workgroups. Here you can use task flows,
shared calendars, shared knowledge bases, checklists and standard
11
12
Orientation to Knowledge Management Implementation
templates, as well as the processes and policies that guide their use.
Communication of knowledge to customers can also be considered a
hand-off issue.
Document and information management – making sure that important
shared documents and other forms of information content are made
easily accessible to those who need them, regardless of which part of the
organization produces them. Here you would use knowledge inventory
audits to identify high-priority information for sharing, and taxonomies
and information architecture to ensure they are easily findable. You may
also need to align your knowledge-sharing and information security
policies to ensure that this information is actually accessible to those who
need it.
Memory
The organization needs to be able to retain key capabilities such as skills,
stakeholder/partner relationships, experience and expertise as people come
and go, and to keep track of its plans, decisions, activities and commitments.
Business issues here include:
Keeping records of knowledge – ensuring that critical knowledge about
key decisions, plans and activities is documented, and embedded into
process and procedure, rather than relying solely on ‘tribal knowledge’.
Here you would combine records management approaches, plus
systematic capture of knowledge, with an ownership structure, ensuring
that someone is accountable for the continuity of each knowledge
topic.
Maintaining capabilities over time – addressing the risk of loss of critical
knowledge and capability as people retire, and ensuring that this
knowledge is retained, made available to, and used by the remaining and
replacing workforce. Here you use approaches from the knowledge
retention component.
Learning
The organization needs to be able to respond appropriately to changes in its
external environment, adapt its practices accordingly, and internalize what
it learns. Business issues here include:
What is Knowledge Management?
Speeding up the learning curve – making sure your employees and teams get
up to speed quickly in new jobs or when dealing with new areas of work
(new projects, new markets, new products, new geographies). This is of
particular importance for organizations seeking to grow, diversify or
explore new frontiers, or organizations with rapid turnover of staff. This
can use a combination of many of the KM approaches above.
Continuous improvement – involves ensuring your projects and business
activities do not repeat the mistakes of the past, and that you can replicate
(and improve on) the successes. New knowledge is built into the
organization’s designs, processes and procedures so that it can build on
its solutions and successes. This is the area of project-based learning,
addressed through processes from the ‘learning from experience’
component.
Standardization – comparing and learning from the disparate practices
across the organization, to find the ones that work best in given
circumstances. Here you use approaches from the ‘best practices’
component. This may also include arming your customer-facing staff
with the knowledge they need to close the deal, or to delight the customer,
or it might involve providing self-help material for your users and
customers.
Business intelligence and decision support – systematically collecting, analysing
and disseminating information about your organization’s external and
internal environment, to support decision making, strategies and plans.
Here, dashboards, data visualization and analytical tools may help.
Development of breakthrough products and services – this business challenge
requires bringing together the knowledge of all relevant staff, together
with external knowledge, to build new ways of doing things, new
products, and new lines of business. Here you use KM processes from the
innovation component.
Tip
Take your prioritized list of KM initiatives from the previous exercise. See if
you can translate them into business terms by explaining how they support
your fundamental business needs.
13
14
Orientation to Knowledge Management Implementation
The supply chain analogy
A particularly useful analogy for KM is to liken it to a supply chain. We
generally think of a supply chain as giving a worker the supplies they need
to do their work. When they are constructing an airplane or selling tins of
beans in a supermarket, the materials they need have to be sourced, assembled and supplied. For a knowledge worker, the raw material of their work
is knowledge. Knowledge management can provide the supply chain through
which that raw material is sourced, assembled and supplied.
The analogy of the supply chain has the benefit of thinking about KM
from the point of view of the knowledge user. What knowledge do the
knowledge workers in your organization need to be able to make the right
decisions and take the right actions? How can that knowledge be supplied
to them both efficiently and effectively? How can it be sourced (the source
often being the experience of others), how can it be packaged in support of
their work, and how can it be transported to the user?
John Browne, the CEO of British Petroleum, was quoted in Prokesch
(1997) as saying that ‘anyone in the organization who is not directly accountable for making a profit should be involved in creating and distributing
knowledge that the company can use to make a profit’. This is a vision of the
organization as a knowledge supply chain, with the profit makers as the users.
Tip
Choose a key knowledge user in a critical role, in an activity you are familiar
with. Map out the knowledge they need to do their job, their knowledge sources,
and the knowledge resources they produce. Determine who the key knowledge
users for those resources will be. Note that sometimes the supply chain is a
loop – the same group of people may both create the knowledge and use it.
The essential elements of knowledge
management
We will discuss the elements of a KM Framework in greater detail in
Chapter 12, but three core principles underpin any KM Framework. They are
as follows.
What is Knowledge Management?
Principle 1. KM must address roles, processes,
technologies and governance
There are four enablers that support KM, like four legs supporting a table.
These are the factors that enable the flow and storage of knowledge:
●●
●●
●●
●●
The elements of roles and accountabilities, such as CoP leaders, knowledge
managers, and knowledge owners.
The process elements, such as after-action review, lessons capture,
knowledge asset creation etc.
The technology elements, such as portals, collaboration tools, search
engines, lesson management systems etc.
The governance elements, such as KM expectations and policy, metrics
and incentives, formats and protocols, taxonomies, and support.
The ISO standard for Knowledge Management, ISO 30401:2018 (ISO,
2018) adds ‘culture’ as a fifth enabler, but culture is different from those
listed above. It cannot be directly managed in the same way, and while it can
either enable or disable KM, it can also be changed through effective KM
practices. We discuss culture in Chapter 19.
Each of these elements should be mutually supportive and closely interconnected. Like the four legs on a table, the four elements of KM are all
equally important. No single element is dominant – they all support each
other, they all support KM, and they all support KM in supporting the business. For example, any one KM technology needs to integrate with other
technologies, and also with processes, roles and governance. If they don’t
integrate, they don’t align behaviours and pull together in a common direction. Through the integrated elements the two ingredients of KM – content
and conversation – begin to build and flow, and the supply chain begins to
deliver.
Principle 2. KM must cover both the elements of
connecting people through conversation, and
collecting and organizing content for access
This is one of the earliest models in the history of KM, but one that sometimes seems to get forgotten. Conversation and content – connecting and
collecting – represent two routes for knowledge transfer between knowledge
suppliers and knowledge users.
15
16
Orientation to Knowledge Management Implementation
The ‘connect’ route supports knowledge transfer through connecting
people and focuses on tacit knowledge sharing. To deliver this connection
we facilitate the transfer of knowledge through conversations, whether these
are electronically moderated or face-to-face.
The ‘collect’ route supports knowledge transfer through collecting knowledge into content and focuses on codified knowledge. To deliver this collect
approach we facilitate the transfer of knowledge through captured and codified content in the form of documents, files, text, pictures and video.
Connect and collect are not alternative strategies. They are complementary components of a single framework and a single strategy which work in
parallel. Your organization will contain critical knowledge of very many
kinds. Some of it needs to be managed as content, and some as conversations. Any complete KM framework needs to enable, promote, facilitate and
otherwise support both conversation and content. Each has its benefits and
drawbacks. Conversations are a far richer medium than content, while content is more scalable, can reach far more people, and has a longer lifespan.
Knowledge can be transferred more effectively through conversations but
more efficiently through content.
Managing conversation without content leaves no traces, other than in
the minds of the people involved. Unless new knowledge becomes embedded and documented in process, or guidance, or recommendations and new
ways of working, it is never truly ‘learned’, and without this we find knowledge has to be relearned many times, with errors being repeated, wheels reinvented and so on.
Managing content without conversation leads KM towards the already
established fields of content management and information management. A
focus on content without conversation results in a focus on creation of
knowledge bases, blogs and wikis as a proxy for the transfer of knowledge,
but unless people can question and interrogate the knowledge in order to
internalize it, learning can be very ineffective. No matter how smart your
systems, content does not know who you are or understand your contextual needs in the way that a colleague can, and it does not know how to
tune itself to your needs and current knowledge level in the way a good
mentor can.
When connect and collect work in unison, you will be supporting four
knowledge ‘transactions’ – discuss, document, synthesize, find/review – as
shown in Figure 1.1. This mirrors the four modes of conversion of knowledge described by Nonaka and Takeuchi (1995): socialization, externalization, combination and internalization.
What is Knowledge Management?
Figure 1.1
The four knowledge transactions
Push
Pull
CONNECT
Discuss
Document
Synthesize
Find/
Review
COLLECT
Table 1.2
T he four transactions of knowledge as interfaces between tacit
knowledge and codified knowledge
To tacit knowledge
To codified
knowledge
From tacit knowledge
Discuss
Document
From codified
knowledge
Find and review
Synthesize
As Table 1.2 shows, the four transactions occur when knowledge is transferred between or within the realms of tacit knowledge (‘knowledge in the
head’) and codified knowledge (‘knowledge captured in digital or written
form’).
Connect and collect therefore can be seen as representing the four transactions below:
●●
●●
●●
●●
discussion of knowledge, the means by which conversations on the
‘connect’ route are conducted;
documentation of knowledge, the means by which content on the ‘collect’
route is created;
synthesis of knowledge, the means by which content on the ‘collect’ route
is combined into new updated and structured knowledge, and old
knowledge removed;
search and review of knowledge, the means by which content on the
‘collect’ route is accessed and internalized.
17
18
Orientation to Knowledge Management Implementation
Principle 3. KM must address push and pull
(aka supply and demand)
Look back at Figure 1.1. The four knowledge transactions support both
push and pull, which represent knowledge supply and demand. Push is the
transfer of knowledge driven by supply (publishing, presenting, teaching,
blogging, tweeting or loading material to a knowledge base or wiki), and
pull is the transfer of knowledge driven by demand (asking a question on
a forum, or searching an intranet). The ideal KM framework runs push
and pull in parallel, as both supply and demand are valid ways of instigating knowledge flow. A KM supply chain, as described earlier, will require
demand (pull) for knowledge at one end of the chain, and supply (push) at
the other.
As in economics, push without pull (supply without demand) leads to
knowledge over-supply and overload, and ultimately to destruction of
knowledge value. Pull without push creates a market, but any market needs
to be supplied. Knowledge management, whether you view it as an internal
knowledge market or as a knowledge supply chain, needs both push and
pull to function.
Tip
Review the current balance within your organization between connect and
collect, and between push and pull. Which of these is dominant? It is
common to have systematic biases in the way knowledge is addressed: a
bias towards content push for example, or a bias towards connection
through technology. These will need to be balanced with other elements as
you develop your framework. If you find such a bias, consider how you can
rebalance.
Knowledge management as orchestration
Earlier in this chapter we talked about analogue disciplines similar to KM.
These are disciplines that you can learn from in implementing KM in your
organization. There are also partner disciplines that you will need to work
with. These include:
What is Knowledge Management?
●●
human resource – especially human resource development;
●●
organization development;
●●
information and data management;
●●
information security;
●●
risk management and governance;
●●
records management;
●●
IT management;
●●
internal communications teams and corporate communications teams;
●●
internet, intranet, portal and extranet management.
The ISO 30401:2018 standard refers to KM’s ‘adjacent disciplines’ and adds
data management, business intelligence, customer relationship management,
innovation management and quality management to this list (ISO, 2018).
These disciplines may already have some responsibility for some of the
business issues and related KM solutions we described above. In some cases,
there may be grey areas or fuzzy boundaries between your territory and
theirs. It is extremely important that you are able to:
a identify and recognize what they are currently doing that has a bearing
on KM;
b work with them to adapt what they are doing where there are KM gaps;
c negotiate the boundaries, integration and coordination points between
your work and theirs;
d scope KM projects and programmes collaboratively not competitively.
Later in this book we will cover stakeholder management and working with
partners, either in the direct lines of business, or in these partner (or competitor) disciplines. When you clarify what KM means for your organization, you will also need to clarify how KM integrates with the work of these
other disciplines. In short, you will need to become an orchestrator of KM
activities as much as an implementer.
Tip
List out the partner disciplines that exist in your organization. Visit them and
learn how they see their main responsibilities, and what their current
priorities and projects are. Take notes on where these priorities and
19
20
Orientation to Knowledge Management Implementation
projects meet KM needs that you have identified. Ask them for feedback
where they think the KM function could integrate with what they are doing,
and on where they think you could offer help. To avoid raising unrealistic
expectations, explain that you can’t take on everything and will have to
prioritize. Promise to consult them as your implementation planning
progresses.
Summary
Although knowledge management is a fuzzy and poorly defined topic, you
have many analogue disciplines such as safety management or risk management which you can use as models for KM implementation, and you can be
guided by the experience of other knowledge managers in choosing what to
include within your KM implementation. Analogues like the KM supply
chain, or KM orchestration, give you alternative views of your task, which
you must remember to translate into terms that the organization will easily
understand.
Ensure that you take a complete view of KM, including:
●●
●●
●●
the elements of people, process, technology and governance;
the four transactions of discussion, capture, synthesis and finding/reusing;
and
the two drivers of push and pull.
However you finally define KM for your organization, make sure your definition is shared with your manager and your steering committee and broadly
accepted within the organization. Then you can proceed to the next step of
developing your implementation approach, which we will cover in the next
chapter.
References
ISO (2018) Knowledge management systems – requirements – ISO 30401:2018,
ISO, Geneva
Knoco (2017) Knowledge Management Survey [online] https://www.knoco.com/
knowledge-management-survey.htm (archived at https://perma.cc/9PHN-STK3)
[accessed 26 January 2019]
What is Knowledge Management?
Nonaka, I and Takeuchi, H (1995) The Knowledge Creating Company: How
Japanese companies create the dynamics of innovation, Oxford University Press,
New York
Prokesch, S E (1997) Unleashing the power of learning: an interview with British
Petroleum’s John Browne, Harvard Business Review, 75 (5) pp. 146–68
21
22
02
The stages
of KM
implementation
This chapter takes a high-level overview of KM implementation, and identifies the various options and stages. It contains the following elements:
●●
a comparison of six approaches to implementing KM, with the advantages
and disadvantages of each;
●●
the five phases of the recommended ‘trials and pilots’ approach;
●●
the parallel opportunity-led programme of quick wins;
●●
the escalating levels of management decision.
The different implementation approaches
There are many different approaches for KM implementation, but in this
book we intend to focus on the implementation method that we have found
most successful. The main implementation approaches we have seen applied
are listed in Table 2.1, with the arguments for and against. The approach we
present in this book is an ‘agile’ combination of a ‘trials and pilots’ approach, with opportunistic delivery of quick wins.
This is not to say that other approaches cannot work; given the right
conditions they sometimes do. However, the odds are weighted against you,
for the reasons explained in Table 2.1.
Our recommended approach
Our recommended approach is a combination of three of the above. The
core strategy is a ‘trials and pilots’ approach (6) to develop the long-term
The Stages of KM Implementation
Table 2.1 Advantages and disadvantages of different KM implementation
approaches
Approach
Description
Pros
Cons
1. Grass roots/
bottom up
KM starts low in
the organization,
without
management
support.
Attractive
concept:
people do KM
because they
recognize its
value and
importance.
Unlikely to work when
KM is up against urgent
activity – KM gets
deprioritized. Multiple
diverse and competing
KM approaches likely to
emerge. Often fails to
reach the tipping point,
unless early success is
deliberately converted
into management
support.
2. Top down
Management
just tell people
to do KM.
Quick. May
appeal to
autocratic
management
cultures.
May create a ‘tick in the
box’ ethic. Multiple
diverse KM approaches
likely to emerge as
people interpret the
management edict in
different ways. KM may
suddenly go out of
favour with changes in
senior leadership.
3. Opportunistic KM is
introduced by
looking for
business
opportunities
and addressing
these one by
one.
A low energy
approach –
you go where
the appeal is.
The KM team can be
rapidly swamped with
some KM activities,
while other components
of the KM system are
not addressed. However
this is a useful
secondary
implementation style, as
described in this chapter.
Fast. An
approach often
advocated by
large
consultancies,
who will help
with the
framework
design.
There is no reliable ‘one
size fits all’ KM
approach, and if you get
it wrong you get it
wrong for everyone.
This is a risky one-shot
approach.
4. Roll out a
pre-designed
KM framework
Design a KM
framework and
roll it out to the
entire
organization
with senior
management
support.
(continued )
23
24
Orientation to Knowledge Management Implementation
Table 2.1
(Continued)
Approach
Description
Pros
Cons
5. Roll out
individual KM
processes or
tools
Roll out
components of
the framework
one by one (eg
search engine,
communities of
practice, etc).
Allows testing
of each
component of
the KM
system.
Spreads the
investment.
Usually a recipe for
failure. Individual KM
components are unlikely
to deliver value on their
own. The organization
will need to take the
value proposition on
faith until roll-out of
every element is
complete, and they are
properly connected and
integrated.
6. Trials and
pilots
Pilot a minimum
version of the
KM framework
in one or more
business areas.
Review,
improve,
expand, repeat.
This could be
termed an ‘agile’
approach.
Secure,
robust, allows
advancement
by discrete
steps and
decisions.
Slow. Management may
be impatient. Risk of
being undermined by
organizational changes,
unless you deliver quick
wins, eg through use of
the opportunistic
approach.
KM framework, combined with an opportunistic approach (3) to deliver
short-term wins. Once the KM framework has been tested and proven to be
robust, then you move to a roll-out approach (4).
Tip
Stick with the implementation approach outlined here, and resist the
alternatives unless you really have no choice. Particularly resist the
pressure to ‘just roll out a technology tool and see what happens’. What
often happens is that the technology reaches 10–20 per cent penetration
and then grows no further.
The Stages of KM Implementation
Figure 2.1
Strategy
(Chapter 4)
The five phases of the recommended KM implementation approach
Planning
(Chapters
11–20)
Testing
and
piloting
(Chapters
21–22)
Roll-out
and
handover
(Chapters
23–26)
Operating
and
improving
(Chapters
27–29)
In this recommended approach, your KM implementation programme will
go through several phases as shown in Figure 2.1, and discussed in the subsequent chapters of this book.
1. Strategy phase
Before implementation, you need a strategy phase, to confirm the need for
KM implementation, and to create the business case and the budget for setting up an implementation team. We provide a high-level overview of KM
strategy development in Chapter 4. For more detail on KM strategy we refer
you to Designing a Successful KM Strategy: A guide for the professional
knowledge manager by Nick Milton and Stephanie Barnes (Barnes and
Milton, 2015). The strategy phase ends with a decision from senior management to move to detailed planning.
2. Planning phase
The detailed planning stage involves a lot of investigation, for example:
●●
a knowledge resources audit (Chapter 11);
●●
assessing the elements of a draft KM framework (Chapters 12–17);
●●
stakeholder assessment, culture assessment and preparation of a
communication strategy and plan (Chapters 18–19).
25
26
Orientation to Knowledge Management Implementation
Finally you will put together a detailed implementation plan that covers
the testing and piloting phase, with a higher-level plan to cover roll-out
(Chapter 20).
3. Testing and piloting phase
The testing and piloting stage (described in detail in Chapter 22) is when
you begin to look for the small ‘proof-of-concept’ exercises where you can
apply a single KM element to a single business issue – for example a peer
assist to help a new project team learn from prior experience before they
start a project, or a lessons-capture exercise to draw out knowledge from a
completed piece of work. You also begin to look for the larger-scale pilot
projects. Components of your draft KM framework can be tested in the
proof-of-concept exercises, and the whole framework will be tested and improved in a succession of pilots. This is similar to the agile software methodology which relies on multiple cycles of development with learning from
each cycle incorporated into the next. Choose your pilots wisely – they
should have a high chance of success, be able to demonstrate clear business
value, and deliver lessons and feedback to improve the framework.
By the time you have got to the end of the piloting stage, you should have
evidence of value delivery through the application of KM, you should have
begun to build a KM champion network (Chapter 21) and you should be
able to finalize your KM framework so that it can be effectively embedded
into the working structures of the organization.
4. Roll-out phase
The roll-out phase (described in detail in Chapter 23) is when the KM
framework is applied across the rest of the organization (those parts of the
business that were not involved in the piloting). The roll-out decision is a
crucial one that needs to be made at the highest level, as this is the decision
to commit the entire organization to the revised KM framework. Take your
evidence of pilot value to your steering committee, and ask them to make
this decision, or to recommend the decision to senior management.
The roll-out will involve setting up components and activities that will
take you through into the operational phase:
●●
documenting the framework;
●●
training people in their new roles;
●●
training people in new processes;
The Stages of KM Implementation
●●
training people in the use of new technology;
●●
finalizing the governance system and the KM policy;
●●
starting to gather and report metrics (Chapter 24).
Roll-out continues until the whole organization has been trained, and is able
to comply with the expectations in the KM policy. At the end of this stage,
the decision will be made to close the KM implementation programme and
hand responsibility for KM over to a KM operational support team, as described in Chapter 26.
5. Operational phase
From the operational phase onwards, KM is treated as ‘part of the way we
work’. There should still be a KM team, but their role is to support and
monitor KM activity in the business. Operational activity will include activities to monitor and continuously improve KM, such as the use of external frameworks to benchmark your KM approach (Chapter 27), working
with external partners (Chapter 28), and enhancing your use of technology
(Chapter 29).
Exceptions to the rule
You may meet a situation where our recommended approach is not immediately possible. For example, KM may have been fully embedded in an
­organization, but only within one business unit. In cases such as this the
business unit itself acts like a very large pilot for the rest of the organization.
The case study below is another example of an exception, where a bottomup KM implementation was needed in order to gain enough support for the
recommended implementation approach to begin.
C A S E S TU DY
One of the authors was approached by the IT department of a small international
business matchmaking agency with a large headquarters and many small offices
around the world. They had identified significant problems with access to
information, knowledge flows, and trust between the different departments, and
they had recognized that an IT solution alone was not going to help. They wanted
to conduct a knowledge audit, and identify useful KM interventions that could
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Orientation to Knowledge Management Implementation
help. However, they had minimal support from their senior management, who
believed that every department was different. Consequently they felt there was
no strong priority for a common KM strategy and framework. Because of this, the
IT team also had a very small budget. We had misgivings, but we were impressed
by the team’s commitment. We trained them and supported them through a
knowledge audit exercise, and they identified three initiatives: (1) the audit
uncovered a core set of information resources from various department silos
that were in wide demand across the organization, and they moved them to the
shared intranet; (2) they placed a micro-blogging tool on the intranet front page
to enable day-to-day sharing of activities and meetings (this became a wild hit
with the country teams, who had previously felt isolated from the HQ, and
appreciated the chance to improve the visibility of their work); (3) they instituted
knowledge transfer interviews with country managers on their trips through HQ,
and published these as regular ‘need to know’ profiles about different countries
and markets. Three years later, these initiatives had changed perceptions and
culture so significantly that the senior management team commissioned a
second audit and an organization-wide KM strategy and framework. While the
bottom-up approach is a risky one, if there is strong commitment and stamina
from a core team and a judicious, well-grounded choice of projects, it can work
to convince senior management that KM has value.
The parallel opportunity-led programme
What we have described above is a strategic long-term programme of
change, based on thorough assessment and analysis, and on trialing and
piloting to iteratively test and refine the framework. This gives a robust
solution, but can be slow. To many parts of the organization – particularly
those not involved with pilots, or at the end of the queue for roll-out – it
might appear that nothing much is happening. The cynics start to whisper
that KM is promising much but delivering nothing. As well as the long-term
strategic development approach, you therefore need to work on visible
short-term progress and providing immediate tangible results, so that people will see KM in action and understand the value it brings. You should be
looking for opportunities to deliver and publicize quick wins at any stage
in the programme (potential quick-win opportunities are discussed in
Chapter 22).
The Stages of KM Implementation
Tip
To avoid the risk of losing focus on your core trials and pilots approach,
consider making one or two team members responsible for the
opportunistic ‘proof-of-concept’ activity stream, so that the opportunistic
work plan can be well bounded and does not consume all your resources.
Make sure that you have regular liaison across the two activity streams so
that cross-connections and lessons can be exploited.
Escalating levels of management decision
As you work through these phases you will be working at escalating levels
of management decision. The evidence gathered at each stage will support
the decisions for the next level of activity.
During the planning phase, the first few ‘proof-of-concept’ exercises will
be applied to specific activities within a project or department, often involving the application of individual KM techniques and tools. Perhaps you will
try a knowledge-exchange workshop, a retention interview from a departing expert, or a lessons-capture meeting from a project (more guidance on
these proof-of-concept exercises is provided in Chapter 22). The decision to
conduct a KM proof of concept can be made at team leader level or project
manager level, and little investment of time or money is needed.
Proof-of-concept exercises have limitations: it is hard to scale them up
and the application of a single tool means that the rest of the KM framework will be missing. However, you can often demonstrate the delivery of
local temporary value and gather feedback and user endorsements from the
people involved. This evidence of value can be used to influence the next
level of management, whose support will be needed for the KM pilots. This
is a low-risk way of building common understanding and support.
Piloting, on the other hand, involves introducing a complete KM framework into one part of the business, in order to impact business results. It
might involve, for example, the development of a community of practice
covering a particular topic, or gathering and sharing knowledge between a
number of projects all working on the same sort of work. This is the level at
which real value can be delivered to the business. The pilot needs some fulltime resource from the business and may last for a few months. The decision
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Orientation to Knowledge Management Implementation
to support a pilot will be taken by a programme manager, a divisional manager, or the manager of a business line or product line. Because the commitment is greater, it is useful to have successful proof-of-concept exercises in
the bag so that you can make the case for the piloting stage.
Even in the pilot projects, KM may still find itself hampered by a lack of
senior management support, and by corporate policies and structures such
as internal competition, counterproductive reward mechanisms, inadequate
technical career paths, lack of accountability for knowledge, and so on. To
introduce KM to the whole organization will require the wholehearted support of the senior managers, and high-level decisions to remove some of the
inhibiting factors. It requires tangible steps to support KM as a necessary
component of business activity, to endorse the KM policy, and to develop
the conditions that support a knowledge-focused culture. Support is not just
saying ‘yes’ at a management meeting, or endorsing a budget request. It has
to go beyond that, to permeate the everyday actions, decisions and resource
allocations that senior leaders enact, as described in Chapter 7. The success
of your KM pilots will be important in gathering this kind of senior-level
support and in making the case for the roll-out stage.
Summary
There are several approaches to implementing KM, and all have advantages
and disadvantages. The approach we recommend is a combination of a
staged approach involving piloting and roll-out, together with a set of opportunistic ‘proof-of-concept’ exercises to solve or alleviate business issues.
This process continues until the framework is robust enough for roll-out. In
this approach the necessary long-term strategic change is combined with
regular demonstration of the value of KM. It also allows a steady escalation
of KM support.
We will explore in detail the issues associated with each of the implementation phases in later chapters, and in our next chapter will look at some of
the main pitfalls and barriers you may meet along the way.
Reference
Barnes, S and Milton, N J (2015) Designing a Successful KM Strategy: A guide for
the knowledge management professional, Information Today, Medford, NJ
31
Barriers and
pitfalls
03
This chapter looks at the things that can go wrong in KM implementation.
KM initiatives are complex and multifaceted. They touch on many different
parts of the business, have many dependencies, and offer many opportunities for surprises (unpleasant or otherwise). To identify the pitfalls discussed
in this chapter we draw on evidence from multiple sources: an online survey,
a literature review, our own experience, and case studies from others. These
give several perspectives on the pitfalls and barriers that you may face, and
how to avoid or mitigate them. This chapter covers:
●●
●●
a review of survey evidence;
a review of lessons from the field, within which we identify 12 main
pitfalls:
1 KM is not introduced with a business focus;
2 KM is never embedded into the business;
3 you fail to secure senior management support;
4 you don’t focus on high-value knowledge;
5 you fail to show measurable benefits;
6 the four enablers of KM are not given equal attention;
7 only parts of the KM solution are implemented;
8 you make KM too difficult for people;
9 KM is not implemented as a change programme;
10 the KM team ‘preaches only to the converted’;
11 the KM team fails to engage with key stakeholders;
12 the KM team have the wrong competences.
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Orientation to Knowledge Management Implementation
Survey evidence
As part of a global surveys in 2014 and 2017, answered by over 700 KM
professionals, we asked respondents to rank a number of barriers in order
of the impact they had had on their KM programme, ranking these from 1
to 8 (Knoco, 2017). The results are shown in Table 3.1, with high numbers
representing high ranking and therefore high impact.
Respondents were also asked to prioritize the main enablers for KM
which had proved powerful in supporting them in their KM implementation
programme, ranking these enablers from 1 to 9. The resulting figures are
shown in Table 3.2 (high numbers being high ranking).
The number two barrier and the number one enabler are the same – support from senior management. Without this, you will struggle. With this,
assuming it goes beyond lip service and is sustained, you should succeed.
The implementation approach described in this book is at least partly designed to build the evidence needed to convince senior management to give
you their support.
Table 3.1
S urvey responses identifying the biggest barriers to KM
implementation
Barrier
Average ranking by impact
Cultural issues
5.8
Lack of prioritization and support from
leadership
5.0
Lack of KM roles and accountabilities
4.8
Lack of KM incentives
4.8
Lack of a defined KM approach
4.6
Incentives for the wrong behaviours
(focus on billable activities, rewards for
internal competition etc)
4.3
Lack of support from departments such
as IT, HR etc
4.1
Insufficient technology
4.0
SOURCE Knoco Ltd
Barriers and Pitfalls
Table 3.2
S urvey responses identifying the biggest enablers of KM
implementation
Enabler
Average ranking by impact
Support from senior management
6.2
Championship and support from KM team/
champions
6.2
Evidence of value from KM
5.9
Easy-to-use technology
5.6
A supportive company culture
5.6
Effective KM processes
5.5
Clear KM accountabilities and roles
5.4
Personal benefit for staff from KM
4.6
Incentive systems for KM
4.2
SOURCE Knoco Ltd
Although culture, roles and incentives are seen as major barriers, they are
lower in the enablers table. This is interesting. It suggests some things can be
perceived as strong barriers, but weak enablers. Perhaps culture creates this
tension because it cannot be managed directly as other enablers can. It must
be influenced. Culture, roles and incentives all relate to the engrained habits
of an organization. When your KM initiative is aligned with them, everything goes smoothly, and their role as enablers is barely perceived. When
your KM initiative is not aligned with them, they immediately produce obvious – and multiple – points of friction. This is why all three of these need to
be addressed as part of your KM implementation.
The third enabler relates to the value demonstrated by KM. In Chapter 2
we described an incremental ‘value snowball’ approach involving KM
proof-of-concept projects, KM pilots and an opportunity-led programme of
KM initiatives. This approach is geared towards delivering quick wins and
also demonstrating long-term value. It is critical if we are going to build
management and employee support for KM at ever-increasing levels of seniority and influence.
Technology is seldom a barrier, nor is it one of the top enablers. Anyone
thinking that the solution to effective KM is technology alone is ignoring the
lessons from the past two decades of successful KM! And yet it continues to
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Orientation to Knowledge Management Implementation
be a distractor because it is much easier to buy a piece of technology than to
‘buy’ a piece of KM practice, and this ease of purchase can still be a fatal
attraction for decision makers who know no better.
Lessons from the field
In this section, drawing from the KM literature, a number of case studies, and
our own experience, we identify 12 main areas to watch out for if you want
to avoid KM failure. Where we have used external references they are given
in the text; otherwise, these are factors that we have encountered in our own
experience of working with organizations on KM implementations.
Pitfall 1. KM is not introduced with a business focus
The best way to embed an initiative into the DNA of a business is to have it
driven constantly by a business focus, and neglecting to introduce KM with
a business focus is one of the most common reasons for failure. KM should
not be introduced for its own sake; it should be introduced because it solves
business problems and helps people make better decisions, and so work
better, faster and/or cheaper. You won’t sell KM to anyone, let alone the
doubters, the cynics or the high-level sponsors, by assuming that KM has
self-evident benefits. You won’t get anywhere by saying, ‘We need to improve knowledge sharing’, unless you can clearly demonstrate how ­improved
knowledge sharing will help the organization meet its goals.
C A S E S TU DY
One of our clients took a KM strategy to the executive team of their organization.
It was a good strategy, but lacked business focus. Luckily, rather than kicking it
out, they said, ‘Yes, you can go ahead with KM, so long as you focus it entirely on
the growth agenda. If it can help us grow, then go ahead.’ That’s what the team
did, and now, many years later, they have a wealth of stories showing massive
growth and many hundreds of millions of dollars of value created through the
help of KM.
Barriers and Pitfalls
Once you have a business focus you have to maintain it. KM often involves a complex set of diverse activities. It is easy to get distracted by the
details of implementation and forget the reason why you are doing KM in
the first place. In their case study of a failed KM initiative in a pharmaceutical company, Braganza and Möllenkramer (2002) pointed to a tendency
to support localized KM practices within distinct functional areas, and so
the company built a number of functional knowledge silos, never reaping
the full benefits of what they were doing at an organizational level. Once
you have a business focus, and remain guided by it, then it is much easier
to identify, understand and support the knowledge interdependencies
across the business.
Business focus will be a common theme of this book, but we will give it
special attention in Chapter 22 which covers pilot projects and proof-ofconcept exercises.
Pitfall 2. KM is never embedded into the business
Many KM programmes do not survive in the longer term because they
were never embedded into normal business activities. They may be delivered by a strong team and a charismatic leader, but they are delivered as
something separate – not fully integrated into the work structure and
management framework of the company. Once the charismatic leader
leaves, KM withers and dies. Rosina Weber says that implementation
needs to be ‘inside the process context’ (Weber, 2007), and in analysing
a KM failure within a pharmaceutical company, Braganza and Möllen­
kramer (2002) talk about the need to contextualize KM ‘within natural
­activity areas’.
The goal of your implementation programme should be to embed a selfsustaining approach to KM in all elements of the business, with clear governance and good support, and clear evidence of sustainable culture change
and business value. Don’t stop your implementation until you have got to
this point, and even then, plan for a handover period until embedded operational KM is up and running. Stopping a KM programme before this point
is a common reason for failure, and given that it may take many years to
reach this point, you need to ensure that your high-level sponsor (see point
3 below) is in it for the long run. Chapter 23 will cover what is involved in
embedding KM.
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Orientation to Knowledge Management Implementation
Pitfall 3. You fail to secure effective senior
management support
In order to embed KM in the business, changes to the business need to be
made. You may have to change the incentives policy, perhaps removing the
‘factory of the year’ award that drives so much internal competition, or the
accountabilities of the heads of different corporate functions may need to
include accountability for the maintenance of certain knowledge areas. If
managers in the business lines do not accept responsibility for the quality of
the knowledge assets under their care and of the knowledge processes that
drive their core activities, then you are in trouble (Weber, 2007).
You may have to persuade high-level groups to respond to the output of
knowledge capture sessions whenever these uncover organizational improvements that can be made. You may need to introduce a new technology across
the entire organization. For all of these changes you need support at the highest
level, which is why senior management support is both the biggest enabler to
KM implementation (if present) and the one of the biggest barriers (if absent).
Note the word ‘effective’ in the heading to this section. Sponsorship and
support cannot simply be lip service. They need to be followed up by political cover while the KM programme is getting under way and before it shows
results, by appropriate resource allocations, by changes in policy and
­process, by clearly defined deliverables, and by properly enforced accountabilities. Steve Barth identifies a failure to follow through with sufficient
investment and resources as a common failure point (Barth, 2000), which
may well be an outcome of insufficient senior support. We further explore
the role of senior management in Chapter 7.
C A S E S TU DY
In a study of KM implementation challenges in Singapore, Lambe and Tan (2003)
found that a superficial understanding of KM among the sponsors and steering group
led to over-optimistic assumptions about what could be achieved with limited
manpower and resources, and an under-appreciation of the resources, effort and
time that were actually needed to show results. This clearly implies the need for a
constant process of engagement, communication and education with your sponsor
and steering group, to ensure that their support remains well-informed, and effective.
Barriers and Pitfalls
Pitfall 4. You don’t focus on high-value knowledge
In her review of factors influencing failure in KM implementations, Rosina
Weber talks about overambitious attempts ‘to develop a monolithic organizational memory for the whole enterprise’. The knowledge that was captured and stored was generalized and non-specific because it was meant to
be accessible for everybody (Weber, 2007). However, all real work in enterprises is highly specific and context dependent. The quality of knowledge
in the shared knowledge base depends on how relevant and valuable it is for
the work of your colleagues in the organization. Over-abstraction reduces
the utility of the knowledge. If you forget this fact you have forgotten as
important a factor as your business focus.
The drift towards inappropriate forms of knowledge happens all too easily. In their study of a failed initiative in a pharmaceutical company, Braganza
and Möllenkramer (2002) describe how a team in charge of building a
knowledge base, once they had started, became obsessed with completing all
the elements that could be captured (eg customer data, competitor intelligence, sales data, staff details) without considering the natural working patterns of the end users. Without an understanding of the end users’ everyday
activities, the team was unable to prioritize which knowledge was to be
collected, and did not focus on supporting the work that people actually did.
It was then hard for users to filter through the ‘noise’ and identify what
would be useful for specific tasks.
Instead your KM should focus on the knowledge of high value – both to
the organization (the ‘strategic knowledge areas’ described in Chapter 4)
and to the knowledge workers (the knowledge resources audit described in
Chapter 11).
Pitfall 5. You fail to show measurable benefits
Rosina Weber cites the failure to show measurable benefits to the business
as one of the major risks to a KM implementation (Weber, 2007). If you
have completed a robust KM strategy development process and identified
where your business focus should be, and if you maintain that business
focus, then you can mitigate this risk (Barnes and Milton, 2015). However,
you also have to show value and benefits to the front-line staff as well as to
your sponsoring organization. The knowledge workers you impact with
your KM initiatives need to see benefits to them and their work, or they will
not participate, contribute, or share (Weber, 2007).
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Orientation to Knowledge Management Implementation
In a set of lessons learned from implementing KM at Siemens, Gibbert,
Probst and Davenport identify two pitfalls they encountered as part of the
KM implementation there. The first, which they call ‘the customer trap’, is
the need to balance the expectations of the business, in terms of value to be
delivered by the KM programme, with the expectations of the end users.
You will need to show clear benefits to both of these stakeholder groupings
(Gibbert, Probst and Davenport, 2011).
Steve Barth, in an analysis of the early failure of KM efforts at the food
manufacturer Pillsbury, calls this the ‘field of dreams trap’. Pillsbury had
identified a clear business focus and successfully sold it to the top management – to create a knowledge-sharing system around batter manufacture
across the different product groups. However, they failed to consider or
make clear what would be the benefits to the teams in the different product
groups. In fact, some of the vice presidents actively discouraged spending
time in sharing knowledge across groups. As Steve Barth puts it:
The batter effort failed to rise because the originator of the idea focused on
the perceived benefits to the organization without considering what incentives
would have to be offered to get people to contribute, while the IT staff focused
solely on delivering a quality technology solution. In short, both wanted to solve
a problem but didn’t ask if it was the right problem to solve (Barth, 2000).
Balancing these two sets of value perceptions also means gearing your communication campaign to both constituencies. We have seen KM initiatives
falter where top management was the main focus of KM communications,
or where end users were the main target, to the exclusion of the other party.
Both constituencies need to be kept on board, and they need to be alerted
regularly to progress and made aware of benefits that make sense to them.
We cover communications in Chapter 19.
Pitfall 6. The four enablers of KM are not given equal
attention
In Chapter 1 we introduced the idea of the four enablers for KM, which we
likened to the four legs on a table. If you find one of these enablers becomes
too dominant during KM implementation, then your table is at risk of becoming wobbly and unstable. If any of these elements are missing completely, your table will fall:
Barriers and Pitfalls
●●
●●
●●
●●
If there are no roles and accountabilities, then KM is nobody’s job and
nobody will do it, or it’s ‘the KM team’s job’ in which case the team will
quickly collapse from being over-extended.
If there are no processes for KM, then nobody knows what to do, or how
to do it.
If there is no technology for KM, then nobody has the tools, and KM can
never extend beyond the immediate and local context.
If there is no governance, then nobody sees the point. KM remains an
optional activity, and nobody has time for optional activity.
Over the years, we have seen that two of these ‘table legs’ – roles and governance – get far less attention than the other two. This is often a contributing factor to the challenges that KM programmes face (Weber, 2007). It is
easy to see this in the frequency of Google searches on the four elements, as
a proxy measure of where the attention typically lies. For example, a search
for ‘knowledge management process’ in September 2018 gave 890,000 results, ‘knowledge management technology’ yielded 219,000 results,
­‘knowledge management roles’ 74,000 results and ‘knowledge management
governance’ 75,000 results. If these are the four legs on the KM table, then
in the wider KM world the longest leg seems to get nearly five times the attention than the shortest leg. Do not fall into this trap. Chapter 12 describes
an approach to building a balanced KM framework.
Pitfall 7. Only parts of the KM solution
are implemented
All too often, KM implementations take only one element of knowledge
management, or one tool or technology, and assume that it will work in
isolation. A common assumption is that knowledge has to be captured and
published, so people go down a route of collecting documents rather than
connecting people, ending with content graveyards that nobody ever visits
or uses. An alternative but also common assumption is that all you have to
do is ‘let people talk and knowledge will share itself’. So people go down a
route of connecting people through social media technology. In reality,
knowledge doesn’t just ‘share itself’ without structure or focus. Taking a
small element of KM and assuming it will work in isolation is like taking
one culinary ingredient and assuming it will create the whole recipe, or like
taking one small element of a central heating system and assuming it will
heat the house.
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Orientation to Knowledge Management Implementation
CA S E S TU DY
A client asked us to come into their organization and capture knowledge from
major successful bids. We held a series of retrospects, and found some really
good success factors which should be repeated in future, and a whole set of
opportunities for improving the bid process, including some things that were
really frustrating the bid teams (mostly related to inappropriate company
policies). We documented the lessons and the opportunities for improvement,
trained the client in the retrospect process, and moved on.
A few months later the client called and said, ‘That retrospect process is
rubbish’. On further questioning, he said, ‘Those issues that were frustrating the
team when we started are still there. They have come up again in the latest
retrospects. Nothing has been changed.’
Of course nothing had changed, as all they had done was introduce one element
of KM – a knowledge-capture process. Retrospects are great for identifying team
learning, but there needs to be a follow-on process to take action on the issue, and
for this particular company, those actions needed to be taken at a high level in the
organization. They had not implemented a process or workflow for addressing the
actions, and had no engagement from senior managers in the learning process.
Pitfall 8. You make KM too difficult for people
Knowledge management is hard enough to implement, without asking people to radically change their work habits as well. You will find the KM implementation journey easier if you can (at least at first) work with the habits
and tools that people already have and already use. For example, if people
need to regularly log onto a new community of practice website to share
knowledge with their peers, and if this is a new habit, then people will forget, or don’t bother, and the community dies. Better to start by linking the
community to established work habits such as email, and ensure members
are alerted to new community discussions through their email.
Here is a recommendation from the former IDEO Chief Technology
Officer Doug Solomon (Solomon, 2010):
If a tool requires people to go out of their way to use it, adoption will always be
a challenge, no matter how wonderfully designed. Wherever possible, strive to
integrate tools into existing work processes – bring the system to the user rather
Barriers and Pitfalls
than the other way around. For example, the IDEO blogging system didn’t take
off until the team added a program that sends digest emails with new content
from the blogs each employee has subscribed to.
In their study of a failed KM initiative in a global bank, Chua and Lam
found that the IT team behind the planned global knowledge network had
failed to consult the end users in the project development phase, and had
little understanding of how they actually worked. When the system was
launched, the users naturally had little understanding of the rationale for the
system or how it was supposed to fit into their work, and little incentive to
share knowledge using the system. It was just too complicated for them
(Chua and Lam, 2005).
You need to reduce the barrier to entry to KM whenever you introduce
new tools and new processes. Make them as simple as you can, and then simplify them again. Build them into existing work habits, such as email. Don’t
expect people to learn new tricks, or make new clicks. Chapter 17 describes
how to build evidence of user habits into the design of knowledge systems.
Pitfall 9. KM is not implemented as a change
programme
KM is a programme of organizational change. It’s not about buying and
rolling out technology and it’s not about adding another task into the project framework; it’s about changing the way people think. It involves changing personal and organizational priorities, routines and habits. KM needs to
be introduced as an organizational change programme, with high-level
sponsorship, a communication strategy, a desired end-state, and step-wise
implementation rather than ‘everyone change at once’. Change needs to
reach a tipping point, and hearts and minds need to be changed one at a
time (see Chapters 18–19). Organizational change is a well-established field,
and KM needs to learn from this field.
Part of the change process is to understand the current impediments to
knowledge transfer in your organization, whether they be inappropriate incentives, conflicting processes, or the capacity of employees to c­ ommunicate,
absorb or apply the target knowledge. This is why a knowledge resources
audit and a culture assessment are useful exercises in planning a KM implementation (see Chapters 11 and 19). The Public Works Department Malaysia
case study in Chapter 36 describes how change management was critical to
the success of their KM initiatives.
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Orientation to Knowledge Management Implementation
Pitfall 10. The KM team ‘preaches only
to the converted’
The KM team are enthusiasts. They see the value in KM, they ‘catch the vision’, and they assume everyone else will catch the vision. As they go out
into the organization conducting the change programme they begin to meet
other enthusiasts, and will be engaged in exciting discussions. However, they
eventually need to move beyond the enthusiasts and engage the rest of the
organization. Experience shows that maybe 20 per cent of people are enthusiasts, maybe 60 per cent don’t care about KM one way or another (they will
do it if their job requires it, but it’s not a big deal either way), and 20 per
cent distrust the idea, or find it threatening. Even though it’s much more fun
to work with the enthusiasts, the sooner you move beyond them and start
the hard work of engaging the other 80 per cent, the better. The tough nuts,
the cynics and the don’t-cares are the people who will force you to demonstrate practical benefits and value. We provide methods of influencing these
three KM ‘market segments’ in Chapter 18.
Pitfall 11. The KM team fails to engage with key
stakeholders
You need to be practical and systematic about who you involve and engage
with. One of the key steps in your initial KM strategy building process
should be a systematic mapping of key stakeholder groups (Barnes and
Milton, 2015). Likely stakeholders include:
●●
the senior management team;
●●
the CEO;
●●
prominent senior sceptics;
●●
key department heads;
●●
the sponsors of pilot projects;
●●
the knowledge workers in the organization;
●●
the KM community of practice;
●●
external bodies you share knowledge or information with.
At the implementation stage, stakeholders may also include, as we saw in
Chapter 1, ‘adjacent’ disciplines or functions in the organization with whom
we need to coordinate. The initial engagement with stakeholders at the
Barriers and Pitfalls
strategy-building stage needs to be sustained and even extended throughout
KM implementation. Rosina Weber notes that failure to engage with all the
key stakeholder groups is a common failure factor in KM implementations
(Weber, 2007). Since different stakeholders may have different needs and
demands, this does not mean doing everything they ask, but it does mean
systematic engagement, communication and, where possible, alignment. In
Chapter 10 we discuss an approach to partnering with stakeholders which
will help to achieve this.
Pitfall 12. The KM team have the wrong competences
If KM is a programme of organizational change, then the KM team needs to
be made up of change agents and change leaders. The team leader, first and
foremost, needs to be a change agent, a visionary leader, capable of working
at the highest levels in the organization as well as the lowest, and with the
ability, mandate and authority to make change happen.
All too often, the KM teams we come across in organizations are not like
this at all. They are often back-room men and women, more at home managing databases and libraries than inspiring change. They prefer working
with computers to working with people. They do not inspire, and they are
not visionary. They are uncomfortable in the boardroom. We have also
pointed out that KM implementation is at least partly an orchestration function. Partner disciplines and functions need to be brought on board and
coordinated with. Working with all four enablers of KM requires facility
with business process analysis, and sufficient knowledge of technology capabilities to be able to work with the IT team without being either unrealistic or brushed off by ‘it can’t be done’.
Finding the right people for the KM team is not easy, but changing the
culture of an organization is not easy either. We cover the role of the KM
leader and the KM team in greater depth in the next two chapters.
Summary
As Chua and Lam (2005) point out, ‘KM projects attract an alarmingly high
level of risk. Nonetheless, many KM project pitfalls can be avoided if they
[are] identified and discussed before the project commences or better managed during the project itself.’ This chapter provides an alternative way of
navigating the contents of this book, by potential pitfalls and their solutions.
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Orientation to Knowledge Management Implementation
Rest assured that all pitfalls are avoidable or can be largely mitigated
with sufficient preparation. Despite the many barriers and the many failed
KM projects, there are also many that have succeeded, and these have shown
us the way to overcome the barriers. You’ll learn about both sides of the
coin in the rest of this book.
References
Barnes, S and Milton, N J (2015) Designing a Successful KM Strategy: A guide for
the knowledge management professional, Information Today, Medford, N J
Barth, S (2000) KM horror stories, Knowledge Management Magazine [online]
http://web.archive.org/web/20060612222246/http://destinationkm.com/articles/
default.asp?ArticleID=923 (archived at https://perma.cc/YNM4-S95G) [accessed
28 January 2019]
Braganza, A and Möllenkramer, G J (2002) Anatomy of a failed knowledge
management initiative: lessons from PharmaCorp’s experiences, Knowledge and
Process Management 9 (1), pp. 23–33
Chua, A and Lam, W (2005) Why KM projects fail: a multi-case analysis, Journal
of Knowledge Management, 9 (3) pp. 6–17
Gibbert, M, Probst, G J B and Davenport, T H (2011) Sidestepping implementation
traps when implementing knowledge management: lessons learned from
Siemens, Behaviour & Information Technology, 30 (1)
Knoco (2017) Knowledge Management Survey [online] https://www.knoco.com/
knowledge-management-survey.htm (archived at https://perma.cc/VCY7-LHL7)
[accessed 26 January 2019]
Lambe, P and Tan, E (2003) KM implementation challenges: case studies from
Singapore organizations, Singapore: Straits Knowledge [online] http://www.
greenchameleon.com/uploads/KM_Implementation_Challenges.pdf (archived at
https://perma.cc/N7BR-WMFF) [accessed 28 January 2019]
Solomon, D (2010) The tube: IDEO builds a collaboration system that inspires
through passion, Management Exchange [online] http://www.
managementexchange.com/story/tube-ideo-builds-collaboration-system-inspiresthrough-passion (archived at https://perma.cc/LU3A-9JCF) [accessed 28 January
2019]
Weber, R O (2007) Addressing failure factors in knowledge management,
Electronic Journal of Knowledge Management, 5 (3) pp. 333–46
45
PART TWO
Preparation and
resources
Executive summary
This section of The Knowledge Manager’s Handbook will help you scope
and resource your KM implementation. Chapter 4 reviews the components
of a good KM strategy, with illustrative examples. Chapters 5–7 describe the
human capital requirements behind KM implementation, namely the KM
leader, the KM team, and the role of senior management. Chapters 8–10
cover what you need to prepare in budget and time allocation, setting aims
and objectives, and finding partners to work with you.
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47
Knowledge
management
strategy
04
It would not be sensible to undertake a knowledge management implementation without a guiding strategy. In this chapter we describe some of the
work that you need to complete as the strategic foundation for your KM
implementation (for a fuller and more detailed introduction to KM strategy
development, see Barnes and Milton, 2015). This chapter covers the following elements:
●●
deciding the strategic principles;
●●
identifying the business drivers;
●●
defining the KM vision;
●●
agreeing the KM scope;
●●
defining the strategic knowledge areas;
●●
assessing the current state of KM;
●●
creating a draft KM framework;
●●
deciding how to handle change management; and
●●
creating a business case.
Each of these tasks is outlined below.
Deciding the strategic principles
Discuss with your sponsor and steering committee the strategic principles
that you will apply to your KM programme. Barnes and Milton (2015) suggest the following 10 principles, which are echoed throughout this ­handbook:
48
Preparation and Resources
●●
●●
●●
●●
KM implementation should be led by the organization and should
support the organizational strategy.
KM needs to be delivered where the critical knowledge lies and where the
high-value decisions are made.
KM implementation should be treated as a behaviour change-management
exercise.
The endgame will be to introduce a complete management framework
for KM.
●●
The framework must be embedded into the organizational structures.
●●
The framework will need to include governance if it is to be sustainable.
●●
The framework will be structured rather than emergent.
●●
A KM implementation should be a staged process with regular decision
points.
●●
A KM implementation should contain a piloting stage.
●●
A KM implementation should be run as a project.
These principles are based on sound practical experience from a large number of KM implementation programmes, and counteract most of the pitfalls
identified in the previous chapter. Do your best to convince your sponsor
and steering group that these principles should be followed.
Identifying the business drivers
Interview a wide range of senior managers to understand the core business
drivers for KM. This will help you understand why KM is important to the
organization. The four main business drivers include:
●●
●●
Operational excellence – improving the internal practices and processes of
the organization so that it operates better, faster, cheaper, safer and cleaner.
For companies facing the risk of knowledge loss as an ageing workforce
approaches retirement age, KM may focus on maintaining the existing
capabilities through the workforce transition. Chapter 35 describes how
the Singapore Youth Olympics had just one chance to build a strategic
capability for excellence in running major events.
Customer knowledge – building a better understanding of customers’
wants and needs, and how to satisfy them. In Chapter 31, Barbara Fillip
Knowledge Management Strategy
describes how KM initiatives at NASA were expanded externally to
ensure that private space companies could benefit from the lessons
learned in NASA’s missions.
●●
●●
Innovation – creation of new knowledge in order to create new products
and services. In Chapter 34, Tan Xinde describes how Huawei Technologies
worked at using KM to accelerate the rate at which employees could
translate knowledge into action.
Growth and change – replicating existing success in new markets or
with new staff, or developing the knowledge to enter new markets.
Chapter 30 tells the story of KM at Mars, and how the senior managers
helped redirect the Mars KM strategy to be completely focused on the
company’s ‘bottom line’ and on the growth strategy that was in place at
the time.
Defining the knowledge management vision
This involves working with your key stakeholders to develop a brief and
engaging statement of what KM will bring to the organization.
C A S E S T U DY
Suurla, Markkula and Mustajärvi (2002) describe the development of KM in the
Finnish Parliament, and the collaborative process used to develop the
parliamentary KM vision with the help of the Members of Parliament. The
team carried out a series of interviews with parliamentary civil servants and
MPs in 2000–2001 in order to understand the current state of parliamentary
KM, the critical knowledge areas related to daily work, the knowledge
requirements and problems, and the central changes affecting KM activities,
in order to establish a vision of reliable and efficient KM for the Parliament.
This was a typical strategic-level data-gathering programme aimed at senior
stakeholders.
The final KM vision, which spoke directly to the culture of the institution, was:
‘The Parliament [will be] an open and competent knowledge organization with a
cooperation-oriented work culture and the capacity and will to learn.’
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Preparation and Resources
Agreeing the knowledge management
scope
This involves working with your key stakeholders to understand the limits
of your KM implementation programme, and to define those parts of the
business and those parts of business activity which are in scope, and those
which are out of scope.
C A S E S T U DY
We were working recently with a financial institution, developing their KM
strategy. Although we agreed that the whole scope of operations should be
included in the KM strategy, including the Head Office and all branch offices,
we decided to make it clear in the strategy document that the KM scope
would exclude customer relationship management, business intelligence,
enterprise content management and learning and development. Although
these areas had high potential value and had natural affinities and
interdependencies with KM, all were considered separate issues already
under investigation by other groups, and therefore out of the scope of the KM
strategy.
Defining the strategic knowledge areas
This step involves working with senior management to identify the
knowledge of greatest strategic impact for the organization, which is
therefore of highest priority to be addressed by the KM programme. This
strategic knowledge assessment is a high-level assessment specifically for
the strategy stage. During KM implementation it will be reinforced and
extended by a more comprehensive and more granular knowledge resources audit.
Knowledge Management Strategy
C A S E S T U DY
When Martin Ihrig of the I-space Institute worked with a group of decision
makers at ATLAS, the major particle physics experiment at the European
Organization for Nuclear Research (CERN), he interviewed many stakeholders to
understand the critical knowledge for the organization, or ‘the knowledge
underpinning its success’ (Ihrig and MacMillan, 2015). Ultimately, only a portion
of the ATLAS knowledge base was mapped, but the list of 26 knowledge domains
was prioritized to identify the eight that were deemed most important to
organizational outcomes, and which should be addressed by KM.
Assessing the current state of knowledge
management
The strategic stage of KM implementation often includes a current-state assessment, in order to gauge the scale of the task. Barnes and Milton (2015)
recommend using the structure of the KM framework as a template for assessment. The framework ensures that you cover all the major components
that need to be in place for effective KM, and will support a realistic gap
analysis. Other potential measures and standards against which you could
assess your organization are described in Chapter 27.
C A S E S T U DY
We recently conducted a current-state assessment of a company’s lessonlearning capability (a subset of KM). The company had successfully captured
many lessons and stored them in a custom-made lessons management system.
We found, however, that a lack of governance and quality control meant that
many of the lessons were of very poor quality, leading to a lack of trust in the
system. There was also no development of company-wide best practices, which
meant that each operating unit had developed its own way of operating and
countered the re-use of lessons from elsewhere with a strong ‘not invented here’
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Preparation and Resources
culture. The KM framework helped to identify governance and the development
of common practices as two areas that the company would need to address in
its renewed KM programme.
Creating a draft knowledge management
framework
An outline KM framework is often created at the strategy stage, to give
some idea of what the final outcome may look like. However, the framework will be refined and fleshed out several times during implementation,
specifically during proof-of-concept exercises and pilots.
Deciding how to handle change
management
One of the recurrent themes of this book is that KM needs to be introduced
as a change management exercise. This begins with the KM strategy phase.
The KM strategy document should contain an outline of how the KM project will employ change management techniques.
CASE STUDY
The KM strategy for the Food and Agriculture Organization of the United Nations
makes an explicit mention of change management, recognizing from the
experience of other organizations that promoting constructive change was
essential to KM implementation. They proposed a four-step culture change
approach (FAO, 2011):
●●
●●
Step 1: Assess needs and establish the case for change.
Step 2: Build the required coalitions for change, in which sponsors within
technical departments and decentralized offices form their own change
initiatives but work collectively towards a shared vision.
Knowledge Management Strategy
●●
●●
Step 3: Share and enhance the vision through an outreach programme.
Step 4: Secure short-term wins – concrete, achievable targets to gain
confidence and buy-in.
Creating a business case
In some organizations, you may need to create an outline business case for
KM at the strategy stage in order to secure further funding. This is not an
easy thing to do at such an early stage. Your strategic business case does not
need to be an exact mathematical and logical case; it just needs to demonstrate that KM will bring more value than it costs.
CASE STUDY
Gorelick, Milton and April (2015) explain how a task force was set up to create a
business case for KM in BP in 1997:
A task force was formed with 5–10 executives… charged with assessing the
state of KM in BP and making recommendations. The task force concluded
that the BP environment had many factors conducive for KM, but that a major
effort was needed to accelerate the pace and benefits of BP’s transformation
to a learning organization, and to maintain the momentum of existing
knowledge efforts. A half billion dollars annual saving was the anticipated ‘big
prize’ for BP if they found a way to better leverage know-how. The steering
committee approved all the task force recommendations… (and) within a
week a decision was made to establish a central KM team reporting to a
corporate Managing Director.
Summary
The KM strategy is a crucial guidance document for KM implementation. The
vision sets the direction for KM, the scope provides the limits for the implementation programme, the business drivers and strategic knowledge areas
provide prioritization and focus, the principles explain how i­mplementation
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Preparation and Resources
will progress, the current state analysis and draft framework define the start
state and end state (and therefore the amount of work to be done), while the
change management section begins to explore how the change will be introduced. Finally, the business case provides the rationale. In the rest of this book,
we will be looking at how your KM strategy is actualized in practice.
References
Barnes, S and Milton, N J (2015) Designing a Successful KM Strategy: A guide for
the knowledge management professional, Information Today, Medford, NJ
FAO (2011) FAO Knowledge Strategy [online] http://www.fao.org/fileadmin/
user_upload/capacity_building/KM_Strategy.pdf (archived at https://perma.cc/
YS6E-ETJF) [accessed 28 January 2019]
Gorelick, C, Milton, N J and April, K (2015) Performance Through Learning:
Knowledge management in practice, Routledge, Abingdon
Ihrig, M and MacMillan, I (2015) Managing your mission-critical knowledge,
Harvard Business Review, Jan–Feb
Suurla, R, Markkula, M and Mustajärvi, O (2002) Developing and Implementing
Knowledge Management in the Parliament of Finland, Edita Prima Oy, Helsinki
55
05
The role,
skills and
characteristics of
the knowledge
management
leader
If your KM leader is not yet in place, this chapter will provide some guidance on who to hire, and what she or he will do. Alternatively, you may already have been appointed to lead the KM implementation programme, and
you can use this chapter to reinforce the skills you already have, and identify
the skills you will need to develop to perform your role.
The chapter contains the following elements:
●●
●●
●●
a description of the role of the KM leader, and a list of recommended
accountabilities;
a discussion of whether the KM leader should be an internal or external
appointment (we recommend internal);
the most important characteristic for an external appointment, namely
practical experience;
●●
the important competencies for the KM leader;
●●
a warning about the ‘personality trap’ for the KM leader;
●●
a useful metaphor for the KM leader – that of a gardener.
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Preparation and Resources
The role of the knowledge management
leader
Also known as the KM programme manager, the director of KM or the chief
knowledge officer, this person is in charge of KM implementation. They are
accountable for designing and introducing a working KM framework within
the business, which delivers business value and is seen by staff and management as supporting effective business practice. The KM leader will act as
project manager for the framework implementation project, and will represent KM at the senior level of management.
The accountabilities of the KM leader during the implementation programme are as follows:
●●
●●
●●
●●
Develop, together with the leadership of the organization, the vision,
objectives, metrics and deliverables of the KM implementation
programme. This is done during the KM strategy phase, which precedes
KM implementation. Full details of the KM strategy phase can be found
in the book Designing a Successful KM Strategy (Barnes and Milton,
2015).
Deliver the implementation project objectives, within the agreed time
frame and to the agreed cost and performance metrics. The KM leader
manages the implementation project. They are accountable for delivery,
for the budget, for managing the members of the KM implementation
team, and for managing progress and activity (the standard accountabilities
of a project manager).
Define and test the KM framework through the testing and piloting
phase, and ensure that the KM framework operates effectively and
efficiently. ‘Effectively’ means that the desired objectives are met, and
‘efficiently’ means within a reasonable range of effort and cost. At the end
of the piloting stage, the KM leader is accountable for delivering a tested
and validated framework.
Ensure that the KM framework delivers business value. Delivering the
framework is not an end in itself; the framework only exists to deliver
business value and the KM leader must keep this value objective
constantly in mind. Very often the success of the pilots, for example, will
be measured in business terms: money saved, time saved, or value
created.
Role, Skills and Characteristics of the KM Leader
●●
Act as champion for the corporate vision of KM. The KM leader is the
figurehead and champion for KM within the organization. She or he is
responsible for ensuring that knowledge management, as applied within
the organization, is understood, and seen as an important and valuable
activity by all of the main stakeholders.
Once the implementation programme is over, the KM leader role changes to
a more operational role, concerned with maintaining KM activity, monitoring and reporting on the application of KM, auditing the application of the
framework on a regular basis, and looking for enhancements to the KM
framework.
Tip
Use this section of The Knowledge Manager’s Handbook to check and
update your job description. Is anything missing? Is there any part of your
job description which is surplus to requirements? Update your job
description accordingly, and if there are any significant changes, be sure to
discuss them with your manager.
Should the knowledge management leader
be an internal or external appointment?
Should the KM leader should be an internal appointment (and often therefore with little experience in KM), or should you should recruit a KM expert
to take this post? Our advice is that an internal appointment gives more
advantages than an external one. KM is a simple idea to grasp, but very difficult to do in practice. The idea that people should share knowledge with
each other and learn from each other is not complicated; the challenge is
getting it to actually happen. Implementing KM is about culture change, and
culture change is both difficult and politically charged, and best handled by
an ‘insider’. Of the knowledge managers surveyed by Knoco in 2014 and
2017, 85 per cent said their KM leader was an internal appointment
(Knoco, 2017).
The KM leader should ideally be an existing respected senior member of
the organization, with a history of leading change, who knows the internal
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Preparation and Resources
politics and knows how to get things done in the organization. Learning
enough knowledge management to lead a KM programme can be done
quickly, with the right mentoring and coaching from specialists. Learning
the politics of an organization can take years, if not an entire career.
C A S E S TU DY
One of us worked with an organization where one of the elements of the KM
framework called for stronger governance in the shape of corporate policies
around the management of records, and clearer guidance about balancing the
need for information security against the need to share knowledge across silos.
With the KM leader, we went to the senior leadership team to ask them for
endorsement to develop clear policies to this effect. Their reaction was
unenthusiastic, and instead of endorsement we got lots of conflicting responses
as disagreements emerged around the table about how to handle the issue.
Several senior leaders thought that KM should be entirely voluntary, and should
not be governed by policy. We were concerned that this would be a roadblock,
but the KM leader was not disheartened. He told his team to go ahead anyway –
‘When they see what the policy looks like, they will understand why it’s
important.’ And indeed, the policies were eventually adopted. The KM leader
knew when he could sidestep the formal approval process and get things done a
different way, because he knew how his colleagues thought and operated.
The most important characteristic
for an external appointment
If there is no suitable and willing internal candidate and you end up appointing an external KM expert to lead an internal KM programme, the first
thing you should look for on their CV is practical experience. There is no
point in hiring a KM expert who doesn’t have a track record of implementation delivery. This point was made forcefully to us by a knowledge manager
in a large engineering firm:
I would (hire) somebody with a practical background – somebody who maybe
likes the academic side and likes to research, but who has put that research back
Role, Skills and Characteristics of the KM Leader
into delivery. If I was recruiting somebody and I had an interview and I asked,
‘Do you think you were successful (in your last KM implementation)?’ and they
said, ‘Yes we were absolutely successful’ I would instantly be suspicious, because
knowledge management is not straightforward. I want practical evidence that it
is painful. I want to see the blood and the guts. I want to know that they have
been there and they have struggled with KM.
What competencies does the knowledge
management leader need?
First and foremost, you need a proven ‘change agent’ to lead your KM implementation. Leading change is different from leading other types of projects, and requires distinct approaches and skillsets. People with a proven
history of change leadership are difficult to find in any organization, but the
ability of the KM leader to deliver change is a crucial success factor for the
implementation project.
Secondly, the leader needs influencing skills. Influencing management,
stakeholders and knowledge workers is a big part of the leader’s role. The
KM leader needs to have strong communication and influencing skills, and
if they are a proven change leader they will already have these. We cover
influencing techniques in more detail in Chapter 18.
The KM leader needs to know the company, the company structure and
strategy, the company terminology and the stories that circulate around the
organization, and they also need to be widely known. Ideally they should
have history and credibility in more than one division, rather than having
spent their whole career in marketing, or in research, or in finance. They
should know the important people, and have strong internal networks.
The KM leader needs the ability to take a long-term view. They need to
be in KM for the long haul, as an implementation project can take several
years before the framework is fully embedded. They need to focus on the
long-term change programme, while still moving KM forward through a
series of quick wins.
Above all, the leader needs to be able to translate KM into the day-to-day
working language of the organization. KM jargon and theory should be
kept within the KM team and their immediate circle of knowledge champions, while to the business, the KM leader should be able to speak in business
terms. This is another reason why the KM leader should be someone with
wide experience within the business divisions.
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Preparation and Resources
Tip
Assess yourself against these competences, and ask your team and your
manager to assess you as well. If you are lacking in any of these areas, see
what you can do to strengthen your competence. Build your network, go on
an ‘influencing skills’ course, or take training in change management. If you
aspire to a KM leadership role in the future, actively seek out diverse roles
within the business (not just in KM), and get involved in change
programmes. Find a mentor who has the qualities and competencies that
you aspire to, and observe how they handle tricky situations and
roadblocks.
The personality trap
A strong, passionate leader is essential for an effective KM implementation
team. However, the risk in relying on the personality of a strong leader to
drive transformation is that when the leader moves on, transformation can
falter.
For example, a project manager working in a major project in South
East Asia took the lead in implementing KM in his part of the business.
He set up a knowledge network of project managers who would meet,
exchange documents, and swap lessons learned for further re-use. And it
worked – in his area he cut costs, shortened timelines and improved
safety statistics. He acted as champion, thought leader, and role model
for KM within the wider business. Then he left, moving on to another
part of the business. The community stopped functioning. Knowledge
capture ceased. Many people in the business claimed that they were unaware of what he had been doing. Knowledge management in the South
East Asia division dwindled away and died. The culture reverted to where
it had been before.
No matter how strong the leader’s personality, and no matter how
much they can get done by personally driving change, there comes a time
when they have to pass over the reins – not to another strong personality,
but to an embedded framework that is going to function no matter who
is driving it.
Role, Skills and Characteristics of the KM Leader
Tip
Always have a succession plan in mind. If you are the KM leader, find
one or two understudies to mentor, or identify potential candidates who
can succeed you if you move on. If you are responsible for identifying
the KM leader, always keep a mental checklist of potential candidates,
and ensure any transition has at least six months’ preparation and
handover time.
A metaphor
People often think of knowledge as being organic. An ecosystem or a garden
is a pretty good metaphor for the world of knowledge in an organization.
Knowledge is something that grows and develops. It can be replicated and
seeded. It is not something solid and static like a car or a factory or a coin
that can be grasped and controlled and physically managed. Instead it needs
to be nurtured and tended.
The KM leader, in this metaphor, is the head gardener. If you want to
produce flowers or vegetables, there is hard work involved. Gardens require
a lot of management to bear fruit.
Let’s assume you are tending the knowledge garden for your organization, driven by a desire to create value for the key stakeholders – the knowledge workers, the management, and your external customers. If you want to
create value from a garden, you don’t just ‘create the conditions so anything
can grow’, because all you will get is nettles, brambles and other weeds.
Gardening is extremely active.
Tilling and fertilizing the ground
For gardening and for KM, you need to get the conditions right for
growth. This is the culture change element of your role – the communication strategy and the hearts and minds campaign described in Chapters
18 and 19. You need to provide the supporting infrastructure. Just as a
gardener needs to put in place the canes, cloches and trellises to support
the new seedlings, so you need to ensure there is sufficient technology to
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Preparation and Resources
support emergent KM activities (recognizing, of course, that technology
alone will not create KM, any more than trellises alone will create a
­garden).
Planting the seeds
These are the proof-of-concept events and the KM pilot projects (Chapter 22);
the early knowledge assets, KM practices and trial communities of practice
that you might set up where there is greatest demand and greatest value.
Watering and fertilizing the growing seeds
As a knowledge manager, the early seeds in your KM garden will need your
supervision and your support. You will need to work with the community of
practice leaders, the knowledge owners and the project staff to ensure the
early KM work does not wither and die through lack of care.
Propagating growth
Some of the plants in your KM garden will thrive. Learn from these, find out
the secrets of their success, and seek to reproduce them elsewhere. Just as a
gardener will take cuttings, runners and seeds from their prize-winning
plants, you too can propagate success from the best performers.
Removing the weeds and pests
If there are any things that hamper the growth in your KM garden – be these
incentives that backfire, loud sceptics, or misbehaviour in community-­ofpractice discussions – then you need to address them, and see if you can remove them before they start to spread. For example, incentives that drive
internal competition may need removal before they stunt the growth of KM
or kill your tender plants.
This is all very hard work, but the rewards for successful KM are the
same as those for a successful gardener – a thriving ecosystem and a mountain of produce.
Role, Skills and Characteristics of the KM Leader
Tip
If the head gardener metaphor doesn’t appeal to you, find another one.
Perhaps you are the knowledge supply chain manager, or the conductor of
the KM orchestra. A good metaphor can often help you keep your role in
context.
Summary
The role of the KM leader is crucial for the success of KM implementation.
In this chapter we have explored the role in detail, discussing the accountabilities, background and competence than an effective KM leader (or head
knowledge gardener) requires. In the next two chapters we will look at the
people who will support the KM leader: the KM team members and your
organization’s senior management.
References
Barnes, S and Milton, N J (2015) Designing a Successful KM Strategy: A guide for
the knowledge management professional, Information Today, Medford, NJ
Knoco (2017) Knowledge Management Survey [online] https://www.knoco.com/
knowledge-management-survey.htm (archived at https://perma.cc/VCY7-LHL7)
[accessed 26 January 2019]
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The KM team
members
06
One of the first decisions a KM leader will need to make is ‘who’s on the KM
team?’ This includes deciding how big the KM team needs to be, the skills
and competences you will need on the team, and the sort of personalities
you need to look for.
In this chapter we cover:
●●
the size of the KM team;
●●
the skillsets you will need on the team;
●●
the attitudes and values the KM team needs to share; and
●●
the roles you will need on the KM team.
How big should your KM team be?
How big is the average KM team? The answer depends on a) how big your
organization is, and b) what you mean by average. The results from the
Knoco 2014 and 2017 global surveys of KM practitioners show that the
mean size for a KM team is nine people, while the most common (modal)
size is four people (Knoco, 2017). However, this figure represents answers
from both small and large companies, and from organizations just starting
KM as well as those where KM is fully established in scope. It makes more
sense to look at the mean KM team size for different company sizes and different levels of maturity as shown in Figure 6.1.
Although KM team size depends on organizational size, with team size
growing progressively with larger companies, this is not a linear relationship. Increasing the organizational size by 10 does not result in a 10-fold
increase in KM team size. Also, even in the smallest companies, there seems
to be a minimum number for an effective team – three people.
KM Team Members
Figure 6.1 A
graph of KM team size for a variety of organizational size ranges and
levels of maturity
KM team size vs organizational size and level of maturity
25
21.9
Average KM team size
20
18.9
15.8
14.3
15
10.5
10
5
0
4.2
10.1
4.7
early stage
well in progress
fully embedded
10.8
5.1
4.5
3.0
100s
1,000s
10,000s
Company size
100,000s
SOURCE Knoco Limited
The non-linear relationship represents the two constraints of building a
minimum capacity, and economies of scale. There are many tasks which all
KM teams perform irrespective of the size of the organization: creating the
KM strategy, designing the KM framework, piloting the KM framework,
etc. However, a successful KM activity can scale rapidly with relatively little
support.
Implementation time can also be traded off against team size. When the
framework is rolled out, during the later implementation stages, the duration of the roll-out is a function of the size of the team that drives it. An
implementation team of three in a 30-person organization can sort out KM
in a few months. An implementation team of 12 in a 30,000-person organization may take a few years to do the same job.
Tip
Build a bottom-up estimate of the size of the KM team you will need to
deliver your KM programme, and then use the statistics here as a
benchmark. Are your figures realistic?
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Preparation and Resources
What skillsets will you need on your team?
There seem to be seven core skillsets people look for in a KM team, although the balance of these skillsets varies from one sector to another. You
will never find an individual who has all seven of these skills, so you need to
select a mix of people to cover all the skills. Here are the seven core skillsets:
●●
business skills;
●●
facilitation skills;
●●
knowledge organization skills;
●●
change management skills;
●●
writing skills;
●●
IT skills;
●●
project management skills.
Business skills
The most important skillset to have on the team is functional experience in the
work of your organization. If you work in a legal firm, you need lawyers on
the KM team. If you work in an aeronautical firm, you need aeronautical engineers on the team, and so on. KM team members need these skills and background to translate KM into the working language and working practices of
the business. When members of the team are working with KM pilot projects
in the business, they want to be seen as ‘part of the business’, not ‘specialists
from HQ who know nothing about our work’. The larger the organization
and the more types of work the organization does, the greater the number of
these business skills you will need, and ideally the KM team will contain people with solid backgrounds in each major organizational function.
Facilitation skills
Next you need people with facilitation skills. Many of the processes in your
KM framework take the form of facilitated meetings, and much of KM is
concerned with conversation. Your KM team will need to facilitate the meetings and the conversations. Look for the natural facilitators, and provide
facilitation training for the other team members as soon as you can. We’ll
discuss this in greater depth in Chapter 13.
KM Team Members
The skills of knowledge organization
Then you need people with skills related to the organization of explicit
knowledge. KM covers content as well as conversations, so you need people
on the team with information management, content management and/or library skills. The areas of metadata, taxonomy and document lifecycle management will all need to be addressed, and you will need some awareness of
records management as well, since records management forms one important aspect of organizational memory. We’ll discuss this in Chapter 17.
Change management skills
Also important are change management skills. The KM implementation
team has a tough job ahead of them, changing the culture of the organization. The ‘soft skills’ of influencing, communication and change are absolutely crucial, and core members of the team will need to be skilled in
­training, coaching and mentoring. The early stages of implementing KM are
all about raising awareness and ‘selling’ the idea. The team leader needs to
be supported by at least one person with presenting and marketing skills.
This person may also help to raise the profile of the organization’s KM
achievements and activities at external conferences.
Writing and journalism skills
You will need people with good writing skills. The processes of knowledge
capture and packaging are in some ways very akin to journalism.
Interviewing, capturing discussions, analysis, summary, write-up, presentation, are all part of the stock-in-trade of knowledge capture. Make sure
there is at least one person on the team with journalistic or writing skills.
IT skills
The team needs at least one person with IT skills, who is aware of the details
of the current in-house technology and the potential of technology as an
enabler of KM. This person should be able to liaise effectively with your IT
department and help define the most appropriate technologies to introduce
to the organization. When the IT team say something ‘can’t be done’, you
need someone who knows enough to be able to suggest an approach or
strategy to get it done.
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68
Preparation and Resources
Project management skills
Finally, since much of KM implementation is project and programme driven,
you need strong project management skills on the team. This includes experience in developing project plans with clearly defined major deliverables,
monitoring progress and managing scope, and adjusting the plans based on
lessons learned during the project.
Tip
Create a skills matrix. Use the seven core skills here as the horizontal rows,
and your candidate KM team members as the vertical columns. Tick off the
skills each candidate team member has, and ensure each of the core skills
is present in the team. Don’t forget to include yourself on the matrix. If you
find some skillsets are missing, think what you can do in terms of training or
recruitment to meet the gaps.
Attitude and values
In addition to the core skillsets, you also need the right attitude and values. The
members of the team need to be passionate and knowledgeable about KM.
They need training in the skills and theories of KM and best practice transfer,
and access to books, conferences and forums on the topic. They should participate in KM communities of practice. They must be enthusiastic about applying KM tools and techniques to enhance the quality of their own work.
Team roles
The skills and competences may translate to specific roles on the team (note
that sometimes one person can hold more than one of these roles). Here are
some of the roles you will probably need.
Project manager
For a large team, you may want to appoint a project manager to look after
the administrative aspects of the project: maintaining the project plan,
KM Team Members
­ anaging the budget, and creating the reports for the steering group. Having
m
a separate project manager will free up the KM leader to concentrate on the
change management aspects of their role.
Knowledge manager
The team will almost certainly need a knowledge manager, to maintain and
document the knowledge of the team, to build and coordinate a KM community of practice (including all KM champions), and to start to build the
corporate knowledge base on KM. This person will play the role of subject
matter expert for KM within the organization.
Communications lead
You will need somebody in charge of communications for the team, who
can manage and deliver the communication strategy and plan. In a larger
team, tasked with implementing KM across a large and complex organization, this is often a full-time role, and may even involve more than one
­person. Make sure this person is a skilled communicator, perhaps with a
marketing or internal communications background.
KM coaches
You will need people to go out and support KM activities in the organization. These people deliver the ‘proof-of-concept’ exercises and work with
the business implementing the pilots. This is the primary role for the businesspeople within the team.
Finally you may need people to take accountability for specific components or projects within the KM programme. Your IT specialist may take
accountability for the development of supporting tools, your knowledge organization specialist may take accountability for developing the enterprise
taxonomy, and so on. However, make sure that all of the roles work as a
coordinated team and not in isolation, otherwise the KM framework that
you develop and deploy may not work as a complete system.
Summary
The KM team has an important and varied set of tasks. They need to help
develop new ways of working and new knowledge-friendly behaviours
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Preparation and Resources
across the organization, and to do this the team needs to contain the correct
mix of skills embodied in a clear set of roles. Establishing the team is a key
step in the implementation programme. With the right team, you can accomplish anything. With the wrong team, your implementation will be
much more difficult. Even the best team, working with the best KM leader,
will need support from senior management. This support is the subject of
our next chapter.
Reference
Knoco (2017) Knowledge Management Survey [online] https://www.knoco.com/
knowledge-management-survey.htm (archived at https://perma.cc/VCY7-LHL7)
[accessed 26 January 2019]
71
The role of
senior
management
07
In addition to the KM leader and team, senior management also have a key
role to play. Besides helping them understand their sponsorship and steering
role, you may also need to coach them in supporting KM implementation.
This chapter covers the following topics:
●●
the role of the sponsor;
●●
the risks to effective sponsorship;
●●
the KM steering team;
●●
working with the other senior managers.
The role of the sponsor
The sponsor is the person who commissioned the KM implementation. They
act as your internal client for the implementation project and your representative at high levels, so the higher the level of your sponsorship, the easier
your job will be. Ideally you would want a C-level sponsor. At the World
Bank, for example, the president of the bank acted as sponsor for a KM programme to deliver his vision of ‘a knowledge bank’ – using KM to increase
employee effectiveness and efficiency across the organization. You would be
very lucky if you had such high-level sponsorship. It is more common for
sponsorship to be delegated down to a functional head or divisional head.
The main elements of the sponsor role during KM implementation are as
follows:
●●
To agree, with the KM leader and team, the aims and objectives of the
implementation programme and how these will be measured. The sponsor
is the primary client for the programme and will be the person who
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Preparation and Resources
judges the success or failure of the implementation programme, so make
sure you agree clear objectives which can be measured easily and
unambiguously.
●●
●●
●●
●●
●●
To challenge the KM team over these objectives. It is not the job of the
sponsor to give the KM team an easy ride. To show value to the business,
your KM objectives should be tough, and it is the sponsor’s role to add
some challenge.
To provide the required resources to deliver those objectives. The sponsor
provides the budget for the KM programme, which pays for the salaries
of the KM team and any travel that may be needed. They also provide the
legitimacy. They are the figurehead for the programme.
To provide the business view to the KM team, and represent the needs of
the business to the programme. The sponsor should help the team
understand what knowledge is strategic to the organization, so that KM
activities can fully support the strategic agenda for the business. To this
end, the sponsor often appoints and chairs a steering team (described
later in this chapter).
To regularly review progress. The sponsor chairs the review meetings that
ensure the implementation project remains on track.
To make commitments to proceed. This is an important point. The KM
team will deliver results, but they expect the sponsor to make decisions
based on those results. The expectations might be expressed like this:
●●
●●
●●
●●
‘If we deliver an effective plan to deliver KM, and demonstrate that the
key processes can work in the organizational context, we expect you
to give us approval to move to piloting.’
‘If the KM pilots fully deliver against the agreed objectives, we expect
you to endorse and support KM roll-out.’
‘Once roll-out has started, we expect your support in removing the
organizational barriers.’
To champion KM at a senior level. KM will not be the sole priority for
the organization, and there will be many issues competing for management
attention. The role of the sponsor is to talk and lobby on behalf of KM,
to ensure the resources are protected, and to broker alliances and remove
conflicts with other initiatives which may be going on. The sponsor is
also expected to provide political cover for KM in the early stages, before
results begin to show.
Role of Senior Management
●●
To remove barriers. Once implementation reaches the roll-out phase,
there may need to be changes to the way the organization operates in
order to allow KM to deliver its value; changes to the project management
framework, the reward and recognition system, or the accountability of
subject matter experts, to name but a few (see Chapter 23 for more
details). The sponsor may need to press for these changes in order that
the value from embedded KM can be fully delivered.
The risks to effective sponsorship
There are a few ways in which your sponsorship can be sub-optimal, and
you should be aware of these and prepared to redress the balance wherever
possible. Here are the top three.
A sponsor with a one-sided view. In Chapter 10 we describe how an HR
sponsor could be too interested in the KM roles, an operational sponsor
could be too interested in the KM processes, and so on. In each case you
need to ensure the sponsor’s view is balanced with other views through
the use of a KM steering team, as discussed later in this chapter.
A sponsor who is too low in the organization. Many of the roles of the
sponsor mentioned earlier – lobbying, removing barriers, brokering
deals – require the sponsor to have power and influence, which requires
a level of sponsor seniority.
A sponsor who is uninterested in KM. Where a sponsor has been appointed
with no real motivation or interest in KM, you will have real problems in
driving KM forward and getting it embedded into the business. See if you
can use your organizational connections to negotiate an interested and
committed sponsor. If not, then ask your sponsor, ‘What would you need
to see, in order to be fully enthusiastic about KM?’
Tip
How good is your sponsor? Do they pass the tests above? If they fall short,
what can you do to improve the situation? Use your peer networks in the
wider KM community to source ideas and strategies.
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Preparation and Resources
The knowledge management steering team
In change management terms, one of the critical elements is the steering
committee, known in change management terms as the ‘guiding coalition’.
This is an active team of diverse leaders who drive the change effort by
­providing guidance, resources and decision-making authority. A successful
steering committee is powerful in terms of its composition (titles, expertise,
reputations, relationships, leadership skills, access to support and resources),
their mutual level of trust and their shared objectives.
KM will usually need such a team to drive the change and steer the programme, particularly in large and complex organizations. The steering team
can also ensure that the business is fully represented in the planning and
decision making within the KM implementation. Steering team members
should represent the main functions (IT, HR, quality, etc) and the main lines
of business (marketing, sales, production, etc) in order to represent all primary stakeholders. They are not a decision-making board, but an advisory
board to the sponsor and so to the KM leader. They give decision-making
authority in the sense that decisions will be well informed, relevant to the
business, and likely to garner support.
The steering team members do not have to be KM converts. In fact, it is
probably useful if some of them have some level of scepticism. This adds a
level of real business challenge to the programme, and can ensure that objections are met and resolved early on. The steering team can also act as ambassadors for the KM programme in their own part of the business. The head of
IT, for example, can ensure that the needs of the KM programme are honoured by the IT department, the head of HR can help ensure KM expectations are included in the annual appraisal system, and the head of operations
can help identify and facilitate KM pilots in the operational departments.
The steering team should meet on a regular basis, for example quarterly,
chaired by the KM sponsor. They meet to review the progress and performance of the KM programme, and to advise on next steps.
Tip
Try to ensure that HR, IT, Projects, Strategy and R&D (if you have these
departments) are represented on your steering team. Try to ensure that it is
the head of department who attends, and ask your sponsor to make it clear
that this is what he or she expects.
Role of Senior Management
Working with the other senior managers
As you move into the later stages of KM implementation, the involvement
of all senior managers becomes increasingly important. Managers are
among the most powerful influencers of culture, so a manager who has
not bought into KM can create significant drag on behavioural change
that is needed. The senior managers are some of the most important
stakeholders and ‘selling’ KM to them will require many of the influencing techniques described in Chapter 18. By introducing KM into the manager’s business, you can help improve delivery, save money, increase
­customer satisfaction and reduce risk. In return, you will need several
things from them:
●●
●●
●●
●●
●●
You need them to invest in KM resources and roles within their part of
the business, for example the knowledge managers, subject matter experts
and KM champions. Help them to see that this is an investment rather
than a cost.
You need them to help steer the KM programme in their part of the
business. They should help the KM team understand which knowledge is
strategic for that specific business unit or business group, so your KM
activities can fully support the manager’s business agenda.
You need them to lead by example. KM is not something which will only
be done by the junior grades – the managers need to be involved as well,
so you would expect them to take part in KM events, and to contribute
their own knowledge.
Managers need to take the lead in setting an expectation for managing
knowledge in their part of the business. They need to make it clear what
they expect to see from their staff, asking questions like ‘Who have you
learned from?’ and ‘Who will you share this knowledge with?’ They need
to challenge their direct reports to continuously improve performance
through applying knowledge from others.
It is not enough to set expectations. They need to follow up on these
expectations. The organization will be watching closely how senior
managers deal with people who shirk their KM responsibilities, and who
refuse to learn and share. It will send a very negative message if senior
management ignore non-compliance, or reward and recognize the wrong
behaviours. This includes fostering internal competition that discourages
open sharing, rewarding the lone hero who ‘doesn't need to learn’, or the
75
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Preparation and Resources
knowledge hoarders who keep it all ‘in their heads’. Ask the managers to
recognize instead those who learn before doing, those who share hardwon lessons, and those who show bravery in admitting to mistakes from
which others can learn.
Tip
Use the guidance given in this section to write a one-page brief for your
senior management on ‘Your Role in Supporting KM’. Discuss this brief, and
their role, with them at the next steering team meeting.
Summary
Support from senior managers is generally recognized as the single most
important enabler for KM success, and its absence as one of the biggest
challenges (see Chapter 3). Ensure that you have an engaged, influential and
supportive sponsor, a representative and high-level steering team, and an
approach to engaging other management-level stakeholders as your implementation progresses.
77
Budget and
timescale
08
One of the big early decisions to be made in your KM implementation is to
decide the size of the budget and the timespan of the KM implementation
project. In this chapter we give you some guidance and some benchmark
figures from other organizations. The chapter covers:
●●
the need for a budget;
●●
the size of the budget;
●●
assigning your budget among the four KM enablers;
●●
benchmarking your budget;
●●
the duration of your KM programme;
●●
the self-funding trap.
The need for a budget
One of our colleagues was in a KM workshop recently with a client, and
raised the issue of KM budgets. One of the people in the room asked, ‘What?
Does KM need a budget?’
Yes, KM needs a budget. All KM programmes should have a budget. You
need a budget to pay the team who will plan and drive the change, bring in
people to help draft your strategy and framework, buy any new software,
and pay the trainers who will train staff in new processes and new roles. For
a global company you will need a travel budget for the KM team to visit and
work with the regions and divisions, perhaps to support the face-to-face
meetings of global communities of practice, or to facilitate knowledge transfer between globally separated projects.
For a large multinational company, the KM budget can easily run into
millions of dollars. This is not a cost, but an investment in greater effectiveness and efficiency. When focused on business value and framed well,
the value that KM will deliver can be 10 or 100 times the cost. Even if
you lack initial senior support and are attempting a bottom-up approach
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Preparation and Resources
to KM, you need to be clear about your costs and your returns if you are
going to translate any success you have into senior management support.
All KM programmes need a budget, no matter what their size or scale.
How big will the budget need to be?
You should first try to calculate the size of the budget from the bottom up, by
listing out your effort and resources required. You can then benchmark this
figure against global statistics. In the later stages of the KM programme the
bottom-up budget can be built from a detailed activity plan, as described in
detail in Chapter 20. However, in the early stages your plan will be poorly defined and the budget will be based on estimates of the cost of the KM team
over the length of the programme, plus allowances for travel, technology spend
and consultancy support. This initial budget therefore contains a lot of uncertainty. However, the costs will clarify over time, and your budget will be a living document. The budget for the roll-out phase, for example, will be much
clearer at the end of the piloting phase than it will be at the beginning. We think
the best approach, as used at Mars (Chapter 30), is to create a plan and budget
with a broad three-year time horizon and a more detailed ­one-year plan.
Tip
Work with your team to brainstorm all the tasks you think you will need to
perform during implementation, and write each of these on a Post-it note.
Use the tasks listed in Chapter 20 as a rough guide, even though more work
may be needed to confirm these later. This will give you the cost of internal
resources needed to complete the tasks. You then need to include external
spend on technology, travel, and any assistance from experienced
consultants to support your implementation.
Assigning your budget among the four
KM enablers
There is no magic formula for allocating your KM budget, but there is a
sense check you should apply to ensure you have covered all the angles. The
four KM enablers of Roles and Accountabilities, Processes, Technology and
Budget and Timescale
Governance were introduced in Chapter 1, and it is worth ensuring that
each of the enablers gets a significant share of the budget:
●●
●●
●●
●●
The spend on KM roles includes defining the roles that will be needed, as
well as coaching, training and supporting the knowledge managers, KM
champions and community of practice leaders in the business.
The spend on KM processes includes facilitating KM processes, documenting
them, and introducing them to the business through pilots and training.
The spend on KM technology includes user requirements analysis,
acquisition of new technology, integrating it into your infrastructure,
maintenance, and training the users.
The spend on KM governance includes monitoring, reporting, value
tracking, creation of guidance and reference material, development of
taxonomies and metadata schemas, engaging with the business to embed
KM into existing workflows, accountabilities and structures, and the
negotiation and drafting of the KM policy.
Often, we find that the companies we speak with spend far more on technology than on the other elements, and much of the time we find that their KM
programme suffers as a result. This is especially the case for KM programmes
that focus on managing and sharing explicit knowledge. Technology alone
will not deliver KM, and an overspend on technology is usually a signal of
a poorly balanced KM implementation approach. Conversely, we have
found that technology spend is significantly weaker among the KM enablers
for KM programmes that focus on learning and improvement. Getting a
balance of spend is crucial to sustainable KM.
Tip
Identify the elements within your budget which relate directly to the four
enablers of Roles, Processes, Technology and Governance. Bear in mind
there will be many other elements of the budget related to managing the
KM programme itself, for example change management, communication
etc, which are not directly related to any single enabler. Are these elements
of the budget roughly comparable, or within the same order of magnitude as
each other? If not, what have you missed? Which elements have you
underestimated?
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Preparation and Resources
Benchmarking your budget
Once you have the bottom-up budget, you can then benchmark it. There are
a few sources of benchmark data, the first of which is the global KM surveys
conducted by Knoco in 2014 and 2017 (Knoco, 2017). As part of this survey
participants were asked to specify the scale of their annual KM budget in
order-of-magnitude terms. Twenty per cent of the participants did not know
how much their budget was, and 10 per cent preferred not to share their
budget figure. The mean KM budget of the remainder of the respondents
was $785,000 per annum.
Obviously the budget will vary according to the size of the organization,
and will change as implementation progresses. The relationship between
budget and company size is non-linear, as shown in Table 8.1.
This non-linear relationship is linked to the same economy of scale we
saw in relation to KM team size. The bigger the company, the bigger the
impact you get from your KM programme and the more ‘bang for your
buck’ in terms of budget investment. KM team size and budget are more
closely correlated, with an average budget per KM team member of
$140,000, reflecting the salaries of the KM team and the uplift for travel
and external spend. This may be another helpful benchmark figure for you
to use.
Table 8.1
T he mean annual KM budget against company size and stage
of KM implementation, from survey data in 2014 and 2017
Organization size
(# of staff)
Early stages Well in progress KM fully
of KM
with KM
embedded
Hundreds of staff
$140,000
$200,000
$290,000
Thousands of staff
$400,000
$1.3 million
$1.1 million
Tens of thousands of staff
$600,000
$1 million
$3 million
Hundreds of thousands
of staff
$1.7 million
$1.9 million
$4.9 million
SOURCE Table reproduced courtesy of Knoco Ltd
Budget and Timescale
How long will it take to implement
knowledge management?
One of the most important questions affecting budget is how long the KM
implementation programme will take. KM can take a long time until it becomes embedded, but the period can be shortened with a well-organized,
supported and funded implementation programme. To benchmark how
long KM takes to embed, we can again refer to the results of the 2014 and
2017 KM surveys (Knoco, 2017). Survey participants described the level of
maturity of KM in the organizations in two ways; firstly with an estimate of
the number of years that KM had been a focus for them, and secondly with
a verbal description of maturity, by choosing whether KM was ‘in the early
stages’, ‘well under way’ or ‘fully embedded’.
You can see the distribution of maturity levels in the graph in Figure 8.1.
More organizations surveyed were in the early stages than at any other active
stage. The vertical axis shows the number of responses for each category.
Figure 8.1
Organizational KM maturity levels from surveys in 2014 and 2017
Which of the following best describes the current status of KM
within this organization (or part of the organization)?
300
278
Number of responses
250
229
200
150
115
100
53
50
18
15
0
We do not
We are
intend to
investigating
start
KM but have
not yet
knowledge
management
started
We are in
the early
stages of
introducing
KM
We are well
in progress
with KM
KM maturity status
SOURCE Figure reproduced courtesy of Knoco Ltd
KM is
embedded
in the way
we work
We tried KM
and have
given up
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Preparation and Resources
Looking at maturity levels by how long the organizations had been doing
KM is also instructive. The figures below demonstrate the relatively long
timescales involved in KM implementation:
●●
●●
●●
Organizations that self-assessed as ‘in the early stages of introducing KM’
had been doing KM, on average, for 3.5 years.
Organizations that were ‘well in progress with KM’ had been doing KM,
on average, for 8.7 years.
Organizations that said ‘KM is embedded in the way we work’ had been
doing KM, on average, for 13 years.
These figures are borne out by the experience of the Information and
Knowledge Management Society’s ‘KM Excellence Awards’ between 2008
and 2012 in Singapore. In these awards, silver showed significant business
impact in parts of the organization, and gold showed pervasive business
impact across the organization. In line with the figures above, silver and
gold award winners had typically been implementing KM systematically
and methodically for eight or more years.
If the early stage lasts more than 3.5 years, and embedding takes place
somewhere after 8 years and before 13 years, then KM is a long-term affair.
This does not mean that it takes 8–13 years to show business value, or return on investment. With well-chosen pilots, you can show value very early
on. But it does mean that it takes a long time for KM to become fully sustainable and embedded in the organization. KM implementation takes
longer for large organizations, as you might expect. Figure 8.2 shows that
for small organizations of fewer than 300 staff, the average number of years
at which they judged they were ‘well under way’ was just over five, compared to nearly 10 years for the organizations with over 100,000 staff.
Tip
Use these figures to sense check the timeline for your KM implementation
and your budget. Allow for the size of your organization and your starting
point – whether you have a supportive culture, or have any elements of KM
in place already. If your budget and timescale are radically different from
the global benchmarks, then seek external advice from experienced peers
or well-established KM consultants to check your figures.
Budget and Timescale
Figure 8.2 Average number of years doing KM vs. KM maturity levels by ­organization
size (number of staff)
Average number of years KM experience for
companies at each maturity level
16
14
12
10
8
just starting
6
well under way
embedded
4
2
0
100 to 300 1,000 to 3,000
10k to 30k
100k plus
Company size categories
SOURCE Figure reproduced courtesy of Knoco Ltd.
Beware the self-funding trap
We have seen more than one organization where the KM team was told they
had to become ‘self-funding’. In other words, they would receive no centrally funded money, but instead would generate funds to cover their own
operating costs by charging the business for their services. This is not a valid
model for KM implementation for the primary reason that it causes the
team to become tactical rather than strategic. In Chapter 2 we discussed the
dual implementation approach of delivering short-term business wins, while
at the same time driving long-term organizational change. If the KM team
becomes self-funding then they will be motivated to deliver the quick wins
for the business, but nobody will fund them to do the long-term cultural and
behavioural change. You should resist this pressure, and avoid the self-­
funding trap!
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Summary
Implementing KM is a lengthy process requiring a substantial budget. You
can use benchmarking to build early estimates, but be prepared to refine this
as you progress and gain more experience of your own organization’s special characteristics. The message that ‘KM is long term’ may arouse concerns
that KM might not be able to show returns to the business in the short and
medium term. In the next chapter we address this by looking at how to set
business goals, metrics and SMART objectives for the programme.
Reference
Knoco (2017) Knowledge Management Survey [online] https://www.knoco.com/
knowledge-management-survey.htm (archived at https://perma.cc/VCY7-LHL7)
[accessed 26 January 2019]
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09
Aims and
objectives for
the KM
implementation
programme
In this chapter we address the aims and objectives that you set for your KM
programme. We assume that you have already developed a KM strategy, and
that you have a shared vision with your sponsor about what KM can
achieve. Now you need to get much more specific, and start to define what
your KM programme will deliver, in measurable terms.
This chapter covers the following topics:
●●
benefits mapping;
●●
setting interim objectives;
●●
making your objectives measurable;
●●
choosing the key business metrics;
●●
setting your targets;
●●
dealing with imposed targets;
●●
what to do if you cannot measure value in monetary terms;
●●
the risk of confusing measures with targets.
Benefits mapping
The aims and objectives of your KM programme need to be expressed in
terms of organizational outcomes. It is tempting to write objectives such
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Preparation and Resources
as ‘deliver better access to knowledge’, or ‘improve innovation and the
retention of knowledge’, but neither of these is a helpful objective in business terms. Your organization does not exist to retain knowledge or deliver access to knowledge, but to make money, deliver services, or sell
products. The KM objectives need to be linked to these organizational
objectives, so that everybody is clear that what you are doing is supporting the core business of the organization. We use a technique called benefits mapping as a graphical way to link your planned KM interventions
to the objectives of the business. The template for the benefits map is
shown in Figure 9.1.
Figure 9.1
KM
interventions
Benefits map template
Business changes
Measurable
outcome
Strategic
goals
There is a column on the left where you put your planned KM interventions;
in the column on the far right you put the main strategic goals for the organization; then, to the left of this, identify a number of measurable outcomes relating to those strategic goals. The space in between is where you
create your benefits map.
Let’s imagine that you are working for a sales and marketing organization. Your main strategic goals are growth, profit and sustainability, so you
begin by entering these in the right-hand column.
Aims and Objectives for the Implementation Programme
You have decided with your team that suitable KM interventions might
include the creation of a new markets community of practice, a sales wiki, a
marketing knowledge base and a consumer forum. You enter these down the
left-hand column. Then, starting from the left, you map what each of the
KM interventions makes possible. These go in the ‘business changes’ area,
on the left, with an arrow coming from the relevant intervention, as shown
in Figure 9.2.
Figure 9.2
The first round of populating the benefits map
New
markets
CoP
Sharing what
works in new
markets
Sales wiki
Sharing of
sales tips
and hints
Marketing
knowledge
base
Sharing of
marketing
tips and hints
Consumer
forum
Better
understanding
of consumer
KM
interventions
Business changes
Growth
Profit
Sustainability
Measurable
outcome
Strategic
goals
This is the first round of mapping. The second round is to ask what the
changes you have just identified will make possible, and add these as new
boxes moving always to the right, and joined by arrows (for example,
sharing sales tips and hints may make it possible to develop sales best
practices). Then you repeat the process a third time, and possibly a fourth
or fifth time, until the business changes become measurable using standard business metrics, in which case you put them into the ‘measurable
outcomes’ column, linked to the relevant strategic goals. If you are not
able to work your way through to the measurable outcomes on the right,
then this is a sign that the proposed KM intervention may not be appropriate to the business goals. An example of a completed benefits map is
shown in Figure 9.3.
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88
Figure 9.3
A completed benefits map
Identification
of knowledge
gaps
New
markets
CoP
Sales wiki
Marketing
knowledge
base
Sharing what
works in new
markets
Sharing of
sales tips
and hints
Sharing of
marketing
tips and hints
Innovation in
new markets
Development
of new market
best practice
Development
of sales best
practice
More sales
staff use best
practice
Development
of marketing
best practice
Better
marketing
campaigns
Better marketing
Consumer
forum
Better
understanding
of consumer
Improved
share in
existing
markets
Growth
More sales
Profit
Better
customer
retention
Sustainability
Better products
Create
community
spirit
KM
interventions
Happier
consumers
Faster
growth
in new
markets
Business changes
Happier more
engaged staff
Better staff
retention
Measurable
outcome
Strategic
goals
Aims and Objectives for the Implementation Programme
This map establishes a clear relationship between the KM interventions and
the strategic goals. For example Figure 9.3 suggests that by introducing the
KM interventions, we should be able to deliver faster growth in new markets, an improved share in existing markets, more sales, and better customer
and staff retention. Each of these is measurable and each could be a potential business objective for the KM programme. The map can be expressed as
a statement, eg, ‘Through the introduction of a sales and marketing KM
framework, we will increase sales in existing markets and deliver faster
growth in new markets.’ Note that you do not have to list every single objective; just select the ones that you are most confident about and in which
your sponsor and steering team are most interested. Note also that at this
early planning stage, this benefits map represents a set of hypotheses about
how KM should support KM goals. You’ll have to watch the measurable
outcomes column carefully to verify that these hypotheses are correct.
Tip
Create the benefits map in a workshop with your team, and with your
sponsor if possible, using a large whiteboard and Post-it notes. The
workshop format allows you to access a wider range of ideas, and can
unite your team behind the potential business objectives. If you involve your
sponsor it will also reinforce in his or her mind that KM really will help
deliver better business performance.
The interim objectives
The benefits map you have created here represents a long-term view of what
KM will deliver to the organization. However, as we described in Chapter 2,
the implementation project will be delivered in a series of steps, and the preroll-out phases also have specific objectives.
The planning stage
The objectives of the planning stage will be to deliver a credible KM implementation plan and an agreed number of completed proof-of-concept exercises which have been judged by the people in the business to have been
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valuable exercises in their own right. The credibility of the implementation
plan will be judged by the steering team, and the evaluations of the businesspeople involved in the proof-of-concept exercises will be captured as a series
of success stories.
The testing and piloting stage
The objectives of the piloting stage will be to deliver an agreed number of
KM pilots, and through these pilots to deliver an agreed set of business outcomes. The level of business outcome needs to be high enough to convince
the steering committee, at the end of the piloting stage, to approve a systematic roll-out of KM across the organization. In fact, when you are setting the
objectives for the piloting stage, you should agree in advance with the steering committee what quality of outcomes would count as sufficient evidence
to warrant general KM roll-out.
Tip
As we showed in Chapter 8, implementing KM is a long-term process
which can take years to become sustainable and embedded. Rather than
try too hard to develop objectives for the complete project, concentrate
on creating objectives for each stage, or even for each year. If you are
too rigid in your forward planning, then your plan will be unable to adapt
to the changing circumstances of your business. As you progress you
will be able to better understand what KM can deliver to your
organization, and each year you will be able to set objectives with
greater confidence.
Making the objectives SMART
Reaching this level of agreement with the steering committee will be far
easier if you make sure that the objectives are specific, measurable, actionoriented, realistic and time-bound (SMART). SMART objectives are particularly important in the piloting phase, as this phase provides the evidence
to support the major decision to roll out KM. As an example, during the
piloting stage of the BP KM implementation in the late 1990s, the objective
Aims and Objectives for the Implementation Programme
was ‘to deliver $100 million in benefit to the business through KM pilots in
1998’, to be measured through reduced budget submissions from the business in the following year. The objective was very specific, measurable and
time-bound, and although at the time the team didn’t feel it was very realistic, in practice it proved to be achievable.
To create SMART objectives such as this, you need to know:
●●
●●
●●
what business metrics your KM programme will address (these will have
been defined through the benefits mapping exercise, and example metrics
are covered in the next section);
the approximate impact your KM efforts will deliver; and
some way of measuring the improvements in the metrics (which implies
that you already have a baseline measure).
Impact metrics for knowledge management
The metrics that you use to define your KM programme objectives should
be business metrics related to the type of business that you do (other KM
metrics are covered in Chapter 24). Some of the common business metrics
that will be impacted by KM are listed below, with the most commonly used
metrics at the top of the list, as reported in the Knoco 2014 and 2017 KM
surveys (Knoco, 2017).
Time to find information
Your KM framework will almost certainly include components related to
improved accessibility of critical knowledge and information, making it
easier for people to find the knowledge and information they need, and so
improving operational efficiency. To demonstrate these efficiency gains, you
will need to measure how long people spend searching for information before and after KM implementation. This is a very commonly used metric,
but saving costs through reducing the time to find information is seldom a
significant concern for senior managers, and is not always where the major
value of KM lies. Managers tend to be more interested in big topics such as
project cost overruns or the failure to secure large bids. However, in a large
company, and in environments where time is a critical factor (such as law
firms, consulting businesses, fast-moving technology companies), this measure may be important.
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Time to competence for new staff
This metric is important for organizations that are growing rapidly, or
have a high turnover of staff. The more rapidly you can bring new staff to
competence, the more efficiently they will work, and the less you will experience productivity dips while staff get up to speed. As an example, the
US Nuclear Regulatory Commission, a rapidly growing organization, focused their KM efforts on knowledge transfer. Setting up communities of
practice for new inspectors and providing links to training resources reduced by 25 per cent the time it took new employees to qualify, from two
years down to a year and a half. Those employees are able to ‘go solo’
sooner instead of having to be paired with more experienced workers for
longer (Johnson, 2011).
Project or operational costs
By capturing and reusing lessons and best practices from projects and operations, organizations can improve the way they work, eliminate repeat
mistakes, reproduce process improvements, and so reduce cost. The more
expensive the projects and operations, the greater the value that KM can
bring. This is the primary KM impact metric for all organizations involved
in major projects in the oil and gas sector, the construction sector, and in
major engineering companies. For example, Ajimoko (2007) reported a 40
per cent reduction in time and cost to drill a well on the Saih Rawl field in
Oman, through the application of lesson learning.
Project or activity cycle time
As well as doing things more cheaply, KM can help projects do things more
quickly. For construction projects and other projects with large penalties for
delay, speed is of the essence. Taylor (2014) describes how Crossrail (a massive European railway construction project in London) delivered significant
time savings by sharing lessons and best practices through an ‘innovation
portal’:
[At the Pudding Mill Lane site in Stratford, East London] the contractors had
struggled with erecting a reinforced earth wall. They tried a new technique,
which had mostly worked, but there were a few problems. So they captured the
lessons learned and logged the new construction technique on the innovation
Aims and Objectives for the Implementation Programme
portal. A year later, contractors at the Plumstead site, also in East London,
were having difficulties with a reinforced earth wall of their own, while battling
severe time constraints. Fortunately, the innovation team was able to point them
in the direction of the innovation portal and the lessons learned from Pudding
Mill Lane. These were taken and developed further in order to devise a frame in
front of the wall. [This]… took three weeks off production and they delivered
the wall on time.
Product and service quality
For manufacturing companies creating products, for organizations such as
legal firms and consulting companies delivering services, or for government
departments that generate policies and support citizen services, product or
service quality is a very important business measure. Poor-quality products
and services can result in rework, waste, product recall, unhappy customers,
and even lost customers. For such organizations, product or service quality
can be the most important measure KM can impact; even more important
than cost or time. Steve Wieneke of General Motors used an existing taxonomy, 138 best practice teams and a set of subject matter experts to populate and maintain ‘Technical Memory’, a database of explicit knowledge and
best practice designed to standardize product quality (Wieneke, 2008).
According to Ash (2007), early outcome metrics demonstrated the value of
this KM initiative:
During the 36 months in service, for vehicles sold during 2000 through 2003,
actual warranty costs dropped by almost 20 per cent below forecasts. The
catalogue of engineering solutions, technical memory and closed-loop learning
are three of the current 10 activities identified as the engineering enablers
driving the warranty cost down.
Sales volume and market share
For sales organizations, cost, time and quality may be insignificant compared to the impact of increased sales. Firms such as Mars (Chapter 30),
Kraft Foods, Coca Cola and Heineken all deploy at least some of their KM
activities in service of sales. KM can also impact the success of bids and
competitive tenders, as shown in the example below from Aon Insurance
(Adams, 2004).
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CA S E S TU DY
Aon Australia’s Melbourne office received an invitation to tender for the
insurance business of a leading Australasian toll-road company, which was held
by one of Aon’s major competitors. The timeframe for the tender submission was
very tight, allowing for little time to gather data and statistics. The Australian
account director sent an email to the Property GPG [global practice group, a
knowledge-sharing forum similar to a community of practice] requesting urgent
benchmarking information that would demonstrate Aon’s global expertise in the
field of toll roads, tunnels and bridges.
Information on the insurance cover of similar companies was quickly
collected from across the globe… Property experts from China, Hong Kong,
Canada, Brazil and Belgium sent details regarding their clients’ cover, which
were anonymized to protect their identities – a good data protection policy.
The practice group was able to visibly demonstrate exactly what the toll
company’s international peers were paying for property cover and provide details
about limits and deductibles. Within 24 hours, Aon’s Melbourne office received the
information; two days later the presentation was made to the company and less
than two weeks after that Aon Melbourne was appointed as the new broker.
Customer satisfaction
For many customer-facing organizations, the critical business metric is not
cost or time, but customer satisfaction. Satisfied customers mean loyal customers, with high levels of customer retention leading to a stable or growing
market share. An example of KM impacting customer satisfaction is provided by Lawley (2007), who describes how a combination of coaching and
communities of practice improved the operation of call centres at the telecoms operator Orange.
KM practitioners are often criticized for running initiatives that cannot easily be
assessed in traditional business terms, such as return on investment. However, in
this case the results were almost immediate and quantifiable. The KM team could
point to a steady increase in the customer satisfaction figures in the months after
the community [of practice] system was put in place, increasing from 69 per cent
to 76 per cent. This was a remarkable achievement in such a short space of time
and primarily attributed, in the company, to the change in coaching style.
Aims and Objectives for the Implementation Programme
Tip
When choosing metrics to measure the impact of your KM programme, it is
best to select from the standard set of business metrics already being
collected and reported in your organization. These metrics have been chosen
because they are important to senior managers, and will already have a
baseline to allow you to recognize the poor performers whom KM can help,
and to measure progress against. If instead you create your own set of
metrics, then firstly you have to create your own baseline, secondly you have
to create your own measurement system, and thirdly you need to convince
your senior management that these metrics are significant to the business.
Setting the value targets and estimating ROI
All of the metrics described in this chapter can be positively impacted by KM,
as the stories show. Your benefits map will help you identify which metrics are
most likely to be impacted by the KM initiatives you are proposing. These
metrics will allow you to measure success, and will help you determine the
value targets you will aim for. Value targets are most important for the piloting
stage of KM implementation, as the value delivered from the KM pilot projects
will create the business case for KM roll-out, as we discussed in Chapter 2.
The best way to set your value targets is to sit with people from the business and work back through the benefits map to see where the leverage points
are for KM, and to estimate how much difference KM can make. For example, Figure 9.3 above suggests that a ‘new markets’ CoP can drive the development and application of best practices in new market development, leading to
faster growth. You may have selected this area as one of your pilot projects,
and if so you would need to estimate the value a KM pilot may deliver.
In this example, you would work with people in the new markets area to
discuss:
●●
●●
The current growth rates of the new markets (measured in income
growth, sales growth, or whatever the standard business metric is). This
forms your baseline.
The current limits on growth, whether any of these might be related to
knowledge, and whether the business will support your assertion that
developing and deploying best practice will accelerate growth.
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●●
●●
How much impact knowledge sharing might have – for example, if the
slowest-growing markets were to learn the secrets of success from the
fastest, what impact might this have? Could they grow 10 per cent faster?
Twenty per cent faster?
The overall growth rate improvement in the new markets that KM could
therefore deliver.
This growth rate improvement will inform your target for the new markets
pilot.
Usually each of the targets for your pilot projects can be converted into
monetary terms. Imagine you agreed that KM could realistically help deliver
a 3 per cent improvement in new market growth. You should be able to
convert this figure into improved sales and improved profit. You can then
sum up the monetary targets to create an overall target figure for the p
­ iloting
phase.
It is worth saying at this stage that it is better to under-promise and overdeliver. If you feel you could realistically deliver $20 million in benefit from
your KM pilot projects, then perhaps it is safest to set $10 million as your
official target. The road to value delivery is complex, and one or more of your
pilot projects may be withdrawn, or fail to deliver the expected value (this is
less likely if you select the pilots wisely, following our advice in Chapter 22).
Tip
As part of your pilot project planning, create separate benefit maps for each
of your pilot projects, in conjunction with the pilot project sponsor. These
benefit maps will be very helpful in determining pilot-specific targets, as
well as providing a valuable framework for discussing KM value with the
sponsor.
Dealing with imposed targets
Sometimes you do not have the luxury of choosing your own targets. The
1998 BP $100 million value target in mentioned earlier in this chapter was
not calculated by the KM project team, but imposed from above by the
steering committee. In a circumstance such as this, you may have little
Aims and Objectives for the Implementation Programme
ability to negotiate. If this is the value they need to see to be convinced of the
importance of KM, then that is the value you need to deliver.
Here again, working through the benefits map with the relevant business
leaders can help you to identify ways of extracting greater value from the
pilots. For example, if the benefits from the KM interventions in the lefthand column do not look like they can deliver the expected benefits, then go
back to your team and ask, ‘What else should we be doing to increase the
value?’ Working through the benefits map is an iterative process, from left
to right, and from right to left, until all the stakeholders are comfortable
that it represents a practical and feasible representation.
What if you can’t measure value
in monetary terms?
Not every organization will measure value in monetary terms. A fire and
rescue department, for example, does not measure its success in terms of
money. Neither does a hospital. Both are much more likely to focus on
measures of quality, where quality can mean the difference between life and
death (reduction of mistakes, adverse outcomes, accident and injury rates,
or improved recovery rates). Time measures may also come into play – time
to competence for new staff, time to effective response to an emergency situation, waiting time for patients.
There is always a way of measuring the value that KM brings. The important thing is to find an outcome that is valued by both knowledge workers
and management, that KM can impact, and that you can measure in some
way. It helps if there are existing benchmarks for the outcome, and if this
outcome is already reported to management.
Not all measures should be targets
It is worth adding a cautionary word here. While effective KM planning
depends on rigorous approaches to measurement and setting targets, it is
sometimes easy to get distracted by the measures we use, and to confuse
value measures and outcome targets with activity measures (see Chapter
24). It is tempting, before you achieve your desired outcome targets, to seek
some indicators of progress, especially if your targets are ambitious. For
example, if you establish a community of practice, you may want to
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measure participation rates to be assured that you are on track. This is an
activity measure, and although participation rates in a community of practice are suggestive, they do not actually tell you whether you are moving
towards your desired value outcomes.
Not all measures work well as targets, and turning them into targets can
have unintended consequences. Take this example from IBM’s efforts to
build a repository of best practices in the 1990s (Barth, 2000):
Contributions [to a knowledge base] were reflected in performance evaluations
and/or bonuses. Everyone submitted. But we were on a calendar year, so 90 per
cent of our submissions came in between December 15th and 31st. Worse, there
was no process to monitor the quality of the written contributions. Not only did
they all come in at one time, but they were incredibly long and unintelligible.
Forced to improve the method, IBM eventually created a community submission
process involving a network of experts that on a rotating basis review, comment
on and request contributions to the knowledge base.
By turning the metric of submission quantity into a target, IBM was actually
compromising the quality of its knowledge base, and subverting its original
intent. We will cover the topic of KM metrics in more detail in Chapter 24.
Summary
This chapter covers one of the most difficult areas in KM: setting objectives
and targets, and demonstrating value. The benefits mapping approach that
we described here is a tool to help you and your internal customers work
through how and where KM can add value, which leaves you with the tricky
last step of estimating exactly how much value you think you may be able
to deliver. Notice this is an iterative and collaborative activity, undertaken
with your business customers.
Despite its difficulty, this step is crucially important. Throughout this
book we have linked KM and business value, and when you come to set
your KM programme objectives you have to make this link not only explicit, but also something against which your performance will be measured.
Luckily the amount of value which KM can create is often far greater than
we realize. Be bold, set your targets, and have faith that you will reach them.
Aims and Objectives for the Implementation Programme
References
Adams, S (2004) Practice makes perfect, Inside Knowledge, 9 (4), pp. 25–27
Ajimoko, O (2007) Technical limit thinking produces steep learning curve, World
Oil, 228 (7), pp. 103–6
Ash, J (2007) Case report, General Motors: changing gear, Inside Knowledge,
10 (8) pp. 18–21
Barth, S (2000) KM horror stories, Knowledge Management Magazine [online]
http://web.archive.org/web/20060612222246/http://destinationkm.com/articles/
default.asp?ArticleID=923 (archived at https://perma.cc/YNM4-S95G) [accessed
28 January 2019]
Johnson, N Blake (2011) NRC knowledge center helps younger employees benefit
from experts’ experience, Federal Times, 29 August
Knoco (2017) Knowledge Management Survey [online] https://www.knoco.com/
knowledge-management-survey.htm (archived at https://perma.cc/VCY7-LHL7)
[accessed 26 January 2019]
Lawley, D (2007) Call centre KM, in Developing a KM Culture, ed. J Goodman,
pp. 69–74
Taylor, L (2014) Pinch with pride, Association for Project Management News,
November [online] https://www.apm.org.uk/news/pinch-with-pride/ (archived at
https://perma.cc/MS63-RY42) [accessed 28 January 2019]
Wieneke, S (2008) Adopting and adapting product best practices across General
Motors Engineering six years later, in Knowledge Management for Services,
Operations and Manufacturing, ed. T Young, pp. 142–65, Chandos Publishing,
Oxford
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Finding partners 10
to help you
In Chapter 1 we said that one of the functions of the KM team is to orchestrate KM-related activities among partner disciplines. We also said that to
be sustainable, KM has to be embedded in the everyday workings of the
organization. This means that KM is not ‘done’ by the KM team ‘to’ the rest
of the organization; the organization needs to be facilitated through a process of adopting and embedding KM technologies, roles, processes, and governance elements which they can apply and use themselves. These elements
usually have distinct functional units that need to be consulted and coordinated with: IT for technology, HR for people and some elements of governance, Strategic Planning for other elements of governance, and Operations
for process.
In this chapter we look at the orchestration role that the KM team has to
play in KM implementation to ensure that the four enablers are properly
coordinated and addressed. We cover the following topics:
●●
who should be responsible for KM?
●●
KM as partnering;
●●
initiating strong partnerships;
●●
transitioning partnerships through your KM journey;
●●
identifying non-obvious partners.
Who should be responsible for KM?
We are often asked, ‘Who should be responsible for KM: IT or HR?’ In fact,
we have worked with KM teams led by many different corporate functions,
from IT to HR to organization development, organization excellence, quality
management, corporate planning, information management, even corporate
communications. We’ve also worked on KM initiatives that were run out of
specific ‘line of business’ operations such as marketing, drilling or R&D.
Finding Partners to Help You
The 2014 and 2017 KM surveys (Knoco, 2017) identified a wide range of
reporting lines for KM teams, shown in Table 10.1:
Table 10.1
Reporting lines for KM teams
Reporting line
Percentage of responses
Separate reporting line to senior
management
21%
Operations
13%
IT
9%
Strategy
8%
Learning and development
6%
HR
4%
Projects
4%
Business improvement
4%
R&D
3%
Innovation
3%
Quality
2%
Sales and marketing
2%
Engineering
2%
Legal
2%
Internal communications
2%
‘Other’
16%
SOURCE Data courtesy of Knoco Ltd
So it seems as if many reporting lines are possible. What is probably more
important is whether:
a the KM team has the high-level sponsorship described in Chapter 7, a
KM leader with the right qualities and influencing skills (Chapter 5) and
a KM team with the right competences (Chapter 6); and
b the team is able to ensure balance between the four KM enablers.
Each of the corporate functions we have mentioned previously is likely to
have a bias towards specific enablers or elements of KM:
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Preparation and Resources
●●
●●
●●
●●
IT has a bias towards technology and finds that easier to deal with, so
KM teams which report to IT may neglect the other enablers.
HR has a bias towards areas like corporate culture, roles and responsi­
bilities, and learning and development, and KM teams which report to
HR may not have the capability to influence the other enablers with any
great authority.
Corporate functions like organization excellence, quality management
and corporate planning may have insight into the operational areas of the
business, but KM teams which report to these functions may not have the
background to deal with the cultural and technology aspects of KM.
Corporate Communications is likely to have a bias towards ensuring
good information flows and situation awareness, but a KM team within
Corporate Communications may have weaknesses in dealing with areas
like learning, expertise, knowledge retention and KM technologies.
These functional biases are risks, but if treated carefully the risks can be
managed. For example, one of us worked with an IT team that developed
and implemented a balanced and effective KM strategy covering both tacit
and explicit knowledge needs. They started small, focused on getting good
results for the business, solved some pain points, attracted the attention of
HR, who came on board to support them on the people side of the equation,
and also involved corporate planning, who helped to integrate KM planning
into the annual work planning process. They were able to manage the risk
because the KM leader had the qualities (and the patience) we described in
Chapter 5, and because the sponsor (the CIO) was willing to step outside
her comfort zone and try some small experiments.
However, we have also worked with an enlightened IT team that also
came up with a balanced KM strategy, but then met with an antagonistic
response from the HR team, who refused to cooperate because ‘IT is intruding on our turf’. The technology aspects of the initiative were able to proceed, but the people, process and governance aspects were stymied by the
refusal of HR to treat KM needs as a priority in their work plan. It turned
out that the IT Director and the HR Director did not get along, and although HR attended meetings during the strategy development process,
they were uncommitted, and bided their time until action was required, at
which point they refused to acknowledge KM as a priority in their agenda.
If you have influence over the decision on where KM should reside, then
the ideal is that the KM team exists, during the implementation phase, as a
Finding Partners to Help You
separate small department or task force with a separate reporting line to
senior management (the most popular option in Table 10.1). They can then
develop ways of working with the other key functional departments.
There are three structural ways of working with these key functions:
1 If several of these functions are grouped together in a ‘corporate support’
cluster, then the KM department can be located within this cluster, under
the same boss.
2 Select your project sponsor based on their oversight or influence over the
corporate functions you will need to work with.
3 Ensure that the other functions are represented (ideally by the heads of
function) on your KM steering team (Chapter 7).
At the end of the day, however, there is no ‘one size fits all’ answer. You will
need to read the culture and politics of your organization in order to understand where the influence and capabilities needed to implement KM reside.
Tip
If you have not yet identified the reporting line for the KM team, consider
the balance of needs listed above, including the sphere of influence of your
KM leader and sponsor, the key functions that will need to be involved
in KM implementation, and the accountability to the business. Where
should KM be placed in your context?
KM as partnering
‘Partnering’ is a concept most highly developed in the world of non-profits,
NGOs and commercial joint ventures, but it is a useful one for KM implementation. Partnership is more structured than collaboration, but it is less
formal than a set of delegated responsibilities. Partnership expresses a voluntary coalition, developed and agreed upon as equals, where the different
partners bring different resources and capabilities to a commonly agreed
agenda. It recognizes that the partners have differing priorities and agendas
outside the partnership agenda, and that they need to balance the benefits
of partnering with their other needs. Hence it stresses ‘complementary
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­ bjectives’ over ‘common objectives’, ‘agreements’ over ‘­ contracts’ or ‘mano
dates’, and ‘participation’ over ‘consultation’ (Tennyson, 2003).
This is a useful model for KM, because all of KM’s likely partners (HR, IT,
L&D etc) have responsibilities and priorities that go beyond KM. KM may
be at the centre of your universe but it is not at the centre of theirs. In a partnering approach, this is explicitly recognized and transparent to everybody
involved, and the approach is one of respectful negotiation. The implications
of the partnering approach are very clear. From the KM strategy phase onwards you will need to identify your potential partners and engage with them
so that they can participate in the planning for the next stage.
Your KM steering team (Chapter 7) is the mechanism for enacting the
partnership. The partnering approach makes it clear that the KM steering
team is not a group of ‘to be consulted’ stakeholders, but a ‘to be engaged’
group of stakeholders, actively involved in planning, resourcing and reviewing each cycle of activity. The resource mapping technique is a useful tool for
identifying and engaging potential partners. Figure 10.1 shows a resource
map template for a typical KM project.
Figure 10.1
Resource mapping template
Information
collection
Documentation
Needs analysis
Desk research
People
Accommodation
Volunteer, activity
participants
Champions
Representatives
Offices
Venues – meeting rooms,
training rooms,
refreshments
CAPABILITIES
Technology
People
Process
Governance
Relationships
Supplies
Line departments,
managers
Specialists, experts
External suppliers
Information
dissemination
Staff communications
Communication
channels
Word of mouth
SOURCE Adapted from Tennyson (2003)
Printing
Collateral
Equipment, IT
Finding Partners to Help You
This template can be used within your team to brainstorm potential partners to join your KM steering team. Use it to think about what resources
you will need for your next stage of activity, in each of the capability areas
of technology, people, process and governance, and in each of the likely resource needs, from information collection, to accommodation and supplies,
to information dissemination, people, relationships and expertise. Identify
the partners who can give you access to those resources and capabilities.
Tip
Together with your team, look at your outline KM strategy and use the
resource mapping framework to brainstorm who you should engage as
partners in the implementation stage.
Initiating a partnership
The resource mapping template is also a powerful engagement tool at the
beginning of each partnering stage, when the invited partners are gathered
to a partnering initiation meeting. When partners attend this meeting they
will have differing perceptions and expectations, and probably differing levels of motivation as well. The purpose of the initiation meeting is to create a
shared agreement that will form the basis of your activity throughout the
next phase, whether it be identifying proof-of-concept projects, expanding
to pilots, or implementing a full KM roll-out.
An initiation meeting has four distinct stages.
1. Assessment of need
The partners need to have a shared understanding of the current situation,
the major problems or challenges to be overcome, and a common understanding of the root causes to be addressed. Depending on where you are in
the process, you may have different input to share with them, for example
the needs analysis for the KM strategy, or the knowledge resources audit
findings (described in the following chapter). Your partners will have their
own perspectives on this input, and these perspectives need to be heard and
acknowledged.
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2. Shared vision
If you have developed a KM strategy you should already have a vision statement for what KM should achieve for the organization. This needs to be
accepted, internalized, and/or adapted by the partners in terms that they are
comfortable with. The shared vision is what helps the partners to identify
and agree on an over-arching goal for the next phase of activity.
3. Benefits and costs of partnering
At this stage, before you move to firm commitments, the partners need to
have a frank and open discussion about the benefits and costs to them of
participating. Thus far, you have been speaking in terms of the benefits to
the organization as a whole. However, partners also need to be clear about
what concrete benefits they will receive for their own functions as a result of
the KM initiative. They also need to be open about their constraints and
challenges, and the potential cost of participation.
Maybe HR has an intensive competency framework consultancy about
to start. Maybe the IT department is in the middle of implementing a
CRM project and it is not going well. Maybe Corporate Communications
is tied up with getting the Annual Report out, and is currently understaffed.
It is important that these constraints and commitments are surfaced,
because if they are not surfaced they cannot be addressed, and three things
can happen: (1) your plan ends up being too ambitious and impractical;
(2) you lose the opportunity to clarify the benefits to participation to key
partners; or (3) you lose the opportunity to leverage parallel projects and
activities by exploiting their own needs analysis and information-­gathering
activities, or by aligning KM projects to support those other corporate
initiatives.
If your organization culture is not very open and transparent, and you do
not feel that participants in the meeting will be open about their hesitations
and concerns, then you will need to do significant pre-work before the initiation meeting to gather this insight. This might be through one-on-one
meetings. After that you will have to skilfully facilitate the meeting to elicit
these factors of concern. It’s not sufficient that you alone are aware of these
constraints. In effective partnering, all the partners need to have this sense
of transparency about benefits and costs.
Finding Partners to Help You
4. Agreed objectives and contributions
Once there is a strong common understanding of benefits, costs and constraints, the partners need to agree what the objectives are for the next stage
of KM implementation activity. As part of this, they need to agree how they
will contribute to these objectives, and what the expectations will be about
roles, responsibilities and accountabilities. This is where the ‘respectful negotiation’ begins, as they seek to balance this initiative with their other priorities and other demands on their time and resources.
The resource map template shown above can be useful here. Post a large
version of it up on the wall, and working from the agreed objectives, ask the
partners to brainstorm contributions into each section, using Post-it notes.
Continue until everybody agrees that the resource commitments match the
agreed objectives.
At this stage, in the spirit of respectful negotiation, your partners may
wish to go back and check with colleagues before any hard commitments
are entered into. Hence we would normally separate this initiation meeting
from an action-planning meeting, at which firm commitments, timelines,
and accountability procedures are agreed.
Transitioning the partnerships
Partnering implies repeated cycles of activity. Your partnering needs should
be reviewed at every transition you make, from KM strategy to identifying
proof of concept, from proof of concept to pilots, from pilots to full roll-out.
This is to ensure that you have the appropriate resources and support you
need for each stage of activity, as it spreads and as it scales up.
Some partners will stay with you for the long haul, but their contributions will change. Some partners will come in early and drop out for a while
if they are not actively needed, then be reintroduced later on. Sometimes the
role of a KM partner becomes institutionalized, and a formal part of their
functional responsibilities. This is more and more likely to happen as the
KM implementation matures, and as you start transitioning from implementation to steady state (Chapter 26).
At each stage, each partner should review the partnering requirements
for the next phase. Healthy partnerships are continually reviewed and renewed
as the environment matures. These transitional stages need to be celebrated. Tell
the story of the partnership up to that point, what it has achieved, and the challenges it has faced and overcome. Celebrate the contributions of the different
partners. They become a model for partnership in your successive phase.
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Identifying non-obvious partners
Some partners are obvious; they are the corporate functions that bear significant responsibility for one of the four enablers of KM. We have already
identified several of them. Some partners are less obvious; they are functions
or disciplines with whom you have overlapping and sometimes competing
interests.
Policy owners
Because one of your enablers is governance, any owners of corporate policies are potential candidates for engagement as partners because their policies might compete or conflict with yours (the creation of a corporate KM
policy is discussed in Chapter 23).
We worked with an organization whose CEO and senior management
enthusiastically endorsed a policy statement that said, ‘It is our policy that we
increase our organizational efficiency and effectiveness through knowledge
sharing and reuse’. Some time later we came across the same organization’s
information security policy that said, ‘Sharing of information is on a need-toknow basis only’. Here we had two policies that were, if not in conflict, at the
very least in tension with each other. The role of a corporate policy is to
clarify what is expected of employees, but we had muddied the water by not
resolving an important inconsistency at the outset. The KM team worked
with the information security department to develop a set of compatible policies giving much clearer guidance on what information and knowledge
could be openly shared, and what information needed greater protection.
Policy owners may be constrained by legislation, regulation, contractual
or external compliance requirements, in areas such as privacy, confidentiality, intellectual property rights, commercial risk, or compliance against audited standards. All of these may have some bearing on how knowledge
pertaining to that policy domain is captured, stored, protected and shared.
Information and data management functions
‘Adjacent’ disciplines are also potential flashpoints for discord if not identified early. These include records managers, data managers (and owners of
data-based business applications), information managers and corporate
­librarians.
Records managers deal with the capture and preservation of documentary records of the organization’s decisions and activities. While accessibility
Finding Partners to Help You
and usability of records is within their remit, as a profession they have
tended to place greater emphasis on preserving the integrity and reliability
of records than on ensuring that they are easily accessible for everyday use.
If your goal is improved accessibility, you’ll have to work with them on
making sure the records within their purview are actually more easily retrieved and used.
Data managers deal with data in structured form, often in line of business
applications, to support specific activities and transactions, and also to support decision making through the use of analytics and reporting tools.
Information managers deal with information support to the business
such as the management of information in documents and structured or
unstructured web content. Your work in knowledge organization (Chapter
17) may overlap substantially with theirs.
Corporate librarians typically look after published information resources
made available to the organization, both electronic and hard copy, manage
subscriptions to databases and other types of content, and may do selective
dissemination of information to specific functions in the organization.
All of these functions deal with the more explicit forms of knowledge, but
taken together they already present a confusing spectacle to the average
knowledge worker, before we even add an additional layer of KM. Overlaps
and complementarities should be reviewed and discussed.
Learning-oriented functions
There are some professional functions that span internal organizational
boundaries even though they may have central coordinating functions.
These include project management, quality management, risk management,
and health, safety and environmental (HSE) management.
These functions have two things in common with each other, one of
which makes them particularly amenable to KM, and the other which makes
them formidable resisters if not engaged early in the process:
1 They all have a strong interest in learning. In project management, project
effectiveness, cost, cycle time, and efficiency are all affected by the ability
to learn before, during and after a project so that repeated types of
projects can be completed cheaper, faster and better than their
predecessors. In quality management, quality is often improved, and
these improvements shared, using processes very similar to KM processes.
In risk management, known risks need to be identified and assessed at the
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start of a project or activity cycle (which often requires experience as well
as access to past lessons), effective strategies for avoidance, mitigation or
recovery identified, and triggers identified to alert the team to the
emergence of any risks. In HSE, lessons from previous incidents improve
safety awareness and education, as well as providing a base for avoiding
such incidents in future. The capture of minor incident and ‘near miss’
reports and their analysis can go a long way to improving the safety
culture of an organization.
2 These functions are highly constrained by set procedures and, in some
cases, external regulatory compliance requirements or standards. The
way they conduct their work is highly governed, and changes in how they
work need to be consistent with their pre-existing operating models. It’s
all very well for KM to come in and propose learning processes and
models for knowledge capture and re-use, but if these models are not
consistent with the operating models of the discipline, and do not ‘speak
the language’ of the discipline, they will not be adopted. If these are
functions that are likely to be targets of KM projects, then they need to
be identified, engaged and partnered with at a very early stage.
Tip
1 Make a list of the corporate policies that might have some impact on
how knowledge is managed in your organization, and identify their policy
owners as potential stakeholders and partners.
2 Your business focus will sharpen as soon as you start identifying
candidates for proof-of-concept and pilot projects. Look at the potential
stakeholders in those business areas from the data, information and
records point of view. Do they need to be engaged as partners?
3 Are there any other major corporate initiatives rolling out information
platforms, data-based business applications, or records management
systems? Do they need to be engaged as partners?
4 Which functions in your organization have a strong interest in learning?
Are they highly constrained in the way that they operate? Are they likely
to be targets for KM initiatives, and do they need to be engaged as
partners?
Finding Partners to Help You
Summary
The KM reporting line can affect delivery, and if KM reports through a preexisting corporate function it may face challenges in reaching beyond that
function’s core capability. Given a choice, we recommend an independent
reporting line for the KM implementation programme. More important
than the ‘ownership’ question, however, is the need to engage in active partnering with the other functions in the organization whose help you will
need. In this chapter we have covered the elements of successful partnering.
We will complement this later on in Chapter 18 with some advice on influencing the wider pool of stakeholders. In Chapter 28 we’ll discuss the idea
of working with external parties such as trusted consultants, consortia and
professional peers.
References
Knoco (2017) Knowledge Management Survey [online] https://www.knoco.com/
knowledge-management-survey.htm (archived at https://perma.cc/VCY7-LHL7)
[accessed 26 January 2019]
Tennyson, R (2003) The Partnering Toolbook, International Business Leaders
Forum, London
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113
PART THREE
Assessment and
planning
Executive summary
Part Three covers the critical foundation work for any KM implementation.
Chapter 11 covers the knowledge resources audit, which provides the evidence you will need for detailed planning. Chapters 12–16 will help you
assess your needs against the major elements of the KM framework to ensure that your KM implementation remains balanced and integrated.
Chapter 17 explains how the discipline of knowledge organization supports
the goals of the KM framework. Chapters 18–19 take you through the steps
involved in mobilizing others through the implementation process, and
Chapter 20 will help you turn your assessment findings into a detailed implementation plan.
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115
Conducting the
knowledge
resources audit
11
At this point, you have completed your preparation for KM implementation, you have your KM strategy to guide you, and you should have the
resources to start delivering, embodied in your sponsor, team, leader,
budget and partners. It’s now time to start looking at potential areas
where KM may add value. You may already have conducted some form of
strategic audit or assessment as part of your strategy-building phase, you
may already have identified strategic areas of knowledge on which to
focus, and you now can conduct a detailed, more granular analysis to
help you identify specific potential KM initiatives at the operational level
in your organization. This is called a knowledge resources audit. By
‘knowledge resource’ we mean an identifiable area of knowledge or competence owned by the ­organization, and which may or may not be well
managed.
The chapter covers the following areas:
●●
●●
●●
a definition of the knowledge resources audit and how it relates to other
forms of knowledge audit;
an explanation of why a knowledge resources audit is useful for KM
implementation, and how it helps to avoid common pitfalls;
what it is that we are auditing when we audit operational knowledge
resources;
●●
the steps in a knowledge resources audit;
●●
analysing the results from a knowledge resources audit.
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Assessment and Planning
What is a knowledge resources audit?
We use the term ‘knowledge resources audit’ to distinguish it from the more
generic term ‘knowledge audit’. We need this distinction because the term
‘knowledge audit’ can cover a number of quite diverse activities:
●●
assessment of KM practices or KM capabilities (mentioned in Chapter 4);
●●
a culture audit in relation to knowledge-sharing behaviours (Chapter 19);
●●
assessment against a KM standard (Chapter 27);
●●
evaluation of existing KM programmes and their effectiveness;
●●
creating a baseline inventory of knowledge resources and analysing the
opportunities and gaps.
This latter activity is the one we are focused on in this chapter.
If you have developed your KM strategy in a robust way, you will probably already have conducted a KM assessment and identified strategic organizational knowledge areas that need to be protected, preserved, scaled up
or created (Barnes and Milton, 2015). Strategic knowledge areas are highlevel capabilities in an organization. To be able to work towards implementation and help you define practical KM projects, they may need to be
­broken down to more operational level components through a knowledge
resources audit.
For example, in a tax authority, a strategic knowledge area or capability
might be ‘how to detect tax fraud’. To be able to figure out what to do
about protecting this capability, we need to break this down to how the
capability works out at operational level. For example, knowledge embedded in algorithms that analyse tax payment patterns, segmentation of
­taxpayers and benchmarking them to detect anomalous behaviours, the
experience of seasoned tax officers in spotting anomalies that the algorithms don’t catch, investigation skills, forensic analysis of tax records, explicit knowledge embedded in guidelines and checklists, case studies and
lessons learned from past investigations, and so on. We need to understand
how well these knowledge resources are managed for each major tax type
such as income tax, property tax and corporate tax. We need to be able to
understand the knowledge flows that feed the strategic capability, and to
detect gaps and risks in the operational knowledge resources, or blockages
in the knowledge flows. This is what an operational knowledge resources
audit does.
Knowledge Resources Audit
The typical output of a knowledge resources audit includes:
●●
●●
●●
an inventory of knowledge resources associated with each key business
activity or strategic capability – in diagrammatic form this is often called
a knowledge map;
a representation of knowledge flows (confusingly, this can also be called
a knowledge map);
an analysis of knowledge risks, knowledge accessibility issues, and
knowledge resource gaps.
How does the audit help a KM
implementation?
In Chapter 2 we recommended a trials and pilots approach to KM implementation, supplemented by a readiness to be opportunistic in responding
quickly to pressing business needs. In such a dual strategy, the knowledge
resources audit helps you to link opportunistic KM projects to the overall
strategy by giving you a clear connection between the strategic knowledge
areas and the specific operational changes that you are making in the proofof-concept and pilot projects. It also gives you a detailed understanding of
how knowledge works at the operational level, and where your leverage
points are in the implementation phase.
If your strategy were compared to building a house, the knowledge resources audit functions like a site survey, to understand the characteristics of
the ground on which you want to build. With a site survey you can make better
decisions about how to build, how high you can build, and what building materials to use. Similarly, a knowledge resources audit can help you avoid pitfalls
in KM implementation, since it will give you a very clear picture of your highvalue knowledge, and any current weaknesses in how it is managed.
What are we auditing?
Knowledge resources audits measure more than just explicit information and
the documented knowledge that is carried in documents and databases. In this
chapter we use a six-part framework to identify different knowledge resource
types, heavily influenced by David Snowden’s ASHEN framework (Snowden,
2000). In the list below we have supplemented Snowden’s framework with an
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additional knowledge resource type which represents the way we access
knowledge in other people through relationships and networks. Here are the
six different types of operational knowledge resource that an organization
typically uses in order to carry out its various business activities.
Documented knowledge
This is the only type of resource that represents completely explicit knowledge, ie knowledge that has been codified in text, pixels, bytes, etc. This type
of knowledge may include printed material such as manuals and standard
operating procedures (SOPs), as well as digital information in shared folders,
databases, systems and webpages, audio-visual materials and other artefacts.
Skills
Skills represent knowledge embedded in people’s ability to perform a task,
usually acquired through training and practice. Skills cannot be communicated through documents, and they differentiate knowledge gained by doing
from knowledge gained by reading. For example, reading a document on
how to ride a bicycle, including how and where to position the limbs and
maintain balance, does not equip you with the skills to ride a bicycle, which
are gained through practice. Skills-based knowledge is differentiated from
experience-based knowledge (described later) in that skills can be trained,
whereas experience requires deepening of knowledge through repeated
practice over time.
Methods
Methods represent a form of implicit knowledge, embodied in ways of
working, but not completely explicit. Methods can be observed in the ways
in which work gets done and can include procedures, processes and workflows, as well as shortcuts and heuristics. We identify knowledge resources
as ‘methods’ if there is a set, routine and habitual way of doing things that
employees learn when they enter a work unit, but when not all aspects of
these methods are documented in SOPs. If a process is completely documented by SOPs, then it will be represented in the audit as a document.
Examples of method knowledge might be processing of various applications
and permits, conducting study trips to learn best practices from others,
benchmarking, regular meetings with customers, and so on.
Knowledge Resources Audit
Relationships
Human beings do not have sufficient brainpower to store all the knowledge
we need for our lives. So we distribute our knowledge socially, meaning that
we do not need to know everything, so long as we have relationships with
people who know the stuff we are not knowledgeable about. We capture
knowledge resources as relationships when the knowledge we need to perform an activity resides within other people, and it is only possible to access
this knowledge through relationships. The relationships might include those
with vendors and suppliers, governing bodies, partners and collaborators,
internal departments where tight coordination is required, or within a community of practice. Some areas of work are highly dependent on access to
knowledge through relationships. It’s usually not enough to know who
knows what, however. We also need some degree of familiarity with each
other (which gives us the ability to understand each other’s needs and communicate concisely and effectively) and some degree of trust (which affects
somebody’s readiness to help us and give us rich replies). This makes relationship knowledge resources much less easy to transfer than, say, documents, methods, or skills.
Experience
Experience refers to the ability to identify trends and patterns in what’s happening around us, and to respond effectively. It is acquired over time and
with frequency of observation and reflection. It is valuable and is not easily
replicated, and contributes to positive outcomes in business activities.
Experience is different from skills because while skills may be trained, experience may not. Skills give us the ability to deal effectively with relatively
standard situations. Experience gives us the ability to deal effectively with
unusual and challenging situations. Examples of experience knowledge resources are risk planning, responding to emergency or crisis situations,
­complex negotiations, and so on.
Natural talent
Natural talent is innate and occurs naturally in people. Some people do certain things better than others because of their natural ability, quite apart
from their training or experience – for example in mathematics, interpersonal skills, art and design. This kind of knowledge resource cannot be
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constructed or replicated. It is difficult to manage but needs to be nurtured
nonetheless. The range of work situations where natural talent is important
is relatively limited (largely because reliance on natural talent constitutes a
risk as it is difficult to replace).
Tip
Try conducting a knowledge resources audit during the scoping stage of
each KM pilot, just focused on that work area, to understand the KM issues,
the knowledge gaps and the knowledge flows.
What are the steps in a knowledge
resources audit?
In a knowledge resources audit you first identify the target business activities you are interested in at the operational level. You can then conduct one
of two main types of audit: a comprehensive audit or a targeted audit.
In a comprehensive audit, you work systematically through the departments in the organization, and through all their core business activities as
defined by them. The comprehensive audit will be slower, but will likely pick
up important organization-wide insights that you may have missed at the
strategy phase.
In a more targeted audit, you focus on those departments and teams that
are engaged in the strategic knowledge areas or the organizational capabilities you have already identified as core to your KM strategy. The targeted
audit will be more focused and swifter to conduct, but you may miss blind
spots not picked up earlier.
It might be worth planning two audits – a targeted one in the early stages
of the implementation programme to identify quick wins and pilots, and a
comprehensive one later as part of planning for the roll-out phase. The success of the earlier targeted audits can help you justify the effort involved in
the comprehensive audit.
Once you have identified the business activities you are interested in, then
you need access to two or three people who have experience in those activities (typically middle managers at the operational level) to help you map:
Knowledge Resources Audit
●●
●●
●●
●●
●●
the knowledge that is currently available and being deployed in those
activities;
knowledge resources that are not currently available but that would help
to make those activities more effective (knowledge gaps);
where the knowledge comes from, how it is accessed, and who has it;
the knowledge resources that are produced as a result of performing the
activity;
where those knowledge resources go, and who applies them.
The maps you produce with these experienced staff will give you rich insight
into the balance between the more explicit and tacit knowledge types, will
give you evidence from the knowledge workers themselves of knowledge
gaps, and will identify existing knowledge flows.
There is another powerful step you can take, however. If you expose the
knowledge maps to the other departments and teams in the organization,
and ask them to identify knowledge resources inventoried in other teams’
maps that would be useful to them in their own business activities, you can
very quickly identify knowledge resources that are not currently being made
widely available, but that would be helpful if shared. This enables you to
identify high-value, high-demand knowledge resources, and can yield unanticipated benefits from the knowledge resources audit exercise. You are
more likely to get these unanticipated benefits from a comprehensive knowledge resources audit than from a more targeted one.
Tip
Review your KM strategy. Which would be more appropriate at the current
stage for your organization, a comprehensive knowledge audit or a more
targeted one? (Hint: this will depend on how focused or broad your strategic
knowledge areas are, and on how important it is for you to improve wide
accessibility to knowledge resources.)
Analysing the results of the audit
If you understand the balance of different knowledge types required to perform the key business activities you are interested in, then you immediately
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have clues about what KM implementation steps would be appropriate or
inappropriate to manage this knowledge.
Documents and data
If you have an activity that is heavily dependent on documented knowledge
resources, then the classic way to improve the management of documents on
any scale is through information management supported by IT systems and
content management or document management solutions. There are also
processes which can be put in place to support management of this knowledge type: eg using standardized templates to introduce consistency in how
documents are presented, developing taxonomies to enhance the findability
of information and knowledge, and so on. Chapter 17 discusses some of
these measures further.
Skills
Skills-dependent activities are most straightforwardly managed through
training. Typical activities are training needs analysis, competency mapping,
training plans and e-learning solutions. However, not all skills work is necessarily delivered in training rooms or online. It can also be supported
through on-the-job training, job shadowing, apprenticeships, coaching and
mentoring.
Methods
Methods represent unwritten routines and heuristics. Because of this, one of
the easiest ways to manage this kind of knowledge is by documenting it in
standard operating procedures, operating guidelines, FAQs, quick tips or
step-by-step tutorials. However, methods that are quite sophisticated or
complex (for example where skills or experience are also involved) might be
better managed by giving people access to more experienced colleagues
through a help desk, expertise directory, or supervisors.
Relationships
There are three ways to enhance relationship-based knowledge access. First
is allowing staff to find others with relevant knowledge, for example people
Knowledge Resources Audit
directories listing areas of expertise or experience. Second is providing the
capacity to ask a person for help, and this is not easily done on a ‘cold-call’
basis. It is much easier if the different parties are already known to each
other, and ideally have trust relationships already formed. This is why proactive socialization opportunities, building up the informal social capital
among groups who belong to different knowledge domains, are so powerful. Thirdly, the development of communities of practice focused on critical
knowledge areas encourages the formation of structured and facilitated relationships through which knowledge can flow. Chapter 13 discusses this in
further detail.
Experience
Business activities that have a heavy reliance on experience-based knowledge are more vulnerable to the departure of key people, and trickier to
manage. Development of experience can be facilitated through job placement, assignment to specific work areas, career- and succession-planning
programmes, knowledge retention and transfer programmes, mentoring,
coaching and job shadowing. KM processes such as knowledge exchanges,
peer assists and retrospects provide facilitated opportunities for experiencebased knowledge to be identified, discussed and shared. Communities of
practice can discuss and share experience through community dialogue processes such as knowledge exchange. While it is a more challenging set of
knowledge resources to manage, the acquisition and sharing of experience is
a core task for knowledge management.
Natural talent
Natural talent can only be managed by managing the people themselves.
Once you are aware that a particular work area is especially dependent on
natural talent, then you need to rely very heavily on your HR processes for
attracting, motivating and retaining the talent you need. There’s very little
else you can do in the way of growing or transferring this kind of
knowledge.
Besides the insight that the balance of knowledge resource types gives
you, there are some other specific pieces of analysis that you can undertake
to sharpen the focus and usefulness of your implementation projects. We
call this a ‘RAG’ analysis, standing for:
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●●
●●
●●
Risk analysis – the more tacit types of knowledge resource (relationships,
experience, natural talent) expose you to greater risk than others because
they are harder to acquire, transfer or grow. In a risk analysis of the maps
you will look at tacit knowledge resource dependencies, and check
whether those knowledge resources are concentrated in just a few people,
whether you are at any risk of sudden loss, and whether you have
processes in place to identify, capture, transfer, or grow this knowledge.
Accessibility analysis – when you capture the data about the knowledge
resources you will also capture data about where they are located and
who has them. When you expose the maps to other departments, you
pick up information about the latent (currently unmet) demand for key
knowledge resources. You can put these two pieces of analysis together
and identify strategies for making high-value knowledge resources more
accessible to those who can benefit from them, either by moving them to
a common platform (in the case of documents) or documenting them (in
the case of methods) or providing knowledge retention and transfer
programmes in the case of the more tacit knowledge resources.
Gap analysis – when you conduct the mapping sessions, it is important to
ask the representatives if there are any knowledge resources that are not
currently available that would make the activity more effective. These
‘desired’ knowledge resources are your knowledge gaps. Once you know
what the gaps are, and have assessed them for criticality, you can identify
strategies to meet those gaps.
The analysis from a knowledge resources audit will throw up a lot of insights and ideas that will be candidates for quick-win proof-of-concept
­projects or KM pilot projects. It is important that you sense check these
candidates against the priorities outlined in your KM strategy.
Summary
The knowledge resources audit is a powerful method for surfacing potential
KM interventions that have both strategic and operational benefits. It helps
you focus on the knowledge that is in most need of attention, and engages
with some of your most important stakeholders – the knowledge workers.
In this chapter we have identified the purpose, scope and content of a knowledge resources audit, and described how it connects to the KM strategy and
feeds into the KM implementation planning. In subsequent chapters we
Knowledge Resources Audit
look at how you begin to build and test your KM framework, and engage
with that other ‘ground level’ factor, your organizational culture.
References
Barnes, S and Milton, N J (2015) Designing a Successful KM Strategy: A guide for
the knowledge management professional, Information Today, Medford, NJ
Snowden, D (2000) The ASHEN model: an enabler of action, Knowledge
Management, 3 (7), pp. 14–17
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The knowledge
management
framework
12
In this chapter we take a high-level look at the management framework for
KM that you will need to implement. An effective embedded KM framework is your final goal, and your implementation programme is a process of
designing, testing and refining the framework. This chapter introduces the
concept of the framework, and provides a template structure. We cover:
●●
the concept of a framework;
●●
why a framework is needed;
●●
the principles behind the framework;
●●
a KM framework template;
●●
different types of framework;
●●
framework – structured or emergent?
What is a management framework?
Every management discipline is implemented as a framework, and KM
should be no exception. By a ‘framework’ we refer to a linked and integrated set of roles, processes, technologies and governance that ensures that
an asset is properly managed. ISO 30401:2018, the management system
standard for Knowledge Management, uses the term ‘management system’
instead of ‘framework’, but the term ‘system’ is so commonly used in KM
circles for the IT system alone that we prefer the word ‘framework’ as less
ambiguous. The ISO standard also identifies roles, processes, technologies
and governance as the elements that need to be in place for a sustainable and
responsible exercise of the discipline. ‘Culture’ is sometimes identified as a
Knowledge Management Framework
framework element, but we see culture as an output as well as an input –
something that KM creates as well as requires. Moreover, culture cannot be
directly managed in the way that other framework elements can. ‘Content’
is also sometimes identified as a framework element, but we see content (as
well as conversation) as being managed by the framework, rather than being
an element of the framework itself.
Let’s investigate this concept by looking at another management framework – the framework for financial management. Although knowledge and
money are not the same, both require an organization-wide integrated management framework if they are to flow round the company in an effective
and systematic way. Some of the common elements of financial management
frameworks are as follows.
●●
Financial management roles:
{{
{{
{{
{{
●●
●●
budget holders – the people accountable for money within projects
and operations;
accountants and cost engineers – the people doing the nuts and bolts
of money tracking;
central finance team – the people who shuffle money between the
projects and operations;
CFOs and Finance Directors – the people accountable for the financial
management system itself.
Financial management processes:
{{
financial planning and forecasting;
{{
budgeting;
{{
invoicing;
{{
cost control;
{{
cost tracking;
{{
billing;
{{
financial reporting.
Financial management technology:
{{
technology for logging and tracking transactions, such as SAP;
{{
technology for reporting figures, such as Excel;
{{
technology at point-of-sale, including tills, cash registers and card
readers.
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●●
Financial management governance:
{{
financial policies;
{{
accounting standards;
{{
legal requirements;
{{
monitoring and auditing;
{{
training and support.
All of these elements fit together into a financial management framework,
allowing money to be acquired, tracked, spent and reported, and helping
develop and sustain a culture of fiscal responsibility. The complexity of the
framework needs to fit the scale of the operation. The framework listed
above has 19 elements. Financial management frameworks in very large
organizations can easily have more elements; in very small organizations
some of the elements may be merged together.
If any of the elements were missing, the framework would be severely
weakened. Imagine how well financial management would perform with no
budget holders, or with no financial reporting, or no company-wide financial technology, or no auditing. Each element of the framework protects
against risks of failure in the financial management function. Financial management therefore needs a minimum framework consistent with the scale of
the business, and if there are holes in that framework, financial management
becomes impossible.
Why we need a framework for KM
A KM framework, like a financial management framework, will contain a
mix of roles, processes, technologies and governance, which collectively enable the acquisition, sharing, maintenance and re-use of knowledge. Like
financial management, KM needs a minimum number of elements in the
framework, and if there are holes in that framework, KM becomes unviable.
Here are some examples of the risks:
●●
●●
If there were no people accountable for KM within projects and
operations, then no attention would be paid to KM because it would be
‘nobody's job’, and it just would not get done.
If there were no defined process for knowledge capture, the organization
would not know what to capture, or when, and each unit would capture
knowledge in its own way (or not) rather than to a common standard.
Knowledge Management Framework
●●
●●
If there was no consistent KM technology, there would be no way of
compiling, comparing and communicating knowledge across the
organization.
If there were no KM governance, there would be no way of knowing
whether people were doing proper KM, people would cut corners and
fudge practices, and soon a consistent approach to KM would disappear.
The benefit therefore of applying a management framework to KM is to
ensure that all enabling elements are covered and that there are no missing
elements. If we return to the concept of KM as a supply chain, as we discussed in Chapter 1, the framework ensures that the supply chain is complete. Every element of the framework is a link in the chain, and a complete
framework means there are no links missing.
Tip
Review some of the existing successful management frameworks in your
organization, and map out the roles, processes, technologies and
governance that sustain them. Look at quality management for example, or
safety management, or HR management. These successful frameworks will
give you some idea of the level of scale and complexity your KM framework
may need to be viable in your organization.
A template for your KM framework
In Chapter 1 we introduced the four knowledge enablers of roles, processes,
technologies and governance, and the four knowledge transactions of discuss, document, synthesize and find/review. These match the enablers in ISO
30401:2018 clause 4.4.4, with the exception of culture, as mentioned above,
and our four knowledge transactions match the four elements of ‘Knowledge
conveyance and transformation’ in clause 4.4.3 (ISO, 2018). Together these
can be used as the axes of a 16-cell table which we recommend as a template
for building a KM framework. The purpose of using these elements as the
axes of the table is three-fold:
●●
to provide you with a generic template that can apply in any organization
of any size in any industry;
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Assessment and Planning
●●
●●
to ensure the framework is as complete as possible and that all enablers
and transactions are addressed;
to enable compliance with two of the clauses in ISO 30401:2018.
An empty framework template is shown in Table 12.1.
Table 12.1
An empty KM framework template
Discuss
Document
Synthesize
Find/review
People
Process
Technology
Governance
The 16 cells in the template are listed below, and detailed examples of potential roles, processes, technologies and governance to be incorporated in
your framework are given in Chapters 13 through 16:
●●
roles for facilitating or supporting discussion;
●●
roles for facilitating or supporting documentation of knowledge;
●●
roles and accountabilities for knowledge synthesis;
●●
roles for facilitating or supporting finding and reviewing knowledge;
●●
processes for discussing knowledge;
●●
processes for documenting knowledge;
●●
processes for knowledge synthesis;
●●
processes for finding and reviewing knowledge;
●●
technologies for supporting discussion;
●●
technologies for supporting documentation of knowledge;
●●
technologies for knowledge synthesis;
●●
technologies for supporting finding and reviewing knowledge;
●●
governance for knowledge discussion;
●●
governance for documentation of knowledge;
●●
governance for knowledge synthesis;
●●
governance for finding and reviewing knowledge.
Knowledge Management Framework
Please note that some governance elements such as an overall KM policy or
a taxonomy may apply across the different knowledge transactions, and
some roles may fit in more than one box. We suggest using the table as a
check for comprehensiveness.
An example of a completed KM framework is shown in Table 12.2, based
on a KM framework for an energy company. An example KM framework
for a legal firm is shown in Table 12.3.
Table 12.2
An example completed KM framework for an oil company
Discuss
Document
Synthesize
Find/review
People
Community of
practice
leaders and
facilitators
Lesson
capture
facilitators
Knowledge
owners for each
critical
knowledge topic
Knowledge
managers for
projects and
departments
Process
Knowledge
Lessons
exchange, peer capture
assist
meetings,
after action
review
Technology
Discussion
Lessons
Wiki, portal
forum, Yammer database, blogs
Governance Defined set of
CoPs,
community
charters and
business cases
Table 12.3
Expectations
for lessons
capture, quality
standards for
lessons
Distillation and Before action
packaging of
review, KM
knowledge,
plans
creation of best
practice
KM policy,
taxonomy,
metadata,
information
architecture
Search, tags,
RSS
Expectations
for lessons
re-use
An example completed KM framework for a legal firm
Discuss
Document
Synthesize
Find/review
People
Practice area
experts
Practicerelated
communities
Professional
support lawyers
Practice area
experts
Professional
support
lawyers
Process
Online
discussion
Post-matter
reviews
Precedent
collection
Creation and
update of
precedent
library
Pre-matter
research
(continued )
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Assessment and Planning
Table 12.3
Technology
(Continued)
Discuss
Document
Synthesize
Discussion
forum,
Yammer
Post-matter
review database
Intranet portal Search
Expectations and
quality standards
for precedents
filing
Taxonomy,
metadata,
information
architecture
Governance Guidelines for
practice areas
and
communities
Find/review
KM policy
Other organizations may complete the framework with different roles, processes, technology and governance elements. The next four chapters will
help you determine how you populate this table for your own organization.
Tip
Do you already have some elements of KM in place? You can review your
current organization against this template, to see which elements are
already in place and working well, which are in place but require
improvement, and which are completely missing.
When you might need more than one
framework
Different parts of your organization may operate in different ways, and you
may therefore need to introduce more than one KM framework. For example you might work for an organization that creates consumer products,
with one division working in projects to develop new products, one division
concerned with manufacturing the products, and a third concerned with
supporting customers and answering their queries. In a situation like this,
you may develop a KM framework for each distinct context:
●●
a project-based framework for the product development division, using
processes such as KM planning and lesson-learning meetings, and
developing a wiki covering promising technologies and state-of-the-art
ideas;
Knowledge Management Framework
●●
●●
a separate framework for the manufacturing division, based on knowledge
of the manufacturing process, with lessons created from six-sigma
meetings and outage analysis;
a third framework for customer support agents, with a customer-facing
knowledge base containing best-practice articles that answer common
customer queries.
The key, in a case like this, is to use common framework elements wherever possible – a common Yellow Pages system, common search, and a
common community of practice software, for example – only developing
separate elements when these are needed to address different working patterns. In addition, a common taxonomy is needed across all the different
KM frameworks, so that all parts of the organization use the same terms
to describe the same things.
If, however, the different divisions in your organization work in much the
same way, then try from the start to introduce a common KM framework.
This will be challenging if your KM initiatives have started bottom-up in
multiple divisions. In this case you’ll need to devote some effort to harmonize the different KM approaches that each division has introduced.
Summary
The KM framework is the complete management framework for KM. You
will design, test, pilot and roll out this framework during your implementation programme. We recommend a framework template which covers the
four enablers of KM applied to the four ‘knowledge transactions’. A complete KM framework will have something in place for each cell in the framework template, ensuring there are no links missing in your KM supply chain.
In the next few chapters we will cover the columns of the framework template one by one and suggest some options for you to populate the cells for
your own organization.
Reference
ISO (2018) Knowledge management systems – requirements – ISO 30401:2018,
ISO, Geneva
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The knowledge 13
discussion
elements of the
KM framework
Steven Denning, one-time head of KM at the World Bank, said at the Ontario
KM summit in 2006 that ‘the learning capacity of an organization is directly
related to its ability to hold conversations’, and we truly believe he was right.
Many management disciplines are based on conversation. Safety management
is driven by conversations about safety, in order to drive awareness of safety
issues and identify mitigating actions. Risk management is driven by conversations about risk, in order to drive awareness of risks to projects and to identify
mitigating actions. KM is similarly driven by conversations about knowledge.
We discussed in Chapter 1 how conversations and content are the dual
paths by which knowledge is transmitted, and we said that discussion should
form one of the main components of your KM framework. In this chapter
we describe some potential framework elements for knowledge transfer
through conversation:
●●
dialogue as the preferred form of discussion;
●●
roles for knowledge discussion;
●●
processes for knowledge discussion;
●●
technologies for knowledge discussion;
●●
governance for knowledge discussion.
Dialogue as the preferred form of discussion
Conversation is widely recognized as the most effective KM tool there is.
Knowledge and experience can be shared through conversation, but not
Knowledge Discussion Elements
through every type of conversation. Conversations have many functions,
and knowledge sharing is only one of them. Conversations can take the
form of:
●●
●●
●●
●●
●●
small talk and social chatter, where the process of communicating is
more important than the content;
social cohesion, the purpose of which is to align people through agreement,
for example sharing impressions of a football match or a TV episode you
have both watched;
reporting and debriefing, which are ‘broadcasts’ where people state facts
and opinions for an audience (many project meetings are like this);
argument and debate are the ‘win/lose’ conversations where someone has
an opinion and defends it against alternative opinions;
dialogue is conversation with the aim of exploring different perspectives
and reaching mutual understanding (though not necessarily agreement).
Dialogue is the kind of conversation we need to promote in order to facilitate knowledge sharing in organizations. The goal of dialogue is not winning nor convincing, but reaching a deeper level of collective understanding.
Dialogue involves asking questions, seeking clarification, testing understanding, and looking for that ‘aha’ moment when the knowledge is really
transferred. It helps us access and build deep tacit knowledge, it allows us to
check whether we have really understood the knowledge, and it allows us to
co-create knowledge through the experiences of many people. Dialogue requires listening skills as well as debating skills, as people allow their opinions to be challenged and, indeed, welcome that challenge. It requires trust
and openness, but it generates trust and openness as well.
Dialogue is a very difficult conversational style to achieve, requiring good
facilitation. Without this it can easily degenerate into debate and argument,
and the opportunity for effective knowledge sharing is lost. The roles and
processes we describe below are designed to foster knowledge transfer
through facilitated dialogue.
Roles for knowledge discussion
Here we describe two sorts of role: roles related to conversation within communities and networks, and roles for facilitating conversation between individuals and teams.
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Assessment and Planning
Communities and networks
In KM a major purpose of communities and networks is to provide shared
access to the tacit knowledge which people hold in their heads. Once the
person is connected into a network that transcends the organizational
boundaries, their tacit knowledge becomes ‘linked into a system’ and becomes more accessible to others. Much as a piece of explicit knowledge
joins the organization’s knowledge base when made accessible and searchable, so a piece of tacit knowledge joins the organization’s knowledge base
when the knowledge holder is connected, made accessible and findable
through a network or a community of practice.
For any organization working from multiple offices or in many countries,
communities and networks will be an element of your KM framework (see
the Mars case history in Chapter 30, for example). When KM is fully embedded, you would expect to see a community or network associated with
every business-critical knowledge topic. Successful communities span organizational boundaries, and are large enough to contain a wealth and diversity of knowledge. Figure 13.1 shows how the effectiveness of communities increases with community size (as rated by community members).
Figure 13.1
The average effectiveness rating for communities of practice as
community size grows
Community effectiveness vs community size
(internal communities only)
5
Average rating for community effectiveness
136
4.5
4.5
4
3.5
3
3.2
3.2
50
100
3.9
3.9
500
1,000
2.8
2.5
2
1.5
1
10
Community size
SOURCE Knoco global KM survey 2014–2017 (Knoco, 2017)
5,000
Knowledge Discussion Elements
Roles within a community or network
There are a few distinct roles to be played in a community, the key role being
the community leader – the person who is accountable for ensuring the community functions as a knowledge-sharing and learning vehicle. This leader is
involved in the start-up and growth of the community, and in developing
and maintaining the community processes. The choice of a good leader is
crucial to the effective operation of the community. The leader often reports
to a community sponsor.
In some cases, the leader appoints a facilitator, while in other cases, the
leader also takes the facilitator role. The facilitator should be a recognized
networker within the community. Their role is to facilitate the linkages and
relationships between the members, to facilitate online community discussion, and potentially steward any community output – for example through
documentation. A good facilitator leads from within, energizes the community, and builds trust and ownership among the community members. The
main tasks of the facilitator include:
●●
building membership and welcoming new members;
●●
maintaining activity and energy through a rhythm of events;
●●
setting the behavioural style of the community;
●●
managing discussions and inviting participation;
●●
managing relationships;
●●
brokering connections between members.
There are often no formal roles in a community of practice apart from the
leader and/or facilitator, and there is no single structure that will suit all
communities of practice. Communities thrive on the energy and participation of their members, and so build their own identities and characters,
much as individuals do. You will undoubtedly see many levels and forms of
participation within the community, including:
●●
●●
●●
core team members, who work with the leader and facilitator to nurture
and grow the community;
subject matter experts, who manage areas of community knowledge (this
role is described in more detail in Chapter 15);
active community members, engaged in asking questions and sharing
knowledge;
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Assessment and Planning
●●
●●
community sub-groups, which can be set up to work on allocated tasks
or specific topics;
lurkers – community members who at the moment are just observing and
learning.
Discussion facilitation roles
Good facilitation is essential to effective face-to-face KM processes. Effectively
identifying and exchanging knowledge in a meeting requires high-quality interactions between people through the medium of dialogue as discussed earlier. The role of the facilitator is to:
●●
●●
●●
●●
maintain high-quality dialogue in service of delivering the desired outcomes
of the meeting;
ensure balanced input from many people;
explore the learning significance of disagreements without descending
into argument;
allow good discussion while still finishing the meeting on time.
Facilitation is a form of assistance and guidance that makes it easier for a
group to effectively deliver the objectives of KM processes such as retrospect, peer assist, or knowledge café. The facilitator manages the process of
the meeting (including the quality of the dialogue) while the group itself
looks after the content.
Most organizations that value knowledge sharing also value facilitation,
simply because good facilitation produces high-quality sharing.
CA S E S TU DY
The leader of one KM programme we were involved with trained his entire KM
team in facilitation skills and found that this not only enabled them to facilitate
KM processes, it also gained them access to many non-KM meetings, where
they were able to introduce KM processes into the agenda. Part of your KM
implementation may well include the deliberate development of facilitation skills
in the organization, as in the Public Works Department Malaysia case study in
Chapter 36. In some cases the KM team can provide these services, or you can
use KM champions as facilitators (Chapter 21).
Knowledge Discussion Elements
Processes for knowledge discussion
For knowledge to be effectively transferred through dialogue, the conversations need structure and process as well as facilitation. These conversations
can occur online, or face-to-face.
Online Q&A
The most powerful mechanism for online knowledge sharing within a community or network is through question and answer. Q&A-based discussion
allows members of a dispersed, sometimes multinational, community to
help, teach or advise each other. A community member can raise a question
on a specific topic, and anyone in the community with knowledge or advice
to share can answer. Some Q&A forums send the questions only to a group
of experts, such as the ‘Ask Anglo’ system in Anglo American, the mining
giant (Roberts, 2006). Others send them to the whole community.
A Q&A forum can be a lifeline for individuals who are geographically or
organizationally isolated (in a remote branch office, for example), as it allows them to tap into the knowledge of their peers elsewhere in the organization. Part of the role of the community facilitator (discussed earlier) is to
support asking and answering within the community forum, through encouraging questions, prompting for answers, requesting clarifications, and
summarizing discussion threads.
Question-based knowledge ‘pull’ seems to be a much more effective
mechanism for transferring knowledge within communities than ‘just in
case’ publication ‘push’ of knowledge articles. Knowledge pull is a question
looking for an answer, or a problem looking for a solution, and so there is
greater certainty that the shared knowledge will be applied. Grant (2013)
says that ‘direct requests for help between colleagues drive 75 to 90 per cent
of all the help exchanged within organizations’. For the word ‘help’ we can
substitute the word ‘knowledge’.
C A S E S TU DY
Ash (2007) shares a story from an employee of the engineering and construction
multinational Fluor, which describes how an online forum was used to gain valuable
technical knowledge. A question was posed about the design for a piece of refinery
equipment called an electrostatic coalescer, which contained a salt-bed drier:
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Assessment and Planning
Within three days, three responses were received, from Haarlem
[Netherlands] and the Calgary [Canada] offices. They provided project
references and contacts for each of the different design options
considered. The information underlined the strong effect of operating
temperature on salt-bed efficiency: at too high an operating temperature
the efficiency of the salt bed is eliminated by the brine solubility in diesel…
Based on this information and project references, our recommendations to
the client were to pre-cool the diesel feed to 60°F with a chiller before
being sent to the coalescer and to eliminate the salt-bed drier…The
elimination of the salt-bed drier saved the client money on equipment cost
(reduced by €1m) and operational cost. Our client is so pleased that a new
work order has been awarded to Fluor: a similar study for the other refinery
of the client. This study represents a business value of €700,000.
Face-to-face discussion
Periodic face-to-face meetings for knowledge transfer, despite the associated
time and travel cost, are highly effective if well structured and well facilitated, because they allow discussion of knowledge and experience in a hightrust environment. All face-to-face knowledge transfer meeting processes
are based on dialogue, and the specific process you select depends on how
many teams have the knowledge, and how many teams need the knowledge.
For knowledge transfer from one team to one other team, an appropriate
choice may be the Baton-Passing process (Keyes, 2012, p. 256). This process, invented at Pfizer by Victor Newman when he was their Chief Learning
Officer, involves the transfer of knowledge and lessons from one team to
another team that is either tackling similar work or continuing the first
team’s work. The process involves the following steps:
●●
●●
●●
The first (knowledge-holding) team maps out the process of the work
they have just completed, as a timeline or a mind map on a large sheet of
paper.
They identify learning points within the map (often using Post-it notes)
where they have gained useful new knowledge.
The second team use different-colour Post-it notes to identify areas where
they want to learn from the first team.
Knowledge Discussion Elements
●●
●●
The two teams explore these learning points through dialogue.
The second team then creates an action list to decide what they will do
with the knowledge they have gained.
For knowledge transfer from one team to many other teams, an appropriate
choice is the Knowledge Handover process (Milton, 2010, p. 126), often
held when one team has completed a project and wishes to transfer its lessons to others. The process involves the following steps:
●●
●●
●●
●●
●●
Prior to the meeting, the project team discusses, identifies and documents
the lessons and new knowledge they have gained from the project.
They publish these lessons to people they think might benefit, and invite
them to co-create an agenda for the knowledge handover, which will
focus on those topics of most interest to others.
At the meeting, these topics are discussed one by one, and a brief
presentation from the project team is followed by a much longer period
of questions from the visitors.
Where several topics are discussed in parallel sessions, these are followed
by a full-group session to summarize the main learning points from the
parallel sessions.
At the end of the meeting the visitors summarize the main things they
have learned through the session, and the actions they will take on
returning to their own projects.
For knowledge transfer from many teams to one team, an appropriate choice
is the Peer Assist process (Milton, 2005, p. 49). A peer assist is often held when
one team (the host team) is planning a project and wishes to learn from the
experience of visitors. This process involves the following steps:
●●
●●
●●
●●
●●
The facilitator sets the ground rules of the Peer Assist – openness and
generous listening from the host team, positive advice and feedback from
the visitors.
The host team explain their context, and list the issues they believe they
need to learn about, including options they have already considered.
The visitors outline their past experience and add other issues that they
believe the host team also need to learn about.
Each issue is discussed through dialogue in small teams.
The visitors then summarize their advice to the host team, and the host
team summarize the actions they will take as a result of the new knowledge
they have gained.
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Assessment and Planning
For knowledge transfer between many teams, or involving many diverse
members of a community of practice, an appropriate choice is the Knowledge
Exchange process (Young and Milton, 2011, p. 40). A knowledge exchange
is often held as a way for people to compare different approaches to a task
and decide on a best practice. This process involves the following steps:
●●
●●
●●
●●
The group divides the topic in question into its main components (tasks
within a process, components within a design, etc).
Dialogue sessions are held around each component, participants share
their experiences and the approaches they use, and they attempt to
combine their knowledge to develop a ‘current best’ solution based on
existing knowledge, as well as identifying current knowledge gaps.
Where the components are discussed in parallel sessions, the recommended
best practice is validated with the rest of the attendees.
A documented knowledge asset is produced based on the discussions at
the knowledge exchange.
Technologies for knowledge discussion
Software to support discussion of knowledge can include discussion forums
to allow online Q&As, people-finder software to find the relevant people to
discuss with, and some forms of discussion-focused enterprise social media.
Discussion forums and Q&A forums provide locations where users can
post messages for others to read, answer and comment on. Often the discussion is hosted on a website, and users can interact directly on the site or via
email. Good facilitation helps the longer-lasting discussions to stay focused
and avoid ‘topic drift’.
A people-finder system is an index of ‘who knows what’ – a knowledge directory for the organization. It is an easy way to locate anyone working in the
business, based on their knowledge and expertise. The system will be based
around a knowledge taxonomy, to allow people to categorize their knowledge
and experience, and so be searchable and findable. The people-finder system
does not create the knowledge flows that come from mutual familiarity and
trust, but it does help locate knowledgeable people. Your discussion processes
are then necessary to build the familiarity and trust needed for knowledge flow.
A range of enterprise social media exists for use in organizations. The
ones that most strongly support conversation threads, dialogue and people
finding will be those that are most valuable for KM. Others, such as the
Knowledge Discussion Elements
enterprise equivalents to Twitter, can be useful for promoting awareness of
people’s ideas and activities, so long as you have other tools and processes
to help them develop the conversations.
Tip
Avoid the temptation to have multiple competing conversation channels
or technologies in the organization. There should be one technology to
support discussion, so people know which technology to use to when
asking a question, knowing that this will allow them to access all the
relevant tacit knowledge. Multiple channels that fulfil the same purpose
introduce confusion and duplication, scatter conversations, reduce
the energy and activity that flows in any single channel, and increase the
chance that critical knowledge will get lost somewhere between the
supplier and the user.
Governance for knowledge discussion
Some of the governance elements to support knowledge discussion might
be:
●●
a defined list of required communities and networks;
●●
a business case and a charter for each community or network;
●●
an expectation that every employee should have a profile in the company
people finder;
●●
training for all community leaders and facilitators;
●●
training for facilitators;
●●
●●
●●
requirements that projects conduct certain processes, such as peer assist
or baton passing;
reference materials and guidelines for all discussion processes and
technologies;
success stories from community and network knowledge transfer.
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Assessment and Planning
Summary
Exchange of knowledge through conversation, specifically through dialogue, will be a vital component of your KM framework. This is likely to
include communities of practice, with their own specific supporting roles,
technologies and governance, and a suite of processes for face-to-face
knowledge transfer supported by trained facilitators. You will need to test
these KM framework elements in your own context, and select the discussion components that will work in your organization and that can be embedded into your own procedures and systems.
References
Ash, J (2007) Case report, Connecting People, Inside Knowledge, 10 (9), pp. 20–23
Grant, A (2013) Givers take all: the hidden dimension of corporate culture,
McKinsey Quarterly, April [online] https://www.mckinsey.com/businessfunctions/organization/our-insights/givers-take-all-the-hidden-dimension-ofcorporate-culture (archived at https://perma.cc/GAU9-T9DD) [accessed 29
January 2019]
Keyes, J (2012) Enterprise 2.0: Social networking tools to transform your
organization, CRC Press, Boca Raton, Florida
Knoco (2017) Knowledge Management Survey [online] https://www.knoco.com/
knowledge-management-survey.htm (archived at https://perma.cc/VCY7-LHL7)
[accessed 26 January 2019]
Milton, N J (2005) Knowledge Management for Teams and Projects, Chandos
Publishing, Oxford
Milton, N J (2010) The Lessons Learned Handbook: A practical knowledge-based
approach to learning from experience, Chandos Publishing, Oxford
Roberts, R (2006) Anglo American: advancing through technology, Optima,
November [online] https://www.angloamerican.com/~/media/Files/A/AngloAmerican-Plc-v2/media/publication/optima-docs/optima-volume-52-2.pdf
(archived at https://perma.cc/MF6X-6MJA) [accessed 28 January 2019].
Young, T and Milton, N J (2011) Knowledge Management for Sales and
Marketing, Chandos Publishing, Oxford
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The knowledge 14
capture and
documentation
elements of the
KM framework
In this chapter we focus on the first step in content-based knowledge transfer, namely the documentation of that knowledge. Knowledge capture is a
core component in your KM framework, to ensure that new knowledge is
recorded on an ongoing basis as a part of operational work. We cover:
●●
the difference between documented knowledge and information;
●●
roles for knowledge documentation;
●●
processes for knowledge documentation;
●●
technologies for knowledge documentation;
●●
governance for knowledge documentation.
The difference between documented
knowledge and information
Documenting knowledge is not the same as filing information. In Chapter 1
we discussed the knowledge supply chain, the purpose of which is to provide the knowledge workers with the knowledge they need to make decisions and take actions. Therefore we need to document as knowledge those
things which others can learn from and act upon, such as insights, lessons,
advice and experience. This is the knowledge that needs to be documented,
and it is distinct from normal work-related information products such as
reports, budgets, maps and diagrams.
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Assessment and Planning
You may also need to collect some of the work products to accompany
the documented knowledge in order to illustrate and give context to the
documented knowledge. We can therefore think of four types of output
from work activity, of which three are handled as part of KM:
●●
●●
●●
●●
undocumented knowledge, still in people’s heads, transferred through
conversation (Chapter 13);
documented knowledge: insights, lessons, advice and experience from
which others can learn, transferred as content (this chapter);
high-value information which gives context to, and provides examples
for, the documented knowledge, also transferred as content (this chapter);
all other kinds of information, which will be handled by an information
management framework rather than the KM framework. Your knowledge
organization activities (Chapter 17) cover both information and knowledge,
in order to connect your documented knowledge with related information.
It is the creation of documented knowledge and the capture of high-value
information that we address in this chapter.
Roles for knowledge documentation
There needs to be defined accountability for knowledge documentation
within the line organization, so that individuals in the projects and departments know whether they are accountable for ensuring that lessons and new
knowledge are documented. Sometimes it is seen as everyone’s job to capture knowledge, but even then some accountable roles are needed to make
sure that everyone is actually doing his or her job. Usually the project manager or department manager is accountable for making sure this happens in
their specific project or department, and they frequently call on the support
of specialist KM roles to help them.
Four such supporting roles are described below: knowledge engineers,
­lesson-learned facilitators, learning historians and knowledge base publishers.
The knowledge engineer (Milton, 2007) is the key knowledge documentation role in any KM approach that focuses on analysing complex decision
making applied by experts, and turning this analysis into rules and guidance
that less experienced people can use, or incorporating it into expert systems.
The knowledge engineer might work with a retiring expert as part of a
knowledge retention programme, or may work to set up a knowledge base
for an Artificial Intelligence system.
Knowledge Capture and Documentation Elements
Historically the knowledge engineer was focused on creating expert systems, but frequently the major challenge for this role is in eliciting the
knowledge in the first place, rather than in creating the subsequent system.
The task of the knowledge engineer is as follows:
●●
●●
●●
●●
Assessing the problem for which the knowledge needs to be acquired and
packaged.
Eliciting the knowledge – the most difficult step, and where the skills of
the knowledge engineer are most important. There is a range of techniques
for knowledge elicitation, with interviews being the primary method,
augmented by techniques such as analysed problem solving, card sorting
and the creation of concept maps (Milton, 2007).
The elicited knowledge then needs to be structured into an expert system,
a knowledge base or a knowledge asset. The knowledge engineer creates
the structure and populates it with the elicited knowledge.
The structured knowledge needs to be validated through review by subject
matter experts and by validating the knowledge against known outcomes.
Tip
If your KM framework is likely to include knowledge engineering, or the
creation of expert systems, then seek training in knowledge elicitation skills
for one or more members of your KM team.
Lesson-learned facilitators play a similar role to knowledge engineers, working in the field of lesson capture and documentation. We discuss lessoncapture meetings such as retrospects later in this chapter. The completeness
and quality of the lessons captured at these meetings depends on the quality
and objectivity of the dialogue at the meeting, and an external skilled facilitator is crucial to delivering good-quality output. The main tasks of the lesson facilitator are as follows:
●●
●●
●●
to facilitate lesson-capture meetings so that observations are discussed
and explored in order to draw out insights and lessons;
to ensure lessons are fully discussed, with balanced insights from all
project team members;
to ensure the lessons are captured and expressed in a clear and usable
way;
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Assessment and Planning
●●
●●
to document the lessons and (if appropriate) enter them into the lessons
management system; and
to monitor agreed follow-ups such as changes to procedures and verify
that they are actually completed.
A third possible role is that of the learning historian. This role is linked to
the concept of a learning history, described by Kleiner and Roth (1997) as a
written narrative of a company’s recent set of critical episodes such as a
corporate change event, a new initiative, a challenge met, or even a traumatic event such as a major reduction in the workforce. The learning historian creates a learning history through the following steps:
●●
interviews and data gathering from participants in a project or activity;
●●
distillation of knowledge, and establishment of key themes and plots;
●●
creation of a learning history in narrative form;
●●
validation of the contents through reflective feedback;
●●
dissemination and publication of the learning history, with guidelines on
application and learning transfer.
Finally, organizations operating customer-facing knowledge bases often
embed the role of knowledge base publisher within the support departments. The publisher is authorized to create and modify content within the
knowledge base, making articles (which may have been authored by others
in their team) visible to partners or customers. The publisher therefore needs
to combine good technical knowledge and writing skills with deep understanding of the knowledge base and its use, and knowledge of the various
target user groups.
Processes for knowledge documentation
Knowledge documentation involves extracting tacit knowledge from people’s heads and recording it in written, diagram or audio-visual form. The
main challenge is that people who are the source of the knowledge do not
always know what they know until they discuss it.
Sometimes organizations set up a system whereby people voluntarily
identify lessons and new knowledge, and add them into a lessons database,
wiki or knowledge base. We believe you capture only a small proportion
of the knowledge this way, because people are often not aware of what
Knowledge Capture and Documentation Elements
they know, or are not aware of other people’s needs and how their knowledge could help.
Another issue is the cognitive bias known as the curse of knowledge,
where once we know something, we find it hard to imagine not knowing it.
Our knowledge has ‘cursed’ us. We have difficulty sharing it with others
because we can’t readily re-create their state of mind (Heath and Heath,
2007). This bias makes it very difficult for experts to effectively capture their
own knowledge unaided in a form that others can use.
A much better alternative is to use dialogue- and questions-based processes, led by a facilitator, to first identify what people know, and then probe
for the detail that makes the knowledge re-usable. The question-based approaches use a similar format, where the questioner (the interviewer, knowledge engineer or facilitator):
●●
●●
●●
identifies learning points;
explores these learning points to find the root causes for success, or the
heuristics used by the expert;
asks a future-tense question to require the person or team to analyse the
learning and create a recommendation. Questions might include:
{{
What would be your advice for someone doing this in future?
{{
What mistakes might a novice make?
{{
If you were doing this again, what would you do differently?
{{
If you could go back in time and give yourself a message, what would
you tell yourself?
There are two main approaches for timetabling these questioning processes: reactive and scheduled. The reactive approach triggers documentation of knowledge as a result of a notable operational success, near miss
or failure (for example a safety incident, loss of a major client or significant project overruns). Many companies have mandatory processes for
reviewing these failures. The successes are often less obvious, though one
company we have worked with uses global consultants and technical directors to identify, on their global travels, good practice that needs to be
documented. The approach of Appreciative Inquiry (Barrett and Fry,
2012) is often employed when analysing notable successes, and represents
a question-based alternative to problem-focused analysis. Appreciative
Inquiry looks to analyse the best approaches in order to define an even
better future.
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Assessment and Planning
The scheduled approach, common within project-based organizations
and customer support teams, is to schedule knowledge-capture and documentation processes within routine business processes or project activities.
Some of the more common capture processes are discussed below.
Tip
To build a culture of knowledge capture we recommend the scheduled
approach. Once you have tested and piloted knowledge documentation
processes, try to get them scheduled into the project cycle or operational
cycle as distinct tasks within the normal process flow.
Interviews
An interview is the most effective way to capture and document knowledge
from an individual. Interviewing is a form of dialogue – a question and answer process which continues until the interviewer feels they have reached
core knowledge, expressed as future recommendations. The interview may be
taking place as part of a knowledge retention programme, because an expert
holds knowledge which needs to be incorporated into an expert system, or
because they have been through a valuable learning experience which needs
to be analysed and documented. The stages of the interview are as follows:
●●
●●
Identify the main learning points to be discussed. Before the interview,
talk with the individual, his or her manager, team-mates and community
of practice (whichever are appropriate) to identify what topics the
interview needs to cover.
At the interview, explore each topic one by one. Ask about success factors
and challenges, and explore the root causes behind each one. For example,
you might say, ‘One of the success factors you mentioned was teamwork.
Can you tell me how this good teamwork was achieved?’ Explore
counterfactuals – other ways that the situation might have unfolded –
because this can pick up heuristics the expert themselves may be unaware
of, and also help to distinguish the expert’s approach from that of less
experienced people. Finally you need to ask a question designed to
capture advice and recommendations for the future, for example, ‘If you
were advising someone starting a similar project, what would you advise
them to do to ensure good teamwork?’
Knowledge Capture and Documentation Elements
●●
●●
●●
●●
As the interview progresses, you might find that new avenues of questioning
develop. The interview can become a cycle of asking questions, exploring
the answers, summarizing and feeding back, and developing new questions.
It is often useful to chart out the progress of the interview in something
like a mind map, to stay on track.
Don’t be satisfied with vague answers; press for specifics. You are looking,
all the time, for recommendations for the next knowledge worker doing
similar work. Also listen out for mention of important documents,
diagrams and other material which might be useful to collect. Once you
have gathered as much knowledge as you can from each topic, summarize
and move on to the next.
End the interview by asking the interviewee to summarize the main
lessons. For example, ‘As a summary of what we have been discussing, if
you were speaking to somebody who was just about to start on a similar
project tomorrow, what would your key points of advice be?’
For a further range of techniques to access deep knowledge from experts,
see Milton (2007) and Crandall, Klein and Hoffman (2006).
After-action review
The after-action review (AAR) is a regular team-based questioning process
to get at the ground truth behind the results of an exercise or activity
(Milton, 2005, p. 59). It is a process both for discussion (and could have
been included in the previous chapter) and for knowledge capture. AARs are
usually conducted immediately after brief actions where there is learning
potential, eg a maintenance team ending a shift at an oil refinery, a fire crew
after dealing with a fire, or a nursing team at a shift handover.
In an AAR the team’s expectation of an event is compared with what
actually happened, and the facilitator leads a questioning process to find the
reasons for the difference between the two. Where there is a difference between expectations and reality, there is potential for learning. The process
involves dialogue around five questions:
1 What was supposed to happen (during the activity we are reviewing)?
2 What actually happened?
3 Why was there a difference between 1 and 2 (either a positive or a negative
difference)?
4 What have we learned?
5 What do we need to do to sustain (keep doing) this, or what changes do
we need to make to embed this lesson?
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Assessment and Planning
The quality of the questioning determines the value of the knowledge derived from an AAR. Superficial questioning gives shallow knowledge that
has limited use. Deeper questioning, maybe using the technique of ‘the five
whys’ (Bicheno, 2008, p. 152), gets at the deeper knowledge, where the real
value lies. Where AARs are run by team leaders, you will need to provide
training in the skills of AAR questioning, and in particular training on how
to probe with sensitivity and without blame, especially where things did not
go as well as expected.
Creation of A3 reports
An A3 report is a process developed by Toyota for reviewing and documenting learning about product failures and product design improvements
(Kennedy, Harmon and Minnock, 2008). It looks at one specific problem
identified by direct observation or experience, and offers a structure for
analysis and resolution, documented on one side of A3 paper. There are up
to seven sections in the A3 report, each often recorded graphically with
charts, diagrams and photographs.
The steps for creating an A3 report are as follows:
1 Identify the problem with the current design – what’s the background?
2 Conduct and document research to understand the current situation.
3 Conduct and document root cause analysis (eg through the five whys).
4 Develop a target state.
5 Determine actions or countermeasures to address root causes.
6 Create an implementation plan with accountable actions and costs, to get
from the current state to the target state.
7 Develop a follow-up plan, including preparation of a follow-up report.
A3s are a reactive process, documenting the knowledge from a solved problem, ideally completed by a focus group of two or three people. They can be
stored in hard copy in a ring binder, or online in a lessons management
system.
Retrospects
The retrospect is an externally facilitated team meeting, held after the end of
a project or project milestone, where the team identifies and analyses ­learning
Knowledge Capture and Documentation Elements
points through discussion and dialogue, in order to identify and document
lessons and actions for the future (Milton, 2005, p. 68). Retrospects are used
by project-based organizations from every industry, and the use of retrospects is mentioned in the Huawei case study in Chapter 34. Mega-projects
may hold many retrospects in a single project; one company we worked
with held a series of 30 retrospects to cover different aspects of a multi-­
billion-dollar project.
At the retrospect, the facilitator leads an inclusive discussion to identify
what went well and what did not go to plan in the project, why the successful elements succeeded, why the failures and mistakes happened, and how
future projects can repeat the success and avoid the failure. The key questions in a retrospect are therefore what, why and how; very open questions
which allow full exploration of the lessons learned. Note that there is no
‘who’ question. Like the AAR, the retrospect is a no-blame process.
The process of a retrospect is as follows;
●●
●●
●●
The learning points for discussion are identified – either beforehand by
canvassing views of the project team, or at the meeting. These should
include success factors for the project as well as problem areas or areas
for change.
The learning points are prioritized, with priority given to those that had
a big impact on the project, and are transferable to other projects.
Each prioritized learning point is discussed as if it were a single AAR, as
described above.
Tip
A retrospect of a high-profile project forms an excellent proof-of-concept
exercise for KM, since it will certainly surface re-usable knowledge that
can produce value elsewhere in the business. Look for successful projects
where learning has been gained, and offer to facilitate a retrospect.
Technology for knowledge documentation
In this section we cover two types of technology – recording technology and
knowledge storage technology.
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Assessment and Planning
Recording technology
Traditionally, meeting facilitators stand up at the front of the room and write
bullet points on a flip chart. However, when a good dialogue gets going, there
is no way that you can write bullet points quickly enough, and in enough
detail, to capture the subtleties and the context of the knowledge that is being
discussed. You therefore need to record the meeting or interview. Acquire a
digital voice recorder, and either transcribe the recording yourself (time consuming, but accurate) or use a transcription service (more economical, but
they may not understand the technical context or terminology). Although it
is rapidly improving, voice-recognition software is not yet sufficiently advanced to reliably auto-transcribe a group discussion on technical topics. Nor
will it know how to highlight the most salient comments from a discussion.
Video recording is also a good way to capture knowledge – not by recording a whole retrospect or interview (boring and dull to re-watch) but
by recording short summaries immediately after the interview or retrospect is over. The human voice and face give context, humanity, and credibility to the knowledge, and allow the creation of multimedia knowledge
resources.
Tip
Buy some good-quality digital audio recorders and video recorders for your
KM team. Link the audio and video snippets to the fuller documentation and
learning outcomes, so that the audio and video clips function as shop
windows to the content. Consider podcasts and video broadcasts. Do not
worry too much about capturing cinema-quality video. The power of
amateur self-recorded video is clear through the popularity of YouTube,
wikiHow and online video bloggers.
Storage technology for newly documented knowledge
It is often possible to place new knowledge directly into your long-term
knowledge store by editing a wiki page or posting an article in a knowledge
base. Such long-term knowledge stores are covered in the next chapter.
However, there are some cases where new knowledge is stored temporarily,
on its way to the long-term store, perhaps as provisional knowledge needing
later validation, or as ideas, lessons and observations. Some options for this
storage of provisional knowledge are as follows:
Knowledge Capture and Documentation Elements
Lessons management systems
If lessons are being learned from many projects, then these lessons need to be
captured and stored somewhere where they can be compared, searched, and
transferred from one project to another. They need to be captured in a consistent format (for example through form-based entry), and stored with a
consistent set of metadata to allow easy retrieval in a single system to which
all the projects will have access. This should involve an active workflow system where lessons are pro-actively routed to those who need to see them, and
actions associated with lessons are sent to those who need to take action.
Usually the actions involve embedding the lessons into process and guidance,
and lessons are archived once they have been embedded to ensure the system
is not overloaded with old lessons. A lessons management system also generates a set of metrics that support oversight of the lesson-learning process.
Blogs
While it is possible to use discussion forums to share learning reflections
from operations, blogs are a far better mechanism for sharing new
knowledge with a community or network. A blog allows such knowledge
to be tagged, people can discuss the knowledge through the comments
system, and if you set up a series of topic-specific blogs then individuals
can subscribe to topics that interest them, allowing them to be instantly
notified of new relevant knowledge. The community then has two tools,
with the blog being a push tool for very current documented knowledge,
and the discussion forum (Chapter 13) being a pull tool for undocumented knowledge.
Governance for knowledge documentation
Here are some of the possible governance elements to support knowledge
documentation:
●●
●●
a knowledge retention strategy focusing on identifying the risk of
knowledge loss from the departure of key individuals, and actions taken
to document or transfer their knowledge;
defined expectations (and compliance measures) for the process and
frequency of lesson capture within projects and work activities, the use of
A3 reports during product development, or the creation of knowledge
articles as part of normal work;
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Assessment and Planning
●●
●●
a clear definition of the knowledge collateral needed from projects;
style guides and quality expectations for lessons, A3s and knowledge
articles;
●●
training for interviewers, lessons facilitators and knowledge engineers;
●●
reference materials for all processes and technologies;
●●
collection of success stories from the use of lesson learning and A3s.
Summary
Documentation of new knowledge is another vital component of your KM
framework. It will require its own roles and accountabilities, processes, supporting technologies and governance. You will need to test these in your
own context, and select the documentation components that will work in
your organization, and that can be embedded into your own procedures and
systems.
References
Barrett, F J and Fry, R E (2012) Appreciative Inquiry: A positive approach to
building cooperative capacity, Taos Institute, Chagrin Falls, OH
Bicheno, J (2008) The Lean Toolbox: The essential guide to lean transformation,
Picsie Books, Buckingham, UK
Crandall, B, Klein, G and Hoffman, R R (2006) Working Minds: A practitioner’s
guide to cognitive task analysis, MIT Press, Cambridge, MA
Heath, C and Heath, D (2007) Made to Stick: Why some ideas survive and others
die, Random House, New York
Kennedy, M, Harmon, K and Minnock, E (2008) Ready, Set, Dominate: Implement
Toyota’s set-based learning for developing products and nobody can catch you,
The Oaklea Press, Richmond, VA
Kleiner, A and Roth, G (1997) How to make experience your company’s best
teacher, Harvard Business Review, 75 (5) pp. 172–77
Milton, N J (2005) Knowledge Management for Teams and Projects, Chandos
Publishing, Oxford
Milton, N R (2007) Knowledge Acquisition in Practice: A step by step guide,
Springer-Verlag, London
157
The knowledge 15
synthesis
elements of the
KM framework
Any organization that is successful at documenting knowledge has to address the issue of knowledge synthesis. Effective knowledge documentation
will create a rapidly increasing amount of lessons, good practices, blog
posts, wiki pages and knowledge articles, and this volume of material means
that the same knowledge may be documented many times, knowledge from
different places and different times may contradict each other, it may be very
difficult to find the knowledge you need among the many tens of thousands
of documents, and each individual knowledge worker is required – often in
a hurry – to figure out their own answer from this mass of evidence.
Knowledge synthesis is required to constantly process this mass of material
into integrated, organized and useful guidance.
In this chapter we cover:
●●
what knowledge synthesis is;
●●
what synthesized knowledge ‘looks like’;
●●
roles for knowledge synthesis;
●●
processes for knowledge synthesis;
●●
technologies for knowledge synthesis;
●●
governance for knowledge synthesis.
What is knowledge synthesis?
Knowledge synthesis is the summary, collation and integration of multiple
sources of documented knowledge into a single set of guidance material,
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Assessment and Planning
which knowledge workers can use to help guide their business decisions and
business activity. Any organization that is focused on best practices will employ a step of knowledge synthesis within their KM Framework. For ­example:
●●
●●
●●
●●
Shell collate their best practices (‘practices worth replicating’), their
lessons learned, and the results of community discussions into synthesized
guidance within the Shell wiki. ConocoPhillips take the same approach
with their community wiki sites.
Most militaries collate all lessons and observations from the field into
guidance documents on all military processes. These are called ‘doctrine
manuals’, which represent synthesized knowledge on these processes.
General Motors synthesizes its technical knowledge into a set of ‘Approved
Best Practices’.
Many service organizations create knowledge bases for their customerfacing staff, customer-facing chatbot or directly for their customers,
containing an article to answer every customer query. This article is based
on the best current response, and is updated as circumstances change.
The issue of synthesis is often neglected by organizations. It is more common
to see ever-growing collections of individual documents that staff have to
make sense of than it is to see collated and synthesized best practice. However,
this puts the burden on each user to sort and sift through the collection to find
something that is current, valid and relevant. Synthesis, although requiring an
investment of time from the expert(s), saves time overall by giving the users
easy access to the best and most reliable knowledge from multiple sources.
What does synthesized knowledge
look like?
Synthesized knowledge is a single set of structured material, validated by a
process owner, practice owner or community, collated from many sources,
structured in the most useful way for the knowledge user, and containing
guidance telling the knowledge worker how to perform or approach a task,
design or sell a product, or how to interact with a customer.
Synthesized knowledge may contain some or all of the following:
●●
process guidelines;
●●
techniques and methods;
Knowledge Synthesis Elements
●●
product design guidelines and principles;
●●
checklists;
●●
FAQs and answers to questions;
●●
templates;
●●
exemplars;
●●
tips and hints.
It is unlikely to include such items as project documents, case histories or
individual lessons, unless these are used as illustrative examples.
Synthesized knowledge can also be categorized by the validity or the
‘weight’ that it carries, as described below.
There is the ‘must follow’ knowledge: the company standards that have
been signed off by the knowledge owners and/or management (with the
endorsement of any relevant community of practice) as being the only safe
or effective approach. Examples might be the operating procedures for a
nuclear plant, or the in-flight checklists for a Boeing 777.
There is the ‘should follow’ knowledge: the ‘current best practice’ which
the community and the knowledge owner collectively agree is the best way
to do something in a certain circumstance or context, and which should
therefore be used as a default unless you have a good reason to do otherwise. This knowledge can often be found in the community wiki or knowledge base, and there will be generally some form of validation procedure to
determine that this really is the best knowledge available at the moment.
Finally there is the ‘could follow’ knowledge: the good ideas, tips and
hints, good examples, and templates drawn from the community forums
and the best of the ‘knowledge collateral’ we discussed in the previous chapter. It is useful material, but its use is optional.
Tip
Creating synthesized knowledge for a critical knowledge topic is often a
good candidate for a pilot or a proof-of-concept exercise. Choose a single
user group where you know there are scattered knowledge resources that
would benefit from synthesis. Use this pilot to experiment with the best way
to store and structure the knowledge so that it can be easily and effectively
used by its target users.
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Roles for knowledge synthesis
The primary role for knowledge synthesis is that of the ‘knowledge owner’:
the person accountable for managing the contents of the knowledge base for
a particular area of knowledge, and for ensuring the knowledge is s­ ynthesized,
findable, up to date and useful. Alternative names for this role are process
owner, practice owner, knowledge domain expert or subject matter expert
(SME). This person acts as the steward for a particular area of knowledge,
taking accountability for the quality, completeness and currency of the synthesized knowledge.
Some of the specific responsibilities of the knowledge owner are as
­follows:
●●
●●
●●
●●
●●
●●
monitoring the development of knowledge within their specific topic;
ensuring that a set of synthesized knowledge relating to their specific
topic is available, either by writing it themselves or by delegating the
writing activity to others;
ensuring the guidance documentation is findable (see Chapter 16);
updating the synthesized knowledge and standards as new knowledge
and new lessons become available;
monitoring the use of the synthesized knowledge, and acting on feedback
to improve it;
liaising with the leader or coordinator of any community of practice that
covers the topic; sometimes the knowledge owner and the community
leader are the same person, sometimes the community leader reports to
the knowledge owner.
Often synthesized knowledge represents best practice – the ‘should do’
knowledge – and this can be strengthened and supported by a collection of
example documents and content – the ‘could do’ knowledge. The knowledge
owner or owners may need the support of a knowledge base administration
team or team of online librarians to manage and curate these collections of
content, or, in the case of support centre knowledge bases, the collections of
articles designed to answer customer queries. Their role is to:
●●
determine who the customers of the knowledge base are;
●●
carry out market research into customer needs;
●●
work with the knowledge owners to develop and maintain a structure for
the knowledge base;
Knowledge Synthesis Elements
●●
provide coaching and guidance on content creation and formatting;
●●
provide technical editing and technical writing support where appropriate;
●●
monitor content standards;
●●
●●
●●
develop and monitor processes for refreshing content and for removing
old material;
provide coaching in the use of online tools, taxonomy and search engine;
coordinate and communicate feedback on desired improvements to the
taxonomy or supporting software.
Tip
It can sometimes be difficult to find people willing to act as knowledge
owners. Managers often prefer to put the most knowledgeable experts on
the most difficult projects (a very old-fashioned approach to managing
knowledge!) and some of the best experts may initially feel that the job is
unappealing, as it sounds too much like ‘writing down everything I know’.
Make the effort to find experts who are keen to be involved, and work with
them in the early stages so they have an influence on the definition of the
role. Give them the support they need (including the help of knowledge
engineers) to create appealing and valuable synthesized knowledge for
which they can gain kudos and recognition.
Processes for knowledge synthesis
Individual creation
A common approach to synthesizing knowledge is to leave this to the individual efforts of the knowledge owners. However, the knowledge owners
will almost certainly need guidance, training, templates, and some help in
combining multiple viewpoints. The General Motors process for knowledge
synthesis related to car components (Wieneke, 2008) included:
●●
●●
identification of the knowledge topics, and assignment of knowledge
owners to best practice teams covering topics such as front suspension,
rear suspension, steering, etc;
coaching the teams in knowledge synthesis;
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●●
●●
capturing knowledge about individual design attributes from indi­
vidual engineers (attributes were things like safety, squeak and rattle,
manufacturability);
facilitated sessions where the individual views were ‘balanced’ (synthe­
sized) into a best practice overview of the component design.
Siemens developed a five-stage process known as KNAC (knowledge asset
creation process) for creating synthesized knowledge about specific topics
and products (Freudenthaler et al, 2003):
●●
●●
●●
prepare – defining the scope, key topics, terminology and structure;
structure – defining and outlining a set of processes, work product and
tools;
consolidate – describing the processes, work product and tools and
adding best practices and recommendations;
●●
illustrate – adding tips, checklists, examples and slides; and
●●
polish – a final view of layout and formalities.
Knowledge exchange
This process was described in Chapter 13 as a knowledge discussion process, the outcome of which is documented knowledge that has been collectively synthesized by a community of practice.
Wikithons
A wikithon is like a virtual online knowledge exchange, but with more synthesis and less discussion. It is a special event in which content owners, community of practice members and others collaborate intensively on creating
and editing wiki content. Wikipedia call this an ‘editathon’. A wikithon may
last from a couple of hours to a day or more. The event may be face to face
or it may be virtual. As a side benefit, the wikithon often introduces many
new people to the concept of the wiki.
There are many examples of the wikithon in the Federal Government sector in the United States, such as the wikithon for creating the Making Mobile
Gov Wiki, held in November 2011 in a coffee shop in Washington (Glick,
2011), or within the US Army to create online doctrine manuals (Dixon,
2009). Cultural organizations also make use of wikis to synthesize and
Knowledge Synthesis Elements
­reserve indigenous knowledge. In December 2018, a non-profit called
p
BASAbali, dedicated to preserving the indigenous languages and knowledge
of Bali, held a virtual wikithon as a competition with prizes to build context
around their online wiki-based dictionary (USINDO, 2018).
Tip
If you are experimenting with using a wiki as a knowledge base, use a wikithon
as a way to kick-start online content for your wiki, once you have a knowledge
owner identified and the basic structure of the topic worked out.
Technologies for knowledge synthesis
Knowledge synthesis requires a technology where knowledge can be structured, stored, collaboratively synthesized, and continuously updated over
time as new knowledge is developed. Some of the main types of technologies
are listed below.
Wikis
A wiki is a website that allows a number of people to create, edit, add and
delete content, and it can be an excellent platform for creating a synthesized
body of knowledge that evolves over time. Wikis have become a mainstream
method for developing and storing synthesized organizational knowledge in
a form that allows continual updates. Shell makes extensive use of a wiki as
a corporate knowledge base to provide access to operational business knowhow as well as general knowledge on the Shell organization, and also to
make available training material from the Shell University. The content of
the wiki was originally created by subject matter experts, but the articles are
open to comment by readers, and are updated if these comments identify
new lessons or other process improvements. In the Public Works Department
Malaysia case study in Chapter 36, Roznita Othman describes how technical knowledge is shared across the organization via the ‘Jpedia’ wiki.
The popular perception of wikis is one of voluntary, informal, bottom-up
creation of content, drawing on the wisdom of crowds. The most visible
example is Wikipedia, which has no formal content-ownership roles (though
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the editorial roles are very strong), voluntary ad hoc submission, and edits
by the readership. However, there are major drawbacks to this model.
Contribution rates are so low that it requires a huge user base (not usually
available in the enterprise), and the voluntary nature of the model results in
a skewed distribution of contributors (predominantly young, unmarried
western males). It can also result in a skewed distribution of content (the
Wikipedia article on ‘knowledge management’, for example, is only a third
of the length of that on the Star Wars movie franchise).
Successful wikis in commercial firms or public-sector organizations instead ensure that each wiki is part of a KM framework, stewarded by a
knowledge owner, with clear processes for updating and ‘feeding’ the wiki,
and clear governance. For example, one training organization we worked
with had a client profile wiki, and a reasonably regular turnover of new
trainers. New trainers joining the organization had a responsibility as part
of their orientation and induction to interview the more experienced trainers about the company’s clients, and to update the wiki with new insights.
The new trainers got a rapid orientation to their colleagues and the clients,
and the wiki was kept current.
Portals
A web portal is a site accessed through a web browser which provides structured access to information and documented knowledge. One problem with
early portals is that they were not designed for comments or for collaboration. They were primarily document libraries. For well-established and mature processes, this is not a problem, as content will be only rarely be added
or updated. However, for process knowledge that is dynamically evolving, it
can be very useful to allow readers to comment on the documentation, or
even to edit it as new lessons are learned and new knowledge becomes available. Newer-generation portals, some of them working on sophisticated
wiki software, have more collaboration capabilities, and can be valuable
tools for communities of practice.
Some of the advantages of portals include:
●●
●●
●●
intelligent integration and access to enterprise content, applications and
processes;
improved communication and collaboration among customers, partners,
and employees;
unified, real-time access to information held in disparate systems;
Knowledge Synthesis Elements
●●
●●
personalized user modification and maintenance of the website
­presentation;
consistent look and feel, headers and footers, colour schemes etc, which
gives the user a sense of consistency, uniformity, and ease of navigation.
Knowledge bases
‘Knowledge bases’ refers to technology that is designed to support:
●●
customer-facing staff in answering customer questions;
●●
customers seeking answers to their own questions;
●●
●●
AI-powered bots that can interact with customers on standard types of
enquiry;
internal users in very structured knowledge domains seeking solutions to
frequently encountered issues.
For example, with powerful search and tagging supported by a defined taxonomy, a customer agent can find existing solutions to customer questions,
removing the need to create a new solution. Tracking solution re-use and
user ratings of the usefulness of the answer allows close monitoring of the
knowledge base quality and value.
Governance for knowledge synthesis
Governance elements to support knowledge synthesis can include:
●●
●●
a listing of critical knowledge topics within the organization, often
structured into a well-maintained corporate taxonomy (Chapter 17);
a clear assignment and delegation of accountability for ownership of
these topics;
●●
a defined expectation for what ‘knowledge ownership’ entails;
●●
training, coaching and support for knowledge owners;
●●
a career path and succession plan for knowledge owners;
●●
●●
defined expectation and compliance measures for the quality and update
frequency of synthesized knowledge;
monitoring the use and application of the knowledge;
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●●
●●
reference material for all processes and technologies;
regular collection of success stories regarding the re-use of synthesized
knowledge.
Summary
Like the other knowledge processes, knowledge synthesis also requires its
own roles and accountabilities, processes, supporting technologies and governance. You will need to test these in your own context, and select the
components that will work in your organization, and that can be embedded
into your own procedures and systems.
References
Dixon, N (2009) If the Army can put its doctrine up on a wiki, you’ve got no
excuse [online] http://www.nancydixonblog.com/2009/09/if-the-army-can-putits-doctrine-up-on-a-wiki-youve-got-no-excuse.html (archived at https://perma.
cc/P2LC-BEDB) [accessed 29 January 2019]
Freudenthaler, K et al (2003) Entwicklung eines KM Framework und
Implementation Guide, Wissensmanagement 2003, pp. 309–14
Glick, D (2011) Federal workers stage Mobile Gov Wikithon to aid agencies,
Breaking Gov [online] http://breakinggov.com/2011/11/18/federalworkers-stage-mobile-gov-wikithon-to-aid-agencies/ (archived at
https://perma.cc/8ZJG-TNYD) [accessed 29 January 2019]
USINDO (2018) BASAbali Virtual Wikithon [online] https://www.usindo.org/
pec-events/basabali-virtual-wikithon/ (archived at https://perma.cc/Y44KDCQU) [accessed January 29 2019]
Wieneke, S (2008) Adopting and adapting product best practices across General
Motors Engineering six years later, in Knowledge Management for Services,
Operations and Manufacturing, ed. T Young, pp. 142–65, Chandos Publishing,
Oxford
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The knowledge- 16
finding and ­­
re-use elements
of the KM
framework
All the work of documentation and synthesis described in the previous
two chapters will be of no value if people do not re-use and apply the
­captured and synthesized body of knowledge. The ‘find and re-use’ step
includes the issue of ‘internalization’, which means appreciating and understanding the content of the documented knowledge, getting it ‘into
your head’ and into your internal repertoire. Once knowledge is internalized it can be applied, but first it must be located, accessed, reflected upon
and discussed.
This chapter flows directly into the topic of the next chapter, knowledge
organization, and covers:
●●
the challenges of knowledge re-use;
●●
incentivizing knowledge seeking;
●●
the importance of findability;
●●
roles for knowledge finding and re-use;
●●
processes for knowledge finding and re-use;
●●
technologies for knowledge finding and re-use;
●●
governance for knowledge finding and re-use.
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The challenges of knowledge re-use
There are many barriers to finding and re-using knowledge. Ghaedian and
Chen (2012) identified several barriers in a study of KM at Volvo Trucks in
Sweden:
1 Lack of time to stop doing the task and search for knowledge.
2 Captured knowledge was not consolidated (synthesized).
3 It was not easy to access knowledge.
4 It was not easy to search for and retrieve knowledge.
5 It did not occur to some employees that there might be answers for their
question somewhere in the organization.
6 Re-using knowledge was not a focus.
7 The culture did not support the reading of documents to acquire knowledge.
8 There was no clear flow of knowledge from project to the line organization
and/or to other projects.
9 There was no good structure to help employees build up their network.
Some of these barriers are related to an incomplete KM framework (item 2
applies to synthesis, item 9 to discussion, and item 8 to the lack of any defined framework). Lack of processes, roles, governance and tools for enhancing findability and accessibility of the knowledge is responsible for
items 3 and 4. Other items relate specifically to the lack of a ‘culture of
seeking’. The claim in item 1 that there is no time to seek knowledge is actually saying that ‘seeking knowledge is not prioritized’, and this is reinforced
in items 5, 6 and 7.
Incentivizing knowledge seeking
Many clients ask us, ‘How should we incentivize knowledge sharing?’ We
answer, ‘Don’t incentivize knowledge sharing. Incentivize knowledge seeking, and sharing will follow.’ Knowledge sharing in the absence of a defined
demand for knowledge usually achieves little, because it is in the re-use of
knowledge that we demonstrate the value of sharing. Without an appetite
for knowledge re-use, knowledge sharing can actually be counterproductive,
resulting in unvisited databases full of unwanted knowledge, and the feeling
Knowledge-finding and Re-use Elements
that ‘KM is a waste of time’. It is better to create the appetite for knowledge
before you create the databases, and creating demand will stimulate supply.
Knowledge seeking can be incentivized in three ways:
●●
●●
●●
Managers can create a high-performance culture, where people are
encouraged to continually push the boundaries of performance and to go
beyond what they already know. People who are satisfied with current
performance have no reason to learn, but if they wish to go beyond the
known limits, they will need to seek out new knowledge.
Managers can set stretch targets to stimulate knowledge seeking. John
Browne, the CEO of BP, set the expectation that ‘every time we do
something, we should do it better than the previous time’ (Prokesch, 1997)
and backed up this statement by continuously raising production targets
or continuously cutting budgets. Teams had to search for knowledge in
order to meet targets.
Managers can set expectations for knowledge seeking. The technical
director in one organization we worked with mandated that no project
would be approved if it could not demonstrate learning from other
projects.
The importance of making knowledge
findable and accessible
Making knowledge findable means making sure it is well tagged for search
and well structured for browsing. People often complain that ‘we wish our
in-house search engine was as good as Google’, but Google operates on
quite different principles from internal corporate content. Its search rankings rely at least partly on the number of hyperlinks between web pages, and
online content owners work hard on optimizing their pages to achieve
search results. Google also employs thousands of engineers who work on
search results pages – none of this is true of internal corporate content.
Knowledge also needs to be accessible, as there is nothing more frustrating than to see that a knowledge resource exists, and then not to be able to
access it because the folder it sits in is protected. There are a few mechanisms for supporting accessibility. Minimally, you can add a ‘request access’
feature to your system, which routes your request to the person responsible
for the knowledge artefact. More comprehensively, your KM policy,
which we cover in Chapter 23, should give guidance on how to balance
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i­nformation security concerns with the benefits of knowledge sharing and
re-use, so that staff don’t unnecessarily restrict access to content.
Your people should be aware that the knowledge resources exist for their
use. At induction and orientation, they need to be provided with an introduction to the knowledge resources and to the key tools – the search engine,
the community directory, the yellow pages – and told that they are expected
to use these resources as well as contribute to them.
The resources themselves need to be ‘ambiently findable’, which means
that by their very nature, they pop up when you start looking, or when you
are engaged in a task that requires them (Morville, 2005). For example, in a
project management portal, at the project initiation stage, as soon as the
project type is selected, links could appear to the relevant synthesized knowledge on projects of that type, while an Artificial Intelligence system in a law
firm might automatically send relevant precedents to a lawyer opening a
new piece of work with a client.
Roles for knowledge finding and re-use
There needs to be accountability for knowledge finding, review and reuse within the line organization. The project manager or department
manager is usually accountable for ensuring people seek the knowledge
they need, while the individuals are responsible for performing the
searches and then carefully reading the material they find. In some cases,
such as legal firms and governmental organizations, researcher and analyst roles are created to provide the knowledge workers with access to
documented knowledge.
Part of a knowledge analyst’s role will be to retrieve knowledge and information from various knowledge bases in order to prepare briefings for
customer-facing staff. Many of the big consulting firms have ‘knowledge
centres’ staffed by knowledge analysts, providing knowledge and research
services for client-facing consultants. Typical tasks include:
●●
●●
●●
assessing the knowledge needs of these ‘internal clients’;
gathering and organizing knowledge resources, compiling information
and data from many sources, and preparing statistics;
providing replies and briefings in response to queries by staff, managers
and external clients.
Knowledge-finding and Re-use Elements
The role of the professional support lawyer (PSL) in legal firms is similar to
that of an analyst. The PSL role can be any combination of (Magnusson,
2008, p. 99):
●●
providing know-how (advising lawyers, drafting precedents, providing
updates, maintaining knowledge bases);
●●
providing training (internal and external) and facilitating meetings;
●●
business development (pitch support, client alerts and seminars).
There are also a number of key knowledge organization roles that provide
the tools within the IT infrastructure to support findability.
The enterprise taxonomist is responsible for developing and implementing enterprise-wide taxonomies – the controlled vocabularies that connect
related knowledge and information content together. These vocabularies can
also be used to connect people with content – for example, if somebody is
contributing a lot of knowledge on a particular topic area, then that taxonomy tag can be associated with their staff profile in the system. When somebody does a search on that topic, they can then see the knowledge as well as
the people who are closely associated with that topic. When connected to an
actively managed competency framework, a taxonomy can have even greater
power in helping project or engagement managers find suitably qualified
and experienced staff for projects (Lambe, 2007, p
­ p. 106–12). The taxonomist is responsible for mapping these connections into the taxonomy.
The information architect is responsible for designing the information
and knowledge environment of the organization so that information resources are easily navigated and easily findable. They work very much like
the architects of a physical space – ie organizing and signposting the ‘information space’ so that people can navigate it easily. The information architect
needs to identify and analyse the information and knowledge needs of different users in the context of their work, and needs to work closely with the
taxonomist. The taxonomist provides the terminology and categories, and
the information architect designs the overall environment using the taxonomy to support the identified user needs.
The enterprise search specialist is responsible for ensuring that the search
technology is deployed in a way that effectively exploits the taxonomy, and
that it supports the information architecture design.
For example, an enterprise taxonomy will usually collect all the alternate
ways that a taxonomy term can be expressed, and connect those alternate
terms to the controlled term in the taxonomy. Then, whenever a search query
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uses one of those alternate terms, the search engine retrieves all the resources
(and people) tagged with the taxonomy term. This is a way of overcoming
‘scatter’ of resources when searchers use different words to mean the same
thing. The search specialist has to configure the search engine to do this.
Similarly, the search specialist will provide the taxonomist with reports of
the most frequently used search queries. These are terms that should be considered for inclusion in the taxonomy or the collection of alternate terms, because
they are evidence of how people are thinking about the knowledge content.
The search specialist works with the information architect to provide the
targeted ‘ambient findability’ of knowledge resources we talked about earlier. The information architect identifies the needs for knowledge resources
in a specific context. The search specialist deploys the taxonomy and the
search technology to go looking for those resources and pipe them through
to the relevant user interface.
Processes for knowledge finding and re-use
The best-known process for knowledge finding and re-use is the before-action
review. Here, finding and reviewing knowledge resources is incorporated into
a discussion process. This works best as a fixed step in a project management
process flow, and is held at a project initiation stage. In the British National
Health Service (NHS), a before-action review is part of a mandated process
flow for projects, and is primarily a facilitated discussion session guided by the
following four questions (Health Education England, 2018):
1 What are we setting out to achieve?
2 What can be learned from similar situations and past projects from
elsewhere?
3 What will help deliver success?
4 What are the actions we need to take to avoid problems and apply good
practice?
Question 2 requires some preparation by consulting prior knowledge resources and lessons, and this is where knowledge finding and re-use feeds
back into the planning cycle. In the Singapore Army, the before-activity review is used in a similar way at the planning stage for a mission or operation
(Singapore Ministry of Defence, 2014, p. 208).
Knowledge-finding and Re-use Elements
However, in most organizations the assumption is that individuals will
search for knowledge themselves as and when they need it, with no particular process for discussing and evaluating this knowledge. This ad hoc approach can work when the other elements of the KM framework are in
place, but without that support and when left as an optional exercise it is
often omitted entirely.
A much more systematic process for ensuring knowledge re-use is the
KM planning process (Milton, 2005, p. 117), the outcome of which is a KM
plan. This is a document for a specific project (or department, community of
practice or function), which details:
●●
what knowledge needs to be sought, reviewed and incorporated by the
project;
●●
known knowledge gaps, and knowledge requirements of the project;
●●
where the knowledge will be sought;
●●
how it will be acquired;
●●
who is responsible for its acquisition;
●●
when the acquisition is needed;
●●
what knowledge will be created by the project;
●●
●●
●●
●●
how it will be identified and documented (which processes will be used,
and when);
who is responsible for its documentation;
where the documented knowledge will be stored and how it will be made
findable and accessible;
what KM framework will need to be applied within the project, including
roles and accountabilities, processes and supporting technologies.
The plan is created at a KM planning workshop, held as part of the
­project-planning and initiation activities. The workshop will include a
­discussion of the knowledge needed by the project, and during this discussion, actions will be assigned for knowledge seeking. The KM plan therefore drives the behaviour of knowledge finding and review, as many of the
knowledge-seeking actions will involve searching for documented knowledge. A simpler approach to this is the knowledge gap analysis process
(Milton, 2015).
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Technologies for knowledge finding
and re-use
There are four main technologies to support knowledge finding and re-use:
●●
tagging systems and tag clouds;
●●
enterprise search and search-based applications;
●●
autoclassification tools;
●●
taxonomy management systems.
Tagging systems are frequently used in conjunction with knowledge-sharing
tools such as blogs, wikis and online discussion platforms. They allow users
to define and attach keywords (‘tags’) to their posts. Tag clouds are an extension of this. Here, the most frequently used tags are presented in a cluster
on the page, and the font is scaled according to the frequency with which the
tag is applied. This is a good way of identifying trending topics in a rapidly
flowing knowledge-sharing environment.
The disadvantage of tagging systems is the lack of control over the terms
that are chosen. One person might use the term ‘infectious diseases’, another
‘communicable diseases’, another ‘vector control’, and another ‘disease
transmission’, for posts that are all about the same underlying topic. Even
the same user may tag the same topic differently at different times. Without
some form of management or control, such as the integration of tags within
an enterprise taxonomy, these related posts would not be brought together.
This is where knowledge organization capabilities come into play (see the
following chapter).
Enterprise search refers to technologies that match queries to results. In
its simplest form, a search engine takes a search query and matches it against
an index of terms it has already prepared, each of which is in turn linked to
knowledge and information resources. However, there is a great deal of
work involved in making enterprise search results relevant to the users. This
usually involves:
●●
Establishing rules to make sure that the terms that get into the index are
highly significant to users and representative of the content. For example,
a document that contains the word ‘Google’ is not necessarily ‘about’
Google, so a search engine needs to be told how to identify the ‘aboutness’
of a document so that it can compile a smart index.
Knowledge-finding and Re-use Elements
●●
●●
Establishing rules for how search results are prioritized depending on
where the index words have come from – eg the taxonomy metadata, the
document title, abstract or specific sections in a well-structured document.
Establishing rules for how search results are prioritized depending on who
the user is, based on what the system knows about their search, download
or tagging behaviours, or their functional role in the organization.
Search-based applications are extremely targeted uses of a search engine,
usually in conjunction with a taxonomy. For example, earlier on in this
chapter, we referred to examples of ‘ambient findability’ where knowledge is
piped through to specific situations and contexts where it will be relevant
and useful. These examples are powered by the enterprise search tool, which
in this case is matching resources to specific pages in a workflow. Opening
the page triggers a pre-defined query, pulling all the most relevant resources
connected with that activity.
Autoclassification tools are a means of assigning tags or taxonomy topics
to documents without the need for manual tagging by users (Hedden, 2016,
Chapter 7). These tools are designed to reduce the burden of manual tagging, especially where knowledge contributors are under time pressure, or
where they might not be aware of the relevance of their contribution to
other people, and might therefore not assign the tags that are relevant to
those users. Autoclassification tools work best with named entities (places,
people, organizations) or with very clearly defined technical vocabularies
(such as in engineering or law), and less well with abstract topics like activities, subject areas, or concepts. This is because the tools work on term
recognition – where the language is extremely variable, the tool is weaker;
where the language is reasonably tight, and where you can define clear rules,
the tool works better (Reamy, 2016).
Used in combination with taxonomy and search, these tools can be very
powerful. For example, the BBC uses an autoclassification tool which is integrated into the story-filing interface for its journalists. As the journalist
types his or her story, the system recognizes the names of people, places and
organizations using a reference taxonomy, and it uses the search engine to
automatically populate the right-hand column with links to prior stories
about those people, places or organizations. The journalists will correct
the suggested terms and add their own taxonomy topics, because they immediately recognize that the tool makes their work easier (Shearer and
Tarling, 2013).
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Enterprise taxonomy management systems address the problem where
large and complex organizations are using multiple knowledge-sharing and
storage platforms (online communities, discussion forums, knowledge bases,
content libraries, portals supporting workflow, lessons databases). Without
a common enterprise taxonomy, these systems become knowledge silos,
each using their own sets of topics and finding aids. If related knowledge
content is to be pulled together, even with an enterprise search engine to
crawl across these systems, then it is important that content is tagged consistently using the same controlled vocabularies. An enterprise taxonomy
management system provides a central place where all the controlled vocabularies that make up the taxonomy and the metadata can be governed,
maintained and updated. The system then provides these vocabularies to the
content systems that need them, and to the search engine to consult. Without
such a system, the task of maintaining consistent vocabularies across multiple platforms becomes very labour intensive and error-prone (Hedden,
2016, Chapter 5).
Tip
The full technology and governance requirements for knowledge finding
and re-use will not become clear until well into your trials and pilots
approach. Do not commit too early to a single set of technologies or
knowledge organization tools. As you run your pilots, keep a running log of
the finding and re-use requirements that emerge, and regularly review
them, before building an integrated set of requirements.
Governance for knowledge finding
and re-use
Some of the governance elements which will support knowledge finding and
review are as follows:
●●
●●
a clear assignment and delegation of accountability for ensuring projects
and other activities learn from the past;
a defined expectation for searching and reviewing documented knowledge,
and incorporating any relevant knowledge in future work;
Knowledge-finding and Re-use Elements
●●
a defined expectation for the accurate tagging of documented knowledge
to support findability, and for ensuring that access rights support sharing;
●●
a defined expectation for KM planning and the use of KM plans;
●●
monitoring compliance with these expectations;
●●
training and support in the use of taxonomy and search technology;
●●
collection of success stories regarding the re-use of knowledge and the
value created from re-use.
C A S E S TU DY
Hewlett-Packard (HP) introduced a rewards programme called ‘KM stars’. Here,
individuals were awarded a ‘star’ for offering knowledge (posting a document or
answering a forum query), and five stars for re-using knowledge, in order to give
added incentives for re-use. Re-use can be difficult to measure, but HP
overcame this by introducing a ‘re-use forum’ in which people could share
stories of re-use and earn multiple stars. The system automatically generated a
leader board, and each month three people (each from different regions)
were selected to receive a financial reward and the recognition from their VP.
A fourth winner was selected from the re-use forum. In return, each winner was
required to write a short story of how they got to be the KM star, and this
provided a valuable series of peer-level success stories of knowledge re-use
(Garfield, 2018).
Summary
Knowledge finding and re-use, the crucial step for delivering value from
documented knowledge, is a step which often seems to get little attention,
and is frequently left unsupported and ungoverned. You need to give particular attention to this element of the framework if you are to reach your
goal of a complete ‘knowledge supply chain’ for the knowledge workers in
your ­organization.
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Assessment and Planning
References
Garfield, S (2018) The role of evolving technologies: accelerating collaboration and
knowledge transfer – HP KM case study by APQC [online] https://medium.
com/@stangarfield/the-role-of-evolving-technologies-accelerating-collaborationand-knowledge-transfer-hp-km-case-5bfc39ce85c0 (archived at https://perma.cc/
GM6Z-X9SW) [accessed 30 January 2019]
Ghaedian, S and Chen, B (2012) How to support and facilitate knowledge flow in
product development at Volvo group trucks technology, Master of Science
Thesis, Chalmers University of Technology, University of Gothenburg, Sweden
Health Education England (2018) Before Action Review [online] https://kfh.
libraryservices.nhs.uk/wp-content/uploads/2018/06/CS47408-HEE-LKSPostcards.4.pdf (archived at https://perma.cc/8WLU-A22W) [accessed
30 January 2019]
Hedden, H (2016) The Accidental Taxonomist, 2nd ed, Information Today,
Medford, NJ
Lambe, P (2007) Organising Knowledge: Taxonomies, knowledge and organisational effectiveness, Chandos Publishing, Oxford
Magnusson, J (2008) Roles in a legal services context, in Knowledge Management
for Services, Operations and Manufacturing, ed. T Young, pp. 98–100, Chandos
Publishing, Oxford
Milton, N J (2005) Knowledge Management for Teams and Projects, Chandos
Publishing, Oxford
Milton, N J (2015) How to conduct a knowledge gap analysis [online] http://www.
nickmilton.com/2015/12/how-to-conduct-knowledge-gap-analysis.html
(archived at https://perma.cc/3QTU-LSXE) [accessed 30 January 2019]
Morville, P (2005) Ambient Findability: What we find changes who we become,
O’Reilly Media, Sebastopol, California
Prokesch, S E (1997) Unleashing the power of learning: an interview with British
Petroleum's John Browne, Harvard Business Review, 75 (5), pp. 146–68
Reamy, T (2016) Deep Text: Using text analytics to conquer information overload,
get real value from social media, and add bigger text to big data, Information
Today, Medford, NJ
Shearer, M and Tarling, J (2013) Unlocking the data in BBC News, ISKO UK
[online] https://slideplayer.com/slide/1481436/ (archived at https://perma.
cc/9XTT-9VKF) [accessed 30 January 2019]
Singapore Ministry of Defence (2014) The Army Warrant Officer and Specialist
Guidebook, 2nd ed [online] http://www.mindef.gov.sg/dam/publications/eBooks/
wospec/ (archived at https://perma.cc/96PZ-RXGK) [accessed 30 January 2019]
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Knowledge
organization
17
We have already covered several aspects of knowledge organization, such as
knowledge synthesis (Chapter 15), and findability, internalization and re-use
of knowledge (Chapter 16). These are all manifestations of knowledge organization. Knowledge organization is the capability that underpins our
ability to make knowledge and information available and findable for re-use
across the enterprise.
In this chapter we focus on the need to have a systematic and evidencebased methodology for organizing explicit knowledge and supporting documents, and for connecting this content with people (subject matter e­ xperts)
and with community discussion topics. Without this methodology, it will
be difficult to be systematic and consistent in the service of your KM
­framework.
In this chapter we cover:
●●
●●
grounding knowledge organization in the business drivers;
the three components of knowledge organization: taxonomy and metadata,
information architecture, and search;
●●
taking an evidence-based approach;
●●
using the knowledge resources audit to focus on what counts;
●●
testing and validating the knowledge organization system.
Grounding knowledge organization
in the business drivers
Knowledge organization involves designing an infrastructure to serve specific needs and purposes. These needs and purposes flow through from the
business drivers via the KM implementation objectives, as discussed in Part
Two of this book.
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Assessment and Planning
For example, one of the objectives might be to ensure that lessons learned
in one part of the organization can be re-used in other parts, so as to avoid
wasted cost or to reduce risk. This has implications for the taxonomy, because it would have to provide a common way of categorizing lessons that
all interested parties could make sense of, even though in their functional
silos they might use different terminology. For example, in a project with the
military, we found that both Military Police (MPs) and Guards Formations
have duties to protect strategic installations such as army bases, power stations or government offices. MPs call it ‘Key Installations Protection (KIP)’,
and Guards call it ‘Protection of Installations (POI)’. The taxonomy has to
broker that difference in terminology, so the related lessons can be gathered
for analysis, synthesis and re-use.
Another objective might be to speed up the learning curve of new recruits, so as to maintain strategic capabilities in a period of high turnover or
growth. That would have an impact on the taxonomy and information architecture design, for example in the scope of the knowledge resources being
focused on (the knowledge items they need), and in the technical complexity
of the terms being used (new recruits can’t navigate technically complex
language as easily as experts).
Tip
Remind yourself of the business objectives and KM implementation
objectives identified in your preparation stage. Identify the priorities that
impact your knowledge organization approach such as common taxonomy,
information architecture and enterprise search.
The three components of knowledge
organization
Taxonomy and metadata
A taxonomy is a controlled vocabulary for a set of categories and topics, to
describe what a document is about and to tag people (eg with topics of expertise), community domains, or topics of discussion in a community. This
allows you to connect content with content, and content with people and
communities.
Knowledge Organization
‘Controlled’ means that there are defined roles, rules and processes for
approving changes to the vocabulary, to ensure that the taxonomy continues
to serve its intended purpose. Without control, people will add their own
terms to the vocabulary on an ad hoc basis, and the taxonomy will slowly
lose its ability to bring together related resources as intended.
In many cases, a taxonomy has a hierarchical structure. Detailed topic
terms are clustered together under more general category headings. This
hierarchy allows us to organize a large number of topics in a user-friendly
way. Other taxonomies, however, are small and simple enough that they can
be presented as a flat list with no hierarchy – for example, a simple taxonomy of types of car could contain just seven terms: economy, family, saloon,
luxury, sports, off-roader and commercial.
Enterprise taxonomies serve multiple user groups and multiple content
collections across the whole enterprise, to enable the bringing together of
content, people and communities from across functional siloes and to enable knowledge re-use and discovery of new insights. Because of the diversity
of use they have to support, they should consist of multiple controlled vocabularies rather than a single, monolithic, hierarchically structured vocabulary, for the following reasons:
●●
●●
Large organizations have to manage findability for many hundreds of
thousands (or even millions) of knowledge and information resources – a
single taxonomy hierarchy to cover all this content would be far too
complex and difficult for users to navigate.
The way a single hierarchy is organized must favour a single particular
perspective. For example, if we organize lessons at the top level by project
type, then by project activity, and then by customer, we are taking a
‘project’ view of the hierarchy, and this will be far from ideal from the
customer manager’s point of view. The customer manager would
obviously prefer to organize the hierarchy by customer type first.
The solution for this is to build a system of controlled vocabularies called
taxonomy facets. Each facet is a smaller vocabulary covering just one aspect
of the content – in the example above, we would have three facets: a project
type facet, a customer facet, and a project activity facet. A document (or
conversation, or expert) would be tagged according to each facet, so that
both the project manager and the customer manager can find resources
equally easily, from the perspective that makes most sense to them. Faceted
taxonomy structures are also much simpler and easier to navigate than
large, single-hierarchy structures.
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The process of identifying which facets are relevant and important to the
different user communities is called facet analysis, and requires a ­thorough
understanding of the different communities of knowledge workers that need
access to the same knowledge resources. Your ­knowledge resources audit
can provide this understanding, because the knowledge maps describe how
knowledge resources are used in different ­business activities.
Metadata refers to structured data about a resource. For example, author,
title, subject keywords, date of publication, access permissions, are all individual pieces of metadata that might be associated with a document.
Metadata is also used for other resources such as people and communities.
Metadata is used for three main purposes:
●●
●●
●●
Identifying content – descriptive metadata captures unique identifiers
such as author and title fields and distinguishes each document from all
others.
Helping systems manage content – eg administrative and structural
metadata captures things like version numbers, archiving date, security
and access permissions, and file types to tell the system which applications
to use to read it.
Aiding retrieval of content – eg descriptive metadata captures things like
taxonomy topics, user-defined tags, content types and document
descriptions.
Taxonomy facets supply the vocabularies for the descriptive metadata components that aid retrieval. This is why enterprise taxonomists are also usually responsible for their organization’s metadata schema – the framework
that specifies which metadata will be gathered, how it is defined, how it will
be collected, which controlled vocabularies are used and what purposes they
should serve (Lambe, 2007).
Information architecture
‘Information architecture’ refers to the overall design of the information
environment such as websites, intranet, knowledge bases, portals and community spaces. It requires a close understanding of the different user groups
and their needs, such as will be gained from the knowledge resources audit.
The work product of an information architect includes:
●●
A high-level map of different knowledge systems and supporting tools such
as search and taxonomy management systems, showing the relationships
and information and content flows between the systems.
Knowledge Organization
●●
●●
A system-level map, or site map, showing how the system is structured
for easy navigation by its users.
A page-level map, or ‘wireframe’, showing the labels that act as signposts
to sections, pages or information actions such as a comment, a submission,
or a link to a knowledge owner’s contact details. ‘Pages’ here refers to
web­pages within a KM system – whether it be an intranet page, a know­
ledge base page, a wiki page or page within a community collaboration
space.
In order to organize an information or knowledge environment for the main
user groups, information architecture design is almost always bottom-up.
Wireframes that meet the needs of the knowledge workers are created,
tested, analysed and refined iteratively. User requirements are aggregated
and analysed to provide the knowledge flow and navigation requirements
for the information environment being designed. As these system-level requirements are identified, the site structure and system architecture maps
are built to accommodate them in an efficient manner.
The information architecture focuses on the overall environment within
which knowledge content is managed and navigated, while the taxonomy
provides the core vocabularies describing individual pieces of content. Both
use labels, but with different levels of granularity and different purposes.
This is why information architecture labels and taxonomy labels often have
overlaps but are not identical.
Search
When people talk about search they often think of the technology that
makes up enterprise search, while failing to appreciate the design component of search. Search technology is only as good as the rules configuring the
way the tool indexes documents, the way it exploits taxonomy structures,
and the way it supports navigation through the designed information environment, as we saw in Chapter 16 on findability and re-use.
Taxonomies (and other metadata), information architecture, and search
are three interlocking components that make up a knowledge organization
system. Very much like a KM framework, when these components don’t talk
to each other through an over-arching design and common implementation
methodology, then their effectiveness is drastically reduced.
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Taking an evidence-based approach
to knowledge organization
The facet analysis step in taxonomy design, and the iterative designs of information architecture, cannot be conducted on the basis of intuition, guesswork, or limited sets of opinions. It needs to be evidence-based.
In the field of knowledge organization we talk about three types of evidence, or ‘warrant’:
●●
●●
●●
Content warrant refers to the evidence of how knowledge and infor­
mation content is currently described and organized by users. This
evidence can be gathered by collecting existing classification schemes
and taxonomies, folder structures and site structures, labelling schemes
for collections of content, content pages for synthesized knowledge
products etc. Typically this content warrant has been built up cumulatively
over the years without an overarching framework, and while it tells you
what the ‘ambient’ vocabulary is in an organization, it does not tell you
which documented knowledge is most relevant and useful at this point
in time.
User warrant refers to evidence about the most important and frequent
work activities of the different user groups. User warrant requires building
a series of use case scenarios for the different user groups covering a
range of key work activities that are dependent upon knowledge and
information consumption. The user warrant provides the context and
purpose of information and knowledge use, and so helps to determine
which parts of the content warrant are most significant and relevant.
Standards warrant refers to situations where a work group needs to
exchange information and knowledge with other groups, whether internal
or external, and therefore needs to use a standard shared vocabulary. For
example, government funding agencies need to report upwards into their
national statistical system, and so need to use standard taxonomies for
industries, institutions, population segments, etc. In some cases, user
warrant may conflict with standards warrant – ie the standard vocabularies
do not match the way that users think about and describe their resources.
In this case, you create cross-walks between the user-oriented taxonomy
vocabulary, and the required standard, so that the system can automatically
associate the two sets of terms and connect related information content
even if it was only tagged with one of the two alternatives.
Knowledge Organization
Taking an evidence-based approach means having a systematic method of
collecting all three kinds of warrant. We recommend you start with the user
warrant, which helps you understand the knowledge work that the taxonomy and information architecture will support. The content warrant then
gathers all the existing vocabulary systems and organizing systems for using
information and knowledge, and these either form input to the taxonomy or
will need to be mapped to the taxonomy through a thesaurus, so that variant forms of terms in use are recognized by the system and associated with
their respective taxonomy terms. Finally the standards warrant indicates
where standard taxonomies and classification schemes need to be used.
Using the knowledge resources audit
to focus on what counts
Each of these evidence-gathering activities can be conducted separately.
However, this will be labour intensive. By far the most efficient and effective
way to structure the evidence collection is to use the knowledge resources
audit (Chapter 11), which although principally aimed at identifying operational knowledge resources, gaps and flows, can also be used to capture user,
content and standards warrant:
●●
●●
●●
The knowledge resource descriptions in the knowledge maps represent a
current overview of the key knowledge resources that support key
business activities across all departments, and they provide the current
vocabulary of how your staff think about the knowledge they use – ie the
current content warrant.
The knowledge resource maps are organized around key work activities
and provide the context in which information and knowledge are used,
so they form the basis for user warrant.
The audit can generate maps of internal and external knowledge flows
that can help you identify the need for standards warrant.
In addition to the knowledge resources audit, you need additional evidence
gathering for the content warrant, for example collecting existing taxonomies,
classification schemes, folder structures, vocabularies etc. You can also use
reports of common search queries from your search engine, and commonly
used uncontrolled tags in your tagging system, as valuable content warrant.
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Assessment and Planning
The challenge with content warrant is in discerning which vocabularies
and organizing principles are most relevant and current now. By providing
a complete overview focused on key activities, the knowledge maps give you
a framework that will help you design the knowledge organization system
in a way that focuses on areas of current relevance and need. All the other
evidence you collect needs to be incorporated, but it is incorporated as background material, pointing to the key vocabulary that is of current concern.
In Chapter 16 we saw there are several different terms to describe ‘infectious
diseases’. In fact, ‘infectious diseases’ is an historical term, and the current
term is ‘communicable diseases’. In this case the term ‘communicable diseases’ goes into the taxonomy, and ‘infectious diseases’ is captured into the
system as an alternate term so that resources using the older term can still
be retrieved using the newer term (Lambe, 2007).
Tip
If you have completed a targeted or comprehensive knowledge resources
audit, analyse your maps for key user scenarios. Pull out the knowledge
resource descriptions for documents to gather the vocabulary describing
document types. Pull out the activity descriptions and the knowledge
resource descriptions for methods and skills to gather the vocabulary about
key activities and processes. Pull out the knowledge resource descriptions
about experience and natural talent to gather the vocabulary about expertise
topics. You are starting to build the core of a useful enterprise taxonomy!
Testing and validating your knowledge
organization system
You design your knowledge organization system to meet the KM objectives
you have defined. Once you have gathered your three forms of warrant and
referred back to your business objectives and KM implementation objectives, the taxonomist can begin the facet analysis to identify the taxonomy
facets that will serve key user needs, while the information architect can
start identifying key use case scenarios against which to start designing and
testing the wireframes. These are both skilled technical tasks, so you will
Knowledge Organization
need professional help to do this, whether in-house or from external specialists. Both the taxonomy and the information architecture design will need
iterative testing against the use case scenarios, to give assurance that the
taxonomy and information architecture designs do actually improve findability and accessibility of knowledge resources. You will need to measure
against a baseline (before and after), and typical measures would include:
●●
speed of completing knowledge-seeking tasks;
●●
quality of results in relation to the task;
●●
completion/non-completion rates of tasks;
●●
number of mistakes and dead ends in completing the task;
●●
confidence level in searching/browsing behaviours;
●●
●●
consistency in tagging behaviours using the taxonomy (inconsistent
tagging means that the same resources will be scattered);
accuracy of user predictions in where to find specific materials.
Using metrics such as these means your design will be highly defensible.
Anybody with an opinion will be able to propose ‘better’ designs when it
comes to taxonomy and information architecture, but when you can use
empirical testing to show that performance of key tasks is rendered more
effective by the design, you become less reliant on opinions and can build an
evidence-based culture.
Once your taxonomy and information architecture designs are complete,
you can turn to the search design. The information architect sets the requirements for the role of search in delivering the information and knowledge
resources to each key user interface in turn. Examples of key user interfaces
might be a search page, a search results page, a topic structure page, a dashboard, and so on. These are ‘interfaces’ and not passive pages, as the user can
take actions using the search engine to refine or sort or organize the contents
on the page. The page and the interactions on the page need to be structured
in a way that suits the different user groups. The taxonomy and metadata
schema provide the vocabulary content for the search engine to work with.
Summary
The role of knowledge organization during KM implementation is primarily
a design task, integrating the capabilities of taxonomies (with other metadata), information architecture, and search. To be effective, it requires a
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Assessment and Planning
systematic, evidence-based approach, grounded in a thorough understanding of the current reality in your organization. The knowledge resources
audit is extremely effective at providing this understanding, as well as helping you to define the goals to be achieved by the design. The work involved
in taxonomy, information architecture and search design is skilled and technical. Not all specialists combine these three sets of skills, and very often the
three roles will need to work as a team to create (and subsequently maintain) your knowledge organization design.
Reference
Lambe, P (2007) Organising Knowledge: Taxonomies, knowledge and organisational effectiveness, Chandos Publishing, Oxford
189
Influencing the
stakeholders
18
You can’t change your organizational culture all at once; you can only
change it one heart and one mind at a time. A lot of KM implementation
involves working with and influencing your key stakeholders on an individual basis. In this chapter we cover:
●●
a template for mapping stakeholder buy-in;
●●
the knowledge manager as salesperson;
●●
segmenting your audience;
●●
influencing tactics;
●●
when to use the influencing tactics;
●●
a case study from NASA.
The steps of the buy-in ladder
Even when we realize that culture is changed one heart and mind at a time,
we also need to realize that each individual does not change their heart and
mind all at once. There are a number of steps before an attitude is changed
(Figure 18.1) and it is worth understanding these steps, as you cannot move
an individual more than two or three steps in any one interaction.
The steps are these:
1 First contact – the first time that the individual hears the term ‘knowledge
management’.
2 Awareness – they become aware of KM as something that may be an
issue or an opportunity within the organization.
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Assessment and Planning
Figure 18.1
The stakeholder buy-in ladder
Awareness raising
Engagement
Embedding
Commitment threshold
Adoption
Trial
Institutionalization
Internalization
Acceptance
UnderAwareness standing
First
contact
Increasing level of buy-in
3 Understanding – where you help them understand what KM means (in
basic terms).
4 Acceptance – where you help them realize that KM holds value for them
and for the organization.
5 Trial – the point at which they agree to try KM. This leads to the first
commitment threshold – the commitment to act. This is your ‘sell’ – the
point at which the individual ‘buys’ KM, at least temporarily.
6 Adoption – assuming the trial has gone well and delivered value, this is
when the individual agrees to adopt KM in the longer term.
7 Embedding into work process – this is where the individual, team and
eventually company embeds KM into work process, as described in
Chapter 23.
8 Embedding into culture – this is where people within the organization
internalize KM as ‘something we just do’. At this stage it becomes a core
value.
There are therefore many steps, and it is easy to underestimate the importance of each one. Many key stakeholders or stakeholder groupings never
go beyond the trial stage, or perhaps they adopt KM but never embed it. It
is only when the majority of your key stakeholders get to step 7 (embedding)
that KM is relatively safe, and even then you need to take care of the final
step, the internalization step, so that the culture becomes pervasive and
­unconscious.
Influencing the Stakeholders
Tip
Use the ‘eight steps’ template to map the current buy-in level of each of
your key stakeholders, and to plot how you want to move them up the buy-in
ladder over the next few months. You can certainly raise awareness and
understanding through general communications, but at some point you will
need to start to involve individuals in direct conversations to get to the ‘trial’
stage. Use the template to determine the priority and timing of the
conversations you need to have.
The knowledge manager as salesperson
You can introduce the topic of KM to the organization and raise the levels
of awareness and understanding among your stakeholders through general
communication and education (as described in the next chapter). This can
move stakeholders to the ‘understanding’ and hopefully ‘positive perception’ levels, but to take the next step, where your stakeholder commits to
trying KM, you need to move from being an educator to being a salesperson.
Salespeople often have a bad reputation, based on the conventional idea
of product-based selling as persuasion, regardless of the quality of the product or service. In KM, our ability to sell is as dependent on the credibility we
have as it is on the ‘pitch’ itself. However, your effectiveness in implementing
KM also depends on your influencing and selling skills. You may have designed the best KM framework in the world, but the world will not beat a
path to your door in order to use it. You have to go out and sell it, which
means you need to know some of the tools and methods of selling and
­influencing.
Understand what the customer is buying
You first need to understand what the customer is buying. You may know the
statement by Harvard marketing professor Theodore Levitt: ‘People don’t
want to buy a quarter-inch drill. They want a quarter-inch hole’ (Christensen,
Cook and Hall, 2006) – and they want that hole to put up shelves so their
house is tidy. A person selling electric drills is actually selling the ability to
improve your house. Similarly, your stakeholders are not buying KM, they
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are buying something wider, which KM can deliver to them, and you need to
understand what that is. Two of the more common ‘wider things’ that the
customer wants are protection and opportunity.
KM can offer protection against lost knowledge, repeat mistakes, inefficiencies and risks: all of the things we mentioned as potential pain points in
Chapter 4. This the primary selling point for a knowledge retention and
transfer strategy, for example. In industries and countries with aging workforces, you can usually show worrying figures about projected knowledge
loss, and you can talk about the risk that this ‘corporate amnesia’ poses to
continued effective operation. A knowledge retention programme protects
against loss of capability.
You can also sell knowledge management as an opportunity. Most organizations already have a lot of knowledge, held in the heads of individuals
or scattered in many knowledge stores, which they are underutilizing. This
opportunity to capitalize on an undervalued resource is a powerful argument. Which manager would not want to gain value from managing a resource they already have?
Tip
Based on your knowledge of the stakeholders, what is the ‘wider sell’ you
can make? What can KM deliver to them (eg protection or opportunity) that
they may be in the market for? Remember, different groups of stakeholders
may require different ‘wider sells’!
Segmenting your audience
Every salesperson needs to know their market and their customer base. To
sell KM, you can think in terms of three market segments:
●●
The one in five people who instinctively ‘get’ KM and become immediately
enthused, moving rapidly from ‘first contact’ to ‘positive perception’ and
‘trial’. In our experience, about 20 per cent of staff are likely to be early
supporters of the idea of KM, and will become your allies, your supporters
and the early adopters.
Influencing the Stakeholders
●●
●●
The three in five people who don’t care about KM one way or the other.
They will engage in KM if they have to, if it’s part of the job, or if everyone
else is doing it. If KM is voluntary, or unusual, they won’t bother. Moving
them to the ‘trial’ phase of buy-in will require a range of influencing
tactics described later in this chapter.
The remaining one in five who really don’t like KM at all. They think it
is a personal threat to make them expendable, or a way of ‘stealing their
ideas’. These people will resist KM, unless it is made unavoidable and
fully embedded into performance management so that their job prospects
suffer if they refuse to share. These people will be very difficult to move
to the ‘positive perception’ stage, let alone higher than that. Here your
primary tools are going to be peer pressure, ‘social proof’, appeals to
authority and compulsion.
If you introduce KM as a voluntary activity, you only reach the 20 per cent
in the first market segment. Many organizations have found this to be a
typical sort of adoption rate when internal use of social media such as blogging and microblogging is introduced ‘bottom up.’ Adoption does not spread
beyond the enthusiasts, 80 per cent of the organization remains uninvolved,
and so 80 per cent of the knowledge remains untapped and unmanaged.
You need to use the 20 per cent of enthusiasts to create ‘social proof’
(described later) which will draw in the others. Use the supporters and early
adopters to conduct the pilots, deliver the benefits and share the stories that
will convince others that KM will help them in their work, and convince
management to set KM as a corporate expectation.
Also you won’t complete the journey until KM becomes inescapable. If
the company is committed to KM, then the last 20 per cent, who really don’t
like it, need to know that their future is at risk if they continue to avoid or
sabotage the KM efforts.
Sometimes it makes sense to directly influence these sceptics early in the
implementation programme, as the case study below demonstrates.
C A S E S T U DY
One very successful KM practitioner we know was working in a law firm in the
1990s. Lawyers are famously difficult to influence in favour of putting effort into
KM, because their rewards are directly tied to time spent on client work, not on
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internal knowledge sharing. Our friend approached the most sceptical law
partner and said, ‘We’re putting a new KM framework in place. Tell me where
your biggest pain points are, and we’ll try to address them.’ He wasn’t convinced,
but told her that as long as she didn’t make any extra work for his lawyers, she
could work on solving a few of his pain points. She chose the issues that she
knew could scale beyond this partner, and got to work. Pretty soon she had other
partners stopping her in the corridor, asking why this particular partner was
getting so much attention, and when they could start benefiting from KM. She
told them she’d bring them on to the project roadmap as soon as she could, and
created a timeline for them to follow. By going for the most sceptical partner and
doing a good job, she had created a ‘KM pull’ effect that meant she had to do
very little selling anywhere else.
Influencing tactics
The knowledge manager needs to understand the basics of influencing and
persuasion in order to move the stakeholders up the buy-in ladder. The book
Mind Gym (Bailey and Black, 2014) describes nine influencing tactics you
can select from, based on the character and situation of the ‘buyer’. These
are described below, together with the sorts of things you might say to your
stakeholders.
Reasoning – using logical argument to make a case. Your argument might be
something like:
KM, if applied to the bidding process, should improve our bid conversion rate
by 20 per cent, which would be worth $5 million in new business. We calculated
this by looking at the bid losses over the last three years that could have been
avoided through re-use of knowledge and best practices.
Reasoning will almost certainly be necessary to support your case with all
stakeholders, even if other influencing techniques will create the closing
‘sell’. You therefore need to create a compelling logical case for KM, which
needs to be a case for the individual as well as for the company.
Inspiring – appealing to emotions and creating the vision. You would use
this approach when you want to generate emotional commitment to the vision. The inspiring tactic demands conviction, energy, and passion, but is
particularly effective with the 20 per cent of early adopters:
Influencing the Stakeholders
Imagine what it would be like to have knowledge at our fingertips – to know,
at every decision point, what we have tried in the past, what works and what
doesn’t work. We hold 10,000 years of experience in the heads of our staff –
imagine what would be possible if that resource was available to everyone in the
building.
Asking questions – leading the other person to make their own discovery of
the value of KM:
When do your people use knowledge? Tell me about some of the important
decisions where knowledge is critical. If we had a situation where every person
facing such a decision had complete access to the knowledge they needed, how
much more business do you think we could win? And how certain are you that
people in this situation are currently handling this vital knowledge in a rigorous,
systematic, managed way?
This is one of the more difficult tactics to use because it is impossible to
know how the other person will respond. You have to be able to think on
your feet, but if you can, this is one of the most powerful approaches to use
when talking to senior staff.
Cosying up – your stakeholder will almost always feel positive toward
someone who makes them feel good about themselves. This is the cosying
up tactic:
Dan, you are the smartest and most progressive leader in the whole
management layer, and I know you are always looking for the next way to
really improve your department. Let me tell you about this new thing called
knowledge management.
Don’t use this approach when talking to people who are much more senior
than you, and when cosying up can look like ‘sucking up’. And don’t use it
when you don’t believe what you’re saying. People find it very easy to detect
insincerity.
Deal making – when you give another person something in return for their
agreement with you:
Susie, I would like to make a deal with you. Let me set up a KM pilot in your
part of the business, and I guarantee you a 10 per cent improvement in your
results within three months.
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Your ability to use this approach depends very much on your confidence
and ability to offer something in return. To maintain trust, make sure you
deliver on any promises made!
Favour asking – simply asking for something because you want or need it:
David, I really need a favour. I need an area of the business to set up a trial
Lesson Learning System, and your department would be perfect. Can you help
me?
This tactic works well only when the other person cares about you or their
relationship with you. If used sparingly, it is hard to resist, but be aware you
may have to pay back the favour at some point.
Using silent allies (aka social proof) – using the fact that others are getting
value from KM as an argument in its favour. Social proof consists of sharing
stories of people, as similar to your ‘buyer’ as possible, who are using KM
and gaining benefits as a result. This is the ‘voice of the person on the street’
you see in TV commercials endorsing a product. The reason the advertisers
use this approach is because people are influenced by such stories. On a deep
subconscious level, people who are uncertain about a product will use the
‘person on the street’ as an indication that they will get value from the
­product.
This technique works well with the 60 per cent audience segment that
doesn’t care about KM for its own sake but might be convinced by benefits
other people got:
Here is one of our engineers talking about how KM helped him deliver his
project ahead of time, by giving him immediate answers that helped him solve
his problems.
You can use social proof to support KM as follows:
●●
●●
●●
●●
Begin conducting trials and ‘proof-of-concept’ studies of KM in-house,
with your most willing advocates (see Chapter 22).
When the trial is a success, ask the advocate to tell their story on camera.
Record a short YouTube-style video story along these lines – ‘This was
my problem, I tried KM as a solution, this was the benefit I got.’
Use these videos widely – embedded in PowerPoint, on the company
Intranet, in your KM introductions etc, and as part of your KM
communication programme (Chapter 19).
Influencing the Stakeholders
Tip
View each success in KM, no matter how small, as an opportunity to gather
social proof. Keep a video camera with you (luckily most digital cameras,
smartphones and tablets can record video) to record the voice of the
‘person in the street’ describing what KM delivered for them.
Invoking authority – appealing to a rule or principle.
You must hold your lessons-learned meeting – it says so in the project
procedure.
This technique is one you use late in the roll-out programme to convince the
20 per cent of laggards, once you have the support of senior management,
when the KM policy is in place (see Chapter 23), and when KM has become
a clear expectation. You can make excellent use of a statement or short
video from your chief executive as a way of invoking authority. BP, for example, made very wide use of a key quote from the chief executive at the
time, John Browne, to support the expectation for KM: ‘Our philosophy
should be fairly simple: every time we do something again, we should do it
better than the last’.
Forcing (‘do it or else’). The best example of the use of this tactic in KM
comes from Bob Buckman, then CEO of Buckman Labs, with his statement
that ‘the people who engage in active and effective knowledge sharing
across the organization should be the only ones considered for promotion’
(Buckman, 2004, p. 145). This is a technique that senior management can
use on your behalf, and that may be needed to remove the last few vestiges
of KM non-adoption late in the roll-out phase. Obviously this tactic cannot
be used until KM has become fully adopted and fully embedded, when
managers and knowledge workers alike are completely convinced of its
value.
Tip
Before trying these techniques on your stakeholders, practise on the KM
team and KM champions until you (and they) have a repertoire of
influencing tactics that can be used with different people.
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When to use the influencing techniques
Figure 18.2 shows when to use the various influencing techniques. Reasoning,
inspiring and question asking are useful at any stage, but they are going to
be particularly important in the early stages of implementation, and when
working with senior management. Deal making, favour asking and cosying
up come into their own when trying to influence middle managers to host a
KM pilot. The use of social proof/silent allies is particularly important during the roll-out phase. Invoking authority and forcing can only be used later
on, during or after roll-out, once KM has become a clear corporate
­expectation.
Figure 18.2
When to use the different influencing techniques
Senior
management
Reasoning
Middle
management
Deal making,
favour asking,
cosying up
Inspiring
Asking questions
Knowledge
workers
Strategy phase
Piloting phase
Silent
allies
Invoking
authority
Roll-out phase
Forcing
Post roll-out
Tip
Conduct an after-action review after each ‘sales’ conversation. What
worked? Why was it successful? What did not work? Why not? What will
you do differently (or repeat and reinforce) in the next conversation?
Summary
Implementing KM involves working with the stakeholders, systematically
taking them up the buy-in ladder one step at a time, using sales techniques
and influencing tactics. Make sure you are fully aware of these techniques
Influencing the Stakeholders
and tactics, make sure you have practised them and rehearsed your arguments. This is the hard work of KM implementation: changing the hearts
and minds of the key stakeholders one by one, and step by step.
References
Bailey, S and Black, O (2014) Mind Gym: Achieve more by thinking differently,
HarperOne, New York
Buckman, R (2004) Building a Knowledge-Driven Organization, McGraw Hill,
New York
Christensen, C M, Cook, S and Hall, T (2006) What customers want from your
products, Working Knowledge [online] http://hbswk.hbs.edu/item/what-­
customers-want-from-your-products (archived at https://perma.cc/F3P9-NFWZ)
[accessed 30 January 2019]
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19
Culture,
communications
and change
Any KM implementation must understand and engage with the underlying
organizational culture (or in a large organization, subcultures). By culture,
we mean common and widespread patterns of values, attitudes and habits
of behaviour and thought. Because these are habits they are largely automatic, and are reinforced by the frequency with which they are encountered
in other people. This makes cultural traits self-reinforcing and hard to
change. For effective communication and change, it is essential to have a
very clear view of the traits and behaviours that either support or oppose
your KM implementation goals. Once you have this view, you can target the
specific cultural traits that you want to leverage or address, in both your
communications and your change management efforts.
In this chapter we cover:
●●
●●
KM as an agent of culture change;
mapping the current culture – using a dimensions approach or an
archetypes approach;
●●
cultural drivers;
●●
communication and change;
●●
the communication plan.
KM as an agent of culture change
KM requires a supportive culture, yet how do you develop the culture without doing KM? Should you wait for the culture to change, and then start
your KM initiative, or should you start your KM initiative knowing you
have to reshape the culture? Our advice is to do the latter. KM is itself such
Culture, Communications and Change
a powerful agent of behaviour and culture change that there is no point in
waiting for a favourable culture to emerge by itself.
Use the introduction of KM as a programme of culture change through
the following steps:
●●
●●
●●
●●
●●
First map the culture, so you understand the barriers you need to address
and the cultural habits you can work with.
Then look for small areas of the business where the cultural barriers are
weakest and/or the need for knowledge and KM is strongest, and make
these your pilot areas (see Chapter 22).
Deliver success in the pilot areas, then use these success stories in your
communication programme as ‘social proof’ (Chapter 18).
Repeat the last step as many times as it takes for the new cultural habits
to catch hold.
At the same time, lobby your sponsor and steering team to start removing
the institutional barriers to the new culture that you have identified.
Mapping the current culture
Your first step is to understand the current culture, and identify those attitudes that are likely to create barriers to KM behaviour as well as those attitudes and behaviours that may support it (ISO, 2018). There are two main
ways of mapping organizational culture:
●●
the cultural dimensions approach, and
●●
the cultural archetypes approach.
The cultural dimensions approach
The approach of analysing culture into a set of dimensions originated with
two competing management theorists, Geert Hofstede and Fons Trompenaars,
in the 1960s and 1970s (Hofstede, 1984; Trompenaars and Hampden-Turner,
2012). Although both methods were used to build a theory of national cultures, they originated in employee surveys in large organizations, which were
then used to identify distinct cultural traits within those organizations.
In this approach, distinct cultural traits are identified as separate dimensions, and each dimension is presented as a scale with opposing traits at each
end (see below). A representative sample of the target audience are surveyed,
usually through a questionnaire, to find out where they score on each ­cultural
dimension, and the results are aggregated to form a cultural profile for the
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target group. As with any framework, the dimensions you select depend on
what aspects of culture you are interested in exploring. In our case, we are
not interested in national cultures, we are interested in cultural traits that affect learning and knowledge use in organizations. We have identified 10 potential dimensions to an organizational learning/KM culture, listed below:
Open vs defensive. The extent to which people feel comfortable having their
performance (including mistakes) analysed for learning purposes. The
negative aspect of this is defensiveness – the sort of behaviours you see
developed in a ‘blame culture’.
Honest vs dishonest. The extent to which people will filter knowledge and
information when communicating with peers or seniors. This is sometimes
described as ‘transparency’. There is some overlap between openness and
honesty, but dishonesty and defensiveness are recognizably different.
Empowered vs disempowered. The extent to which people feel able to act on
knowledge, independent of approval from their leaders. A disempowered
culture is where you have to ask your manager’s permission to access and
re-use knowledge, or it can be a culture of micro-management.
Learner vs knower. The extent to which people put a value on acquiring new
knowledge as opposed to the knowledge they already hold in their heads.
This distinction is explained well by Maddock and Vitón (2010), who
describe a ‘knower’ culture as one where new ideas are shut down, and a
‘learner’ culture as one which is not only open to new ideas but goes out
of its way to find concepts contrary to its own.
Need to share vs need to know. The extent to which people offer their knowledge
to others rather than keeping it secret. This refers to the level of risk that
people perceive in sharing knowledge with others. ‘Need to know’, ‘for your
eyes only’, ‘top secret’ are all part of the need-to-know culture.
Challenge vs acceptance. The extent to which people seek to understand
why things are the way they are. It is more about intellectual curiosity
than just learning and it encompasses a willingness to embrace innovation
and to challenge the status quo.
Collaborative vs competitive. The extent to which people identify with and
share in the success of colleagues, rather than feeling they are in
competition with them.
Remembering vs forgetting. This is the extent to which people acknowledge
and incorporate the past when making plans for the future and the extent
to which they consciously record decisions, judgments, knowledge etc for
future reference.
Culture, Communications and Change
Strategic patience vs short-termism. This is the extent to which people
consider the ‘bigger picture’ and try to understand how their actions fit
into the broader, longer-term vision for their organization.
Relentless pursuit of excellence vs complacency. This is the extent to which
organizations acknowledge there is always room for improvement.
Organizations most deserving of being called ‘learning’ ones are those
that admit how far they have yet to go.
C A S E S TU DY
A common cultural trait is the ‘not invented here’ syndrome. This is classic
‘knower’ behaviour, indicating that people do not trust knowledge that comes
from others, and if they haven’t invented it themselves, they won’t accept it. One
team leader countered this with what he called ‘no single source solutions’. He
set the rule that he would not accept any solution invented only by the team. He
wanted every solution to come from multiple sources, which meant that the team
had to learn what others had done. This was a simple rule, but he was able to
use it to drive ‘learner’ behaviour and eliminate ‘knower’ behaviour.
The cultural archetypes approach
The archetypes approach, pioneered in KM by David Snowden (Snowden,
2005), involves gathering stories about both positive and negative experiences around knowledge and learning behaviours from groups of around
8–12 people. To get a representative collection of experiences, you will need
to run six to eight workshop sessions with different groups, involving staff
of different profiles and length of service.
After the stories have been gathered, each group reviews its transcribed
stories and tags them for values, attitudes and behaviours, using Post-it notes:
●●
●●
●●
Values describe implicit beliefs in the culture, and may be expressions of
the cultural traits described above.
Attitudes describe the way that people respond automatically to each
other – for example, confrontational attitudes when challenged.
Behaviours describe typical responses to situations and people, and reveal
underlying values and attitudes.
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Collectively, these Post-it notes give a revealing picture of the underlying
culture. After the tagging exercise, the stories are removed, and the participants cluster their Post-it tags by affinity, then each small group will take a
cluster of tags and create a fictional character or persona embodying those
attributes.
Any single session can create 5–15 archetypal characters that are fictional
representations abstracted from the behaviours and traits that occurred in their
stories. This abstraction process is important, because it allows the group to
generalize from specific experiences, and not to point the finger at individuals.
Over the series of focus group sessions, you will find that similar archetypes
emerge, which are clustered and given to an artist for representation, and the
descriptions of the archetypes are consolidated and tidied up (Lambe, 2007).
Typically this exercise will identify 10–15 archetypes that collectively
represent the dominant cultural behaviours of the organization. These archetypes are very context rich – behind them are numerous example stories
of how this pattern of behaviour plays out in practice.
For example, a common archetypal behaviour we have encountered is
called ‘the squirrel’, which represents the behaviour of building a private
hoard of all the information and knowledge resources they need to do their
work. The squirrel is hesitant to share this because, while it works for their job
duties, they are not sure whether it is appropriate for other colleagues, fearing
it might create issues that will ‘bounce back’ and give them problems later.
Over several years, we have identified archetypal behaviours that occur
across many different organization types, and we have created a set of cultural archetypes cards (available at http://www.straitsknowledge.com/
store_new/organisation_culture_cards/). With these, a less time-intensive
approach can be adopted, where a sample of the different employee groups
selects cards for patterns of behaviour they recognize. The results are aggregated, and the 10–12 most frequently selected cards are taken to represent the cultural profile of the organization. However, while very rapid, this
method lacks the contextual richness of the background stories that give
specific examples of how these behaviour patterns work in practice in that
organization. To mitigate this, you can run short focus groups just sharing
stories on the most frequently recognized archetypes.
Which method should you use?
Both approaches have strengths and weaknesses. The dimensions approach
is highly structured and focuses on known factors that affect knowledge
Culture, Communications and Change
sharing and learning in organizations. It is also fairly easy to run, analyse
and draw high-level conclusions from, and it provides a baseline to measure
cultural behaviour changes in future surveys. However, it may not capture
unusual cultural traits that are not represented in the framework, but that
have an impact on knowledge use in that organization.
The archetypes approach is more labour intensive, but can capture cultural traits that fall outside standard frameworks. The stories that are collected provide rich contextual background to the frequently recognized
­behaviours, and this often helps in analysing the drivers and constraints that
shape the culture, but this method is less appropriate for creating a baseline.
If you have the time and the resources, then a combination of both methods
is ideal and will give you a more holistic picture.
Understanding the cultural drivers
Once you understand the culture, the next step is to understand what drives,
shapes, or reinforces the culture. What drives the squirrel to hoard, or what
results in a high ‘knower’ score? There are often factors such as leadership
behaviours, infrastructure issues, and incentive systems that reinforce the
current culture. For example, the ‘squirrel’ behaviour is often reinforced by
poor quality of information on the common sharing platforms, and a lack
of information governance and quality control.
The dimensions approach also helps to identify potential drivers of change:
●●
●●
●●
●●
●●
Defensiveness is driven by the way the organization responds to failure.
Where failure is punished, either formally or informally, people will be
defensive.
Dishonest behaviour is often influenced by leadership behaviours. Where
leaders model an honest and transparent leadership style, employees
often follow.
Disempowerment is driven by many factors, such as the number of layers
of approval required for new work, or the details of the objective-setting
system, or micro-management of employees.
Knower behaviours are driven by the ways in which people are recognized
and rewarded, particularly the recognition of ‘lone heroes’ and ‘squirrels’.
Need-to-know behaviours are driven by a concern for information security,
and by relying on the individual to be secure rather than the IT system.
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Assessment and Planning
●●
●●
●●
●●
Non-challenging and complacent behaviours come directly from leadership.
If leaders do not challenge the status quo, neither will their staff.
Competitive behaviours are driven by incentives such as ‘forced ranking’
of individual staff appraisals, or by requiring operational units to compete
for bonuses, budgets or prizes.
Forgetting behaviours are also driven by leaders, and reinforced by the
lack of a KM framework that makes remembering easier.
Short-termism is often driven by the incentive system, the prime example
being the hourly billing system employed by many consultancies and
legal firms. Here the pressure to deliver work in the short term acts
against the need to reflect and capture knowledge that can be used in the
long term.
Understanding the cultural drivers helps us to identify the levers of change
that can be built into the change management plan, and this helps in shaping
the messages in the communications plan.
C A S E S TU DY
One of the authors worked with a company trying to introduce best practice
sharing between a number of factories who competed for an annual ‘factory
of the year’ award. The company decided to make ‘best practice sharing’ part
of the award criteria, with each factory required to submit a quota of best
practices. The wily factory staff waited until just before the award deadline,
then issued all their best practices in one submission; early enough that they
counted towards the award, but so late that none of their rival factories could
benefit from reusing the knowledge. Competition therefore trumped
knowledge sharing.
The KM paradigm shift
Behind all of the cultural elements described above is the idea that the culture change involved with introducing KM is a change in attitude – a paradigm shift. We see it primarily as a shift from seeing knowledge as personal
property, to seeing it as collective property, as shown in Table 19.1.
Culture, Communications and Change
Table 19.1
The KM paradigm shift
From
To
I know
We know
Knowledge is mine
Knowledge is ours
Knowledge is owned
Knowledge is shared
Knowledge is personal property
Knowledge is collective/community
property
Knowledge is personal advantage
Knowledge is company advantage
Knowledge is personal
Knowledge is inter-personal
I defend what I know
I am open to better knowledge
Not invented here
If it’s from a credible source, we should
use it
New knowledge competes with
my personal knowledge
New knowledge improves my personal
knowledge
Other people’s knowledge is a
threat to me
Shared knowledge helps me
Admitting I don’t know is
weakness
Admitting I don’t know is the first step to
learning
The idea that the KM culture change is based on a paradigm shift is central
to the communication campaign, and to the use of success stories to paint a
picture of the new attitudes, described in Chapter 18 as ‘social proof’.
Communication and change
Communication is a big part of your change management strategy. It is through
communication that you move the bulk of your organization up the first three
buy-in steps described in the last chapter: first contact, awareness, and understanding. In a 2009 blog post, Seth Kahan described his lessons from leading
KM at the World Bank, and contrasted his first KM initiative (which failed)
with his second (which succeeded, thanks in part to increased communication).
The first initiative was ‘comprised of a few select, world-class thought
leaders who drew on a dedicated budget to design and implement a powerful new tool they hoped would revolutionize the way business was done. We
met in closed meetings, witnessed remarkable demonstrations, and marvelled at the power of the Internet to spread knowledge.’ In other words,
KM was being pushed by a closed group, who were interacting only with
other enthusiasts. Unsurprisingly, nothing came of it.
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The second initiative, with no budget and no resources, ‘told everybody
what we were up to. In fact, we spent a good deal of time in the beginning
figuring out how to tell as many people as we could, as fast as possible. We
even met regularly with our detractors, as their input was sometimes
needed the most.’ The second initiative was being run as a change programme, with communication extending beyond the closed group of supporters, and engaging with everyone. Within two years, it had changed the
organization. Seth identifies seven lessons for KM change based on his
experience (Kahan, 2009):
●●
●●
●●
●●
●●
●●
●●
Communicate so people get it and spread it. As he says, though, this is not
one-way communication, but a conversation that spreads.
Identify and energize your most valuable players. These are your suppor­
ters and KM champions who can help to drive KM forward.
Understand the territory of change. Seth had a method for mapping
stakeholder support, similar to the method we describe in Chapter 18.
Accelerate evolution through communities – at least in large dispersed
organizations. Smaller co-located organizations may find other ways to
introduce and implement KM.
Blow through bottlenecks and logjams. Seth suggests a ‘SWAT Team’
mentality. But please don’t bulldoze people!
Create dramatic surges in progress. Seth suggests special events to drive
progress. Another way is to create energy around celebration of early
successes, and to build on social proof.
Keep your focus when change comes fast. When KM is successful, it can
accelerate alarmingly, beyond your ability to cope.
Tip
Ensure your communications are not written in KM jargon, but use the
language of the business. Terms such as innovation, collaboration,
providing know-how to the front-line workers, finding best practices,
learning from experience and speeding up the learning curve are easier to
understand than terms such as knowledge creation, knowledge synthesis,
tacit knowledge sharing and so on. If you find yourself using terms like
‘tacit’ and ‘explicit’ – think again!
Culture, Communications and Change
The communication plan
Communication is key to a change campaign, and we believe that communication planning needs to be a core component of KM implementation.
Your communication plan should be based on the following principles:
●●
Start the communication plan from day one – the same time as you start
the KM strategy.
●●
Make a member of the team accountable for the KM communication plan.
●●
Ensure ‘communication’ is a line item in your KM budget.
●●
●●
●●
●●
●●
Identify your main stakeholder groupings and the main communications
channels and which messages are appropriate for each one.
Draft a ‘simple message’ that provides the logical case for KM and also
paints the vision (thus covering the reasoning and inspiring tactics
described in Chapter 18).
Address the cultural drivers directly in your communications, using plain
language.
Create a standard communication pack, for example a standard set of
PowerPoint slides and videos, which all members of the KM team and all
KM champions can use.
Brand your communications with a logo and strap line. Consider the use
of collateral such as mugs, corporate calendars, mouse pads.
●●
Ensure communication to ‘all staff’ happens at least quarterly.
●●
Build an internal mailing list or social media channel.
●●
●●
●●
●●
Ensure communication to the most important stakeholders is face to face,
using the influencing techniques described in Chapter 18.
Communicate your plans, even if the details are not yet clear.
Until any early wins are demonstrated, all widespread communications
should be internal within the organization, and should focus on the first
buy-in steps of first contact, awareness and understanding.
As soon as you have some successful proof-of-concept exercises, the
communication campaign should use these success stories to deliver
social proof, and you should begin communicating outside the organi­
zation so that external perspectives can be brought in to reinforce your
internal messages.
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Tip
Develop distinct communication channels and messages for each major
stakeholder group. You need to balance the expectations of the senior
business managers with the expectations of the knowledge workers. These
two customer groups may have different expectations and requirements
from KM that need to be taken into consideration, and they certainly have
different value propositions. Your communication channels therefore need
to communicate ‘what’s in it for us’ both for the senior managers and for the
knowledge workers. There may be other stakeholder groupings as well,
such as the company experts, or the customer-facing staff. Think about the
best channels and messages for each.
Summary
Shortly after Michael McCurry, Clinton administration press secretary, left
the White House, a writer for the Harvard Business Review asked him what
he says when people ask him how to become better communicators. ‘Know
what you’re trying to say and say it precisely and simply,’ McCurry answered. ‘And be committed to telling the story over and over again. You
have to persevere’ (Coleman and Barquin, 2010). Perseverance and repetition are especially important when trying to influence cultural change, because cultural habits are deeply engrained.
Plan your KM communications, make someone accountable, identify
your audiences, channels and key messages, and persevere! Be reassured – if
your messaging is done right, you can never over-communicate.
References
Coleman, C and Barquin, R (2010) The Rule of 151: How to move knowledge
management and business intelligence from margin to mainstream,
BeyeNETWORK [online] http://www.b-eye-network.com/view/12617 (archived
at https://perma.cc/ZUJ6-MVR4) [accessed 30 January 2019]
Hofstede, G (1984) Culture’s Consequences: International differences in workrelated values, 2nd ed, Sage, Beverly Hills, California
ISO (2018) Knowledge management systems – requirements – ISO 30401:2018,
ISO, Geneva
Culture, Communications and Change
Kahan, S (2009) 7 lessons for getting change right, Fast Company, 21 May [online]
https://www.fastcompany.com/1285129/7-lessons-getting-change-right (archived
at https://perma.cc/65K3-TR72) [accessed 30 January 2019]
Lambe, P (2007) Organising Knowledge: Taxonomies, knowledge and organisational effectiveness, Chandos Publishing, Oxford
Maddock, G M and Vitón, R (2010) Knowing vs. learning, Business Week, 17
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knowing-vs-dot-learning (archived at https://perma.cc/ZEZ8-7JUL) [accessed
30 January 2019]
Snowden, D (2005) Stories from the frontier, E:CO, 7 (3–4), pp. 155–65
Trompenaars, F and Hampden-Turner, C (2012) Riding the Waves of Culture:
Understanding diversity in global business, 3rd ed, McGraw-Hill, New York
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20
Preparing
the KM
implementation
plan
When you prepared your first KM plan and budget, as described in
Chapter 8, you had not at that time conducted many of the defining activities such as the knowledge resources audit, the stakeholder analysis, the
culture survey and the outline KM framework. By the time you reach the end
of the planning stage, however, you will have far greater clarity on the challenges you face, the missing gaps in the framework that need to be filled, the
people you will need to engage, the potential business pilot areas, and the
communication programme you will need to run. Now is the time for detailed planning. In this chapter we cover:
●●
how to create the implementation plan;
●●
possible components of the implementation plan.
How to create the implementation plan
In the Mars case study (Chapter 30), Linda Davies describes how she developed an implementation plan for her KM programme following standard business planning practice; detailing costs, resources and proposed activity with a
broad three-year time horizon and a detailed one-year plan, submitted annually as part of the regular business planning cycle. This is a good approach to
take, creating a one-year detailed plan as part of a longer outline plan.
Prepare the detailed plan in an interactive workshop, involving the whole
KM team and as many KM champions as you feel is appropriate. A workshop format utilizes the collective knowledge and organizational experience
Preparing the KM Implementation Plan
of the whole team. Book a meeting room with a long blank wall, and line
this with a long roll of paper. Bring a large supply of Post-it notes. Mark the
months for the first year along the top of the paper, followed by the quarters
for the two subsequent years. Use one colour of Post-it note to mark the
main milestones for KM implementation. These might be, for example:
●●
strategy approved (if approval has not yet been given);
●●
implementation plan approved – start of piloting;
●●
end of piloting – approval for roll-out;
●●
end of roll-out.
Then begin to identify, through discussion or brainstorming, the main tasks
you will need to perform to reach each of these milestones. A list of possible
tasks is provided later in this chapter. For each task, mark down on a separate Post-it note (one per task):
●●
●●
●●
the duration of the task;
the number of working days of effort it will take to do the task (effort is
not the same as duration – a task might take a month, but only require a
few days’ work during that month);
the resource you will use to do this task – for example a KM team
resource, an external resource like a consultant or contractor, or a KM
champion.
Put these tasks on the papered wall in rough order. Ask the attendees at the
meeting to review the set of tasks and wherever necessary:
●●
●●
Move tasks so that they follow other tasks on which they depend (for
example, the task of delivering the first internal KM training course needs
to come after the tasks of creating the training material and publicizing
the course). Draw lines between dependent tasks.
Add new tasks which should be on the wall and aren’t (for example
presenting the first KM engagement workshop can’t be done until the
communication plan is completed, and the engagement slide set created).
Once you have all the tasks on the wall and have agreed them, photograph
the wall to create a record, collect the Post-its and close the meeting. The
tasks then need to be moved to a spreadsheet or a project management tool.
You may have your own standard project-planning template, but we present
one here that works well.
Create a spreadsheet with rows for tasks and columns for weeks of the
year, as illustrated in Figure 20.1. Mark in the main holidays such as
213
214
Assessment and Planning
Christmas, New Year or Eid. Place the tasks on the rows, clustering them
into major groups. Where you have two types of resources assigned to a
task, for example a KM training course delivered by an external consultant
and attended by the internal KM team, enter this as two rows, one for each
resource. Then place the number of days this resource will be working on
this task into the relevant week. For example, Figure 20.1 shows that an
external resource (Ext) will spend 5 of 10 allocated days in week four providing KM training, which will be attended by the KM team.
A sum of the horizontal rows determines the total working days spent on
each task (which should agree with the working days estimate on the Post-it
notes), while a sum of the vertical columns gives the total working days for
each week.
Plot the working days per week onto a chart to visualize the resource
requirements, and identify tasks that need to be reassigned or rescheduled in
order to smooth out the resource. An example of this is shown in Figure
20.2, where the required days per week are plotted for three resources: the
CKO, an external consultant, and the internal KM team. You can see periods
(for example in Week 5) where the CKO will be overloaded, working more
than five days per week, so some of the CKO tasks need to be assigned to the
KM team members or to the consultant. The resource requirements from the
KM team are up to 15 days per month and will rise higher once the CKO
tasks are reassigned, implying a three-person KM team is needed. This particular plan is based on a Middle Eastern example, and the long gap in between weeks 24 and 34 represents Ramadan and the hot summer months.
Once the KM implementation plan is complete, and you have a good
view of the resource requirements, then the next step is to present this to
your steering committee for their review and endorsement.
Tip
Beware of ‘Planner’s Droop’. This is the phenomenon where the first few
months, where you have a good idea what will happen, are filled with tasks,
but the later months are almost empty because you do not yet know what
you will be doing. This can be seen to an extent in Figure 20.2, where weeks
43 through 49 look suspiciously quiet. Revisit the tasks, brainstorm what
else may be needed at this future date, increase the resource requirements,
and if necessary add 20 per cent contingency for the things you don’t yet
know you will need to do.
Figure 20.1
A portion of an example KM planning spreadsheet
Piloting phase
Jan
Task # Task
KM team 1
Appoint internal Chief
set-up
Knowledge Officer and
Knowledge Management team
2
Train CKO and KM team in
knowledge management
tools and techniques
3
Attend above training
4
Ongoing coaching for CKO
and KM team
5
Attend coaching above
6
High-level briefing, in the
absence of a CKO
Feb
Resource Total days W1 W2 W3 W4 W5 W6 W7 W8 W9 W10 W11
Int
4
1.0 1.0
Ext
10
5.0
Int
Ext
20
20
###
Int
Ext
24
4
1.0 1.0 1.0 1.0 1.0 1.0
4.0
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Assessment and Planning
Figure 20.2
A resource plot created from a KM plan spreadsheet
25
CKO
KM team
Consultant
Working days per week needed for KM tasks
20
15
10
5
0
W
1
W
3
W
5
W
7
W
W9
1
W1
1
W3
1
W5
1
W7
1
W9
2
W1
23
W
2
W5
2
W7
2
W9
3
W1
3
W3
3
W5
3
W7
3
W9
4
W1
4
W3
4
W5
4
W7
4
W9
51
216
Week numbers
Potential elements of the KM plan
Below is a list of potential tasks that may appear in the detailed plan. Each
of these tasks is taken from real-life KM implementation plans, but few if
any plans will include all of them. This list simply suggests options, intended
to remind you of tasks you might otherwise overlook.
KM team development
●●
select and appoint team members;
●●
train team;
●●
schedule team meetings and study time;
Preparing the KM Implementation Plan
●●
schedule team attendance at conventions and conferences;
●●
schedule representation on seminars, courses etc;
●●
schedule team learning and knowledge-sharing activities;
●●
manage team knowledge;
●●
create team website;
●●
manage team website;
●●
provision orientation pack for new team members;
●●
scope and publish a tender for consultant support (if needed);
●●
review submissions and interview consultants;
●●
select and brief consultant.
Culture analysis
●●
conduct culture survey;
●●
conduct culture workshops and focus groups;
●●
identify culture drivers, enablers and blockers;
●●
●●
review these with steering team and develop action plan for removal of
blockers;
repeat culture survey.
Stakeholder engagement and communications
●●
create communications and stakeholder management strategy;
●●
conduct stakeholder mapping;
●●
create the communication plan;
●●
decide logo and branding;
●●
define the high-level message;
●●
define more targeted messages;
●●
issue regular communications (eg quarterly);
●●
identify and design promotional collateral;
●●
seek and gather success stories;
●●
publicize success stories internally and externally;
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Assessment and Planning
●●
create engagement material for KM champions;
●●
plan and deliver internal KM conference;
●●
engage one-on-one with key stakeholders;
●●
prepare for, and speak at, external conferences;
●●
prepare and implement awards and recognition schemes.
Training and coaching the knowledge workers
●●
finalize training content:
{{
for each new role;
{{
for the KM champions; and
{{
for general awareness training.
●●
plan and advertise the training;
●●
deliver KM training;
●●
set up KM community of practice;
●●
facilitate knowledge sharing in KM community of practice;
●●
coach and support the KM champions and KM team members.
Framework definition
●●
develop audit tools;
●●
conduct audit of current state (eg knowledge resources audit);
●●
analyse business process and knowledge flows;
●●
identify best-in-class approaches;
●●
identify gaps, opportunities and options to fill the gaps and to meet
opportunities;
●●
define potential roles;
●●
define potential processes;
●●
define potential governance;
●●
review these with steering committee;
●●
finalize first-pass framework.
Preparing the KM Implementation Plan
Technology definition
●●
conduct user survey and/or make observations;
●●
define use cases;
●●
analyse business process and knowledge flows;
●●
conduct technology requirement analysis;
●●
compare requirement against a range of options including ‘do nothing’;
●●
select technology and vendor options;
●●
scope and publish a tender for technology vendors;
●●
review submissions and interview vendors;
●●
select and brief vendor.
Knowledge organization system definition
●●
translate KM implementation objectives into requirements for taxonomy,
metadata and information architecture;
●●
conduct user warrant, content warrant and standards warrant analysis;
●●
conduct facet analysis for taxonomy and metadata;
●●
create use-case scenarios to test the taxonomy and information archite­c­
ture design;
●●
design and test taxonomy;
●●
design and test information architecture design;
●●
integrate search engine with taxonomy and information architecture design;
●●
design and test search interfaces;
●●
define governance and maintenance framework and processes for the
taxonomy, information architecture, search results and content/document
management lifecycle.
Proof-of-concept work (examples)
Lessons learned:
●●
select opportunity for lessons learned;
●●
meet the project managers to agree the approach;
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220
Assessment and Planning
●●
conduct and document the lessons learned session;
●●
train internal staff in lessons facilitation;
●●
conduct trial of lessons management and lessons re-use;
●●
provide continued lessons learned support;
●●
capture learning and stories.
Knowledge retention:
●●
select opportunity for knowledge retention;
●●
meet with HR to agree the approach;
●●
identify priority individuals for knowledge retention and engage with
their line managers;
●●
conduct workshop to create knowledge transfer plan;
●●
facilitate knowledge capture;
●●
facilitate knowledge transfer;
●●
create and review knowledge asset;
●●
capture learning and stories.
Knowledge transfer:
●●
select opportunity for knowledge transfer;
●●
meet the stakeholders to agree the approach;
●●
facilitate the knowledge transfer session;
●●
train internal staff in knowledge transfer facilitation;
●●
continued knowledge transfer support;
●●
capture learning and stories.
Technology test:
●●
select opportunity for technology test;
●●
meet the stakeholders and test user population to agree the approach;
●●
procure evaluation copy of technology;
●●
coach users in use of technology;
●●
facilitate application of technology;
●●
review and monitor usage;
●●
make decision on permanent implementation and integration;
Preparing the KM Implementation Plan
●●
capture learning and stories.
Community of practice (CoP):
●●
find opportunity for community of practice launch;
●●
identify domain, sponsor and potential members;
●●
launch CoP;
●●
develop CoP charter and business case;
●●
coach and support CoP leader in roll-out and growth of community;
●●
work with CoP facilitator on capture of good practices from community
experts;
●●
work with CoP facilitator to define community activities;
●●
work with CoP on appropriate tools and collaboration spaces;
●●
conduct ongoing review of CoP activity;
●●
conduct regular CoP maturity assessment;
●●
capture CoP learning and success stories.
KM pilot projects
●●
select high-grade pilots using experience from proof-of-concept stage;
●●
engage pilot business area;
●●
appoint and train the business lead for the pilot;
●●
scope pilot;
●●
conduct audit and map knowledge of pilot area;
●●
define pilot terms of reference;
●●
define pilot area KM framework working with pilot business area;
●●
finalize roles and responsibilities and governance process;
●●
develop detailed pilot plan;
●●
deliver pilot KM activities;
●●
identify, share and/or and capture knowledge in pilot area;
●●
coach the business lead for the pilot;
●●
coach pilot team members;
●●
create pilot knowledge asset or knowledge base where needed;
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222
Assessment and Planning
●●
monitor and report pilot metrics;
●●
capture learning/success stories/case studies.
Finalizing the framework
●●
●●
●●
●●
review and update the organizational KM framework based on pilot
experience;
collate benefits and develop business case for roll-out;
review roles and accountability statements with steering committee and
HR;
draft templates for KM job descriptions and performance contracts for
KM roles;
●●
review technology plan with steering committee and IT;
●●
review processes with steering committee and relevant business units;
●●
finalize standard templates;
●●
review governance with steering committee and relevant senior managers;
●●
finalize leadership’s KM accountabilities;
●●
finalize role descriptions, accountabilities and performance contract for
the operational KM team;
●●
define KM interfaces with other organizational units;
●●
audit framework against external standard such as ISO 30401:2018;
●●
gain approval for roll-out.
Running roll-out workshops
●●
create manuals and reference material;
●●
create schedule of workshops;
●●
trial roll-out workshop;
●●
improve workshop material;
●●
invite participants;
●●
arrange logistics for workshops;
●●
deliver workshops;
●●
follow-up on workshops.
Preparing the KM Implementation Plan
KM embedding:
●●
draft and agree the KM policy;
●●
draft and agree the KM metrics to be used;
●●
define and agree the KM reporting structure;
●●
define and agree the KM recognition and reward mechanism;
●●
create list of required roles;
●●
update project management guidelines to include new KM processes;
●●
update operational guidelines to include new KM processes;
●●
update reporting guidelines to include new KM governance;
●●
change performance management or rewards and recognition system to
support KM activities.
Reporting and planning
●●
apply KM metrics;
●●
define reporting structure;
●●
monitor and measure KM activity, outputs and outcomes;
●●
conduct annual reporting and planning;
●●
facilitate steering team meetings – preparation and reporting.
Summary
The detailed planning described in this chapter will be needed to secure your
budget for the next stage of KM implementation, and to coordinate your
activities once the plan and budget are approved. In the following chapters
we will look at some of these implementation activities in more detail.
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225
PART FOUR
The implementation
activity
Executive summary
Part Four covers the core of your KM implementation activity. Chapter 21
outlines how to set up a KM champions network to help you in your implementation. Chapter 22 describes how to select and run proofs of concept
and pilot projects, which will help you test and refine your KM framework
in the business. Chapter 23 covers the steps involved in transitioning to a
full KM roll-out, and Chapter 24 gives you a framework for establishing
KM metrics for the business. Chapter 25 provides advice and guidance for
those occasions when your implementation hits obstacles or barriers, and
Chapter 26 covers how to make the transition from an implementation programme to fully embedded KM.
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227
Building the KM 21
champion
network
In this chapter we cover one of the most powerful ways of scaling up KM
activities, and embedding KM awareness and practices throughout the organization: building and empowering a network of KM champions. The
topics we’ll cover are:
●●
what a KM champion is, and is not;
●●
what KM champions are expected to do;
●●
how to identify potential KM champions;
●●
keeping KM champions motivated;
●●
supporting KM champions in their role.
What is a KM champion?
If KM is to be sustainable, KM roles will need to be embedded into the normal working practices of your organization. The KM team remains to manage the KM framework (Chapter 26), while accountability for managing
knowledge itself will become embedded within business roles such as CoP
leaders and facilitators, knowledge managers, and practice owners (described in Chapters 13–16).
There is also a third type of KM role, introduced even before these
business accountabilities are assigned, and which is a vital part of the
culture change programme. This is the role of the KM champion – a
change management role required to broaden the reach of the company’s
KM activities.
228
The Implementation Activity
In the early KM literature, KM champions were mostly described as
s­enior-level activists promoting and advocating KM at a strategic level
(Duffy, 1998; Santosus, 2002; Jones, Herschel and Moesel, 2003). However,
within KM implementation there is also a strong need for operational-level
KM activists, and this is the type of KM champion we describe in this chapter (Abell and Oxbrow, 2001; Bishop, 2002). The content of this chapter is
based on our work in helping clients build KM champion networks, with
input from a 2006 research project conducted with the actKM community
(Lambe and Tan, 2006).
KM champions play an important change management role for KM,
but they differ from KM roles such as knowledge managers and community leaders, in that KM advocacy is often not a part of their job description. They have operational, full-time work obligations and performance
requirements while still acting as unpaid advocates for KM. For this reason it is important not merely to select the right kind of people with the
right kind of attributes, but also to make sure that your performance management policy and framework does not penalize them or impose undue
pressure on them.
What KM champions do
KM champions have three main roles in support of KM at an operational
level. Depending on the stage you are at and the projects you are rolling out,
their responsibilities can be any mix of these three:
●●
●●
●●
advocacy – spreading the KM message;
support – acting as local department-level representatives for KM
implementation activities, providing coaching and advice on KM issues;
knowledge brokering – linking their department colleagues to knowledge
and information resources outside their immediate context.
Typical activities under each of these three roles might be:
●●
Advocacy:
{{
communicating KM messages to their department from the KM team;
{{
helping to influence stakeholders on behalf of the KM team;
{{
encouraging knowledge sharing and learning behaviours;
{{
leading or facilitating KM awareness sessions;
Building the KM Champion Network
{{
{{
{{
●●
gathering and communicating feedback from colleagues to the central
KM team;
collecting stories about KM impact from within their department.
Support:
{{
acting as KM liaisons between the central KM team and their
department manager and colleagues;
{{
playing a role in KM projects at department level;
{{
coaching colleagues in KM-related duties;
{{
facilitating KM activities such as after-action reviews or peer assists;
{{
{{
providing feedback on the usefulness/impact of KM initiatives at
department level;
proactively providing ideas and suggestions for new initiatives or
improvements to KM processes and tools;
{{
identifying potential proof-of-concept exercises or KM pilots;
{{
mentoring and supporting new KM champions;
{{
●●
being a reference point for clarification and explanation of KM activities;
representing their department in KM initiatives planning, review and
needs analysis.
Knowledge brokering:
{{
{{
{{
{{
networking with other KM champions;
identifying major knowledge and information needs in their own
department and seeking out resources that will address those needs;
responding promptly to requests for help from colleagues or other
departments;
pointing colleagues towards relevant resources or colleagues when
they mention an information or knowledge need.
How to identify potential KM champions
The attributes of KM champions have a big impact on their effectiveness.
For this reason, it is always better to let KM champions ‘emerge’ rather than
to select and nominate people for the role based on their job function or
technical skills. Because their role can at different times span ‘lighter’ advocacy work and ‘heavier’ implementation work, and because they have a
229
230
The Implementation Activity
strong peer-influencing role, KM champions need to have the trust and confidence of their peers as well as their managers.
Successful KM champions will be:
●●
well established in their work group, knowledgeable about the group’s
activities, and respected by their colleagues;
●●
helpful and approachable to their colleagues;
●●
able to communicate effectively with peers, superiors and subordinates.
A more detailed set of attributes to support each of the three dimensions of
their work is given in Figure 21.1.
KM champions are often identified and nominated by their department
managers, because they will need the support of these managers in the definition, discharge and recognition of their KM-related duties. Before they
make their nominations, managers need to be briefed on the roles the KM
champions will play, the attributes required to be successful in those roles,
and how to properly support their KM champions.
Figure 21.1
Attributes of successful KM champions
Positive,
energetic outlook
Outcome-oriented
Can-do spirit
Advocacy
Support
Drive,
patience,
persistence
Sociable
Big-picture
awareness
Alert to helping
opportunities
Improvementoriented
Knowledgeneeds
awareness
Knowledge
brokering
SOURCE Lambe and Tan 2006, reproduced with permission
Building the KM Champion Network
KM champions will be most effective when their KM role is:
●●
formally and explicitly integrated with their main job role;
●●
a recognized part of the department’s work priorities;
●●
focused on those elements of KM which support the department’s objectives;
●●
embedded in the job-related processes of the organization (such as job
descriptions, performance management, job reviews, and rewards and
recognition mechanisms).
There are two common mistakes in appointing KM champions: appointing
the ‘new kid on the block’, and relying on the ‘overloaded hero’.
The new kid on the block
While newer, younger recruits may have more energy and ideas than longtime staff, they find it harder to operate effectively as KM champions.
Because they may not be familiar with all aspects of the department’s work,
they are usually not well networked and they may not be able to positively
influence their more experienced colleagues.
The overloaded hero
Many departments will have staff members who have all the right qualities
and attributes to be a KM champion, but these staff members are the usual
targets for all new change initiatives. As they take on more and more, they
become over-stretched and sometimes burned out. While it might appear to
make sense to group related change initiatives such as innovation, KM and
quality under one person, the risk of overloading is a serious one.
Maintaining the motivation of the KM
champions
Even positive, informed KM enthusiasts can become intimidated by the
seemingly broad and open-ended duties of being a KM champion. They can
worry about what is expected of them, how this role will affect their ‘normal’ work, and whether they will get the support they need from their managers, and recognition from their organization.
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The Implementation Activity
Here are some of the questions that new KM champions commonly worry
about (these questions are taken from KM champion orientation sessions):
●●
How important is this role to the organization at large?
●●
Will my manager support me?
●●
Will the central KM team support me?
●●
What specifically do you want me to do?
●●
●●
Will I be equipped with the relevant knowledge and skills to be effective
in this role?
How much empowerment do I really have to influence processes, roles
and behaviours in my department?
●●
What is the timeframe of this responsibility?
●●
Do I have a choice? Can I opt out?
●●
●●
●●
Is this over and above my normal job responsibilities? How do I manage
both?
How will I know if I’m doing a good job in this role?
Will I be rewarded or recognized for taking on this additional
responsibility?
Underlying most of these questions is a desire for clarity and detail. Even if
the role appears challenging, you will improve the motivation of the nominees significantly if you can reduce the uncertainty surrounding it. Provide a
clear, specific set of terms of reference, and ideally an appointment letter
from your senior KM sponsor.
Here are some other ways you can help keep the KM champions motivated, brainstormed by KM champions themselves at their orientation sessions. We find this list works well as a checklist to prepare for building a KM
champions network.
1 Reduce uncertainty by being specific, for example about criteria for
appointment, timeframe of appointment, amount of time to be allocated
per week, known duties, key performance indicators, recognition
mechanisms, and available support.
2 Provide immediate, regular, visible support, for example regular faceto-face sharing opportunities between KM champions, and between KM
champions and the central KM team. Provide training on a regular basis.
3 Give them a sense of ownership, for example by allowing them to have an
influence in how their role is defined, to negotiate priorities and balance
Building the KM Champion Network
of duties with their managers, and to discuss their role with other KM
champions and with the KM team.
4 Give them a sense of identity and recognize their efforts, through a formal
appointment, by organizing a kick-off and orientation session, by
communicating regularly with their managers and the senior management
team about the importance of their role, and by collecting and publicizing
stories of their impact and effort.
5 Recognize them for their achievements. If possible, ensure the champions
are recognized through traditional methods in their performance manage­
ment process. If the KM champion role can be made part of their job
description, then provide feedback to their manager about how well they
have played this role. For the best performers, recommend to their line
manager that they receive a bonus, remembering to cite examples of
where they performed particularly well. If the KM champion role is not a
formal part of their job description, then find a way to recognize them
through your centrally coordinated KM activities, for example through a
central awards scheme (Chapter 23).
Tip
Draft a set of terms of reference for the KM champions in your organization,
bearing in mind the implementation stage you are at, and the pilots you may
want to implement. Remember to cover:
●●
Why this role?
●●
Why have we nominated you?
●●
How long is this appointment for?
●●
What are your duties in the next three to six months?
●●
How many hours per week are you expected to devote to this role?
●●
How often will the KM champions meet?
●●
What support will the KM team provide?
●●
What are your key performance indicators?
●●
How will your performance in this role be reviewed?
●●
How should you hand over to your successor?
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234
The Implementation Activity
Supporting the KM champions
There are a number of ways in which the KM team can provide support to
KM champions. We describe five of these ways below.
Train the champions
The KM champions will need to be trained in the skills they need to perform
their role. Certainly you should offer them training in KM-specific skills and
generic skills such as facilitation, but you may also offer them training in
change management and influencing skills.
Provide them with resources to do their job
Much of the KM champion role is communication and advocacy, so they
need access to the communication resources of the KM team. We described
the communication plan and strategy in Chapter 19, and the KM champions will play a key role in this strategy. Give them access to the slidesets,
videos, posters and other communication mechanisms, so they can spread
the word in their own part of the organization. Better still, create a communications pack specifically for the KM champions, to ensure a consistent
message is spread throughout the organization.
Build a KM community of practice
Once KM implementation is over, KM will be an established discipline and
like all disciplines will need its own community of practice (CoP) so the
practitioners can support each other in their KM roles. Kick off this CoP
early in the KM programme and use it as a way to connect and support the
KM champions to become independent champions for KM within the organization, by giving them access to knowledgeable peers, and helping them
feel that they are ‘not alone’.
C A S E S TU DY
One of the authors was the moderator for an organizational KM community of
practice, known as the KMUnity. About 180 KM champions and advocates
shared their knowledge in a virtual workspace, with an email discussion forum,
Building the KM Champion Network
a facilitator, and a website for storing collective knowledge. The conversation
within the community ebbed and flowed but proved to be an invaluable way to
keep alive a sense of purpose around the topic of KM, and to answer the
questions of the KM champions. Some examples: a knowledge manager in
Australia wrote saying he was finalizing his performance contract and
objectives and could anybody assist by describing KM performance
indicators? A supporter in internal audit raised a question about virtual
meetings: did anybody have any experience or guidance to offer? A community
facilitator asked for help in sharing large documents across the world. Many
other similar queries were raised and were quickly answered by others in the
community.
Make the KM champion role a recognized role
in the organization
Work with the champions’ line managers to ensure their KM duties are embedded in job descriptions and subject to performance review and recognition. Work with HR to ensure that their role as KM champions is taken into
account in considering promotion possibilities. Recommend key performance indicators for the role. Gather and publicize stories of KM champion
contributions, so that the organization recognizes this as an important role
for business success.
Hold KM events
Provide a regular rhythm of face-to-face events for the champions, as a way
for them to provide support to each other. At these events the KM champions
can identify and share common issues, offer feedback and ideas, undertake
training in KM-related skills, and consolidate their sense of collective identity
and confidence in their role. This might be a monthly, quarterly or annual
rhythm depending on the size and geographic dispersal of the KM CoP.
The central KM team will play an important part in organizing these sessions, and should be present to share updates and progress with the KM
champions, and to listen to and record their input. While initially the agenda
for such meetings may be quite highly structured by the central KM team, it
is desirable that ownership of the content and structure of the meetings
gradually transfers to the KM champions themselves. This strategy will
more likely produce a vibrant and resourceful CoP, with a longevity that
may outlive the central KM team.
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The Implementation Activity
CA S E S TU DY
Gorelick, Milton and April (2015) tell this story about a regular face-to-face
meeting of local KM champions in BP, told from the point of view of the KM team
representative at the meeting:
It was a mixed group sitting around the small meeting table in Brussels –
mixed not only in terms of nationality but also in terms of understanding of,
and commitment to, Knowledge Management. Some were enthusiastic
converts, already driving forward their own initiatives in the business.
Some were new to the topic, but had heard enough to know there was
some potential. Others were still trying to come to grips with the topic.
These were the members of the Knowledge Management pool for BP Oil
Europe – the major part of BP’s fuels and lubricants marketing business –
and this was one of the monthly pool meetings.
… we were going around the table reviewing what we were doing in our
parts of the business to deliver value through management of knowledge.
Clyde had been sitting quietly in the corner, looking rather puzzled. When
we got to him he spoke up: ‘Look, I'm still not really sure what value there
is in this Knowledge Management stuff. I mean, if my manager asks me to
justify to him the time I spend here with you, what can I reply? Where is the
real business benefit here?’
Nick took a deep breath, ready to trot out the examples and success
stories that he had used so many times to justify expense on Knowledge
Management, but before he could start to speak, the others had already
begun to reply. Richard explained the value that had been generated by
reducing the cost of service station construction in Europe. Sath talked
about how much value could be generated if the different call centres that
we were implementing around Europe could learn from each other.
Someone else mentioned the Peer Assist on leaky storage tanks. Clyde
nodded thoughtfully; yes, he could see the value. He would try a Peer
Assist for himself. Nick thought to himself, ‘These people do not need the
central KM team anymore, they have each other for support.’
Building the KM Champion Network
Summary
In this chapter we have covered the important role of the KM champions in
helping to advocate, promote and support KM in every part of your organization. It’s important to recognize that this is probably a non-specialist
part-time role, and that the KM champions, particularly at the beginning,
will need a lot of support. However, the skills and attributes you need in
your KM champions network are common to many of the skills and attributes you will need in your core KM team. Together with the KM champions
network the core team can form a KM community of practice, to develop
skills, heighten KM awareness, stimulate KM activity, and provide feedback
and ideas on KM implementation.
References
Abell, A and Oxbrow, N (2001) Competing with Knowledge: The information
professional in the knowledge management age, TFPL, London
Bishop, K (2002) New Roles, Skills and Capabilities for the Knowledge-Focused
Organisation, Standards Australia, Sydney
Duffy, D (1998) Knowledge champions, CIO Magazine, 15 November
Gorelick, C, Milton, N J and April, K (2015) Performance Through Learning:
Knowledge management in practice, Routledge, Abingdon
Jones, N B, Herschel, R T and Moesel, D D (2003) Using knowledge champions
to facilitate knowledge management, Journal of Knowledge Management, 7 (1)
pp. 49–63
Lambe, P and Tan, E (2006) Guidelines for identifying, motivating and supporting
knowledge champions, Green Chameleon [online] www.greenchameleon.com/
uploads/KMChampionGuidelinesAS.doc (archived at https://perma.cc/LDX64M5R) [accessed 6 February 2019]
Santosus, M (2002) Underwriting knowledge, CIO Magazine, 1 September
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Trials and pilots 22
The ‘trials and pilots’ stage is where you begin to test KM in the business. In
this chapter we distinguish between two types of test:
●●
●●
The ‘proof-of-concept’ trials where you apply a single KM process or
technology to a single business issue in order to demonstrate that it
can be applied in your organization, and sometimes to deliver a quick
win. A proof-of-concept trial usually lasts a few days, or weeks at the
most.
A KM pilot where you apply a complete (but often simplified) KM
framework to a business problem in order to gain knowledge and create
success stories. A KM pilot can last several months, or even a year.
This chapter covers the following topics:
●●
proof-of-concept trials;
●●
where to look for quick wins;
●●
selecting KM pilot projects;
●●
the ‘minimum viable KM framework’;
●●
delivering KM pilots;
●●
reaching the organizational decision point.
Proof-of-concept trials
In the early stages of KM – potentially even when you are still drafting
the strategy – you may need to deliver a number of ‘proof-of-concept’ trials, to show short-term progress and provide immediate tangible results
so people can see KM in action and understand the value it brings. This
was described in Chapter 2 as the ‘opportunity-led programme’ that
should run in parallel with your strategic programme. These trials are
small interventions with a KM tool or process, so people can see it in action, realize that KM is not all smoke and mirrors, and accept that it can
work in your organization.
Trials and Pilots
As you talk with your stakeholders, you and they may be able to identify
many opportunities to test KM processes and technologies. Suitable opportunities might include the following:
●●
●●
●●
●●
●●
●●
A lessons-capture meeting such as a retrospect for a tricky (or successful)
project. For one of the companies we have worked with this was a project
that had gone disastrously wrong, and they effectively said to us, ‘If you
can get learning from this project, then we will believe what you say
about KM’. We did gather learning – some very powerful learning – and
this opened the door to management support.
A peer assist for a high-profile project. This has been the proof of concept
for many companies – a straightforward demonstration that valuable
knowledge can be shared between project teams, and can make a positive
impact to project plans. In Chapter 34, Tan Xinde describes an early trial
of peer assist in a product development unit.
A facilitated exchange of knowledge on a key topic. In another organization we worked with, the proof of concept was getting experts together
from all over the world to build a company best practice on bidding and
winning large government contracts.
Creating a knowledge asset on a key topic. Another client we worked
with was going through a series of mergers, and compiled a knowledge
asset in the form of a set of guidance summarizing ‘what we have learned
about delivering effective mergers’.
A launch event to kick off a community of practice. One of our clients
was seeking to develop knowledge-sharing behaviours, and a successful
community launch gave them the evidence they needed to convince them
this was worth supporting.
A knowledge retention interview from a departing expert. This has been
the proof of concept for many retention-based KM strategies. Management
want to see what is possible, and they want to be convinced that KM can
generate valuable output.
In each case, you should seek to create two things from the proof of concept.
The first is some valuable knowledge, either exchanged between people, or
captured as lessons or guidance. The second is stories, reaction or feedback
from the people involved, saying, ‘Hey, we tried KM, it was great, it was not
difficult, and it created real value’. This is what we described in Chapter 18
as ‘social proof’.
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The Implementation Activity
CA S E S TU DY
This story, adapted from Gorelick, Milton and April (2015) describes an early
proof-of-concept exercise at the charity Tearfund, conducted by their
knowledge manager, Paul Whiffen. Tearfund had a tradition of careful
planning and consultation and was unfamiliar with a trials and pilots
approach, but Paul was keen to start with some small-scale demonstrations
of KM processes.
One of the key activities of Tearfund – critical to its success and to delivery of
its vision and mission – is providing aid in response to disasters. Learning was
not being transferred automatically from one disaster response project to
another, as disasters in different parts of the world were often attended by
different staff, and had very different characteristics. However, there was huge
potential benefit for increasing the effectiveness of response and therefore
saving human lives, if knowledge could be captured, saved and reused. Paul
chose disaster response as an opportunity to test knowledge capture and
re-use. Paul reports as follows:
There is no doubt that demonstrating the Bangladesh retrospect in the
summer of 1999 was a great thing. It was much better to just do something
and demonstrate to people how simple and yet how powerful these
processes are.
The Bangladesh retrospect was well received by people who attended, and
several lessons were identified and recorded which could be used in future flood
response programmes. However, this turned out to be not just an academic
exercise, because shortly after the retrospect had been completed, the Orissa
cyclone hit India and flooding started there.
Although the Orissa cyclone was a sudden-onset disaster, unlike the
floods in Bangladesh that had developed over a period of weeks, Tearfund
found that many of the lessons from Bangladesh were immediately
applicable to Orissa. The first thing that the Asia team leader did was to look
for the Bangladesh lessons, because they were fresh and applicable. He was
impressed by the process, and became an effective advocate for KM at
management level.
Trials and Pilots
Where to look for quick wins
Delivering business value through a proof-of-concept trial will be easiest
when the trial is based on knowledge pull rather than knowledge push, ie
driven by a specific business need for knowledge. Many companies seem to
start instinctively with knowledge push, and with sharing and replicating
best practices. Seductive though this idea is, it doesn’t deliver quick wins to
the business. You might capture best practices on mergers, for example, but
it may be a long time before another merger, and there may be no short-term
opportunity for knowledge re-use. And even if there is an opportunity, there
may be a ‘not invented here’ barrier to deal with.
Instead, find part of the business that has an immediate problem, and
help them use KM processes to find and acquire knowledge in order to solve
the problem. This ‘pulled’ knowledge will find an instant application and a
willing audience, and there should be little or no ‘not invented here’ reaction
to contest against.
Selecting KM pilot projects
Pilots are larger projects intended to test and refine the KM framework. The
purpose of piloting the KM framework is to:
●●
understand what works (and what doesn’t work) in terms of KM within
your organization;
●●
test the framework and look for ways to improve it;
●●
deliver success stories for future influencing;
●●
gather enough evidence of value that senior management will then commit to the roll-out of KM.
An effective pilot will address a knowledge domain or practice area – one
that could cover many business teams and divisions – rather than covering a
single business project or team. It will therefore test the validity and value of
the KM framework in a cross-organizational setting. Suitable business problems for KM pilots, where better access to knowledge can significantly help
performance, are listed below. Some of these may have been identified during
your strategy stage when identifying the key business drivers (see Chapter 4).
All of these are ‘areas of business improvement’ which KM can address,
rather than an opportunity to apply a single KM tool in a specific situation.
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The Implementation Activity
●●
●●
●●
●●
●●
A business-critical activity which is new to the organization, where rapid
learning will deliver business benefits. If the activity is new to only one
part of the organization, then transferring learning from where it has
been done before may give huge benefits.
Repetitive business activity where continuous improvement is needed,
where KM can help accelerate the learning curve.
Activity which is carried out in several locations, and where performance
levels vary, in which case KM can help exchange knowledge from the
good performers to improve the poor performers.
A business area which is subject to rapid change, where innovation and
rapid learning are critical to survival, in which case KM can help by
providing sharing and learning processes, as well as access to relevant
knowledge bases.
An area of rapid business growth where deep experience and skills need
to be scaled up to deliver on projects and services.
When you start looking around, you will find very many business opportunities for KM piloting. Your ‘opportunity jar’ will soon be full to overflowing, and you will need to find a way to compare and rank these piloting
opportunities to find the most promising. We have a set of ranking criteria
we have been using for about 20 years, which includes looking at the following questions:
●●
●●
●●
●●
●●
If the project is successful, will we be able to measure the value, and so
demonstrate that the pilot has ‘worked’?
Is there strong management support for the pilot, and for KM, within the
potential pilot area?
If we create, capture or share knowledge, is it purely for the pilot team or
can others use it across the business, allowing us to leverage the results
and spread the benefits?
Will what we learn in the pilot allow us to scale KM across the organization?
Finally, is there a high probability of successfully completing the pilot in
the required timeframe and with the resources available (money, staff,
KM support etc)?
Any pilot where you can answer a strong YES to all of these questions will
be a top-ranking pilot, suitable for selection as part of your KM programme.
Trials and Pilots
Tip
Make sure you don’t miss the high-level pilots. Lots of managers assume
that KM is ‘something my staff need’ and that pilot projects will address
routine tasks at low levels in the organization. However, KM is of value at all
levels, and managers are knowledge workers too. When you are proposing
KM pilots, look also for pilots at senior level – pilots that look at divestments
and acquisitions, for example, or business restructuring. Delivering a
high-level KM pilot on areas such as these can deliver massive value, and
also get senior managers on your side by solving their problems for them.
The ‘minimum viable KM framework’
There is a concept in lean manufacturing and in start-up companies known
as the ‘minimum viable product’ (MVP), which is the simplest and easiest
version of the product you can build that delivers customer value. The manufacturer builds and releases (often to a customer subset such as the early
adopters) a simple bare-bones version of a product in order to get customer
feedback, learn about the product in use, get some revenue, and gain experience that will inform the next version of the product.
In many ways, these objectives of an MVP are similar to the objectives of
the first few KM pilots. The first KM pilot can be seen as an early-version
prototype of the full KM framework, released to gain learning and user
feedback as well as to create business value. There is real benefit in releasing
a ‘minimum viable KM framework’ as early as possible in the piloting stage.
‘Viable’ means the framework should be complete, rather than having just
one or two elements. ‘Minimum’ means it should be as simple as possible
while still adding value. You don’t need to wait for the full technology or the
fully documented process – start with something simple and gain learning
and feedback.
For example, if you want to pilot KM in an area of the business where
knowledge needs to be shared between multiple business units you could
take one of two approaches. The all-too-common approach is to introduce
a technology (for example, a micro-blogging platform) and anticipate that
people will start to use it. However, this is neither minimum (this technology
is well developed, with many features), nor is it viable (technology alone is
not a full framework). Better to introduce a simple framework such as a
community coordinator (role) who sets up monthly discussions (process)
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The Implementation Activity
using dial-in conference calls (technology) to discuss an identified agenda of
critical knowledge issues (governance). Once the community realizes this
minimum system adds value, then they can start to build upon it, adding
complexity and sophistication until they have a KM framework that fully
meets their needs. This is exactly the approach taken in the case study below.
C A S E S TU DY
One of our former colleagues was a KM champion in an organization that was
just starting KM. Enthused by the first company KM workshops, he decided to
conduct his own KM pilot. He set up a simple framework with a group of
colleagues who, every 10 or 11 weeks, would hold a telephone conference call
about key operational problems and how to solve them. They called themselves
the Operations Forum. The knowledge sharing that took place attracted more
people to the call from different countries, some of them staying up into the night
to join in. One night the head of operations sat in on one of the calls, and was
excited by the knowledge sharing that he was hearing. He gave his endorsement
to setting up an operations excellence community of practice, supported by a
web portal as a common area to gather knowledge and ask questions. The
community then started to grow, driven by the success stories that were being
delivered, and its successor communities are still working nearly 20 years later.
That first conference call involving 10 people on telephones was the
‘minimum viable framework’ from which a sophisticated community of practice
grew. It proved a much more robust starting point than beginning with a portal
might have.
Delivering KM pilots
The three key roles
There will be three major roles in the pilot project.
The first is that of the business sponsor, who acts as the customer within
the business. They play an active role in setting the direction for the pilot,
providing resources, and agreeing objectives and deliverables. The business
sponsor is likely to be the manager of the business unit hosting the pilot, and
it is crucial that they are committed to the success of the project.
Trials and Pilots
The second is that of the local pilot project manager. This person will be
accountable for delivering the results of the project. It is important that this
role is owned by somebody within the business, so that the project is seen as
internal to the business, rather than something ‘which is being done to us by
outside specialists’.
The third role is that of the KM team member who works closely with
the local project manager in implementing the project and providing the
KM processes, tools and technologies. The KM team member can carry
learning from the pilot project back to the KM team, and may work fulltime on the pilot project, depending on its complexity and scope.
Sequence of activities
The following section describes a generic set of activities within a KM pilot
project.
Scope the pilot to determine the constraints and context. The scoping phase
may take a week or more, as you get to know the nature of the business in
detail. Find out:
●●
the key stakeholders in the pilot part of the organization;
●●
the main business issues which KM needs to address;
●●
●●
●●
the current flow of knowledge within the working practices, its bottlenecks
and hold-ups;
the leverage points for KM;
the business metrics KM will address (you may even conduct a benefits
mapping for the pilot, using the process from Chapter 9);
●●
the current (baseline) level of those metrics;
●●
how well those metrics could be improved with good access to knowledge;
●●
whether there are other initiatives going on in this area which could conflict with KM.
After the scoping phase, the three roles described earlier work together to
develop a terms of reference document for the pilot programme, containing
the following sections:
●●
●●
context – background and a brief introduction to the groups or practice
area conducting the pilot;
stakeholders – list of key stakeholders and their requirements;
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The Implementation Activity
●●
●●
●●
key knowledge topics to be addressed – including a glossary, if required;
KPIs to be impacted, and conditions for success – including an analysis of
baseline metrics, so you know what the ‘pre-KM’ metrics were;
pilot project approach and scope – the approach to be used, the (minimum
viable) KM framework to be applied, and the in-scope and out-of-scope
elements;
●●
deliverables from the pilot – including dates and accountabilities;
●●
implementation plan – tasks, durations and resources;
●●
risks and obstacles to be addressed – including mitigating actions;
●●
resources – funding and manpower.
Introduce the concept of KM. Work with people in the business area to explore what the value of KM might be to them. Run some proof-of-concept
exercises. Discuss the proposed KM framework, and be prepared to adapt
this if necessary, based on feedback. Select suitable and simple KM technology, considering local culture, local practices and local work habits. Identify
and engage, or launch, any communities of practice that will support the
pilot. Use activities such as peer assists to engage people in the community
of practice. Use technology to support community discussion and questionand-answer dialogue. Identify appropriate needs for confidentiality.
Train and coach the team members to do it for themselves. Initially the KM
team member will need to facilitate the KM processes. Eventually this activity can be transferred to the people in the business; the KM champions
perhaps, or the supervisors or project leaders. Tailor the training to the experience of the audience and choose a training style that they are familiar
with. Try to gain access to people at all relevant levels in the organization;
not just the managers, but the factory floor workers, the sales staff, the
craftsmen, etc. Knowledge leadership can occur at any level. Make sure the
KM team provides regular and on-call support until the framework is fully
embedded, but limit your role to support – the people in the business have
to ‘do’ the KM. In particular, you need to continue to support and coach the
local pilot project manager.
Build the knowledge base in cooperation with the team. You will need some
sort of store of explicit knowledge as part of the KM framework. You may
pre-populate the knowledge base yourself to be able to demonstrate the
value, but afterwards hand over construction and maintenance of the
knowledge base as soon as possible to someone within the business. The
more you do for the business, the harder it will be to get them to take over.
Trials and Pilots
Review the project against its deliverables. If all goes well, which it certainly
should, then your pilot project should be on track to deliver its objectives of
significant measurable business value through the management of knowledge. If you conducted a benefits-mapping exercise during the scoping phase
of the project, then this will help you track how things are going and adjust
your focus accordingly. Help the local project manager to deliver the project
on time, on budget, and on specification. Hold periodic reviews, just as you
would with any other sort of business project. Look for evidence that the
project is on track against timeline and budget, that the objectives will be
met, and that the benefits will be delivered.
Monitor and report the delivery of value. If you selected business metrics you
hoped to impact (lower delivery time, higher delivery quality, greater sales
volume and so on) and determined the baseline for these, then you need to
monitor when the business metrics start to improve on the baseline. This
improvement may not be solely due to KM, so you also need to find stories
that connect specific KM interventions with specific business outcomes.
Look for ways in which the project can be used as a ‘showcase’ for other
projects. If the project has gone well and delivered value, you want to be
able to use it as marketing material, or as an example that other projects will
want to follow. Collect as much material as you can that can be used as
‘social proof’, while still giving the business the credit for delivery. This material might include:
●●
●●
●●
●●
a measurement of the value delivered, in hard business metrics (money
saved, cycle time shortened, business created etc);
a written or recorded statement from the business sponsor that ‘KM has
generated real business value, demonstrated by the following business
metrics’;
anecdotes and stories of the value created by the exchange of knowledge,
from people at all levels in the organization. Record these on video as
social proof for your communication and influencing (Chapter 18);
the learning history of the pilot project, told if possible by the local
project manager or business sponsor.
Learn from the pilot project. Hold your own AAR at the end of each stage,
and hold a retrospect at the end of the pilot to capture what you have
learned. Feed this knowledge into the company knowledge asset on ‘implementing KM’.
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The Implementation Activity
Reaching the organizational decision point
If you selected your pilot projects wisely, organized them well and supported them in delivery, you should now have some good case studies of
real business value delivered through the use of KM. Your KM implementation programme has reached the crucial decision point – the decision
whether or not to fully adopt KM as a required discipline for the whole
organization.
This decision is the point of no return for KM, and needs to be taken at
the highest levels in the organization. Firstly your steering committee needs
to be convinced that you have enough evidence from the pilots to support
this decision, then they need to support you visibly in taking this decision to
senior management.
Put together a business case which will be convincing to top management, based on your pilot evidence. Use the value delivered through the pilots to estimate the total value of KM to the organization. For ­example, if
you were able to use KM during the pilot phase to reduce the cost of a
project by 16 per cent, then make an estimate of how much you could reduce the cost of all projects. Maybe it would be a bit much to attempt to
reduce them all by 16 per cent – the pilot project was after all chosen because it was a particularly attractive case for KM application – but what if
you could reduce the project bill by 6 per cent? Or 4 per cent?
Then estimate the costs to the organization in making this reduction.
The costs will include any further spend on new technology, the cost of
the roll-out effort, and the annual cost of a KM operational team. You
do not need to include the costs of the people playing a KM role in the
business, unless you are arguing for the creation of new roles where they
did not exist before, such as full-time community-of-practice leaders or
a full-time lesson management team. You also need to list on the debit
side of the equation any changes that will have to be made to embed KM,
as discussed in the next chapter. These changes may not cost money,
but they may cause disruption, and they will need senior management
­support.
Hopefully this business case will provide the basis for a firm commitment
to KM. If not, then ask the senior management what evidence would convince them that KM was valuable enough to adopt, and then continue piloting until you have gathered that evidence.
Trials and Pilots
Summary
In the trials and piloting phase, KM comes out into the open. The proofof-concept trials and the full business-led pilots are where the knowledge
workers at all levels begin to see KM at work in their own context. The
proof-of-concept trials provide the continual feed of quick wins and demonstrations of progress, while the bigger pilots not only provide the testing
ground for the KM framework (remember to start piloting with the minimum viable framework), they also deliver the success stories and social
proof that will convince the managers and workers alike that an investment
in KM is a wise investment.
Reference
Gorelick, C, Milton, N J and April, K (2015) Performance Through Learning:
Knowledge management in practice, Routledge, Abingdon
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23
Roll-out,
embedding and
governance
We suggested in Chapter 3 that the goal of your implementation programme
should be to embed a robust approach to KM in all elements of the business,
adding demonstrable value to the business and supported by a sustainable
KM culture. This chapter describes what embedding means, and how it is
done.
In this chapter we cover the following elements:
●●
what embedding means;
●●
some examples of KM embedding;
●●
finalizing the KM framework;
●●
governance;
●●
the KM policy and expectations;
●●
rolling out KM;
●●
tracking and reporting progress.
What does embedding mean?
Embedding KM means making it part of normal work, rather than an
­add-on. You do this through embedding each of the four KM framework
elements: roles, processes, technology and governance, in support of the
main knowledge transactions (both push and pull).
Firstly, KM roles and accountabilities must be integrated into the
­organization chart. You will need to introduce new full-time roles or additional responsibilities where needed: for example, lesson management teams,
leaders and coordinators for large communities of practice, practice owners,
Roll-out, Embedding and Governance
information architects, and so on. You will need to change some of the accountabilities of existing roles such as the senior experts, so that they are
held accountable for stewardship of your organization’s knowledge. You
will ensure that these new accountabilities are written into their job descriptions, so they are measured and rewarded for the KM component of their
job, as they would be for any other component.
Secondly, you should write KM processes into the work cycles and work
processes. For example, you might change the project management requirements to include mandatory processes for capture of knowledge at the end of
the project or after key milestones, and mandatory processes for r­eviewing
past knowledge at the start of the project. You might change the rules for
project support, so a project gets no money if it hasn’t done any pre-learning
or knowledge seeking. You might change the product delivery process, so that
product development includes a stage for identifying knowledge gaps, and to
ensure that the product work stream is supported by a knowledge work
stream working in parallel with it (see the case study later in this chapter).
Thirdly, you will need to change the technology suite so that KM tools
are available and used as part of the working toolkit, and integrated into the
existing working tools. As we suggested in Chapter 3, if email remains the
number one work tool in your organization, then link your KM tools into
email rather than requiring people to acquire new working habits. Build
technology additions outwards from existing habits.
Finally, you will need to change elements of your organization’s governance. Make KM part of the company values. Write it into the company
policies. Write a KM policy to be signed off by the senior management team.
Change the incentive scheme to remove disincentives to KM. KM g­ overnance
elements are discussed in greater detail later in this chapter.
Do all of these things, and KM will be fully embedded as part of ‘the way
you work’. However, to make all these changes you will need the support of
senior managers, as described at the end of Chapter 22, and many of these
changes will need to be made and approved at very high levels in the
­organization.
Examples of embedded KM
Two illustrative examples are described here, showing how two of the seven
components of KM described in Chapter 1 – communities of practice and
lesson learning – might be embedded in organizations.
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The Implementation Activity
Indicators that communities of practice are embedded
●●
●●
●●
●●
●●
The organization’s critical knowledge areas have been identified, and are
each owned by senior staff (eg the head of engineering, the head of sales
and so on) who have targets and deliverables relating to the company’s
knowledge capability.
The leaders of the communities of practice report to these senior staff,
and have performance contracts with them, stating how they will develop
the communities.
The community leaders take accountability for the development of the
communities and of the community knowledge base.
They may have a budget which they can spend on community development
and development of the knowledge base.
The communities work through defined processes such as Q&A and
face-to-face knowledge sharing, and are supported by a suite of
collaboration tools such as discussion forums, expertise finders or
wikis.
In such a system, the communities of practice perform a key role in developing the organization’s competence through enabling knowledge sharing and
knowledge building. The community leader can track activity and value
through community metrics, success stories and performance metrics, and
they can report this to the senior staff who have oversight and exercise accountability to the business.
Indicators that lesson learning and learning from
experience are fully embedded
●●
●●
●●
●●
●●
The organization has targets for project delivery (cost, time or quality
targets).
These targets are owned by the head of projects.
A lesson management team reports to the head of projects, and takes
accountability for the delivery of effective lesson learning.
The project leaders are accountable for making sure the project teams
learn before, during and after project activities, re-use previous lessons,
and document and publish new lessons.
These accountabilities are defined in a lesson-learning policy.
Roll-out, Embedding and Governance
●●
●●
Delivery against these accountabilities is measured using standard project
management methods such as stage-gate reviews.
All projects use a common lesson management system, supported and
monitored by the lesson management team.
If this accountability chain works well, the lesson management team can
track the development of effective learning through metrics, and through
improved project delivery (including shortened learning curves for repeat
projects). They report this to the head of projects, who reports against their
own targets and deliverables.
In both of these illustrative examples, KM is given a clear and specific job
to do (‘improve or protect strategic organizational capabilities through
CoPs’, ‘improve company performance through project learning’), there are
individuals who are accountable for that job, and the reporting chain supports oversight, accountability and performance management. The job is
clear, accountabilities are clear, the KM framework is defined, performance
is tracked, and KM is embedded.
C A S E S TU DY
The pioneer in KM for product development is Toyota. Based on their KM
successes in manufacturing, they developed the Toyota product development
system, which is an efficient and effective combination of lean manufacturing
and KM (Morgan and Liker, 2006). More recently this has evolved into the
concept of ‘knowledge-based product development’ (Kennedy, Harmon and
Minnock, 2008; Melvin, 2013). KM expectations, processes and roles are
embedded into knowledge-based product development as follows:
●●
●●
●●
●●
the product development process includes a knowledge gap analysis step, a
knowledge-gathering stage, and a stage-gate meeting to ensure all
knowledge gaps are closed;
a defined set of knowledge products are created throughout the process, in
the form of ‘knowledge briefs’;
accountability for the knowledge briefs is clear and is monitored by the chief
engineer;
the knowledge briefs and a knowledge-based product description called a
check sheet collectively form the knowledge products that accompany the
physical product.
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The Implementation Activity
Finalizing the KM framework
Embedding roles, accountabilities, processes and technologies assumes that
you know what these elements should be, and that you modify the company
structures to include these elements. However, before you can modify anything, you need sign-off from the senior managers of the organization that
your KM framework is acceptable and will become adopted as standard
practice. This is where your steering committee becomes crucial. If it contains the right people, such as the head of HR, the head of IT and the head
of projects, then you are in a good position. They will have been involved in
your steering committee throughout your journey, and so will have a good
understanding of what is needed to bring KM to the next level. However,
you and they still have some work to do, namely, working with:
●●
●●
●●
●●
●●
●●
HR to develop the new job descriptions;
HR to define any changes to the rewards and recognition scheme needed
to remove disincentives for KM such as internal competition or forced
ranking of staff;
the head of projects and the head of operations to finalize new requirements
to be incorporated into the project management and operations management
processes;
the head of IT to add the necessary capabilities to the technology suite;
the functional heads, or ‘heads of discipline’, to develop the ownership
structure for knowledge domains, and to identify the communities of
practice and practice owners;
your sponsor to determine the changes in long-term roles and responsibilities for the KM team itself.
If these core people were not in your initial steering group, this engagement
will take a lot longer and will be a lot more challenging, as you may need to
talk each person through the whole history of KM in order to win them over.
Once all these agreements have been made, then they should be enshrined
in a KM policy.
The governance elements of the KM
framework
In Chapter 1 we introduced the idea that governance is one of the four enablers of KM, and in Chapter 12 we stated that governance is one of the core
Roll-out, Embedding and Governance
dimensions of the KM framework. Chapters 13–16 worked through examples of how governance gets translated into KM activities. Once your KM
framework has been finalized and agreed with the steering committee and
senior management, then you can look at KM governance in a broader
sense. This higher-level governance contains three aspects:
●●
●●
●●
The first aspect is the rules, guidelines and expectations for KM within
the organization, which will be rolled out together with the definition of
roles, processes and technologies, and which may be laid out in a KM
policy document.
The second aspect is performance management for KM, which includes
monitoring and measuring KM activity, and linking it to recognition and
rewards (discussed in Chapter 24).
The third aspect is providing continuing support for the business,
including KM training, coaching, and the provision of specialist services.
The permanent KM support organization is covered in more detail in
Chapter 26.
The KM policy
There are three main reasons why people don’t do KM – they don’t want to
do it, they don’t know what to do, or they don’t know how to do it. The first
is solved through performance management, the last through training. To
address the second reason – not knowing what to do – you need a KM
policy. The policy defines, at a high level, what the organization expects
from its staff in the area of KM. The policy clarifies areas such as:
●●
the importance of KM;
●●
the KM approach to use;
●●
how KM objectives should be set;
●●
the expected level of KM activity and behaviours;
●●
the size of project where lesson learning becomes mandatory;
●●
whether community membership is encouraged/expected;
●●
the rules for document classification and storage;
●●
how the requirements of information security should be balanced with
knowledge sharing.
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The Implementation Activity
As well as clarifying expectations, the KM policy also acts as a visible public
management commitment to KM, and having a KM policy is one of the requirements for compliance with ISO 30401:2018, the management systems
standard for KM.
There is no ‘one size fits all’ approach to KM policy writing. Focus on the
areas where you expect there may be doubts, uncertainty or competing priorities.
Typical elements in a KM policy would be:
●●
purpose and desired outcomes from the policy;
●●
scope of the policy;
●●
concise and clear statement of the policy in one or two sentences;
●●
guiding principles behind the policy;
●●
roles and responsibilities under the policy;
●●
guidelines and examples for implementing the policy;
●●
glossary of key terms and definitions;
●●
how the KM policy connects to other corporate policies.
Tip
When you create the first draft of your KM policy, share it with your KM
champions. Tell them that they will be the first line of support for explaining
the policy to their colleagues, and ask them to brainstorm all the questions
they might be asked. Use the most frequently asked questions as input to
refining and sharpening your draft policy, so that it focuses on issues of
concern to staff and management alike.
C A S E S TU DY
One of the more complete KM policies you can find on the internet is that of
NASA (NASA, 2013). As we will see in the case study in Chapter 31, knowledge is
very important for the success and safety of NASA missions, and they have a
strong corporate commitment to KM, laid out in the policy, which contains the
following elements:
●●
a strong header, ‘Compliance is Mandatory’, which makes the intent of the
policy very clear;
Roll-out, Embedding and Governance
●●
●●
●●
●●
●●
an owner for the policy, namely the Office of the Chief Engineer;
a description of the intent of KM to ‘cultivate, identify, retain, and share
knowledge in order to continuously improve the performance of NASA’;
the responsibility of all NASA staff for ‘retaining, appropriately sharing or
protecting, and utilizing knowledge’;
an identification of critical KM activities to be applied, including learning from
experience and knowledge retention;
the requirement that each NASA organization ‘shall implement continuous
improvement of knowledge management processes’.
Model your KM policy on the style of other internal policies already in existence in your organization, such as the HR policy or the IT security policy.
Make sure that your internal policies reference each other where appropriate, and make sure that there are no inconsistencies or conflicts with existing
policies. Ensure that your policy meets the ISO 30401:2018 requirements
from the start – this will be far easier than having to rewrite it later should
you wish to demonstrate compliance with the standard.
C A S E S TU DY
One of us worked with an organization where the CEO and senior leadership had
endorsed a policy that knowledge and information were to be deemed sharable
by default, unless there was a specific reason to protect it. We discovered the
organization also had a data management policy that stated: ‘Data and
information is only to be shared on a need-to-know basis.’ In the KM policy,
non-sharing had to be justified, and in the data management policy, sharing had to
be justified. We helped the organization resolve this conflict by extending the KM
policy principle to the other relevant policies, while giving clear guidelines when a
particular piece of knowledge, information or data type needed to be protected.
Use the policy to define the minimum acceptable level of KM activity that is
expected of an employee. Do not set the expectation too high – a policy
should be something that people can easily exceed but are required to comply with. Focus the policy on communicating the elements that may not be
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The Implementation Activity
obvious to employees. Find a high-level champion who will own the policy.
In NASA’s case, this is the chief engineer.
KM roll-out
Once the final KM framework has been defined and the roles, processes,
technologies and governance are clear, KM roll-out becomes largely a process of education through communicating, training, coaching, and developing performance support tools and reference materials.
Communicating
The communication programme described in Chapter 19 changes gear as
you enter the roll-out phase. Continue to publish success stories as fast as
you can collect them, but you will also need to:
●●
●●
●●
●●
●●
●●
publicize the new KM expectations and policy;
introduce the new roles (for example by publishing an interview with a
community leader);
explain the new processes and technologies;
give use-case examples of how the policy requirements should be acted
upon;
advertise the training events;
try to get some articles from senior managers to endorse the message that
‘the organization has now committed to knowledge management’.
Training
You will need to provide training at three levels:
●●
General awareness training for the knowledge workers in the organization, introducing the elements of the KM framework, explaining the new
KM expectations, and demonstrating the value that KM can bring to the
knowledge worker. Make the training interactive: one organization we
worked with created a ‘knowledge treasure hunt’ which challenged people to find five key nuggets of knowledge using the new tools, thus giving
people hands-on experience of the tools while showcasing some of the
knowledge content.
Roll-out, Embedding and Governance
●●
●●
Specific training for the people with KM roles – the community leaders,
the practice owners, the process facilitators and knowledge engineers – in
order to give them the skills they need to do their jobs. The different roles
may need separate training: for example, a course on community building,
a course on lesson capture, and so on.
Awareness training for the managers to explain the expectation they need
to set for KM within their teams, and their own roles in modelling and
supporting the KM culture.
Coaching
People with specialist KM roles will need ongoing support. You can provide
coaching and regular check-ins from the KM team, and should also invite
the people with KM roles to join the KM community of practice. As this
community grows in size and activity it should become self-supporting while
also allowing the KM team to monitor the development of KM practice
within the organization.
Developing reference resources
Every new role needs a role description, every new process needs a process
description and facilitator guide, and every new technology needs a manual
that can be easily understood by the users. You need to write these and put
them on a wiki (so they can be continually improved), and potentially also
develop e-learning content for the people who can’t attend face-to-face
training.
Celebrating the successes
Roll-out is the time to begin the regular celebrations of KM within the organization. These could take any of the following forms:
●●
●●
An annual internal KM conference, to bring together the KM champions
and the KM professionals to exchange knowledge, experience and stories.
This can be a powerful event to strengthen the KM CoP, and a good way
to gather success stories and present awards.
For large organizations, an annual knowledge fair to show off the benefits
of KM to the organization at large. This is an opportunity for CoPs,
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The Implementation Activity
networks, and innovation and learning teams to share what they have
achieved through the year, and for knowledge-intensive parts of the
business to show off their wares and contributions. Knowledge fairs can
also be combined with ‘knowledge markets’, where participants are
encouraged to register knowledge gaps and needs, and also areas of
knowledge that they are prepared to share. During the event, ‘requests’
and ‘offers’ can be matched up by topic through the clever use of
noticeboards, nametags, or even software apps.
●●
●●
Some organizations have implemented annual ‘fail fairs’, inspired by the
‘annual failure reports’ first issued by Canadian development organization
Engineers Without Borders in 2011. Major failures that were learning
opportunities for the organization throughout the year are presented,
diagnosed, and the key learnings and follow-through actions are described
and celebrated. While this is not something that all organizational cultures
would embrace, it sends a very strong signal about the organization’s
commitment to learning processes.
An annual collection of success stories, as in the case study that follows.
CA S E S TU DY
The US construction company Fluor started their ‘Knowvember’ campaign in
2001 to collect KM success stories. As Will (2008) explains:
In addition to recognizing outstanding knowledge-sharing behaviours, one of
the primary functions of the campaign is to gather and share ‘Success Stories’
of the specific ways employees have benefited from using Knowledge OnLine
[the Fluor KM framework]. These are intended to emphasize the ease and
benefits achieved from using Knowledge OnLine. For example, one awardwinning story was from a member of the engineering community in South
Africa. He was commissioning a plant and found that a transfer line from a fired
heater was leaking. The cost of having to flare natural gas is approximately US
$120,000 per day; therefore, time was of the essence to obtain a solution. Not
having the expertise available locally, he posted a discussion forum topic to the
piping community with an urgent response time requirement of three days.
Within two days, he received responses from Houston, Haarlem and New Delhi
providing the answers needed to fix the plant.
Stories such as this, shared during Knowvember, act to celebrate success, and
spread the message that knowledge management is both important and valuable.
Roll-out, Embedding and Governance
Tracking the roll-out phase
During the roll-out phase, the purpose of KM implementation is to spread
the KM transformation across the entire organization, while continuing to
add business value. You need to track this roll-out in order to identify areas
still to engage, and to report progress. This tracking not be confused with
the permanent measurement and evaluation system you will put in place
once KM is fully embedded and operational (Chapter 24). There are three
main ways to track roll-out.
The first way is to track the percentage of the organization that has
reached a defined KM level. These might be the same eight levels we discussed in Chapter 18 for measuring stakeholder buy-in, and the aim for the
roll-out phase is to get every part of the business to the ‘Adoption’ level. You
could also track roll-out metrics such as the number of training courses run
in each region, the number of people trained, the number of communities
launched, the number of KM champions and so on.
The second is to collect activity metrics for those elements that cross the
organizational divisions, such as the communities of practice and the
­lessons-learned system. Such metric schemes will be discussed in more detail
in the next chapter.
The third is to track the value added by KM to the business. Although the
crucial moment for demonstrating value was when you made the business
case for KM adoption at the end of the piloting stage (Chapter 22), you need
to continue to reinforce the message that KM adds value. The success stories
you collect at the KM conference and via awards programmes will provide
plenty of material for your communication campaign, and you should also
keep a running tally of the total value. Someone at some time is sure to ask
you, ‘Just how much value has KM delivered so far?’ It would be good to
have an answer ready to hand!
Tip
Be prepared to let go of the ‘KM’ term as KM becomes embedded. In an
organization with fully embedded KM, you don’t hear a lot of mention of
‘knowledge management’. However, you hear a lot about the tools and
processes. Instead of people saying, ‘we must do KM’, you hear, ‘we should
hold an AAR’, ‘we should ask the community’, ‘why don’t we put this on the
wiki’. The conversation is now about the activities and the tools and not about
the system itself, and the term ‘knowledge management’ takes a back seat.
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The Implementation Activity
Summary
The roll-out stage of KM implementation involves finalizing the framework,
deciding the governance elements such as the KM policy, determining how
KM will be embedded in the organization, and then running a large-scale
campaign of communicating, engaging, training and coaching. This stage of
the implementation may take several years for a large organization, but
once this roll-out and embedding campaign is complete, KM has truly become part of the way the organization works on a day-by-day basis.
References
Kennedy, M, Harmon, K and Minnock, E (2008) Ready, Set, Dominate: Implement
Toyota’s set-based learning for developing products and nobody can catch you,
The Oaklea Press, Richmond, VA
Melvin, R G (2013) Knowledge Based Product Development: A practical guide,
CreateSpace Independent Publishing Platform, Scotts Valley, California
Morgan, J M and Liker, J K (2006) The Toyota Product Development System:
Integrating people, process and technology, Productivity Press, New York
NASA (2013) Knowledge Policy on Programs and Projects, NASA Policy Directive
7120.6 [online] https://nodis3.gsfc.nasa.gov/displayDir.cfm?t=NPD&c=7120&
s=6 (archived at https://perma.cc/N55Z-4MP9) [accessed 7 February 2019]
Will, A J (2008) The Institutionalization of Knowledge Management in an
Engineering Organization, Working Paper #40, Collaboratory for Research on
Global Projects, Stanford University [online] https://gpc.stanford.edu/sites/
default/files/wp040_0.pdf (archived at https://perma.cc/3VKJ-7EMZ)
[accessed 7 February 2019]
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Setting up the 24
KM metrics and
reporting
system
A robust measurement and reporting regime is an essential component of
sustainable, embedded KM within an organization, because it supports the
continuing oversight and administration for KM activities, and allows the
future KM operational support team to:
1 know where to support and intervene;
2 report the status of KM to senior management on a regular basis;
3 evaluate the continuing benefits and impact of KM to the business;
4 identify any changes to the framework that might be needed as the
business changes.
In this chapter we cover:
●●
the different kinds of metrics and their purposes;
●●
examples of KM metrics;
●●
KM performance management;
●●
KM metrics reporting;
●●
KM metrics as a learning opportunity.
The different kinds of metrics and their
purposes
There are four main types of KM metrics, and each has a specific purpose. It
is important not to confuse them, for reasons we explain below. Together
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The Implementation Activity
they form an integrated system of measurement for ongoing administration,
learning and governance. The four types are:
●●
activity metrics;
●●
performance (or compliance) metrics;
●●
impact metrics;
●●
maturity metrics.
Activity metrics
The purpose of activity metrics is to monitor KM activity and trends and so
track the level of application of KM processes and use of KM technologies.
Activities might be contributions to an online knowledge base, lessonslearned activities in projects, frequency of community-of-practice meetings,
peer assists, question asking and answering, and so on. Specific examples of
these metrics are given later on in this chapter.
Activity metrics will generally be collected by people with KM roles in
the business such as the community leaders, lesson management teams and
knowledge base administrators, who may create dashboards that show key
activity metrics on a month-to-month basis. The KM team (initially the KM
implementation team, but handing over to the KM operational support
team) should review these dashboards to identify trends that may need attention – either downward activity trends that may need further enquiry and
support, or upward trends that may need some reallocation of resources or
indicate opportunities for further value creation.
Tip
It is natural that specific KM activities will ebb and flow in regular cycles,
so do not be alarmed immediately if some activities seem to trend
downwards. These downticks are simply signals for you to monitor more
closely and check in with the relevant people in the business, but you
should not panic at the first sign. As time goes on, you will start to see how
a natural cycle develops in the metrics, and will become better at spotting
significant shifts that may warrant further investigation and intervention.
KM Metrics and Reporting System
Performance or compliance metrics
The purpose of performance metrics is to ensure you have compliance to
your KM policy, identify areas where staff may need support or guidance,
and spotlight exceptional performance. Performance metrics should relate
to critical non-negotiable compliance essential for the value-add of KM to
the business, and should enable line managers to recognize and reward exceptional contributions. Instances of non-compliance to the KM policy need
to be picked up and addressed quickly, so that habits of non-compliance do
not build up. Hence these metrics need to be built into the business process
monitoring dashboards.
Do not confuse activity metrics with performance metrics. It is a common
mistake to turn non-critical activity metrics (such as number of contributions to the knowledge base, or attendance at community-of-practice meetings) into key performance indicators or targets for employees and teams.
When this happens, staff will go through the motions of completing the
­activities but the quality of the contributions will likely suffer, and your
­activity metrics will no longer represent genuine trends in the underlying
KM activity.
Tip
ISO 30401:2018 requires that cases of non-compliance are identified,
analysed, and corrective actions taken. Handle the instances of noncompliance with your KM policy quickly and sensitively, and investigate
with the relevant line manager what the probable cause of the noncompliance is. Don’t jump to the conclusion that it is an attitude problem. It
may be:
●●
●●
●●
an awareness problem, in which case the staff will need guidance and
support;
a skills problem, in which case they will need training or skilled
assistance;
a prioritization problem, in which case they may need some additional
resourcing.
Deliberate recurring non-compliance, however, may need firmer treatment.
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The Implementation Activity
Impact metrics
The purpose of impact metrics is to enable senior management to assess
the continuing contribution of KM to the business, and they should link
back to the intended benefits and outcomes of KM outlined in your KM
policy. Right from the very beginning of your KM implementation you
will have been communicating the intended benefits of KM to the business.
It is essential that you do not lose track of this once KM has become
­embedded.
Impact metrics can be ‘hard’ in terms of quantifiable benefits to the
business (eg reduced costs, improved sales, improved quality), in which
case they will be derived from specific examples continuously gathered
from your KM activity streams. Impact metrics may also be ‘soft’, in the
form of evaluations from managers in the different lines of business as to
the added value that KM brings to the way that work is conducted. ‘Soft’
evaluation metrics like this can be gathered through surveys, interviews
or focus groups. These mechanisms, if conducted periodically, are also
useful ways to identify opportunities to streamline, enhance or fine-tune
the KM processes or the support that is offered by the KM operational
team.
Maturity metrics
The purpose of maturity metrics is to trace the progress in KM maturity of
the organization over time. This can be done for your organizational culture, for example, or it can be done for an aspect of KM such as communities of practice.
You can monitor the maturity of your culture by conducting regular culture reviews as described in Chapter 19. Here you will not have prescribed
targets but you will be looking for positive trends in the culture. If you see
the emergence of worrying trends this is a signal that you should investigate
further, for example through focus groups. Organizational cultures generally evolve slowly, so biennial or triennial reviews are probably going to pick
up more changes than annual reviews.
Some KM activity streams such as communities of practice also have maturity levels. Wenger, McDermott and Snyder (2002) identified five typical
stages in the lifecycle of a community of practice (potential, coalescing, maturing, stewardship, transformation) and Gongla and Rizzuto (2001) ­developed
KM Metrics and Reporting System
a detailed maturity model based on these lifecycle stages, both of which provide good options for measuring CoP maturity.
The purpose of a maturity model is to be able to track longer-term ‘big
picture’ trends over time. As we discuss in Chapter 27, many maturity
frameworks for KM in general are based on generalized assumptions that
may not hold true for your organization, and should be used with caution
as a means of tracking your own unique circumstances. Similarly to activity metrics, it is important that you do not turn your maturity metrics
into targets – as soon as they become known as targets, then the respondents who are giving you the feedback for the components of your model
will be incentivized to give you indicators that are positive rather than
negative.
Examples of KM metrics
Metrics related to KM can be collected through a variety of mechanisms,
and depending on the elements in your KM framework, you will need to
decide on a core set of metrics and introduce them as part of the roll-out.
Here are some examples of metrics grouped by KM activity streams.
Project KM metrics
These may be collected by the project knowledge manager, by a lesson management team, or by the project management office, and reported to the
head of projects. The key metrics will be as follows:
●●
●●
●●
●●
Compliance with the project-based expectations of the KM framework,
such as the creation of a project KM plan, conducting peer assists, or
holding lesson-capture meetings. The target should be 100 per cent
compliance (performance metric).
Completion of all actions within the project KM plan, again with a target
of 100 per cent compliance (performance metric).
Number of lessons learned activities, lessons added to the lessons
database, and instances of lesson re-use (activity metrics).
Evidence of value added through KM activities in projects, and presented
as success stories (impact metric).
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The Implementation Activity
Community of practice metrics
These will be collected by the CoP leader or facilitator and reported to their
sponsor. Key metrics are as follows:
●●
●●
●●
Community maturity level, reported on an annual basis (maturity metric).
Evidence of community value, delivered through solutions to members’
problems, and presented as success stories (impact metric).
Examples of exceptional contributions to the community, collected for
example through nominations of members or through evaluation of
community activity metrics (performance metric).
In addition, the community leader may collect community activity metrics
such as:
●●
number of community members;
●●
number of active community members;
●●
number of community activities and levels of participation in those
activities;
●●
number of questions asked per month;
●●
number of answers per question;
●●
individuals who make most contribution to community success;
●●
time between question and first answer;
●●
number of other forum posts per month;
●●
number of readers of the community blog;
●●
frequency of articles on the community blog.
Knowledge library/knowledge base metrics
Knowledge base metrics may be automatically generated by your knowledge base software, or they may need to be created manually. They will be
collected by the relevant practice owners or the knowledge base administrator, and may include the following:
●●
●●
user feedback and satisfaction ratings, collected through a user rating
system (performance metric);
evidence of value, gathered through user feedback, and presented as
success stories (impact metric).
In addition, the practice owner or the knowledge base administrator may
collect activity metrics such as:
KM Metrics and Reporting System
●●
number of reads per knowledge asset or knowledge item;
●●
number of comments;
●●
frequency of edits and updates;
●●
number of new items;
●●
most regular users;
●●
individuals who make most contributions to the knowledge base;
●●
re-use rate of knowledge assets;
●●
frequency of searches of the knowledge base;
●●
search success rate.
Metrics associated with the lessons learned cycle
Lesson-learning metrics are often automatically created by the lesson management software, should be collected by the lesson management team, and
should be reported to the head of projects. Metrics may include:
●●
●●
●●
●●
●●
●●
●●
compliance with the lessons learned policy (performance metric);
lessons submitted per month (by project, product line, and/or region)
(activity metric);
number of lessons embedded into procedure vs number waiting to be
embedded (activity metric);
time taken to close lessons (activity metric);
individuals who make most contribution to lesson learning, tracked
through a combination of numbers and evidence of value and re-use
(performance metric);
lesson re-use rate (activity metric);
evidence of value delivered through the lessons learned system, presented
as success stories (impact metric).
KM metrics collected through staff survey
Metrics can also be collected through regular staff surveys. Surveys can be a
good way to assess the maturity level of the organization culture, for
­example by a re-run of the culture survey described in Chapter 19, or by
including a couple of questions on KM culture in annual staff questionnaires. Surveys of managers in the different lines of business can be used to
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The Implementation Activity
gather e­ valuations of the impact of KM upon the business, to complement
the specific examples of impact gathered through other means.
KM performance management
If KM is to become truly embedded into behaviours and culture, it needs to
be linked to rewards and recognition. People who perform well at the KM
aspects of their job should feel that this is recognized, and people who perform poorly should feel that this impacts their rewards. The metrics described above should allow good performers and poor performers to be
identified. KM activity can then be linked to recognition and reward in the
following ways:
●●
●●
●●
●●
All individuals with an accountable KM role (knowledge managers,
knowledge engineers, CoP leaders, process owners, lesson management
team members, knowledge base administrators and so on) should have
this role explicitly documented in their personal objectives, to be reviewed
during annual appraisal and rewarded through the normal means of
salary increments, bonuses and promotion.
KM activity in projects such as lesson review and lesson capture should be
reviewed at project stage gates and reported in project dashboards, and
thus linked to the project manager’s performance. It is worth recalling the
quote from Bob Buckman, CEO of Buckman Labs, which we mentioned
in Chapter 18: ‘The people who engage in active and effective knowledge
sharing across the organization should be the only ones considered for
promotion’ (Buckman, 2004, p. 145). Poor KM performance should
therefore be challenged, as well as good performance rewarded.
It may also be possible to reward KM activity directly. Dora et al (2002)
describe how employees of Siemens Information and Communication
Networks were incentivized to submit tips and hints to the online
knowledge base through the award of ‘premium points’ which could be
redeemed for prizes within a bonus catalogue. However, care must be
taken that such submissions are of high quality, and in Siemens each tip
was validated against a set of agreed criteria.
A KM award scheme can be created and run on a regular basis, to
recognize good KM performance. Non-monetary KM awards should be
given to people who have delivered real value through KM, as in the case
study example that follows.
KM Metrics and Reporting System
C A S E S TU DY
An excellent example of a KM awards scheme is the Conoco Archimedes
awards (Conoco, 2013). This contains the following awards categories:
●●
●●
●●
●●
the Give award for the person or team who shared the knowledge of greatest
value to others;
the Grab award for the person or team who generated the most value through
re-using knowledge from elsewhere;
the Gather award for the community of practice that has generated the most
value through knowledge sharing;
the Guts award for the person or team that has shown the most courage in
sharing lessons from failure.
KM metrics reporting
In addition to defining the metrics, you need to define who will collect the
metrics, and how, when and to whom they will be reported. A typical reporting structure is shown in Figure 24.1.
In this structure the KM operational support team collates metrics supplied by the knowledge base administrator, the CoP leaders, the lesson management team, the projects and staff surveys, and provides a collated report
to the KM steering committee. This report could take the form of a master
KM dashboard or KM balanced scorecard.
Some metrics work on longer reporting cycles than others. Activity metrics
should be collected continuously, but generally reported on and acted on periodically (eg quarterly). Compliance-related performance metrics need to be
picked up immediately at the point where compliance is due, so that instances
of non-compliance can be identified and acted upon quickly. Performance
reporting should be synchronized with the (normally annual) performance
management cycle. Impact reporting should be done regularly as part of the
KM communications programme, and again annually in consolidated form
as part of the business review cycle. Maturity ­reporting may be done at longer
intervals (eg biennially or triennially) since organizational maturity levels
generally take longer periods of time to make significant shifts.
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The Implementation Activity
Figure 24.1
Typical KM metrics reporting structure
KM steering committee
Staff survey
Practice owners
K-base
metrics
K-base
administrator
Survey
metrics
Combined
KM metrics
KM team
CoP sponsor
Head of Projects
CoP
metrics
Project KM
metrics
CoP leader
K-base
metrics
Lessons
metrics
Projects
Lesson
management team
KM metrics as a learning opportunity
Each of the metrics we have described has a different primary purpose:
monitoring activities and trends, identifying performance lapses and excellence, evaluating impact and benefits, tracking progress in maturity levels.
However, they also have a secondary purpose, which is to provide opportunities for feedback and learning to the operational KM support team. KarlErik Sveiby, who developed detailed systems for measuring intangible assets,
believed that metrics provided the opportunity to open up ‘learning dialogues’
around trends and changes in the indicators captured by the metrics. He believed that this was an even more powerful benefit than the opportunities
provided by metrics for control or influencing (Sveiby and Armstrong 2004).
Tip
At least once a year, use the highlights of your activity, impact and
performance metrics as the focus for a learning retrospect with the KM
operational team and any key stakeholders. Focus on the lessons to be
gathered from these highlights and trends. Use the insights gathered to plan
adjustments and refinements to your KM support activities and
KM Metrics and Reporting System
arrangements. These retrospects can also feed useful data to your periodic
KM framework refresh, which is described in Chapter 26.
Summary
Your KM metrics system should provide a systematic and integrated way of
monitoring activities and trends, evaluating impact to the business, key performance issues and examples of performance excellence, and, on a ­longer-term
basis, shifts in the maturity of KM (or aspects of KM) in your organization.
At an administrative level, activity metrics and the trends they show help
the operational KM team identify areas for additional support or further
investigation. Impact metrics ensure that the KM activities continue to support the business, and retain the support of business leaders. Performance
metrics help your KM governance and support the rewards and recognition
processes you have set up specifically for KM. Maturity metrics help you
trace improvements in KM capabilities over longer periods of time. All of
your metrics also provide an opportunity for continuous learning and adaptation in your KM activities.
References
Buckman, R (2004) Building a Knowledge-Driven Organization, McGraw Hill,
New York
Conoco (2013) In the news – 2012 Archimedes Award winners, Conoco Spirit
Magazine, Q2 2013, pp. 54–55 [online] http://static.conocophillips.com/files/
resources/2qtr13_spirit-magazine-1.pdf (archived at https://perma.cc/
7YXR-6LKE) [accessed 7 February 2019]
Dora, A et al (2002) Networked knowledge – implementing a system for sharing
technical tips and expertise, in Knowledge Management Case Book, 2nd ed,
ed T Davenport and G Probst, Publicis Corporate Publishing and John Wiley &
Sons, Erlangen and New York, pp. 74–78
Gongla, P and Rizzuto, C (2001) Evolving communities of practice: IBM Global
Services experience, IBM Systems Journal, 40 (4), pp. 842–62
Sveiby, K-E and Armstrong, C (2004) Learn to measure to learn! Opening keynote
address, IC Congress Helsinki, 2 Sept 2004 [online] https://web.archive.org/
web/20160512180508/http://www.sveiby.com/articles/measuretolearn.pdf
(archived at https://perma.cc/3PGG-B9N2) [accessed 7 February 2019]
Wenger, E, McDermott, R and Snyder, W (2002) Cultivating Communities of Practice:
A guide to managing knowledge, Harvard Business School Press, Cambridge, MA
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Dealing with
bumps in the
road
25
No matter how well framed and implemented your KM implementation is,
it is likely you will run into challenges that are unpredictable or beyond your
control. As we pointed out in Chapter 3, KM implementation is a long and
complex process, and it is vulnerable to objections, misunderstanding, shifts
in leadership priorities, resourcing issues, and breaks in continuity in both
your stakeholders and the core KM team. In this chapter we cover:
●●
dealing with common objections to knowledge management;
●●
four major challenges to KM implementation:
●●
scenario 1: over-enthusiastic support;
●●
scenario 2: death by a thousand cuts;
●●
scenario 3: perpetual reset mode;
●●
scenario 4: the showstopper.
Dealing with common objections
There are a number of common objections to KM that you will hear as you
deliver your implementation programme. It is worth anticipating these and
preparing your replies in advance. Here are the five most common, and how
you might address them.
Objection 1. ‘We do this already’
‘We already have a training programme’, ‘all of this is covered by staff induction’, ‘we have a library that takes care of this’, or ‘we have SharePoint’.
Dealing with Bumps in the Road
These are the objections of someone who wasn’t listening when you explained that KM is not a single tool. You need to explain again how KM is
a framework of people, processes, technology and governance. It’s not training (because KM deals with organizational learning, not individual learning), it’s not staff induction (because learning is for all staff, not just new
staff), it’s not just a library (because KM is as much about conversation as
content, and as much about tacit knowledge as it is about explicit knowledge), and it certainly isn’t just SharePoint.
Objection 2. ‘We tried knowledge management.
It didn’t work’
This is a common objection in an organization that has already unsuccessfully attempted KM, and it’s a valid objection. Why try again? What’s different this time? Your first priority is to understand why it failed last time
(usually this will be due to one of the KM pitfalls listed in Chapter 3), and
then you need to explain how you have learned from the failure, as well as
from successful implementations in other companies, and demonstrate how
your approach will be different this time.
Objection 3. ‘It won’t work here, we are different’
‘It may work in western engineering companies, but we are different. We are
lawyers/non-profit/Venezuelan etc.’ Firstly it is very useful if you have a few
case studies of KM working in a similar context to your own, so you can say,
‘It works at organization X, and they are lawyers/Venezuelans/not-for-profit’.
However, at its heart, KM is about how people work effectively while interacting with and learning from other people, and all organizations are made
up of people who are supposed to be working effectively. Unless they can
argue that their people are really not like other people, their argument doesn’t
hold water.
Objection 4. ‘Our people are too busy for this.
It will take too much time’
Too busy to learn, but not too busy to reinvent wheels, rework solutions,
and revisit old problems? Going back to your business case and ROI analysis for KM, you need to explain that KM is a time-saver that can cut project
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The Implementation Activity
times by up to x per cent, and that it’s the efficient person’s way to work. As
one of my colleagues said, ‘You work surrounded by the knowledge of others, why on earth would you not use it? It will save money and time, it will
make your life easier, and you will do a better job.’ Basically, if people are
‘too busy’, you already have a strong signal that KM is needed.
Objection 5. ‘It’s simple – let’s just do it’
This isn’t really an objection; it’s more of a misunderstanding, but it can
short-circuit the careful preparation, planning and resourcing required for
effective implementation. Certainly KM is simple, but it’s not easy. Getting
people to change the way they prioritize things, and to move from seeing
knowledge as personal property to seeing it as collective property, requires
a significant culture shift, and culture change is never easy. So you need to
acknowledge the enthusiasm of this person, and then explain why you can’t
just ‘tell people’ to do KM – it needs a hearts-and-minds change, and that
requires some effort.
Tip
Get together with your KM champions, and while working on some of your
sales and influencing practice conversations, build a knowledge base of
‘Objections to KM and how to answer them’.
Challenge scenario 1: over-enthusiastic
support
One of us worked with a client where there was a clear business focus, a
well-articulated strategy, and where some early proof-of-concept projects
had been very successful. These successes were used to build enthusiasm and
support at senior leadership level. Soon they had the strong endorsement of
the chief executive who would, at every meeting where an organizational
challenge presented itself, translate it into a ‘knowledge-related’ challenge,
and call on the KM team to pick it up. The team struggled to integrate these
requests into their KM roadmap, which became progressively more complex and unwieldy.
Dealing with Bumps in the Road
The core elements they were working on stalled, and the calls for support
to the middle management layer became increasingly tiresome and were ultimately ignored. Two years later the team found themselves being heavily
criticized by the same chief executive for slipping behind on their roadmap,
and failing to deliver what had been promised. As quickly as he had given
support, he withdrew it, the senior KM sponsor was moved to another position, and the team gradually fell apart.
Reflection
What would you do differently from this team? How would you deal with the
increasing demands that come as a signal of senior-level support for KM?
What this example shows is that while gathering support and buy-in is
critical, especially at senior levels, there can be such a thing as ‘too much’
support, as well as ‘too many’ stakeholders. In another case, an attempt
to involve too many stakeholders with conflicting agendas also resulted in
a disastrous loss of focus (Lambe and Tan, 2003). So while an opportunistic approach can be a powerful one, it must always be connected back
to the business focus. Saying ‘yes’ to every request that comes along is a
recipe for over-extension of resources, becoming stretched on too many
fronts, failure to show results where it counts, and ultimately rapid burnout of the team.
Choose your opportunities carefully, and do not be afraid to say ‘no’ or
‘not yet’. Maintain a portfolio of your implementation activities currently
underway and currently under plan, as part of your live KM implementation plan (Chapter 20). This should include proofs of concept and pilot
projects, what stage they are at, and how they are resourced. Every new request should then be carefully evaluated against three criteria:
●●
●●
●●
Is the request aligned with the objectives set out in the KM strategy and the
aims and objectives of the KM implementation plan (Chapters 4 and 9)?
Does the request meet the criteria for a proof-of-concept or pilot project
as outlined in Chapter 22?
Does your current level of resourcing permit you to take on this work, or
will you need to ask your KM sponsor and steering committee to reevaluate priorities and resources?
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The Implementation Activity
Work through these questions with the person making the request. It will
help communicate the framework within which you are working. If you say
no but they insist that the request be considered, then ask them to help you
with the business case, and take it up with your KM sponsor and steering
committee.
Challenge scenario 2: death by
a thousand cuts
One of us was working with a client (a regulatory agency) to develop a KM
strategy, framework and implementation plan. Much of the most important
work in this agency was case-based, and decisions on cases became precedents for how the regulatory framework would be interpreted in future.
However, cases might take many years to resolve, and there was frequent
turnover of the officers assigned to the case.
Technology was clearly an issue, with personal computers and emails
being the preferred modes of working. Coordination and collaboration
were critical but difficult in such an environment, so technology enhancements became a priority. However, there were also issues around poor technology literacy (which was why the previous technology platform had not
been fully exploited), lack of consistency around case processes and workflows, and lack of clear policy and being held to account by leadership for
following the processes that had been defined.
The leadership team recognized technology enhancement as a risk factor,
and so an integrated plan was approved combining minor technology enhancements, development of policies, a performance management framework, and training in business process alignment. Soon afterwards, the KM
team began running into a series of roadblocks.
The HR group, responsible for the performance management framework,
said it was too stretched to take on the performance management review.
The IT team started building out and extending the technology requirements because they saw the end of life of the current platform coming along
in the next 18 months. The requirements for the IT platform were dramatically expanded and the budget became very large. The CEO left, and in the
subsequent reshuffle, the leadership team got distracted from the policy development work. The KM team watched as the different elements of their
KM framework were cut out one by one.
Dealing with Bumps in the Road
Reflection
How would you deal with this issue? What do you do when some stakeholders
in the components of the KM framework (in this case technology) want to
expand their scope and pace, and others (eg people, process and governance)
claim that they are not ready and want to move slower?
In the absence of progress on the people, process and governance fronts, the
KM team quite rightly decided not to attempt the business process alignment exercise, because this depended on policy and accountability, and on
the availability of an enhanced technology platform. Trying to move on just
one of the fronts would have been fruitless, and would have called the credibility of the KM team into question. The IT team went ahead with their
very large budget request for a more complex platform, but it was refused.
A year later, with no progress made, the issue of the renewal of the IT
platform came up again. The KM team went back to senior management
and reminded them of the interlocking components of people, process,
­governance and technology. The senior management finally decided to act
on all four components.
Sometimes you have to stand firm and keep pointing to the ­inter-dependencies
between the elements of the KM framework. Having a visualization of a framework that shows this clearly in the context of your organization will help to
demonstrate how the combined elements of the framework help the organization achieve its desired business outcomes – in this case, successfully prosecuted
cases, more accurate management oversight of case progress, and much more
effective use of their professional staff’s time.
Challenge scenario 3: perpetual reset mode
One of us worked with a client over a period of about three years, supporting
them through the diagnostics and strategy-building phase of their KM implementation. In that time, the KM leader left and was replaced by ­somebody
with little experience in the company, the whole KM team was gradually replaced, and the CEO of the company also changed. The second KM leader
left to pursue further studies, and a third person was transferred in from
another part of the organization. We discovered that we were ­effectively the
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The Implementation Activity
organization’s own outsourced memory of the KM implementation project,
and had to keep briefing the new incumbents and ­stakeholders on what had
been done before.
Every time there was a major change in personnel, the KM activities and
projects were set back by about six months, despite the best efforts of the
hard-working KM leaders and staff. As change agents, they needed to spend
significant time rebuilding familiarity, trust, and effective relationships with
their various stakeholders and customer groups. This is the kind of work
that cannot easily be transferred from person to person. Rapid turnover in
the KM team therefore significantly slowed KM implementation, as stakeholder relationships needed to be built from scratch again and again.
Reflection
How can you work to protect continuity in the core KM team? How would
you mitigate the impact of losing key people mid-implementation?
The importance of continuity in the KM team and their stakeholders is an
often-neglected feature in KM implementations. In fact, in a global survey of
knowledge managers conducted by Knoco, internal reorganization was the
most cited reason for the abandonment of KM. This is something you should
communicate early to your KM leader and steering committee in the preparation stage when first introducing them to their roles (Chapters 5–7). In the
case of our client organization, they were expecting significant organizational change, and should have incorporated succession planning into their
KM resourcing plan, with job shadowing for key people.
In the event that you unexpectedly lose key people, look to your designated KM appointment holders (Chapters 13–16) and KM champion network (Chapter 21) as potential replacement resources. They are familiar
with the way your organization works, they have seen and understand how
KM is applied in the business, and they will have been building networks
and relationships at least within their own spheres of influence.
To avoid the withdrawal of support for KM because of leadership
changes, you can use the advice in this book to make your KM implementation robust. Each of your proof-of-concept and pilot exercises should be
gathering both evidence and allies in support of the value of KM. When
your evidence base and credibility are pervasive across the organization, it
will be difficult to pull the plug even if the leadership changes.
Dealing with Bumps in the Road
Challenge scenario 4: the showstopper
One of us worked with a large funding agency. In the assessment and planning stage, the team identified a major issue with the way funding policy
knowledge was communicated across the organization. Policies were kept
in large, complex Word documents in a folder in the finance division’s
shared drive, with the frequent policy updates being sent out as circulars
by email to all staff. The policy documents themselves were infrequently
updated, so staff were expected not only to be familiar with the contents
of the policy documents, but also to keep track of which circulars superseded which sections of which policies. This had a big impact on work
effectiveness, with mistakes, re-work, and time spent on making verbal
checks with finance staff. In addition, high staff turnover meant that new
staff were taking up to six months to get up to speed on funding policy
and approvals.
The KM team decided that this would make an excellent pilot project to
demonstrate the value of KM. They mapped out the steps in a single funding process flow and linked each step to the relevant policy sections, along
with FAQs, guidelines, templates, and spreadsheets for making calculations. They identified a wiki tool for hosting and updating the policy directly in easily navigated sections, while email notifications would now just
point back to the relevant updated policy section. The wiki also maintained
the ‘history’ of each section, so past policy positions could be checked. The
team then tested the redesigned system and process on new and recent recruits, and demonstrated clear measurable improvements in helping new
staff to get up to speed.
Then they hit a brick wall. The finance department refused point blank
to adopt the new tool and process. Some of their influential people were
deeply attached to the current method of maintaining policy knowledge,
and they told the KM team to go try the new approach on another area
of the business.
Reflection
What would you have done differently to avoid this situation? How would
you deal with apparently irrational behaviours among critical stakeholders
that are detrimental to the business lines?
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The Implementation Activity
The KM team had clearly failed to get a critical stakeholder on board before
they started the pilot. They had approached the finance department at the
pilot planning stage, and were told to go ahead ‘without disturbing the funding policy people’. They took that as a green light, where it was really passive resistance. The KM team then assumed that demonstration of ‘obvious
business value’ would convince the finance department to make the necessary changes.
Sometimes you will meet behaviours that are apparently irrational when
considered in the context of the business as a whole. People will protect
well-established ways of doing things, even if it compromises effectiveness
for themselves or others. There are two ways of mitigating this:
1 Send the decision up the leadership chain. Outline the business benefits
and seek endorsement and direction from above. Unfortunately this can
normally only be done quite late in the implementation process when you
have a solid evidence base to draw on, and wide and deep support at
senior levels.
2 If this pilot area is crucial to your implementation, then commit to
spending a lot of time with the resisting party. Sit with them, identify the
specific barriers to change, acculturate them to the new tools, hand-hold
them through each single change they need to make, and focus on this
single issue with persistence, patience and sheer hard work. Apply some
of the influencing techniques listed in Chapter 18.
To avoid getting into such a situation, use our suggestions for engaging potential partners early on (Chapter 10). Take a good hard look at all of your
stakeholders when evaluating your different pilot options, as outlined in
Chapter 22. Use the buy-in ladder in Figure 18.1 (Chapter 18) to understand the current level of each stakeholder. Try to anticipate objections and
barriers that may emerge from unexpected quarters.
Summary
In this chapter we have looked at how to prepare for the inevitable objections that will come your way, and considered four types of challenge that
can emerge in a KM implementation. Driving organizational change is difficult, and not everything that should go according to plan will do so. The
approach and framework we have given you in this book should help you
to prepare for these challenges, avoid them, or mitigate them when they
Dealing with Bumps in the Road
happen. Remain calm, stay focused on your course of action, and use your
preparation and planning to steady you when needed.
Reference
Lambe, P and Tan, E (2003) KM implementation challenges: case studies from
Singapore organizations (Singapore: Straits Knowledge) [online] http://www.
greenchameleon.com/uploads/KM_Implementation_Challenges.pdf (archived at
https://perma.cc/N7BR-WMFF) [accessed 28 January 2019]
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26
Transition to
the operational
team
Throughout this book we have stressed that KM is a programme of change.
It requires cultural change alongside the development and implementation
of an organizational framework. The focus on culture change is absolutely
vital if KM implementation is going to succeed. Sometimes that leads people
to think that once the change programme is over, the job is done, and that
KM becomes something that ‘just happens’. They think that everyone will
then be naturally sharing and re-using knowledge, and that the need for KM
professionals, a KM department, or a KM organizational framework will
then disappear.
This is not true. The change programme will deliver an embedded KM
framework, and like any management framework such as quality management, safety management or information management, it needs a small
group to monitor and maintain it on an ongoing basis, as well as to respond
to changes and new challenges in the organization and environment.
The change programme can only be considered complete when the framework is in place and under the care of an operational support team for KM.
Without this operational support team, and an embedded framework, an
organization can all too easily tip back into a pre-KM state or the KM
framework can drift away from changing organizational needs. If either of
these things happen, then the risk is that KM will be declared as another
‘failed initiative’.
In this chapter we discuss:
●●
the decision to close the implementation programme;
●●
the role of the KM team after implementation;
●●
knowledge management refresh and update programmes.
Transition to the Operational Team
The decision to close the implementation
programme
Some years ago we were having a discussion on KM implementation with
an experienced knowledge manager, and he made the point that when
organizations view KM as a project, they can often view it prematurely as
a failure if it doesn’t deliver the all of the designated deliverables at the
­predetermined end date. This ‘start and stop’ mentality is a risk with KM,
because so much of KM implementation is indeed structured as projects
and programmes with defined phases, budgets and timelines. However,
KM implementation activity should not stop until KM has been fully embedded, even if this means extending the project. Moreover, KM activity
will not stop once implementation is complete; it will move to a new
stage.
Making the decision to close the KM implementation programme is the
last in the series of decisions we first introduced in Chapter 2. You should
not stop the implementation project until you have good evidence to support making this final decision, and until you have fully completed the handover to the KM operational support team.
Here are some examples of the evidence you should look for:
●●
●●
●●
●●
KM roles are in place for all major divisions and projects (and, if necessary,
for all support functions);
practice owners are in place for all major areas of business-critical
knowledge, and are already performing their jobs well;
communities of practice are in place and active for all major areas of
business-critical knowledge;
all the main KM processes are in use and delivering value, and training
and reference material is available;
●●
lessons are being captured, documented and re-used for business gain;
●●
the main classes of KM technology are in regular use;
●●
the principles and rules of information architecture, taxonomy and
metadata are being regularly applied to a high standard;
●●
the company expectations for KM are well defined in a KM policy;
●●
there are many convincing examples of KM success stories;
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The Implementation Activity
●●
●●
a re-run of the culture audit (described in Chapter 19) shows a marked
shift towards organizational learning and knowledge-sharing culture and
behaviours;
you have a robust measurement and reporting process in place.
Take this evidence to your steering committee, and make the case to them
either that KM is not yet sufficiently well embedded to transition from rollout to operational state, or that it is sufficiently well embedded, and that
KM implementation can make the transition.
CA S E S TU DY
One of the authors has personal experience of a KM programme that was ended
too soon. In 1999, the KM implementation at BP was just starting its third year
when it was prematurely terminated as a result of massive cost-cutting
associated with the aftermath of the BP Amoco merger (the biggest merger in
history at the time). Many supporting programmes within the business were
wound down, and KM was one of them. The first two years of KM implementation
had been devoted to assessment, proof of concept and business pilots, as
described in Gorelick, Milton and April (2015), and the third year was to have
been the start of roll-out.
The team had the vision of ‘99 in ’99’ – 99 business unit knowledge managers
by the end of 1999 – and were in the process of drafting a KM policy known as
the Knowledge Management Assurance Standard (KMAS). Terminating the KM
programme at the end of the piloting stage meant that success was not
complete, with KM only partially embedded. The existing communities of
practice continued, as did KM within the drilling function, while in other areas
KM died away. KM needed to be reinvented several years later in the major
capital projects area (Gibby et al, 2006) and at the time of writing this book there
is still no consistent application of KM across the whole of BP.
The role of the KM team after implementation
The KM team’s role as described in this book thus far has been to design,
test, roll-out and embed a robust and sustainable KM framework, accompanied by the required changes in behaviour and culture. Once that job is
done, the role of the KM team changes to become one of ongoing o
­ perational
Transition to the Operational Team
support. Roles and responsibilities will change, but the need for KM support
professionals will not disappear.
Here are some of the key elements of that continuing role:
1 They need to support usage of the KM framework. This includes training
people in its use, coaching the KM professionals, running the KM CoP,
launching other CoPs, and maintaining the knowledge asset about KM.
2 They need to monitor and report on the application of the KM framework,
collecting and reporting the metrics described in Chapter 24, including
compliance checks on the KM policy, monitoring activity trends for any
evidence of need for intervention or support, measuring the maturity of
key CoPs, and collecting evidence of value.
3 They need to coordinate any KM performance management, as described
in Chapter 24. This includes running annual awards schemes and events,
for example, or finding other ways to recognize the star performers.
4 They need to continuously improve the KM framework. This is also a
requirement of the ISO 30401:2018 knowledge management systems
standard. This may include improving and updating the KM policy, it
may include bringing in new technology or improving the existing
technology, and it may include adapting the processes and roles as the
organization adapts to changes in its environment. We cover this ‘refresh
and update’ activity in more detail later in this chapter.
5 They may take on specialist roles themselves, such as lesson management
roles, facilitating major lessons capture events, or helping develop KM
plans. If your KM strategy is a knowledge retention strategy, the KM team
may run the retention process (planning, prioritizing, interviewing etc).
6 The KM team will manage any outsourced KM services. If you need to
bring in specialist providers for lessons capture, for example, or for
taxonomy or information architecture services, then the KM team act as
the in-house buyers. This ensures coordination and consistency across the
consuming business groups.
Knowledge management refresh and update
As part of its monitoring and reporting role, the KM operational support
team needs to monitor the application of the KM framework, and look for
ways in which the framework can be improved. If you are seeking to comply
with ISO 30401:2018, the ISO management system standard for KM, you
will need to commit to regular audit and continuous improvement of the
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The Implementation Activity
KM framework (ISO, 2018). Generally the improvements will come through
the addition of new processes, more effective metrics, or the acquisition of
newer and better technology. Occasionally they come from an extension of
the KM expectations. For example, an organization that initially applied
KM expectations only to large-scale capital projects may decide, after a year
or two of successful operation, to extend it to medium-scale capital projects.
Improvements and adaptations may be required as a result of corporate restructuring or changes in the business strategy.
All updates to the KM framework should be treated as new projects, with
a definition phase, a piloting phase and a roll-out phase. Rather than running the risk of continually tinkering with small elements of the KM framework and losing the overall shape and focus on supporting the business,
upgrades and changes should be bundled together into a new version of the
framework to be released as a new project. In Chapter 3 we stressed the
importance of keeping all four elements of the KM framework in balance.
Tinkering at the edges with parts of the framework requires regular sense
checks to ensure that the overall balance is being maintained. New versions
of the framework can be released every few years, separated by periods of
stability, consolidation and usage.
C A S E S TU DY
One of us worked with a client (a large government organization) that had
successfully rolled out a KM framework including all four elements in balance
with each other. After some time, the IT infrastructure underwent a major
overhaul, and the KM team was given the responsibility to project manage first
an intranet revamp, and then the implementation of an enterprise content
management system. Other teams were working on a business process redesign
supported by a business process management system across the entire
organization. As each responsibility was added, there was a clear rationale as to
why this responsibility should be managed as a part of KM. The organization
became so preoccupied with the IT-led project and the activities focused on
explicit knowledge that the balance of KM activities started to suffer badly.
Components and responsibilities were being added to the KM portfolio without
clear consideration of the impact on the shape of the overall KM portfolio and
without maintaining the balance and complementarity between the elements of
the KM framework.
Transition to the Operational Team
Tip
At least once per year (half-yearly if the intensity of change in the
organization is high), undertake with your team a review of KM activity
trends, any significant changes in KM activities in the business, new
requests for support, and responsibilities allocated to the KM team. Map
these to the KM framework and determine whether a formal review and
rebalancing is likely to be needed in the foreseeable future.
Summary
The end of KM implementation should not be the end of KM, nor should it
be the end of a KM team, although their roles and responsibilities will
change. The distribution of competences required within the KM team will
shift, from being project oriented with heavy emphasis on influencing and
change management skills, to more operational competencies and technical
and functional specialities, with an emphasis on tracking and reporting. For
these reasons there should be a clear decision to hand over KM to an operational support team, with a transition management plan and a new team
profile for the KM team, until it is time for the next update and release of
the KM framework.
References
Gibby, P et al (2006) Implementing a Framework for Knowledge Management,
Society of Petroleum Engineers, SPE-101315-PP
Gorelick, C, Milton, N J and April, K (2015) Performance Through Learning:
Knowledge management in practice, Routledge, Abingdon
ISO (2018) Knowledge management systems – requirements – ISO 30401:2018,
ISO, Geneva
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PART FIVE
Deepening and
extending your
KM programme
Executive summary
Part Five covers what happens when KM implementation is over, when you
have fully transitioned to operational KM. It focuses on how your KM programme and KM capabilities can be deepened and enriched. Chapter 27
addresses the ongoing use of KM audits, both internal and external, to
benchmark your KM programme and monitor its effectiveness, and gives
advice on the use of maturity models, KM awards and standards. Chapter
28 covers the learning benefits of working with peers, proactive networking
through associations and conferences, and gives advice on working with
consultants and technology companies, Chapter 29 discusses KM and digital transformation, including Big Data, Machine Learning, and Artificial
Intelligence.
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Working
with external
frameworks
and standards
27
Throughout this book, we have referred to a KM framework as something
that is developed for your organization’s specific circumstances – it is
grounded in your mission and business imperatives, and it is customized to
your organization’s specific strengths, gaps and characteristics. Once your
knowledge management system is in place, you should start to look around
for ways in which you can benchmark your system in order to identify opportunities to improve and evolve your organization’s KM framework. If we
want to compare practices across many organizations, and identify better
practices and improvement opportunities, we need more generic frameworks that can be used as a common reference point and against which we
can measure ourselves. This sounds simple, but it is not.
In this chapter we cover:
●●
the benefits and limitations of generic KM frameworks;
●●
KM maturity models – opportunities and dangers;
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KM awards – benefits and limitations;
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standards development in KM;
●●
using the ISO 30401:2018 KM standard;
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self-audit or external audit?
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The benefits and limitations of generic
KM frameworks
One of the fascinations of KM is its infinite variability. Even organizations
of similar size and characteristics in a similar sector can have very different
KM needs.
This infinite variability, and the context sensitivity of KM, can also be
frustrating. It can lead to a ‘Wild West’ culture where:
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There is no standard way of describing KM practices across the profession,
causing difficulty in comparing similar practices and their relative
performance. For example, in some organizations, ‘community of practice’
means a group of people who meet regularly and share tacit knowledge in
a relatively informal, voluntary setting; in others, it means a digital platform
where a group of people builds an explicit knowledge base against an
explicit charter and defined deliverables.
Vendors can make large claims for their own products without any strong
evidence base to support or challenge them.
Inexperienced practitioners find it impossible to judge between competing
alternatives.
There is a tendency to blindly copy successful practices from elsewhere
without regard for the specific contextual needs of your own organization.
KM teams find it difficult to assess how well they are doing against others,
or to identify valid improvement opportunities.
It is difficult to identify a common skills base for KM practitioners as a
profession, reducing career mobility and guided self-development.
KM as a discipline is seen as constantly reinventing the wheel and
revisiting the same old problems without making progress.
These are the risks of entirely internally driven KM without any external,
common reference point. You might succeed, if you follow the advice in this
book, in building a relatively sustainable KM programme that successfully
addresses known needs and gets management buy-in. Over time, as management teams come and go, and as KM teams come and go, it becomes more
important to be able to assess yourselves against the broader external landscape. If you can do so, you’ll reap the following benefits:
External Frameworks and Standards
●●
●●
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you’ll learn faster about emerging practices and about what’s likely to
work or not work, based on others’ experience;
you’ll be able to communicate your needs effectively and locate suitable
advice or help quickly;
you’ll find it easier to recruit KM specialists with the competencies you
need;
you’ll spot emerging opportunities and risks for your KM programme
much faster.
One aspect of this external assessment is the value of networking and of
building relationships outside your own organization, and we will cover this
in Chapter 28. In this chapter, we will focus on whether an external generic
KM framework can provide a useful reference point against which to measure yourself and others.
Generic KM frameworks manifest themselves in three main ways:
●●
KM maturity models;
●●
KM award criteria;
●●
KM standards.
All of these offer the possibility of being able to compare ourselves against
a broader KM landscape and so leverage the collective knowledge of the
KM community. Each has its distinctive limitations, which we’ll address in
the sections below. All of them have a common limitation, which is that the
field of KM is complex, very diverse in the range of practices and methods
it covers, and very context sensitive. This means that any framework that is
generic enough to be used as a common reference point runs the risk of
being too generic to be useful in practice. Worse, it might lead us to blindly
apply practices that are known to be good in general, but in specific circumstances are unnecessary or distracting.
Our biggest challenge in this area is in bridging the gap between very
generic principles and very specific implementation requirements.
KM maturity models – opportunities
and dangers
A common approach to benchmarking your organizational KM framework
is to self-assess your methods and processes against a published maturity
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model with a clear set of benchmarks, or to hire consultants with a proprietary maturity model who will do the assessment for you. Maturity is indicated by the award of a particular ‘maturity level’. The majority of KM
maturity models have a series of descriptors of various levels of KM maturity which can be measured for a series of factors such as leadership or
technology. The assumption behind this is that an organization will progress
from one level to the next in a smooth maturation process: from level 1,
through 2, 3, 4, to level 5 (or whatever the highest level is).
The analogy, if you like, is that of a child. As children mature, they increase
in height and weight, acquire teeth, and develop a range of skills. Maturation
levels in children are easy to determine based on statistics, and you can use
these to determine if your child is ‘an early talker’ or ‘a late walker’.
There are a few problems with the assumptions behind maturity models
when applied to KM. The first is that the model may have gaps or be based
on inaccurate assumptions. There are many maturity models, for example,
which ignore the issue of governance, and others that include content as a
key component (thereby assuming that knowledge management is basically
content management). Most maturity models make assumptions about the
sequence in which things have to happen, and these assumptions do not
hold true universally. For example, awareness of the importance of KM and
senior management support are taken to be early stage precursors for KM
maturity. However, we have worked in organizations where a successful KM
initiative started and matured ‘in the middle’ of the organization with relatively little support or acceptance from senior leadership. We’ve seen others
where senior leadership support did not translate into successful groundlevel KM. A generic maturity model fails to capture this kind of variation.
Because of its complexity and context sensitivity, not all assumptions hold
true all the time in KM. That means the maturity model itself cannot accurately represent the state of KM in those organizations, nor does it necessarily accurately prescribe the most appropriate interventions to improve KM
maturity. Maturity models are blind to specific contexts and needs.
Secondly, in large and complex organizations, where the organizational
landscape is heterogeneous, a maturity model tends to gloss over or average
out significant differences in portions of the landscape, removing them from
visibility and opportunity for action. It also tends to ignore unique but
­salient factors of the environment being assessed, if those factors are not
already captured in the maturity model.
This means you typically get a ‘flattened out’ view of the maturity level of
the organization, and this conceals the really interesting features from a KM
External Frameworks and Standards
implementation point of view, ie hidden outliers that represent significant
points of leverage, or significant gaps that need to be addressed, or strong
capabilities in one part of the organization that could be the focal point for
transfer to the rest of the organization. Maybe you get the maturity ‘score’
you want, but it doesn’t tell you very much about what would be appropriate or useful to do next, except in very generic ways that may not be appropriate to large segments of the organization.
Thirdly, and following from this, the way we implement KM, as we have
described in this book, is not one of gradual maturation across the organization at large, but of spreading the adoption of a new paradigm. It is more
like a forest fire catching hold than the development of a child. Parts of the
organization, like parts of the forest, may be ‘fully alight’ with KM (your
pilot areas for example) while others have not even started burning. Some
parts might be dry and ready for kindling, some may be damp and effectively fire resistant. To try to measure an average maturity in a case like this
is misleading, just as it would be misleading to say ‘the forest fire measures
an average of 100 degrees’ when parts of it are far hotter (up to 800 degrees), other parts far colder, and some are not yet alight.
Finally, when used in the service of an idealized framework for KM, maturity models can start to be ‘gamed’. If, in responding to a maturity model
questionnaire, I am concerned to make my business unit look good, I will be
inclined to be generous in my interpretation of my unit’s KM practices. The
qualitative nature of many maturity model indicators makes it relatively
easy to do this. An indicator such as ‘KM is aligned with the business planning process’ can be interpreted at very different levels of rigour by different
people, and it is difficult to detect these variations when analysing the responses.
For all these reasons, if anything, maturity models are much better used:
a not for assessment and objective benchmarking, but as part of an
internally driven diagnostic and planning mechanism along with a lot of
independently gathered data, such as we describe in Chapters 11–20 of
this book – where the question is not ‘how mature are we against external
assumptions?’ but ‘what can this external model suggest to us about our
strengths and weaknesses, and which of these areas should we prioritize
based on known needs?’; or
b in homogeneous, well-defined contexts such as communities of practice,
knowledge base development, or expertise transfer, where there are
specific, well-known good practices and reliable precursors that hold
true in most cases.
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Tip
Find a few KM maturity models (there are several freely available ones out
there) and compare them against your KM framework, and how you
perceive your current KM needs and performance. Take the frameworks
themselves with a pinch of salt, simply as a different way of looking at KM.
When you compare in this way, do you gain any ideas or insights into your
own KM practices?
KM awards – benefits and limitations
For many years, the aspiration for the KM programme of countless organizations was ‘to win a MAKE Award’. Inaugurated in 1998, the Most
Admired Knowledge Enterprise (MAKE) Award was conducted by Teleos (a
British research company) to recognize organizations that were believed to
out-perform their peers in using knowledge to create shareholder wealth. In
the absence of other international benchmarking programmes, a MAKE
award (or even nomination) was a way of showing that you had ‘arrived’ in
the top flight of KM organizations.
The global MAKE awards were wound up in 2018, and the Teleos organization ceased operation with the retirement of its founder, Rory Chase.
With his agreement, an international group centred on the Hong Kong
Polytechnic University launched a follow-up award programme called the
MIKE (Most Innovative Knowledge Enterprise) awards in 2019. The criteria of the MIKE Award and the process for evaluation (a modified Delphi
Method based on an iterative cycle of scoring by a panel of experts) are
based on the original MAKE framework, with an increased emphasis on
­innovation. ‘We believe the MIKE Award will serve both as a diagnosis tool
for improving innovations in enterprises, and used for international benchmarking’ (Hong Kong Polytechnic University, 2018).
Gaining an award such as this can be very difficult. The MAKE awards
were based on ‘admiration’ and required organizations to secure nominations from their ecosystem of partners, customers and suppliers. The most
admired enterprises were often those who had been doing KM for the longest, who had built up a strong reputation, and who could secure the necessary levels of support. It was difficult for newcomers to gain the same level
External Frameworks and Standards
of admiration without an intensive campaign of publicity and lobbying, and
few organizations have the resources for this. More so than maturity models, there are incentives in award programmes to gloss over KM shortcomings, and to focus on making organizations look good. They are often seen
as popularity contests.
There are several other KM awards associated with conferences, where
the award becomes a lure to secure paid registrations and attendance at the
conference. Others are associated with membership associations, where access to the award process at a reduced price is a means to secure new
­members for the association. The frameworks used to evaluate the award,
the qualifications and diversity of the evaluators, and the process and c­ riteria
for evaluation are not always transparent or consistent. All of these factors
can distort and invalidate being able to use an awards process for benchmarking and learning purposes.
Now, if your goal in seeking an award is primarily for political benefits, ie
to raise the internal profile of KM, and if you are using other mechanisms for
‘real’ benchmarking and self-evaluation purposes (such as evaluation against
the ISO 30401:2018 standard), then a KM award may well serve its purpose
for you. If you are aware of the capacity for bias in both applying for and
giving awards, if you are diligent in completing the award assessment, if the
award giver has a robust evaluation process and feedback mechanism, and if
you have a plan for how to exploit the learning (and comparison) opportunities afforded by an awards framework, then you may well get some benefit
from it. Our advice is to go into an awards process with clear objectives and
a strong understanding of its limitations and capacity for bias.
C A S E S TU DY
As with a maturity framework, it is perfectly possible for an awards framework to
be used as a genuine self-evaluation and benchmarking instrument, completely
unrelated to gaining the award itself. In 2003, a subsidiary of British Energy used
the MAKE awards database, in combination with the British Standards Institute’s
(BSI) guide to good KM practice, to self-assess and identify improvement
opportunities. They used the BSI guide to identify general improvement areas, and
then they used the MAKE database to identify specific good practices from
winning organizations that they could adapt internally (Carpenter and Rudge, 2003).
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Standards development in KM
The KM community has sought to develop standards for KM for almost all
of its modern history. Part of the motivation sprang from the ‘Wild West’
characteristics of the field that we listed earlier in this chapter. But there
were also commercial interests at stake, particularly in the late 1990s and
early 2000s, where private KM certification companies sought to corner the
KM standards market and thereby establish themselves as authoritative purveyors of KM services (Skyrme, 2002). Some early work from standards
institutions in the UK and Europe shied away from producing prescriptive
standards, and instead developed best-practice guidance documents (Farmer,
2002). While Standards Australia produced a Knowledge Management
Standard in 2005, it deliberately framed it as a non-prescriptive standard for
guidance only (Standards Australia, 2005).
In 2011, the technical committee responsible for the ISO 9001 quality
management standard conducted a worldwide survey across 122 countries.
They discovered a high demand to include a requirement for knowledge
management in an update to the ISO 9001 standard. In September 2015, a
new requirement for the proper management of knowledge as a resource (in
the context of supporting Quality) entered the standard for the first time
(Fry, 2015; Wilson and Campbell, 2016):
7.1.6 Organizational Knowledge – The organization shall determine the
knowledge necessary for the operation of its processes and to achieve
conformity of products and services. This knowledge shall be maintained and
be made available to the extent necessary. When addressing changing needs and
trends, the organization shall consider its current knowledge and determine how
to acquire or access any necessary additional knowledge and required updates
(ISO, 2015a).
Meanwhile, also in 2011, the Standards Institution of Israel had successfully
issued a fully prescriptive standard for KM, written in such a way that it
could be used for measuring and auditing compliance against the standard.
They proposed to the ISO to use this as the basis for an international KM
standard. After consultation among the other ISO member countries, this
proposal was accepted and an international technical committee established,
with mirror committees in several member countries. The outcome of this
effort was the ISO 30401 management systems standard for KM, issued in
late 2018 (ISO, 2018). The process of development and release of this standard was not without controversy, for all the reasons we have explained
External Frameworks and Standards
a­ lready in this chapter. But it succeeded where other standards efforts had
not. Part of the reason was that for the first time, the KM standard was not
based upon a generic framework for how KM should be done at all. Instead,
it was developed as a ‘management system’ standard to a common template
used by ISO for all new and revised management system standards, including quality management, risk management, records management, asset
­management, and so on. This makes ISO management system standards interoperable and easily connected to each other.
The standard is therefore not an attempt to develop a standard approach
for KM. This would be crazy – as we have pointed out, every organization
has to do KM in a way that suits their purpose, objective and context, and
there is no standard way that works for everyone. ISO 30401:2018 does,
however, provide a standard template for developing your own customized
KM framework. It does not tell you what the components of the framework
should be for your organization, nor how to implement the specifics of KM,
but if followed it should ensure that the framework itself is developed in line
with organizational goals, and is complete and well managed over time.
ISO lists the following benefits of the management framework approach
to management system standards (ISO, 2015b):
ISO management system standards (MSS) help organizations improve their
performance by specifying repeatable steps that organizations consciously
implement to achieve their goals and objectives, and to create an organizational
culture that reflexively engages in a continuous cycle of self-evaluation,
correction and improvement of operations and processes through heightened
employee awareness and management leadership and commitment.
The arrival of the ISO 30401:2018 standard helps us move beyond the perception of a quarrelsome ‘Wild West’ with all of its inconsistencies, crosstalking and inability to benchmark, learn and share constructively across
the field. It brings a certain promise of legitimacy. There are other benefits:
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It marks a degree of consensus that for the first time shows promise for
meaningful comparison of practice across industries and organizations.
The interoperability of different management standards means that
different management frameworks can be interconnected and made
mutually supportive.
The consensus on the cycle of activities for managing KM as a management
system provides the possibility for developing meaningful competency
and professional development frameworks for knowledge management.
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The Chartered Institute of Library and Information Professionals (CILIP)
in the UK is working on just that, with its new Chartered Knowledge
Manager programme (CILIP, 2019).
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By using the standard, organizations can hopefully avoid some of the
common pitfalls listed in Chapter 3 of this book; lack of business focus,
the incomplete framework, and the lack of attention to stakeholders are
explicitly catered for in the requirements of the standard.
A service organization that claims, and can demonstrate, compliance with
ISO 30401:2018 may find this an advantage when bidding for work. Where
organizations and government agencies are looking for documented KM
capabilities in their suppliers and subcontractors, the standard provides an
objective way to test this.
The standard gives knowledge managers leverage in their organization. You
can say to your management, ‘If we don’t do X, Y and Z our KM won’t be
compliant with the ISO standard’.
However, there are still legitimate concerns about a standard for KM:
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Some feel that the presence of a standard will introduce a ‘tick-box’
mentality, and that organizations will do only the minimum to give the
appearance of compliance.
Some of the requirements of the standard are open to different
interpretations. It is not always going to be easy for an auditor who is
inexperienced in KM to assess the quality, relevance or effectiveness of a
KM initiative – and there are not yet many ISO auditors who have deep
experience in KM.
If an auditor is not deeply familiar with the business context and internal
drivers of an organization, they may not be equipped to evaluate the
relevance or efficacy of some KM practices in relation to business drivers
and stakeholder needs.
Simply being able to document a component that is required in the
standard does not guarantee its effectiveness.
We have also heard the view that the existence of the standard will drive
unnecessary cost into the system, through a desire for compliance and
certification.
It may drive organizations towards practices that look important for
completion against an audit, but are not necessarily relevant to that
organization’s specific needs.
External Frameworks and Standards
Time will tell whether the ISO KM standard lives up to its promise of delivering value, or is treated as a time-consuming and potentially distracting
tick-box exercise. How you apply the standard could be an influence in this,
and that’s what we will look at next.
Using the ISO 30401:2018 KM standard
We believe that the best way to use the standard is as a yardstick against
which to measure the completeness and the application of your KM framework. Buy a copy of the standard, and read through it looking for the word
‘shall’. This word is used over 50 times, and each use of the word ‘shall’
represents something you need to be doing if you wish to comply with the
standard. The first such statement is, ‘The organization shall determine external and internal issues that are relevant to its purpose and that affect its
ability to achieve the intended outcome(s) of its knowledge management
system.’ This is a sentence common to all ISO management system standards, including the Quality Management Standard (Bethune, 2017). If you
can demonstrate, for example by producing documentary evidence, that you
have gone through a valid process to determine these issues, then this is one
step towards compliance with the standard.
The requirements in the standard come in a logical order, and can be
tackled one by one. Once you can demonstrate, through evidence, that you
meet all requirements, then you can claim to be compliant against the
­standard. This would be self-audited compliance, but still gives you and
your management reassurance that you are doing well. Our case study in
Chapter 32 from Petroleum Development Oman (PDO) illustrates how useful this process can be. In that instance, the self-assessment against the ISO
standard produced reassurance as well as insights leading to identification
of desired ­improvements.
You can of course ask an external auditor to audit you against the standard, bearing in mind that the most effective kind of audit is going to be one
where three capabilities are present:
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experience in auditing against ISO management system standards;
experience in a wide range of knowledge management practices and
applications, so that the auditor can probe effectively and not simply rely
on the paperwork provided;
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sensitivity to the contextual particularities (including business drivers,
environment, critical knowledge needs, stakeholders, culture) of the
organization being audited, so that the relevancy of the documented
practices can be evaluated.
We’ll discuss these issues in greater depth in the last section of this chapter.
Whoever does the auditing, there are likely to be some requirements in the
standard that you currently do not meet. Perhaps you have some missing
resources, or KM awareness is low, or you have no formal KM policy, or
you have a policy but it has not been effectively communicated and implemented. Then you can use the audit findings to speak to your management,
demonstrate to them that you cannot meet the ISO requirements, and ask
for resources, budget or support to fill the gap.
Tip
Involve your KM champions in collecting evidence to show you meet the
requirements. They may be able to think of things, or provide evidence, that
you have not thought of. They can provide valuable contextual insights to
aid the audit team. Involve a trusted external third party to challenge you,
and to make sure that your evidence is good enough. If you have worked
with external providers on some of the assessment and planning activities
described in Chapters 11–20, bring them back at this stage so that you have
the benefit of an external objective eye, combined with relatively deep
knowledge of your organization’s unique make-up.
Self-audit or external audit?
Self-auditing comes with some benefits. For a start, if you have shepherded
the KM effort through its cycle from needs analysis, to alignment with the
business needs, to proofs of concept and pilots, to embedding and establishing effective metrics, then you are in a good position to be sensitive to the
way in which your KM efforts are aligned with the specific contextual particularities of your organization. You will have little difficulty in coming up
with strong evidence for each of the requirements of the ISO standard.
However, there are some risks as well. For a start, you have probably
spent considerable time looking for and tracking signals of success in your
External Frameworks and Standards
KM efforts. This can make you less sensitive to signals of weakness or gaps
that exist. Psychologists call this ‘inattentional blindness’, where we increasingly become desensitized to disconfirming factors, because we are focused
primarily on looking for confirming factors (Simons and Chabris, 1999).
If you are less experienced in KM, or dependent on respondents who
are not experienced in KM, there are other risks. There is a common cognitive
bias known as the ‘Dunning-Kruger effect’ where a high level of confidence in
one’s own capability is closely linked to a lack of knowledge about what that
capability actually implies:
Poor performers in many social and intellectual domains seem largely unaware
of just how deficient their expertise is. Their deficits leave them with a double
burden – not only does their incomplete and misguided knowledge lead them to
make mistakes but those exact same deficits also prevent them from recognizing
when they are making mistakes and other people choosing more wisely
(Dunning, 2011).
We often see this effect during knowledge management audits for clients,
expressed as ‘overconfidence through ignorance’, where someone will rank
their organization as good at one element of KM when they are really very
poor, just because they have no knowledge of what ‘good’ actually looks like.
‘Yes, we are very good at sharing best practice,’ they might say. ‘We have a
conference every second year where people present their best ideas.’ And because they have no experience of (for example) daily discussions in communities of practice, or projects that routinely host peer assists with associated
deep discussion of knowledge topics, they think that a PowerPoint-heavy conference is an effective way to transfer knowledge, and that every second year
is an appropriate frequency.
So we find an interesting pattern, where self-assessment says more about
self-perception than objective reality:
●●
●●
●●
a person who doesn’t know much about KM ranks their organization
highly through false confidence;
as they learn a little more about KM, their self-ranking drops dramatically,
and they realize how poor they really are compared to their peers and to
best-in-class organizations;
then, as they actually start to implement good KM, the ranking begins to
climb again.
The Dunning-Kruger effect is one of the primary reasons why self-assessment
of your KM capability carries risks, particularly in the early stages when your
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own KM experience levels are low (or, if you yourself are experienced in KM,
you are relying on the self-assessments of less experienced individuals). It
takes an auditor experienced in both auditing and in KM to get past such
perceptions, and to know how and when to probe deeper past the veil of
­ignorance.
Where you or your respondents are likely to be inexperienced in KM, you
would be better off engaging a trusted third party with wide practical experience in both KM and auditing who can:
●●
ascertain a truer picture of where your organization stands in KM terms;
●●
determine what still needs to be done;
●●
substantiate these insights and communicate them effectively and
convincingly to you and your stakeholders.
Experienced external auditors can often cut through the noise and detail
and see important underlying patterns that internal stakeholders cannot see.
In our case study in Chapter 31, we see how NASA’s external safety-driven
audits were significant interventions that drove major shifts in the direction
and focus of KM and learning processes across the organization.
C A S E S TU DY
In 2016, the Joint Inspection Unit (JIU) of the United Nations led a review of KM
across the UN system organizations. The JIU functions as a kind of auditor
general for the UN system. The team was led by Petru Dumitriu, who was not
himself experienced in KM, but was deeply experienced in the conduct of audits.
The process for a JIU review is standardized and very systematic, involving
initial desk research on both the subject matter and the documentation of
current practices across the system, development of a questionnaire, an
inception report (a detailed plan of action outlining criteria for the review
developed in consultation with all the audited parties), in-depth interviews, and
analysis of both documentation and interviews. There had been a previous
review in 2007, against which this audit was designed and evaluated.
It is important to note that this was not a compliance audit. It was intended as
a benchmarking audit to compare practices across the UN system organizations,
and to identify potential good practices that could be shared. In this sense it was
structured to encourage positive participation, sharing and learning from the
different UN agencies.
External Frameworks and Standards
The audit report came up with a number of key recommendations for how KM
across the UN system could be enhanced, including leveraging the areas where
there were strong practices in place. It resulted in a renewed focus on KM
across the UN system, and a guidance note on KM development from the
Secretary General to the UN General Assembly and to the Chief Executives of the
UN System.
In this case, an experienced audit team without deep KM experience was
able to come in with an objective eye following a well-defined and highly
participative process, and then recommend clear and specific improvement
opportunities that would benefit the UN system as a whole, as well as its
constituent parts (Dumitriu, 2016).
On the other hand, we have already seen that external auditors also have
some limitations. If they are inexperienced in KM, they may not be able to
probe deeply into the subtleties of specific KM practices. It did not matter in
the broad sweep audit of the UN system, but it might matter in the kind of
example we cited above, of ‘we are very good at sharing best practice’ – if an
auditor does not know what good looks like, he or she might take such a
statement and its accompanying documentary evidence at face value.
External auditors also suffer from a lack of knowledge of the particular context and drivers of the organization they are auditing. The ISO standard requires that KM be focused on the critical knowledge needs of the organization.
An external auditor may not necessarily be equipped to evaluate whether the
knowledge focus areas for the KM programme are in fact the most important
ones for that organization’s current needs. He or she may not be able to ascertain easily that all key stakeholder needs were taken into account. And in
­time-pressured circumstances, it is known that in the presence of ambiguity or
uncertainty, external auditors will often fail to probe in any depth – there is no
real pay-off for exerting greater effort, and they will take the documentary evidence at face value (Willekens and Simunic, 2007; Knechel, 2013).
As in most other things in KM, you must make your own judgment on
which model is the most effective for you and your circumstances. Do you
have sufficient experience and the aid of critical external eyes, to conduct a
robust and reliable self-audit? Do you feel the need for an external review,
and in that case how will you compensate for the external auditor’s lack of
contextual knowledge? Or should you take a hybrid approach, involving
partnership between internal and external participants?
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Summary
Benchmarking your KM programme against external practices and established standards is well worth doing. The challenge is finding an effective
mechanism. Off-the-shelf maturity models may give you some ideas and
indications, but there are many pitfalls in their use, and you need to apply
them with care. Similarly, KM awards must be treated carefully, because
they carry strong incentives towards bias on the part of award applicants as
well as award givers. Here, the transparency and objectivity of the process
is extremely important.
Your current best approach may be use of ISO standard 30401:2018.
Although it does not tell you how to do KM, it sets a standard for building,
applying and continually improving a KM framework. There are many
ways in which the standard can help you in your work, and the first should
be an audit against the requirements in the standard document.
However, be aware of the cognitive biases involved in self-audit, and the
limitations of a purely external audit. A hybrid approach using trusted
­external auditors who have some familiarity with your organization, or a
­robust means of documenting and communicating the contextual particularities of your organization, may be the best approach. In this hybrid approach, an externally driven audit can be supported with internally supplied
insights and resources.
References
Bethune, P (2017) ISO 9001:2015–establishing the context of the organization,
Quality Digest [online] https://www.qualitydigest.com/inside/standards-article/
iso-90012015-establishing-context-organization-020117.html (archived at
https://perma.cc/VH2U-9YYD) [accessed 1 March 2019]
Carpenter, S and Rudge, S (2003) A self-help approach to knowledge management
benchmarking, Journal of Knowledge Management, 7 (5), pp. 82–95
CILIP (2019) KM chartership [online] https://www.cilip.org.uk/page/
KnowledgeManagementChartership (archived at https://perma.cc/TY4E-62D7)
[accessed 1 March 2019]
Dumitriu, P (2016) Knowledge Management in the United Nations System, United
Nations, Geneva
Dunning, D (2011) The Dunning–Kruger effect: on being ignorant of one’s own
ignorance, Advances in Experimental Social Psychology, 44, pp. 247–96
External Frameworks and Standards
Farmer, T (2002) BSI Position Statement on Standardization Within Knowledge
Management, British Standards Institute, London
Fry, I (2015) Knowledge management and ISO 9001:2015, RealKM, 14 October
[online] https://realkm.com/2015/10/14/knowledge-management-and-iso90012015/ (archived at https://perma.cc/CJ8R-2UJL) [accessed 5 October 2018].
Hong Kong Polytechnic University (2018) MIKE Award [online] https://www.
polyu.edu.hk/ise/kmirc/research/mikeaward (archived at https://perma.cc/
B8N7-57GE) [accessed 2 March 2019].
ISO (2015a) Quality management systems – requirements – ISO 1001:2015, ISO,
Geneva
ISO (2015b) Management system standards [online] https://www.iso.org/
management-system-standards.html (archived at https://perma.cc/7XN4HWKX) [accessed 1 March 2019]
ISO (2018) Knowledge management systems – requirements – ISO 30401:2018,
ISO, Geneva
Knechel, W (2013) Do auditing standards matter? Current Issues in Auditing, 7 (2),
pp. A1–16
Simons, D J and Chabris, C F (1999) Gorillas in our midst: sustained inattentional
blindness for dynamic events, Perception, 28 (9), pp. 1059–74
Skyrme, D (2002) KM standards: do we need them? [online] https://www.skyrme.
com/updates/u65_f1.htm (archived at https://perma.cc/WZJ8-EXY8) [accessed
31 August 2018]
Standards Australia (2005) AS 5037-2005 Knowledge management – a guide,
Standards Australia, Sydney
Willekens, M and Simunic, D (2007) Precision in auditing standards: effects on
auditor and director liability and the supply and demand for audit services,
Accounting and Business Research, 37 (3) pp. 217–32
Wilson, J and Campbell, L (2016) Developing a knowledge management policy for
ISO 9001:2015, Journal of Knowledge Management, 20 (4) pp. 829–44
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externally
28
Not all your KM work will be delivered by you and your team, and not all
of your KM ideas will come from within. Sometimes you will need to get
insight and assistance from outside the organization, whether it be to take
soundings on a course of action, to gather the experience and objective advice of trusted peers, or to bring in specialist knowledge and capabilities to
your organization.
In this chapter we cover:
●●
building your KM peer networks;
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working with trusted consultants;
●●
working with technology vendors;
●●
scoping and issuing tenders for KM projects.
Building your KM peer networks
Perhaps the most important thing you can do is build a strong network of
KM peers. Get to know other KM professionals in organizations like your
own, and also in quite dissimilar organizations. The first will help you compare practices against similar issues, and the second will give you broader
insight into the range of KM possibilities available. If you can, pay learning
and sharing visits to other KM teams and host visits in return.
Sometimes we hear our colleagues say, ‘Oh, I’m not ready to share yet, we
don’t have anything significant to show.’ To this, we invariably reply, ‘When
you are in the middle of implementation is the most significant learning period you’ll ever have – it’s absolutely the best time to share and get insights
from others.’ Sharing the challenges you are meeting and how you are addressing them helps you articulate them more sharply. This is also the point at
which insights from others might be most valuable. Your personal network of
peers will help you find solutions for difficult challenges, provide other KM
Working Externally
implementations against which to compare your own, offer success-case
­examples to give your management and stakeholders, and can be used for
verification checks when you want to hire a consultant or technology vendor.
There are many ways to build your peer network. Conferences and seminars are a good place to start; use the coffee breaks to meet and chat with
other KM professionals. Make a point of introducing yourself to the people
who ask good questions.
Most countries and regions have at least one annual KM conference.
Some of them are commercial events driven by sponsors and vendors, and
are useful as showcases, but not necessarily for learning about practical, indepth implementations. Some conferences are organized by professional associations, and they tend to be more focused on sharing experience and
cases. Some conferences are more research driven, and can seem quite academic from a practitioner perspective. The conference websites will give you
an idea of their type, and you should ask the organizers for the participant
profile and typical participant numbers.
Training workshops in specialist areas of KM or KM-related topics are
also useful, because they often provide the opportunity to discuss your own
issues in greater depth and work with peers in other organizations on shared
activities. They are often attached to conferences, but can also be offered by
training bodies as stand-alone events.
Besides conferences there are also professional associations of various
types. There are industry consortia such as APQC which typically have corporate memberships, maintain KM resources and case studies behind their
firewall, and organize regular meetings, conferences, and benchmarking activities. There are professional associations that can have both individual
and corporate memberships, and there are volunteer-led networks, which
are very dependent on the motivations and energy levels of the members and
committee members, including you. Get involved and make things happen.
Finally, there are the very loose but long-lived and reasonably active online networks such as SIKM Leaders Community on Yahoo Groups,
KM4Dev on its own platform, and LinkedIn, which has a number of more
or less active KM groups. These forums can be useful for posing questions
and getting a broad range of useful answers, as well as a sense of who is
doing what in KM. Never be afraid to ask questions, whether in person or
online. In our experience, it is the really simple, basic, apparently ‘stupid’
questions that elicit the most interesting, diverse, and useful responses.
Don’t be afraid to contact somebody by email if you have seen them at a
conference, read an article of theirs, or liked a reply they gave in an online
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forum. If knowledge managers are not open to sharing, then they are poor
representatives of their craft. But do respect their time, and don’t expect
them to be able to write you a treatise or detailed case study at the drop of
a hat. They will be busy people just like you. If somebody helps you, thank
them, and look for an opportunity to reciprocate. If somebody shares with
you, or refers you to a useful contact, be prepared to share back, or make
introductions on their behalf. This is how the community maintains its
strength, and how you maintain credibility and influence in your practice.
Working with trusted consultants
This may be the first KM implementation programme you have led. You
may lack experience and knowledge in this area, and you might feel you
would benefit from experienced guidance and support. One approach is to
partner with trusted consultants. We are ourselves consultants, but we have
also hired and worked with consultants. The advice in this section is based
on both experiences.
Many people have a suspicion of management consultants, but the best
of them should be considered as knowledge resources. An experienced KM
consultant will have been involved with dozens of KM programmes, and
can make this experience available to you to help you avoid the pitfalls and
maximize your chances of success. If it accelerates your KM implementation
or improves its effectiveness this will be money well invested. Trusted KM
consultants can make excellent mentors. Select a consultant based on their
breadth of experience. It does not need to be experience in your precise industry, as there are many factors other than industry segment that affect KM
implementation. It is much better to find someone who:
a you personally get on well with;
b shares knowledge openly;
c can communicate effectively at different levels of staff seniority from
working level to senior leadership level;
d has a clear plan and methodology for capability transfer to your team;
e is open to feedback and a relationship of mutual sharing and learning;
f
has a very wide KM experience base;
g has wide professional networks.
Working Externally
There are many advantages and a few potential pitfalls when working with
consultants. The advantages are as follows:
●●
●●
●●
●●
●●
What you are doing only once, a consulting firm may have done many
times. This may be the first time you have conducted a KM assessment,
written a KM strategy or policy, created an organization-wide taxonomy,
or many of the other major tasks associated with KM implementation. It
makes sense to partner with an organization that has done it before,
preferably many times.
A consulting firm will give you an external perspective. Their fresh
thinking can help to revitalize your projects if they have lost momentum,
or become mired in politics. In the previous chapter we identified the
challenges of self-audit, where the Dunning-Kruger effect can mean that
the less you know, the more confident you feel about the current state of
KM in your organization. An external experienced firm has a better
knowledge of what good KM looks like, and will be more capable of
giving you an informed and objective assessment.
A consulting firm can be used to deliver messages to management. Often
senior management will give more credibility to advice from an external
consultant than they will to advice from their own team (this is sad but
true). External consultants can be useful in delivering uncomfortable
messages to your leadership, where you yourself don’t want to burn up
too much of your personal credit. However, you can take this too far. If
your leadership team only hears from your consultant and not from you,
they may doubt your ownership of the KM programme. Share the
platform wisely with them.
A consulting firm can be a useful resource when the workload becomes
too great for your own team to manage. The KM workload is never
steady, and when times are busy a consulting firm can step in and take
some of the load.
A consulting firm can provide specialist skills and capabilities that are
absent from your team. For example, many organizations outsource the
task of retention interviewing, or facilitating lessons capture from major
projects. If you are developing an enterprise taxonomy from a low base,
there is a lot of initial work that is quite different from maintaining an
existing taxonomy. All of these are skilled activities that happen relatively
rarely, and you may decide it is not worth keeping a skilled practitioner
permanently on your team to get them done. It may make more sense to
outsource them.
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However, alongside these advantages come pitfalls and challenges. We have
listed them below with some potential remedies:
●●
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●●
●●
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A consulting firm, unless they have worked with you for a long time, will
not know your organization. They won’t know the people, the acronyms,
the working styles or the organizational culture, and there is always a
danger that they will suggest a KM solution which will just not work in
your context. You need to work closely with them to provide context and
direction, while their job is to provide insight, specialist skills and
experience. Working with consultants in KM needs to be framed as a
knowledge-sharing partnership, not a simple transactional affair with a
set of reports and no real capability transfer. In Chapter 13, we discussed
the importance of dialogue as a knowledge-sharing approach. This holds
true for partnering with consultants as well.
Your own team may feel disempowered and lose morale if an outside
consultant is seen to be favoured over them. Sometimes they may feel
they are ‘not good enough’, sometimes they may feel that the consultant’s
ideas are preferred to theirs, and sometimes they may feel the consultant
is being overly critical. It is a good thing for a consultant to be critical –
an objective eye is partly what we hire them for – but this can introduce
tensions, defensiveness and conflict unless handled sensitively. Look for
consultants who have a reputation for taking a facilitative approach – on
the one hand they are not afraid to be honest, but on the other hand, any
criticism is formative, with constructive, coaching-oriented support. This
again depends on a relationship built on dialogue.
Consultants are typically much more expensive than salaried employees.
Where you need a capability that will likely have to be sustained, a ‘plug
and play’ approach will not work in the medium to long term. Even if
you need a specialist consultant to get started, have a roadmap for
transitioning to permanent headcount.
External consultants may have their own ways of working, which may
not align with yours. They may not be open to having their methods or
findings questioned. Make sure that you frame the engagement as a
partnership involving dialogue and common deliverables from the start,
to set the right expectations.
You will very likely not be their only client, and there is a risk that their
attention may be divided. Have a discussion with them on what they are
already working on, and what the mutual expectations should be in terms
of time to be spent. On your side, KM projects often have internal
Working Externally
dependencies that you don’t entirely control. Timelines may slip, and this
might impact their ability to balance clients and projects. The best
working relationships are where there is a sense of respect for each other’s
time, and a mutual willingness to make adjustments where needed.
●●
There is a risk that when the specified task is over, the consultant leaves,
taking their knowledge with them, and continuity is lost. This is why you
need to make sure that knowledge and capability transfer is a structural
part of the contract, with allocated time and activities for learning and
knowledge transfer, training where appropriate for skills transfer, and
discussion sessions where the rationales for consultants’ recommendations
are probed in depth. In some cases we have seen organizations that will
include an optional component for post-engagement follow-up support.
Look for consultants who have a reputation for staying in touch and who
are open to ad hoc follow-up questions. It is important not to take this
for granted, or to assume they have unlimited time to spend. Time is
money for consultants. However, if they care about the effectiveness of
their work with you, they should be open to staying in touch informally.
Consultants therefore have a lot to add, if you can manage the drawbacks.
Your personal networks can be very helpful in locating consultants with the
experience you need, or for getting feedback on how they work. You can
find good consultants by word-of-mouth referrals, or through browsing
websites, LinkedIn and consultants’ personal blogs. Look for breadth of
experience, and see if you can understand their personalities and consulting
styles.
They will need to fit in with your corporate culture and your team, just
as new staff members should. Meet with them or speak with them by telephone before committing. Check them out at conferences, attend their
workshops. Do they listen well? Are they asking good questions? Do they
jump to solutions too quickly? Do they appear flexible and responsive when
they get new information? Do they seem like they can adapt their approach
to meet your circumstances and needs, or do they expect you to follow their
methodology regardless? Do you have references from previous clients to go
on? What do your professional networks say about them? Do they transfer
knowledge to their clients in their projects? Be aware that some consulting
firms may deliberately withhold knowledge, so that they can sell on supplementary services after the first contract is over.
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Working with technology vendors
If your KM implementation requires the purchase and installation of new
software, then you will have to work with technology vendors. Where you
can often expect some latitude and flexibility in a consulting contract, you
have much less latitude in a software and systems contract. Software is built
to do specific things, and there are significant implications to change requests after contract award, so you want to get your requirements right
before you go to tender. There are two main critical success factors: getting
the requirements specified clearly, and being able to evaluate the best vendor
for your needs. We’ll look at procurement in the final section of this chapter;
we’ll cover vendor selection here.
There are two main types of technology vendor – the primary vendors of
a software system or application (the people who developed the software
and know it inside out) and the system integrators whose job it is to integrate this new software or application into your environment (the people
who typically have highly templated approaches to implementation and
may not know all the software’s capabilities and complexities).
Often, your IT team will prefer the system integrator route, since this
delegates to an external contactor the responsibility for the software’s integration into your IT infrastructure. Internal IT teams often do not like to
take on this responsibility when they are not familiar with an application.
They prefer to be the gatekeeper that validates whether or not the application functions as specified, connects with the infrastructure in the right way,
and does not pose any security risks.
However, if you have any non-standard requirements, you may find that
the system integrator has very little flexibility in how they go about their
work, they may not know how to tweak the system beyond their standard
implementation process, and you yourself may not have sufficient technical
knowledge to specify in depth what they should do. If you think this might
be a risk, then you should probe the system integrators for their level of
­access to the primary developers of the software, and how they deal with
non-standard cases. Can they bring in the software developer as a member
of the implementation team?
Beyond that issue, many of the guiding principles for finding good vendors are the same as for finding good consultants. Use your personal networks, visit or speak to past clients or system users, have conversations with
them, probe them on examples of how they have adapted their platforms to
client needs, check them out at conferences and exhibitions, look for
Working Externally
­ ublished case studies – preferably not the marketing case studies with little
p
in-depth detail, but case studies that illustrate real practices in real
­environments.
Do not take the promises of their salespeople at face value. And don’t be
overly swayed by the glossy demonstrations in conferences or in your meeting room. These demos are highly rehearsed and scripted, with tightly
­defined and controlled content, and they have no dependencies on the messy,
all-too-human environment you will likely be dealing with in your organization. In the technology arena, the saying is that ‘before the sale, everything
is possible’. After the sale, you suddenly start to hear from the technical
people that it’s only possible with heavy customization, which involves additional cost, or it’s only possible with extensive additional resources on
your side, and you get warnings from the system integrators that customizations can compromise your ability to take on future upgrades.
It’s much better to have those conversations before you commit to a purchase, so that you are making well-informed decisions. Don’t just speak to
the salespeople; speak to the technical teams who have implemented this
software for other clients. Look at different implementations if you can,
walk through some real use cases, and get a sense of the variety of ways in
which the software can be implemented. Ask them for trial access to the
software so you can play with it. If there are high stakes involved, with uncertain outcomes, ask for a proof-of-concept exercise to demonstrate the
software’s effectiveness in your environment. Be aware that if a proof of
concept is of any scale, it will likely have to be paid for. Then have your
conversations about flexibility with your prospective vendors.
Scoping and issuing tenders for KM projects
If you find you need support from a consultant or a technology vendor, you
will need to engage in a formal procurement exercise, which may mean
­contacting multiple firms in order to receive bids. Tony Byrne and Jarrod
Gingras have written an excellent book called The Right Way to Select
Technology, which gives lots of practical advice you should follow religiously, from creating the business case, to putting together the selection
team, to developing requirements based on use cases, to finding the best
solutions (Byrne and Gingras, 2017). Here we will focus on the steps that we
find carry most risks in the KM context. The most significant steps in many
KM implementations are going to be how you:
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1 frame the contract;
2 set requirements;
3 invite participation;
4 evaluate bids.
1. Frame the contract
Your first decision, where you have both consulting and technology needs,
is how you are going to divide up the work that needs to be done. Should
the consulting and technology be combined, or put into separate tenders?
Where your procurement exercises are complex and bureaucratic, it’s a
temptation to roll them up together into one big exercise. It also reduces
your risk of a disconnect between the consulting input and the technology
implementation if the same vendor is responsible for an integrated delivery.
The problem, of course, is that the expertise to deliver a consulting project effectively is very different from that required to deliver a piece of technology infrastructure. Some larger consulting companies provide both KM
consulting services and system-related services, while other system integrators take on specialist consultants for that component of the project. If you
are offered this solution, look for partnerships with a good track record
behind them. However, it is by no means clear that you will be getting the
best possible choices for each set of expertise if you put them in the same
bundle. You should consider this as a significant risk factor. Also, the bundled consultancy will inevitably be led by the technical solutions proposed
by the winning vendor. What if the consultancy needs analysis phase discovers that the technology selected is inappropriate? You might be putting the
cart before the horse.
One compromise method we have seen is where the consulting firm is
asked to develop the technology requirements as a deliverable of their project, but not to take responsibility for software selection and implementation. This solution gives you a better chance of evaluating the bidders on
their relative merits, but carries the risk that the technology vendor may not
have the same approach or mindset as your consultant. We have seen technology vendors who simply did not understand the approach recommended
by the consultant, and ended up reframing the deliverables in a shape that
they knew how to deliver.
It can take a strong internal team with deep technical knowledge, which
has worked in close partnership with the external consultant, to be able to
Working Externally
manage the continuity between a consulting component and the technology
implementation. If you think this is a risk, then provide for a piece of work
covering knowledge transfer to the technology vendor in your consulting
contract. We have also seen cases where the consultant was brought back to
evaluate the technology implementation against the initial recommendations before the implementation was signed off.
C A S E S TU DY
A large military organization we are familiar with wanted to develop a Centre for
Lessons Learned. The organization had systematic lessons collection practices
across its various parts but they did not have processes and systems for
aggregating lessons across the organization, analysing them for significant
patterns, and making systemic changes based on that analysis. Because of the
relatively rapid pace at which career officers were rotated in their posts, they
decided to outsource the centre’s staffing on a five-year contract, with the goal
of maintaining continuity for the centre.
Using the US Army’s Centre for Army Lessons Learned as a model for the
requirements, they issued a tender. The tender was won by a major consulting
firm, and staffed by consultants who were embedded in the organization for
the period of the contract. As the first five-year term came to a close, the
organization realized that the centre was not having the impact they had
desired.
Was an external provider staffed by non-military consultants the right way to
go, in an organization that prides itself on its identity and esprit de corps? How
does an external provider gain sufficient depth of field knowledge to be effective
in this role: a) to be able to understand the contexts in which lessons are
gathered, b) to have sufficient in-depth knowledge to be able to perform effective
analysis, and c) to be able to work analysed lessons back into the fabric of the
organization? And yet the initial constraints with rapid career progression for
internal staff remained.
The organization decided not to renew the tender as originally issued, but
proceeded instead to a Request for Information (RFI) – this is a procurement
document that puts a set of goals and requirements out to the marketplace, and
invites responses describing the capabilities of the vendors in relation to the
need. ‘We wanted to see if the market could propose innovative solutions that
met our needs,’ we heard. ‘We knew that the initial set of requirements wasn’t
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working for us, and we knew we didn't know enough to issue a new set of firm
requirements. So we put it out there to see what the market would propose.’
An RFI lengthens the procurement process, but avoids committing to solutions
that turn out to be inappropriate. The responses to the RFI can then inform the
next tender exercise. Frequently, that tender exercise is a closed tender by
invitation, where the most interesting respondents to the RFI are the invitees.
2. Set requirements
There are commonalities and differences in setting requirements for consulting projects and for technology projects. Here are the commonalities:
●●
●●
●●
Set the context clearly – your current situation, where you need to get to,
the goals of the project and the desired business outcomes. Your vendor
or consultant needs to understand where you are now, and where you
want to get to. They will also need to understand the nature of your
organization, its size, its complexity, and if you have attempted anything
like this before.
You will need to find the right balance between setting clear requirements
and being overly specific. This can be challenging – if you are hiring a
consultant because they know more about KM implementation than you
do, it is quite possible that you don’t entirely know what needs to be
done. As one vendor told us, ‘We need to know what you want to achieve,
but don’t tell us how to go about it – we will cover this in our proposal.’
We have seen tenders where the organization has been very specific and
definitive, but the methodology described in the tender was fundamentally
flawed, based on false assumptions about what a good outcome would
look like. Being overly prescriptive risks excluding good vendors who can
see problems with the methodology implied, and who then choose not to
bid for it – because in the evaluation any alternative proposals will be
non-compliant and disqualified.
On the other hand, being too vague about the acceptable deliverables
means that good vendors will translate that uncertainty into a higher bid
price. If you really cannot specify your outcomes and deliverables in any
depth, then consider a small scoping project first, and hiring somebody
who can help you bring some definition to the scope of work that has to
be done.
Working Externally
●●
We have seen cases where the procuring organization has assumed that
the consultant can magically deliver the work without heavy involvement
from your own people. In one communities of practice tender, a
requirement was that ‘the consultant shall establish communities of
practice in key knowledge domains, but shall not take up the time of our
staff in doing so’! Such a ‘hands-off’ approach to the contract is unlikely
to succeed.
There are some important differences between consulting projects and technology projects:
●●
●●
●●
Consulting projects should be able to tolerate a greater degree of flexibility
than technology projects, especially if they are for extended periods
during which your circumstances might change, or when you are in the
early stages of KM and learning as you go. Be clear about the degree of
flexibility required. In some cases we have seen the award of a master
fixed-term contract, defined in quite broad terms, and then a series of
specific task orders issued under that contract with well-defined tasks and
projects, issued as the needs arose.
In technology projects it is important to define a set of typical use cases
in which the technology will be used – describing in layperson’s terms the
work tasks to be performed, how the software is expected to support
those tasks, and what the desired outcomes are. Use cases should describe
current work practices and needs, not imagined ones, and should be
constructed with end-user involvement. These use cases provide context
for the bidders to understand what their software is supposed to do, they
provide realistic test cases specific to your organization for evaluation of
the software (rather than artificially constructed demos), and they reduce
your risk of ‘requirements creep’.
In technology projects, ‘requirements creep’ is when people realize that a
new technology is coming along, and jump on board with ‘wouldn’t it be
nice if it also did this’ requests. This is especially true for IT teams, for
whom the prospect of additional functionality is an attractive feature
that suggests they are getting value for money. However, additional
functionality also adds complexity and can make a technology seem
intimidating and unusable. Resist requirements creep strongly, using your
business case and use cases to filter real requirements from ‘nice to have’
options. If you fail, then hide the extraneous functionality until you have
the core system bedded down and being used effectively.
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3. Invite participation
Although the invitation to participate in a tender can only formally happen
once your requirements are written, in reality you should have been building
familiarity with the vendors and consultants well in advance, even while you
are writing your requirements. The art of requirement writing is to find the
right balance between describing what your organization needs, and soliciting a range of good responses from what the market has to offer.
Consult and research widely, well in advance. If you are rushing
around trying to find vendors after you have written your requirements,
and if you have a very low response to the tender, then you have not been
doing your pre-work well. Tony Byrne and Jarrod Gingras also have
some excellent advice on where to find ‘more than the usual suspects’
and how to evaluate the likely quality of their proposals (Byrne and
Gingras, 2017).
4. Evaluate bids
There are significant differences in how you evaluate bids for consulting
tenders compared to technology tenders (another reason why it’s not always
a good idea to combine them in the same exercise). In consulting projects,
the evaluation is largely qualitative, and is based on your assessment of a
promise, whereas in technology projects the vendor also has something tangible to show, which can be evaluated against known use cases.
In consulting projects, your evaluation is going to be based on a range of
criteria apart from the price – in fact in many organizations it is considered
good practice to evaluate the technical proposal (the description of how the
work will be done) in isolation from and before the price proposal. Price
comparisons are made only after the high-scoring vendors have been shortlisted against the requirements. This way, you know you have good proposals before you consider price factors.
You will have a predefined weightage against criteria such as:
●●
●●
●●
the proposal has demonstrated a good understanding of your needs;
the proposal meets or exceeds your main requirements (sometimes a
proposal may include value-added features that you had not anticipated);
the methodology proposed is well documented, convincing and sound;
Working Externally
●●
●●
the consultant has experience and a documented track record in this
domain and in projects of this complexity, and has client references to
demonstrate this;
the consultant has the financial and personnel capacity to deliver against
a project of this complexity.
Your own internal selection team will determine the weightages against each
of these factors, as well as the weightage to be accorded to price. Bear in
mind that the more complex and broadly defined your project is, then the
more likely it is that you will need to value experience and track record over
price, and the more likely it is that you will value flexibility and adaptiveness
in the approach.
In technology projects, you obviously want some of the same evaluation
criteria – such as track record and experience, a good understanding of your
needs, and the financial and personnel capacity to deliver. But you also need
to be assured that the solution proposed will actually meet the business case
and use cases you defined as part of your requirements. You will want to set
up sessions for your shortlisted candidates, where they take you through demonstrations structured around your own use cases and your own sample sets
of content – not on use cases and content defined by the vendor. Vendors do
not always understand this approach, and remain fixated on selling the unique
features they have defined against their competitors. Byrne and Gingras cite
the example of a vendor who decomposed the use cases ­provided by the tenderer into a set of slides describing a list of detailed functionalities entirely
divorced from the business context. That vendor was dismissed courteously.
As Byrne and Gingras put it, ‘Communicate clearly to bidders that your user
stories best reflect your business priorities. You do not need to waste time with
vendors who do not follow your process’ (Byrne and Gingras, 2017, p. 122).
Tip
For technology projects, involve your KM champions in the development of
use cases, and have a couple of them on the selection committee
evaluating the shortlisted vendors. Also involve the business leads for the
areas of your organization where you have had your most challenging and
your most successful pilot projects. They will be the people who are able to
ask the hard questions, and keep the discussions (and the evaluation)
focused on delivering business value.
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Summary
In this chapter we have emphasized the value of maintaining strong networks across the broader discipline of KM, with your KM practitioner
peers, and with service providers. Start building and maintaining these networks early, so you will be better equipped to learn from others’ experience,
and can seek and evaluate assistance for specific needs when they arise. Bear
in mind that strong networking relationships are always reciprocal and
should bring mutual benefits if they are going to be healthy ones. If you
want to learn from sharing with others, be open about sharing and helping
in return. We also provided some guidance on how to go about formally
engaging consultants and technology vendors. Again, your ability to do this
effectively will be supported by the strength of the prior networks you can
build.
Reference
Byrne, T and Gingras, J (2017) The Right Way to Select Technology: Get the real
story on finding the best fit, Rosenfeld Media, New York
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Knowledge
29
management
and digital
transformation
Organizations are going through a new wave of change, driven by ‘digital
transformation’. In a late 2018 survey of over 400 knowledge managers,
APQC found that two-thirds of the respondents had digital transformation
initiatives in progress, and half of them cited a move towards integrated
cloud-based collaboration platforms (APQC, 2019). Yet the underpinning
technologies behind digital transformation are not always well understood,
and beyond the hype there is little clear guidance on where they are most
effective in support of KM, and where their limitations are. In this chapter
we cover:
●●
the relationship between KM and digital transformation;
●●
the core technologies of digital transformation;
●●
the limitations of artificial intelligence (AI);
●●
KM implications of digital transformation and AI.
The relationship between KM and digital
transformation
Throughout this book, we have described technology as a component of the
KM framework. It is a tool, like other tools, that should support the business goals of your organization and your KM goals. Technology alone
should not drive KM.
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But there is a broader sense in which advances in technology do drive
KM. It was the joint advances in computing and connectivity in the 1990s
that fuelled the first wave of digital transformation (though we did not call
it digital transformation then) when the adoption of email and the web
radically changed business models and organizational ways of working.
This in turn created new pressures on organizations to become more agile,
to be able to coordinate more effectively, to be able to learn and adapt, and
to be able to unlearn outdated ways of doing things. This was the ‘perfect
storm’ that brought knowledge management to prominence in that period
(Lambe, 2011).
We are now in a second wave of digital transformation, created again by
a combination of technological advances:
●●
●●
●●
a transition to cloud-based computing and data storage;
a move from discrete software applications to ‘platforms’ based on standards
with connected but highly adaptive ecosystems of applications;
new techniques for handling bigger and bigger datasets and analysing
them for actionable insights.
From a positive angle, these technological advances create new opportunities
and new affordances – unleashing a wave of experimentation and innovation
and changing the way firms do business. From a negative perspective, this
disruption creates competitive pressures on incumbents in the market and
threatens traditional ways of working. The disruption is at the organizational
level in changing the way business processes are performed, and at the employee level in radically changing or altogether removing people’s jobs.
KM and digital transformation are intimately connected. Both are focused
on how knowledge, information and data can be exploited to improve the
effectiveness and efficiency of organizational processes. Both have a focus on
helping to keep organizations adaptive, agile, innovating and learning from
their environment in real time. The typical approach to digital transformation is very similar to the ‘agile’, iterative, pilot-based approach to KM recommended in this book – start small, find a real business problem to solve,
test often, demonstrate benefits, gain wider buy-in, stabilize and embed
(Herbert, 2017).
Digital transformation can create anxiety among employees who fear that
they will lose their value, just as KM programmes can. The pitfalls are also
very similar, including an assumption that it is all about technology and nothing else, underestimating the need to manage digital transformation as a programme of change, and a failure to build and maintain the right competencies
KM and Digital Transformation
in the transformation team. It is not surprising, then, that KM teams are often
tasked with digital transformation projects, or digital transformation teams
very quickly find themselves in familiar KM territory.
Experienced knowledge managers have many of the competencies, methods and approaches to be able to take on digital transformation projects,
with the strong qualification that to do so they will also need to have good
technical knowledge of the possibilities and limits of the converging
technologies that underpin digital transformation. These are: Artificial
­
Intelligence (AI), Machine Learning, Big Data, and Cloud Computing.
So there is a reciprocal influence between KM and digital transformation.
On the one hand, these technologies will impact the way that KM is done.
On the other hand, KM itself provides frameworks, methods and skills for
managing effective digital transformation initiatives.
The core technologies of digital
transformation
Figure 29.1 shows the interactions between the four main technologies that
create the possibilities and drivers for digital transformation. Artificial intelligence or AI has been around for a long time – it’s an umbrella term that
simply means making machines smarter, to the point where they can replace
or outperform humans.
A specific branch of AI is machine learning, which says that if you give an
algorithm enough data, and give it feedback loops so it can ‘learn’ as it goes,
then the machine can learn by itself without having to have all its operations
programmed through rules. Machine learning has also been around for a
long time, but it is only quite recently that access to very large datasets and
greatly improved computing power has vastly improved the effectiveness of
machine learning.
Big Data refers to the combination of three main things: (a) the availability of lots of data, (b) the proliferation of cheap sensors to gather data, and
(c) the improved computing power to process it, analyse it and apply machine learning algorithms to it.
Finally, the three capabilities of AI, machine learning and Big Data are
increasingly becoming commoditized by the availability of cloud computing
platforms. Cloud-based platforms can deliver vast economies of scale and
effectiveness – providing capabilities that would normally be out of reach to
all but the most technologically advanced enterprises, in:
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Deepening and Extending
●●
the level of computing power available;
●●
the sophistication and adaptability of infrastructure;
●●
the competencies to manage, maintain and continuously improve the
infrastructure.
Machine learning thrives on data – the more the merrier. Major players like
Google, Amazon and Microsoft are deliberately attracting tenants onto
their platforms and making their machine learning tools accessible there –
the more tenants, the more data, the smarter the algorithms become.
Specific applications of digital transformation can include:
●●
●●
developing smarter products or services based on Big Data analytics, such
as ride-hailing services;
robotic process automation – where repetitive tasks formerly done by
people are now done by computers;
Figure 29.1
The core technologies behind digital transformation
Very large datasets that
can be analysed in real
time for reliable
patterns, trends,
predictions
Fe
s
BIG DATA
ed
Fe
ed
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ARTIFICIAL
INTELLIGENCE
APPLICATIONS
Machines can be
‘smart’, can
outperform or
replace humans
in some tasks
Provides power,
scale and speed
Underpin
s
CLOUD-BASED
COMPUTING
MACHINE
LEARNING
APPLICATIONS
Give machines enough
data and feedback
loops, and they can
learn and improve on
their own
KM and Digital Transformation
●●
●●
self-service help supported by smart chatbots that can answer relatively
routine inquiries without human intervention – based on a specific
application of machine learning called Natural Language Processing;
diagnostic and decision-making applications based on highly skilled but
pattern-based human activities such as interpreting X-rays and other
medical images.
The limitations of artificial intelligence (AI)
For all the hype that surrounds them, even now AI and machine learning applications are not especially smart, except in comparison to the rigid software
applications that preceded them. They outperform humans only in well-­
circumscribed tasks that require computational power and speed, and consistency of performance. They are not as adaptive, nor as context sensitive as
humans are, they need to be intensively trained in the specific tasks for which
they are engineered, they need tuning and correction over long periods, and
they need very large, very clean datasets to work from. They are engineered to
perform well in specific, well-understood and predictable scenarios.
With machine learning advances, the applications are getting better at
more complex tasks, such as autonomous driving, interpreting and responding appropriately to natural language queries, or medical imaging. Even
then, they sometimes go badly wrong, especially where their engineers fail
to predict some of the more complex ways in which humans might interact
with them. Here are some examples.
In 2015, Google’s machine learning-powered image-labelling application ran
into controversy when it was found to be labelling photographs of black people
as ‘gorillas’. Three years later, the only fix Google had been able to find was a
rather crude one – simply to remove the labels ‘gorilla’ and ‘chimpanzee’ from
the lexicon. Machine learning depends on large training sets, and clustering
content by similarity – one suspect in this case is that the training sets for the
algorithm are dominated by white people, as are the engineers that write the
algorithms that break down and identify visual features of an image. The algorithms are much better at differentiating fine distinctions in images of white
people than those of black people. Machine learning amplifies common patterns and ignores outliers, unless specifically told to examine them – this means
that it also amplifies biases. If you don’t know how to anticipate or characterize
these outliers (which human beings are collectively quite good at) then the applications can produce some decidedly strange results (Simonite, 2018).
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In March 2016, Microsoft had to withdraw its AI-driven conversational
chatbot Tay, after only 16 hours of it responding to tweets and messages on
Twitter, because it had started making racially offensive tweets. It was not
smart enough to know when its learning algorithms were being manipulated
by users to get it to send racist, offensive and pornographic messages (Perez,
2016). Even now, sentiment engines find it hard to discriminate between
positive words used as praise, or used sarcastically.
In October 2018 an Indonesian Boeing 737 belonging to Lion Air crashed
shortly after take-off, killing all on board. Six months later, an Ethiopian
Airlines 737 crashed in similar circumstances. In both cases, in the early
stages of ascent, the pilots had struggled to bring the plane’s nose up while
the automated sensor-driven systems kept pulling the nose down. The suspect in both cases was a new sensor-driven anti-stall system called MCAS. If
the sensor detects a high angle of pitch at low speeds, then it will tell the
computer automatically to turn the plane’s nose down. This is a different
system from the auto-pilot, and is engaged only when the plane is being
manually flown. It was installed because the instruments and software are
supposed to be faster, more accurate and more responsive than the human
pilots. In the Lion Air case, a faulty sensor told the computer that the plane
was climbing too steeply, and engaged the system. The MCAS software update had been included in the plane’s flight manual, but it seems that Boeing
had not trained pilots in how the system worked. The pilots fought the
computer, not understanding what was happening, and lost. Bad data from
a faulty sensor made a smart system lethal (Davies, 2019).
These examples illustrate the critical dependencies of AI and machine
learning applications:
1 AI applications work best where there is lots of good, clean, data. They work
much less well where the data is incomplete, inaccurate, unrepresentative, or
poorly structured.
2 AI applications don’t cope well with open, human-dominated interactions.
They work best in self-contained processes with limited parameters for
variation. The more variability and complexity, the more training (and
data) they need.
3 AI can be expensive, so you have to place your bets carefully on processes,
products and services that will pay off on the investment it requires.
Training means very expensive human supervision from skilled data
scientists, and can also mean procuring good, clean datasets that
KM and Digital Transformation
accurately represent the target environment. If you can’t procure it, you
have to create it; the big players in AI routinely employ lots of ‘grunt’
labour – employees that spend their days categorizing clean training data.
According to a 2017 Bloomberg article (Laurent, 2017):
These limitations (of AI) mean it’s not yet clear that the cost of automation will
be offset by savings in human capital. Hiring a data scientist can cost more than
$200,000, according to Bloomberg News. Flight-booking company Amadeus
has 40 of them. Siemens says it has more than 200 AI specialists running various
projects. And even Silicon Valley has its grunt workers: Facebook is hiring 3,000
content moderators, on top of 4,500 existing ones. AI cheerleader Amazon has
341,000 employees – three times the number it had in 2012.
KM implications of digital transformation
and AI
There are four main areas where you can add significant value to digital
transformation from a KM perspective. They reflect the four typical kinds of
digital transformation projects we listed above: developing new products
and services based on data analytics; robotic process automation; smart
chatbots providing self-service help; diagnostic and decision-making support based on pattern recognition. The four main opportunities for KM
follow from these:
1 using knowledge organization skills to manage data quality;
2 discriminating the types of expertise that can be modelled by AI from
those that can’t;
3 creating and managing the knowledge bases;
4 managing the change to new capabilities and skills in staff.
1. Using knowledge organization skills to manage
data quality
There are three sets of questions that you need to be able to answer affirmatively in relation to data quality, particularly where your digital transformation initiatives rely on data analytics:
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●●
Do you have the data?
●●
Can you collect the data?
●●
Is your data clean, accurate, representative and consistent? Is it well
governed?
In Chapter 17 we covered the skills and methods required for knowledge
organization – to ensure that search, discovery and re-use of knowledge can
take place effectively across the organization. This is exactly the same set of
skills that is required to evaluate, clean, connect and organize the datasets
that are used in AI and machine learning applications.
2. Discriminating the types of expertise that can be
modelled by AI from those that can’t
In common usage, ‘expertise’ can mean a wide variety of knowledge-based
abilities. It can mean deep technical knowledge (which can be gained from
study), sophisticated skills that require lots of practice, consistent performance
to high standards in routine skilled activities, or deep, experience-based tacit
knowledge, which gives the ability to respond effectively in non-routine, very
challenging situations. It can also mean the ability to integrate logical reasoning with observation and the ability to communicate effectively and coordinate teams. Only some of these types of ‘expertise’ are amenable to modelling
for AI purposes.
It is true that in settings with probabilistic outcomes, the expert is seldom
better – and generally worse – at making predictions and judgments than a
collective answer from a community of practice, say, or ‘the wisdom of
crowds’. And in settings with rules-based outcomes, especially where the
range of outcomes is limited, computers increasingly outperform the expert.
Michael Mauboussin calls this the ‘expert squeeze’ (Mauboussin, 2009).
This transition from expert decisions to computer-aided decisions has driven
the rise of AI as a distinct tool within the KM toolkit. But it is not always
recognized that AI does not perform well in types of expertise that do not
fall into that probabilistic, rules-based category.
In Chapter 11 we gave you a framework for categorizing six different
kinds of knowledge resource: documents and data, method knowledge,
skills, experience-based knowledge, relationships, and natural talent. The
knowledge types that are most accessible to modelling for digital transformation and AI purposes are fully explicit knowledge (documents and data),
implicit knowledge (method knowledge) and teachable skills.
KM and Digital Transformation
Tip
Choose an area of work that you think has some promise for a digital
transformation initiative – perhaps for robotic process automation. Follow
the steps given in Chapter 11 for a knowledge resources audit, tracing the
key activities and the knowledge type dependencies of those activities. if
(a) the main dependencies are for some combination of documents and
data, method knowledge, and/or skills, and (b) there is high economic
payoff for digitizing this process, then you probably have a good candidate.
If there are high dependencies on experience-based knowledge,
knowledge-carrying relationships, and/or natural talent, then AI will
probably be very difficult to model reliably.
Assuming you have ascertained that the knowledge and expertise area you
are interested in is amenable to digitalization, then the knowledge capture
and documentation elements of the KM framework covered in Chapter 14
will probably be of some help. The knowledge synthesis elements covered in
Chapter 15 might also be relevant.
Again, assuming you have characterized the knowledge accurately, you
can then use AI as a powerful tool to provide easy and reliable access to
critical knowledge. What AI is doing here is automating the supply chain for
knowledge and removing the bottleneck previously represented by the
­‘experts’ in that area. It provides an augmentation of knowledge work that
will help increase the productivity of the knowledge worker, giving them
quicker access to better knowledge, and protecting the organization against
the loss of experts when they leave. It reduces the risk of mistakes, and allows more to be done with fewer people.
Even assuming you have found a good candidate for an area of knowledge or expertise that the AI applications can model well, you will very frequently find cases where the process is not completely self-contained, and
that there are situations when human intervention is going to be required, ie
edge cases where the complexity of the work exceeds the capabilities of the
AI tool. Good AI applications will have built into them the ability to recognize the boundary conditions where the AI itself recognizes that it is outside
its area of competence, and where it needs to transfer control to a skilled
human operator. This was the key failure in the Boeing 737 example we
cited above.
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For example, a chatbot can be trained to recognize when a customer is
getting frustrated or angry, or where the query is outside its ability to interpret and respond. It will then politely transfer the customer to a human
operator – who, we hope, can perform better on cases that require enhanced
communication skills or more sophisticated knowledge.
3. Creating and managing the knowledge bases
If the AI is interrogating a knowledge base, the knowledge base needs to
contain clean knowledge. For example, an AI-powered chatbot answering
customer queries needs a clean, reliable and constantly updated knowledge
base just as much as contact centre agents do. That’s a job for the knowledge
manager, as most knowledge bases are decidedly unclean to start with.
Again, Chapters 14 and 15 on knowledge documentation and knowledge
synthesis will be relevant here.
The knowledge supply chain needs continual improvement. New knowledge comes in all the time, and needs to be added to the knowledge base.
The performance of the product or service needs to be tracked, and you
need to look at the lessons that are being learned. Sometimes the AI algorithms need tweaking to deliver better performance. All of these things are
jobs for the knowledge manager, and the knowledge discussion elements of
the KM framework covered in Chapter 13 can be helpful here.
4. Managing the change to new capabilities
and skills in staff
Digital transformation devolves to computers some activities that were previously done by humans. Sometimes these are routine, mechanical tasks, as
in robotic process automation. Sometimes they are highly skilled but analytical tasks based on pattern recognition, such as diagnosing medical conditions from X-rays and scans.
This partial digitalization of work means that the profile of work changes
for the employees that previously did those things – this is true whether they
remain in your organization, or whether they are on the market looking for
new jobs. As computers take on more of these types of work, employability
factors shift to focus on the skills and competencies that still require humans, and the forms of expertise that computers cannot model well – for
example, the ability to detect and respond to edge cases and outliers, dealing
with relatively rare but important events, and social coordination.
KM and Digital Transformation
For example, one of us was once conducting a knowledge-capture session
with a senior engineer, who said that his favourite way to train new guys
was to give them bolt-from-the-blue examples to work with: ‘Imagine pump
3 has stopped, pipe 7 is running at 500 degrees, and there’s smoke coming
from the turbines. What do you do?’ Even if the event and solution are fed
into an AI engine, if it is a rare event, it will not be surfaced as a primary
response to a set of multiple confusing signals unless it is artificially ranked
as significant by the data scientist controlling the algorithm. As we know in
complex challenges, there is a lot of ambiguity and uncertainty – multiple
confusing signals can mean any number of things, and the machine must
work probabilistically through a hierarchy of possibilities. It is simply not
possible to predict and promote all such rare cases, and also do the work of
representing typical and frequent patterns accurately. AI works on patterns
and similarities, and predictable variations.
Humans, on the other hand, are good at this kind of stuff because we
imbue rare but critical events with emotional force. We remember these
things, we become sensitive to them out of proportion to their statistical frequency. In rare but significant events, our inconsistency becomes a strength.
As the knowledge work of humans shifts toward a dependency on the
more complex forms of knowledge, the role of the knowledge manager as a
manager of change, and as a facilitator of learning, becomes more important.
Chapter 19 on culture, communications and change will provide helpful
guidance here.
CA S E S TU DY
When the Immigration and Customs Authority of Singapore (ICA) embarked on a
major digital transformation over a decade ago, they realized that a lot of the
work of their immigration officers was non-value added. When they analysed
their data on immigration offences, they saw that the infringement rates for
long-term pass holders (such as work permit holders, permanent residents and
people on student visas) were negligible.
And yet their highly trained officers spent hours every day sitting at immigration
desks looking at people’s faces and passports, and stamping the relevant page; or
sitting in visa offices processing paper applications and verifying people’s identity
and documents at physical desks with long waiting queues. Amidst all the noise
and boredom in administering a highly compliant population, they were also
expected to spot issues with higher-risk individuals coming into the country.
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Deepening and Extending
So they took a number of key steps:
●●
●●
●●
●●
They automated the visa application and renewals process for the low-risk
population on long-term passes, and put it online.
They put in automated immigration gates equipped to read biometrics for
Singapore passport holders and long-term pass holders, for immigration exit
and entry.
They trained their immigration officers in data analytics, immigration
enforcement and investigation.
They captured key insights from analysing their data on recidivism, human
trafficking or immigration risk factors into automated programmes that now
provide alerts to immigration officers sitting at passport control desks, when
passports and flight numbers are scanned in.
Now, a sample of entrants to Singapore will be flagged at passport control and
taken aside for polite interviews based on risk factors identified by the computer
system. The skilled work of determining whether the passenger actually poses
any risk is done by the immigration officers, not the machines.
In all of this process of change there was no significant headcount reduction
among the officers. Despite apprehensions among the officers when the
initiative started, the outcome has been an extremely effective programme of
change management and of knowledge and capability enhancement, as the
more routine aspects of the job are replaced by machines or augmented by
AI-powered alerts. The job itself has become more challenging but significantly
more interesting.
The final component of managing new capabilities is essential for effective
digital transformation. An organization on a digital transformation journey,
involving technologies like Big Data, AI and chatbots, needs to develop new
knowledge and new capabilities, and part of the knowledge manager’s role
will be supporting this knowledge development. We will have to help the
organization learn how to clean datasets, how to train algorithms, how and
when to augment humans with machines, and how best to deliver value in a
digital world. This is new and strategic knowledge, and KM will be needed
if we are to deliver the maximum benefit from this knowledge.
KM and Digital Transformation
Summary
In this chapter we have reviewed the key features of digital transformation,
and the ways in which knowledge managers can both support it and benefit
from it. KM and digital transformation have many things in common, including their pitfalls. Knowledge managers should be well equipped to guide
and support digital transformation initiatives, provided they have a good
understanding of the strengths and limits of the core technologies involved.
References
APQC (2019) Knowledge Management in 2019, APQC, Houston, Texas [online]
https://www.apqc.org/knowledge-base/documents/knowledge-management2019-executive-summary (archived at https://perma.cc/8CQU-WBYD) [accessed
16 March 2019]
Davies, A (2019) Boeing plans to fix the 737 MAX jet with a software update,
Wired, 13 March [online] https://www.wired.com/story/boeing-737-max-8ethiopia-crash-faa-software-fix-lion-air/ (archived at https://perma.cc/P7D79MQN) [accessed 16 March 2019]
Herbert, L (2017) Digital Transformation: B.U.I.L.D. your organization’s future,
Bloomsbury Business, London
Lambe, P (2011) The unacknowledged parentage of knowledge management,
Journal of Knowledge Management, 15 (2), pp. 175–97
Laurent, L (2017) The limits of artificial intelligence, Bloomberg, 13 June [online]
https://www.bloomberg.com/news/articles/2017-06-13/the-limits-of-artificialintelligence (archived at https://perma.cc/D24W-SSL3) [accessed 16 March
2019]
Mauboussin, M J (2009) Think Twice: Harnessing the power of counterintuition,
Harvard Business Review Press, Boston, Massachusetts
Perez, S (2016) Microsoft silences its new A.I. chatbot Tay, after Twitter users teach
it racism, TechCrunch [online] https://techcrunch.com/2016/03/24/microsoftsilences-its-new-a-i-bot-tay-after-twitter-users-teach-it-racism/ (archived at
https://perma.cc/ZKF8-LVVK) [accessed 16 March 2019]
Simonite, T (2018) When it comes to gorillas, Google Photos remains blind, Wired,
1 November [online] https://www.wired.com/story/when-it-comes-to-gorillasgoogle-photos-remains-blind/ (archived at https://perma.cc/BQ6L-G8K7)
[accessed 16 March 2019]
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PART SIX
Case histories
Executive summary
This Part contains seven detailed case studies written by KM practitioners
about KM implementations in a variety of different organizations and geographies. They demonstrate that KM implementation is not a one-size-fits-all,
linear methodology; it is an adaptive, iterative learning process, focused on
delivering business value. Chapter 30 provides a textbook illustration of
securing senior support for KM, based on a consistent focus on business
value and judicious use of impact metrics. Chapter 31 describes the evolution of KM at a national space agency, combining both centralized and distributed elements. Chapter 32 describes an early application of ISO
30401:2018 to review KM progress in an oil and gas company. Chapter 33
describes how knowledge networks were used as part of a comprehensive
KM framework in another global oil and gas company. Chapter 34 describes
an iterative piloting approach in a fast-moving, rapidly growing technology
business. Chapter 35 provides an unusual case of a ‘green field’ KM effort
for the Singapore Youth Olympic Games, using very simple technology and
a grounded focus on consistency, learning and knowledge transfer. Finally,
Chapter 36 describes the KM journey over the past decade in a public-sector
agency in Malaysia, illustrating how KM was first rolled out, then embedded, and then how its sustainability was addressed.
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Implementing
KM at Mars
30
B Y L I N DA DAV I E S
Former Knowledge Management Director, Mars, Incorporated
Context
Mars, Incorporated (Mars) is an American global manufacturer of
confectionery, pet food, and other food products. The company is privately
owned and employs more than 75,000 ‘Associates’ in more than 74
countries. This chapter details the main implementation phases of KM at
Mars, which took place from 2003 to 2011.
KM and collaborative networking have a long history in Mars. The company is typified by a very informal means of communication, and networking is a key element in the way things are done. In earlier days, when the
company was smaller, much of the connectivity and knowledge sharing was
achieved by Mars family members travelling to business units, spotting connections and prompting people to get in touch and work together. As Mars
grew, this was no longer an efficient method of connecting associates and
the journey to an embedded KM organization began. This journey has provided a number of key learning points.
Know why you’re doing what you are doing
KM in Mars started formally in 2003 with a KM conference attracting
around 100 associates from around the business. Initial KM work streams
in that first year led to a second conference one year later that came to the
attention of the Mars CEO. The great excitement at such senior support was
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Case Histories
rapidly muted by his strong guidance that whilst he ‘instinctively believed
that KM would benefit the business’, until he could understand specifically
how this would happen, the conference could not go ahead.
I now look back on that series of events and see it as the key that unlocked KM at Mars. It taught me the utmost necessity of knowing why we
were doing what we were doing, of focusing on the business need, and determining the size of the benefit KM could bring. It made me realize that we
must be able to articulate the business gains we were aiming to achieve with
the KM initiatives and how we would deliver these gains. And it highlighted
that unless we ourselves could clearly explain the importance of our activities and how they would help the business, we could not expect anyone else
to understand KM and what it could offer.
In March 2004 we went back to the CEO with a plan that focused on
how KM could help deliver on the Mars strategy. This revolved around the
four techniques that we believed offered most benefit within the Mars
­culture – communities of purpose, communities of practice, peer assists and
knowledge capture. For each of these we detailed how and when it would be
of benefit, accompanied by examples from other companies of the benefits
achieved. The plan was approved and we were given 18 months to ‘prove
the concept’ of KM.
Focus on critical activities that help
deliver strategy
The first few KM initiatives chosen were critical. The initial plan notes that
‘There is neither the time nor the money to capture all information and simply hope that this helps do everything better. KM efforts must be focused on
key performance drivers where it will have maximum impact’. With limited
timescale, resource (a KM team of three) and budget, the pilot applications
had to be chosen carefully, to avoid spreading the resource too thinly. Only
those activities that promised an obvious and demonstrable effect on the
achievement of a key strategic objective were undertaken. We developed a
flow chart to assess each potential project to ensure the team stayed focused
and did not get distracted by less impactful initiatives. We developed a habit
of focusing on how to use knowledge to solve the business problem, rather
than on how to use a particular KM approach more widely.
Implementing KM at Mars
Initially, the whole KM team was focused on a few key areas to demonstrate the gains that could be achieved. Communities of purpose were believed
to offer the biggest potential, and senior associates were invited to nominate
key strategic challenges that were proving difficult to crack using standard
approaches. Four were chosen for further review, one of which was subsequently dropped as the challenge was too broad. This delivered a valuable
lesson about bounding problems and dividing them into manageable pieces.
The remaining three challenges provided a framework for the following year’s
activities, with a community of purpose formed for each.
Each KM team member was responsible for one community of purpose.
When required, other resources were either borrowed from the business
units or contracted in from outside. In general there was one KM team
member and around half a contractor per challenge. The communities of
purpose were set a clear business objective and specific targets that could
not be achieved by each unit/region working alone. We set impact metrics
and measured them regularly. Each had a senior associate as champion and
a community leader who was visibly responsible for global progress,
­resource and funding. These communities provided a forum that focused
expertise on the specific challenge, provided a route for knowledge to flow
around the business, and created a targeted network of associates who could
call on each other for advice and support.
Within each community of purpose, the principle of focus on business
impact continued. Each community focused on two or three work streams
at a time, mainly using peer assists or knowledge capture and dissemination.
The work streams were reviewed every six months and, as soon as they were
substantially completed, were replaced by new activities. The impact of the
communities of purpose was measured several times per year and reported
at a senior level, keeping visibility high and ensuring motivation/commitment to the activities. The communities rapidly delivered significant benefits
to the business, providing buy-in to KM activities at the very top.
The power of focusing on two or three challenges in any one year became
apparent, resulting in rapid progress and big wins and proving the concept
of the value that KM can bring to the business. This led to a regular increase
in KM budget and resource, which enabled subsequent initiatives. The principle of focus became core to the KM team, with a structured plan submitted each year containing initiatives clearly focused on a maximum of two to
three key business objectives.
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Plan the roll-out to build the KM story
From the beginning, KM was run as a separate division with its own business plan, detailing how and why KM was to be implemented. The initial
plan in 2003 noted:
Knowledge is an asset and must be treated as such. Working our knowledge
assets requires as much effort and attention to detail as any other asset. The
acquisition of knowledge is not accidental. It has to be actively planned and the
implementation of this plan must be resourced.
The business plan followed standard business planning practice, with a
broad three-year time horizon and a detailed one-year plan submitted annually as part of the regular business planning cycle. This detailed the overall
objectives for the following year, the timescale for the planned activities,
plus the costs and resource requirements. In this way, KM became part of
the standard operating timetable, which ensured budgets were agreed and
incorporated in the right timeframes, and provided another route to communicate KM activities and performance to a wide audience.
With Phase 1 (communities of purpose) delivering significant benefits, the
next phase was designed to investigate the benefits achieved when KM was
applied widely within one functional area. All the KM resource (outside of the
communities) was focused on activities within Sales – a function which offered
big potential benefits from KM activities and where there was ‘pull’ for KM.
The functional leader was passionate about connecting people and developing/
sharing best practice and clearly saw the potential to be gained from widespread KM. A number of networks of senior associates were created around
the key Sales challenges, which drove the development and dissemination of
best practice and training in key areas. Sales directors from all segments and
regions were connected through a managed network, and a website was created and actively managed to link all sales associates globally. These combined
to deliver significant benefits, in terms of both sales growth and cost savings.
Go where there is ‘pull’ and keep all activities
relevant to the business and to associates
Communities of practice (CoPs) have been widely used in Mars, and have
been most successful when focused on a specific challenge that is part of associates’ daily activities. They have had greatest success when headed by an
Implementing KM at Mars
associate with a passion for the challenge, and where the line management
chain understands and supports the purpose and benefits of the community.
However, some communities failed to thrive, often due to the lack of a core
purpose linked to the day-to-day job of associates. If the activities of the
community did not directly deliver against business objectives, the community ultimately ground to a halt. The solution was for the senior network formed around each challenge to identify the business areas where
knowledge sharing could help, so that CoPs could be formed around each
of these.
Likewise, knowledge sharing and best practice development has thrived
where it has been related to day-to-day activities and linked to key business
challenges. The communities of purpose identified the key practice areas and
served as senior champions for the development of best practice. Additionally,
community leaders were charged with ensuring that each community member both gives and receives knowledge and expertise, to ensure benefit to all.
The key learning was to ‘go where there is pull for KM’. There have been
areas that offered potential for KM but where the appetite for KM initiatives was lacking – these areas never succeeded. When there was a clear need
allied to a keen interest in KM, the potential for success was much higher.
Measure the business impact of KM activities
The need to demonstrate the impact of KM initiatives means that you must
measure impact. It quickly became obvious that it was the impact metrics in
relation to the business challenges that demonstrated the power of KM to
the business and generated acceptance, rather than the KM activity metrics
(we did use activity measures to help trace the link from KM activities to
results). For example, measuring the number of hits to a website or people
involved in a knowledge capture is only a diagnostic aid; the real measure is
the impact on the bottom line, whether a cost saving, increased sales or
other performance improvement.
The need to measure the impact meant that each KM initiative had a
clearly articulated business performance objective, and each work stream
had a cost and a value. Defining these often took a significant chunk of time!
The means by which performance would be measured was agreed at the
beginning of each initiative, wherever possible using existing business measures. Performance was reported to the sponsor and project champions at
regular intervals, never more than six months apart.
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In addition, the KM team’s performance was formally reviewed on an
annual basis. Progress against the objectives was reviewed and the plans and
budget for the following year agreed. This review provided a showcase for
KM, demonstrating how it had helped strategy. It also generated senior-level
understanding and acceptance of KM activities. Once KM had achieved a
high level of acceptance, the formal review was no longer necessary and KM
is now reported as part of the standard business review.
Be consistent
Once the KM concept had been proven in the Mars culture, we needed to
develop a position and presence within the business. Consistency was key to
this, including the consistent focus on a few key activities, regular reporting
of the team’s activities in a standard format, and inclusion in the normal
business planning cycle. Branding of the team and marketing of the activities was also necessary. A team logo and team colours were developed along
with a suite of marketing brochures outlining the key KM techniques, where
they could be used, how they deliver value, and examples of where they had
been used in the business. These were made available in hard copy and
­online. Standard formats for reports and presentations ensured the work of
the KM team was recognized. A regular rhythm of communications in a
consistent format to key stakeholders helped to keep KM initiatives ‘top of
mind’ as a valuable business tool to solve critical issues.
Select the team members carefully
The central KM team began as a small team focused on large-scale projects
that spanned product categories and/or regions and targeted specific global
business challenges. Its areas of responsibility included:
●●
full support for selected communities of purpose;
●●
global knowledge capture around key strategic challenges;
●●
●●
communication of the benefits of communities of practice and training
associates in their use;
identifying and developing the KM techniques and approaches most
suited to the Mars culture, and training associates in these.
Implementing KM at Mars
As belief in the approach grew, the team increased in number, gaining an
additional team member every one to two years. As each additional team
member joined, KM activities for an additional function or business area
were added. Each team member therefore had overall responsibility for a
specific business area, which provided continuity and built the experience
base.
Choosing the right type of person to join the team was paramount. Team
members were selected on the basis of business acumen and experience, interpersonal skills, especially listening skills, and ‘political’ agility. There was
no requirement for KM qualifications or experience – these could be taught.
The team members came from a wide variety of disciplines and backgrounds,
which built strength and experience into the team. The one thing they have
in common is a strong ability to interact and build relationships with ­people.
KM at Mars is about building strong and vibrant networks and ­facilitating
this means having very strong people skills.
Build top-down support
Top-down support has been critical throughout our KM journey. From day
one the understanding and sign-on from senior leaders has enabled KM to
deliver its potential. Each project had a senior-level sponsor whose role was
to identify the focus areas, ensure the initiative remained relevant to the
business, and communicate with their peers. They also set the expectation
that associates within their division should share and use knowledge. The
role of the KM Director was to ‘sell’ KM throughout the business. Using a
clear understanding of the key challenges of the business and the needs of
senior leaders, the leadership communicated the potential benefits and directed the team to the areas of greatest need.
Ensuring the senior leaders understand and appreciate the value of KM
has been a constant requirement, as the various leadership teams change
and evolve over time. There has been a constant communication programme
amongst senior leaders to ensure their understanding of KM and its impact
in their area – this has been rolled out as the initiatives reach each function.
This is particularly important when associates change, especially those leading or championing an initiative. It is at this time that some initiatives have
stalled – ‘a new broom sweeps clean’. Support from the most senior leaders
has helped ensure the new incumbent knows the expectation on them to
continue key KM activities.
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Embed critical knowledge via existing
business processes
A number of activities have been identified through KM initiatives that are
deemed to be critical to future Mars strategy. Chosen by the business leaders
in each function, these have been incorporated into Mars standard approaches that are documented and mandated throughout the corporation.
This route is only taken for the very few actions that are deemed to be critical. These are chosen by the business leaders within each function.
Other knowledge areas have been embedded through training. Mars
University offers a comprehensive training programme for associates, and
key elements from knowledge capture have been developed into training
courses, workshops and booklets. Other activities have been launched at
workshops or conferences and are positioned as ‘concentrated experience’
for use by others in a similar situation. These are adopted by associates because they deliver a real benefit – the initial work to identify critical areas
and understand how KM would deliver benefit helps ensure the output is
relevant to associates’ daily work lives.
When is it over?
What happens when implementation is over? In my experience it is never
over! There is a continual need to keep the focus on key strategic issues and
to ensure the team is not distracted by other activities. The constant rotation
of senior leaders, community leaders and sponsors requires a continual
communication of the role and benefit of KM. However, as KM spreads
more widely throughout the business and the number of associates directly
impacted by KM increases, the role changes. Associates new to roles are increasingly arriving aware of the benefit of KM and/or arriving to find teams
regularly sharing and using knowledge and demanding to do so. Our role
then becomes more about communication around specific applications and
a continual communication of the benefits achieved from KM.
Implementing KM at Mars
Summary
The implementation of KM at Mars is almost a textbook illustration of
many of the principles in this book. The constant focus on business drivers,
the selection of key knowledge areas, the communication programmes, the
step-by-step approach to delivering business value at each stage – all of these
are real-life applications of the recommendations from previous chapters.
The result for Mars has been an ongoing journey of embedding KM as a
crucial element of business performance.
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31
NASA –
emergence,
evolution and
resilience of
a KM programme
BY B A R B A R A F I L L I P
Former KM lead within the Flight Projects Directorate, Goddard
Space Center
Context
The National Aeronautics and Space Administration, better known as NASA,
was created as a US Federal Government agency in 1958. In pursuit of its
mission, NASA has, over the years, played a key role in the creation of new
scientific and engineering knowledge. It has also suffered a number of highly
visible failures, including the Challenger and Columbia Space Shuttle
accidents. Aerospace is a high-risk enterprise and NASA has always needed
to balance innovation and risk taking with safety, sound project management
and, ultimately, accountability to taxpayers. The Agency’s complex and
diverse programmes and projects are managed from NASA headquarters in
Washington, D.C., as well as through NASA’s nine Centers and smaller
facilities in locations around the country, often in close partnership with
higher education institutions, commercial partners, and even the space
programmes of other countries. This technical and organizational complexity
demands effective management of critical knowledge.
NASA
Building a resilient KM programme
While some organizations have seen KM come and go, NASA has consistently worked to improve and strengthen its KM programmes. At the Agency
level, KM needs to be embedded within the core business of the organization (engineering), and closely aligned with learning processes in partnership with NASA’s internal training arm. Combined with continuous top
leadership support for KM, these two factors have contributed to the resilience of the KM activities over two decades.
Another key contributor to the resilience of KM at the Center or
Directorate level is a focus on value. This focus is a necessity for the survival
of any KM programme. Within the Centers, budget pressures are such that
KM may not be perceived as a priority. The Center-level CKOs must continuously focus on delivering valuable services to their internal constituents.
There is little tolerance for wasted resources (people’s time and funding) in
an organization where funds, when they are available, are directed as much
as possible to NASA’s missions and the hard deliverables that will always be
given priority. A KM activity that does not add value and that does not contribute to ‘mission success’ does not survive very long.
In addition, NASA’s KM activities have evolved over time to accommodate the decentralized nature of the organization and in reaction to key
events and external pressures. In response, rather than attempting to centralize the KM function, NASA made a concerted effort to provide a HQbased coordinating function with some responsibility for setting policy at
the Agency level, combined with flexibility at the Center level and within
the Directorates. This means the KM efforts can be adapted to local requirements and efforts can be focused on the knowledge that is critical to
the respective Centers. This ‘federated approach’ to KM has provided the
necessary flexibility and tailoring of KM activities at the Center level while
helping the organization as a whole to leverage the combined experience
of the different Centers through the NASA KM Community (Prusak and
Schwartz, 2015).
The NASA KM Community
The members of the geographically dispersed NASA KM Community currently meet on a quarterly basis, alternating face-to-face meetings with
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Case Histories
virtual ones. The community brings together all the individuals who have
KM responsibilities across NASA for a couple of days of presentations and
conversations. The topics addressed at the quarterly meetings typically include a mix of community updates and announcements, an occasional external presenter, and interactive discussions around issues of interest to the
community. For example, one Center may present progress on a technology pilot in support of KM and another may share lessons learned from a
special knowledge-capture initiative.
In the summer of 2018, the NASA KM Community met in one of NASA’s
nine Centers, the Glenn Research Center in Cleveland, Ohio, for one of the
face-to-face meetings. One item on the agenda was a session titled ‘How Did
We Get Here?’ The purpose of the session was to reflect upon the evolution
of KM within the organization. With a mix of KM elders and newbies in the
room, it was an opportunity to recollect how it had all started and reflect on
some of the key milestones along the way. A simplified timeline, based on
the one that was created on that day, is presented in Figure 31.1. The rest of
this chapter will provide additional context and analysis.
KM at NASA headquarters: a tight bond
with internal training
From their inception in the late 1990s, the KM activities at NASA headquarters were embedded in the Engineering Directorate. NASA’s two primary
lines of business are science and engineering. The ultimate goal is to contribute to new scientific discoveries related to the exploration of space, which
requires extensive knowledge of aerospace engineering. It made sense for
KM to be located within the Engineering Directorate at headquarters.
Within this Directorate, KM started with a strong focus on knowledge
sharing within NASA’s corporate training programme, the Academy for
Program and Project Leadership (APPL). APPL was launched in 1999 and
later renamed APPEL. Early knowledge-sharing efforts at headquarters included the launch of the Lessons Learned Information System (LLIS), a
publication called ASK magazine, and the Masters Forums, which provided opportunities for project managers to share their experiences and
lessons.
Meanwhile, some of the other NASA Centers were developing their own
Center-focused KM programmes.
NASA
Figure 31.1
Timeline adapted from Lipka (2018)
Collecting and sharing
stories from projects
1999–2001
ASK magazine
CAIB report
Portal & CoPs
NASA Portal &
Engineering Network CoP
deployed (2005)
NASA@Work is launched
(2010)
ASAP report
Knowledge
Map & Toolbox
An overview of KM
activities across the
organization
New portal featuring
video-based lessons
learned resources (2015)
APPEL and the CKO
join forces
2018
APPEL Knowledge
Services
2013–15
Critical Knowledge
Gateway
2011
Recommendation to
strengthen KM
programme and
appoint CKO (2011)
2008–10
Internal
crowdsourcing
2003–5
Lessons from the
Columbia Accident for
NASA as a Learning
Organization (2003)
APPL
NASA’s APPL programme
provides team and
individual professional
development support
LLIS
NASA Lessons Learned
Information System
initiated
GSFC appoints a
Chief Knowledge
Architect (2003)
KM policy (v1)
KM policy focused on
lessons learned
NPR 7120.6 (2005)
Program
lessons
JSC appoints
a Chief Knowledge
Officer (2006)
Center-specific efforts to
document lessons from
key programmes such as
Apollo, Shuttle, and ARES
I-X
NASA KM
Community
First Agency-wide
CKO is appointed
First face-to-face meeting
of the NASA KM
Community
KM policy (v2)
Broader policy to include
KM strategic approach at
Center level and ‘Federated
Approach’ to KM (2013)
New Agency CKO is
appointed
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Case Histories
KM at a NASA Center: Goddard Space Flight
Center
Two Centers led the way with the establishment of the position of Chief
Knowledge Officer. The Goddard Space Flight Center (GSFC) in Greenbelt,
Maryland named a Chief Knowledge Architect in 2003 (later renamed Chief
Knowledge Officer).
Just a few months before this hiring at GSFC, the Space Shuttle Columbia
had broken apart during re-entry, leading to the tragic loss of seven astronauts. In August of 2003, the Columbia Accident Investigation Board report
was released.
Columbia Accident Investigation Board
(CAIB) report
NASA’s space shuttle Columbia broke apart on 1 February, 2003 as it
returned to Earth from a 16-day science mission. All seven astronauts
aboard were killed. NASA created the Columbia Accident Investigation
Board (CAIB) to investigate the accident. The board released its report in
August of 2003, concluding that the tragedy was caused by technical and
organizational failures.
Of particular significance from a KM perspective was the fact that some
of the organizational failures were reminiscent of the Challenger accident of
1986; a key observation of the CAIB report was that ‘NASA has not
demonstrated the characteristics of a learning organization’ (CAIB, 2003).
Under these challenging circumstances there was a renewed emphasis on
becoming a learning organization. The newly appointed CKO developed a
Goddard Learning Plan, which was updated regularly over the following
eight years, and which provided a framework for the implementation of core
KM practices within GSFC in support of the Center’s mission (Rogers, 2011).
The programme established a strong foundation on a set of key KM principles and developed a series of KM practices such as case studies and the
Pause and Learn, both of which have spread to other NASA Centers. For
example, NASA case studies are used extensively both within NASA and in
academic programmes as effective teaching tools. At GSFC, case studies
NASA
have been used in stand-alone workshops, embedded in training programmes, and integrated into the new employee orientation programme.
The Johnson Space Center (JSC) in Houston, Texas, named its first chief
knowledge officer in 2006, as a direct result of the Columbia accident and
the fact that there were so many parallels with the earlier Challenger accident. In other Centers, KM functions were implemented in a more ad hoc
fashion or as secondary duties for specific individuals.
Evolution of KM at headquarters
and at the Centers
APPEL in its earliest form was a direct response to the Challenger accident.
The failures of the Mars Polar Lander and the Mars Climate Orbiter, both in
1999, had prompted a Government Accounting Office (GAO) audit, which
had ultimately highlighted ‘fundamental weaknesses in the collection and
sharing of lessons learned Agency-wide’ (GAO, 2002). The combined impact
of this GAO report and the CAIB report on the Columbia accident in 2003
(CAIB, 2003) spurred a new focus on knowledge management across the
Agency. One of the key responses was NASA’s first Knowledge Management
Policy document (NPR 7120.6), established in 2005. This was a clear effort
to provide a common framework for processes related to lessons learned.
The policy document, which was heavily based on the existing lessonslearned processes in place at the Jet Propulsion Lab (JPL), clarified roles,
responsibilities and processes for contributing lessons to the existing Agencywide lessons-learned database. Other policy documents already stipulated
some of the responsibilities in terms of documenting lessons learned at the
project and programme levels; therefore this KM policy document was limited in scope to the coordination mechanisms for collecting and publishing
lessons at the Centers, and for inclusion in the Agency-level database.
The early 2000s also saw the launch of some IT-focused KM initiatives at
NASA headquarters, emerging in parallel to the knowledge-sharing activities supported under APPEL. Knowledge was to be made more accessible
through portals and communities, and the first Agency-wide KM portal and
the Engineering Network Communities of Practice were launched in 2005.
At GSFC, the Goddard Learning Plan was being implemented and the
core KM practices were becoming further embedded into the routines of
project work. In other Centers, KM activities were being implemented based
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on Center-specific needs. For example, the Johnson Space Center (JSC)
launched Johnson Knowledge Online in 2008, to capture Apollo and Shuttle
Program lessons. Among other actions, JSC implemented the NASA JSC
Space Shuttle Program Tacit Knowledge Capture Project in 2008 as part of
its longstanding Oral History Program.
In 2009, The Exploration Systems Mission Directorate (at HQ) and the
Ares I-X project collaborated to capture systems lessons. The Directorate initiated a 12-month collaboration with the Ares I-X project management and
project team members to capture and document process-oriented systems
engineering and engineering management stories and lessons. The materials
were presented in a rich narrative combining video-based stories capturing
first-hand experiences carefully bundled with relevant ‘knowledge artefacts’
such as technical reports and project documentation (NASA, 2011).
While many of the KM efforts were focused on documenting lessons
from critical projects, others were looking towards innovation. In 2010,
NASA@Work, an internal crowdsourcing platform, was launched. NASA@
Work was designed to increase innovation and access to ideas and ­knowledge
from within the NASA community (NASA, 2016). Individuals post their specific problem or ‘challenge’, and anyone in the community can contribute to
the interactive discussions and submit solutions and feedback. The programme
is incentivized with some (non-monetary) awards. For example, one challenge
shared across the platform was to find low-cost automotive and related sensors for lunar landing applications. The winner of this challenge was an intern
engineer who came up with a solution that involves the combined use of laser
pulses and long-distance laser-range sensors to produce a more accurate picture of the lunar surface when coming in for a landing (NASA, 2018).
Innovative approaches coming out of this crowdsourcing effort can lead to
completely new and unconventional ways of thinking about tricky problems
like landing on the surface of other planets and even asteroids.
Strengthening of the programme
at the Agency and Center levels
Throughout the past several decades, highly visible failures and external
reviews have provided critical impetus for a renewed emphasis on knowledge and KM. In 2011, the annual Aerospace Safety Advisory Panel (ASAP)
report drove some significant new initiatives (ASAP, 2012).
NASA
Annual ASAP report
Since it was established in 1968, the Aerospace Safety Advisory Panel
(ASAP) has been evaluating NASA’s safety performance and advising the
Agency on ways to improve that performance. The ASAP bases its advice
on direct observation of NASA operations and decision making. In the
aftermath of the Columbia accident, Congress required that the ASAP
submit an annual report to the NASA Administrator and to Congress,
examining NASA’s compliance with the recommendations of the Columbia
Accident Investigation Board (CAIB), as well as management and culture
related to safety.
The 2011 report’s recommendations included 1) the creation of a more systematic approach to capturing implicit and explicit knowledge; 2) the appointment of a formal Agency-level chief knowledge officer; and 3) the designation of chief knowledge officers or equivalent positions at each Center
and Mission Directorate (ASAP, 2012).
In response to the report, the first Agency-level CKO was named, as well
as Center- and Directorate-level CKOs where there were none before. A
couple of years later (2013), a new KM policy was put in place (NASA,
2013). Going well beyond the earlier focus on lessons learned, the new policy gave the Centers greater responsibility for creating Center-level KM strategic approaches under what was now explicitly referred to as a ‘federated
approach’ to KM. The policy on KM formally recognizes that ‘knowledge at
NASA is governed on a federated basis: each Center, Mission Directorate,
and supporting organization can determine the approach that best meets
their needs’ (Prusak and Schwartz, 2015). A summary of the situation is
provided by Ed Hoffman, the CKO, in the box below.
Today [February 2013], NASA is a different organization than it was a
decade ago. The importance of knowledge has been recognized
throughout the Agency… Painstaking efforts have been made to
document the closeout of Space Shuttle and Constellation to preserve
the invaluable knowledge developed in the course of those programmes.
Every Center and Mission Directorate has either a chief knowledge
officer or a point of contact to serve as the advocate for the knowledge
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needs of the organization’s practitioners. Cross-agency support
organizations such as the NASA Safety Center and the NASA
Engineering Network foster knowledge exchanges that connect
practitioners throughout the Agency. These interwoven threads are
helping create a resilient knowledge organization (Hoffman, 2013).
The new policy also institutionalized the quarterly meetings of the NASA
KM Community, resulting in two face-to-face and two virtual meetings each
year. The KM Community, through its leader, the new Agency CKO, briefed
NASA leadership on a quarterly basis. This allowed for regular communications with top leadership to establish the seriousness of the initiative and
maintain continuous buy-in.
To accommodate Agency-wide budget cuts, some necessary adjustments
were made to the KM programme. ASK magazine was closed and replaced
with more digital content, and the annual Project Management (PM)
Challenge, which had gathered hundreds of people within NASA and the
aerospace industry for years, was replaced with a much more targeted
Virtual PM Challenge.
A major effort was also undertaken to document and share critical
knowledge through a new Critical Knowledge Gateway, featuring videobased lessons learned (NASA, 2019).
The new CKO’s office also started an effort to better document and communicate what each of the Centers and Directorates were implementing in
terms of KM activities. The result was the NASA Knowledge Map and the
Knowledge Toolbox. The Knowledge Toolbox served as an educational reference to support KM practice, while the Knowledge Map provided a userfriendly registry of KM activities searchable by Center or category. Six broad
categories of KM activities were identified, as shown in Figure 31.2, and this
continues to serve as a classification framework used Agency-wide.
Drilling down through the Knowledge Map, you would discover, for example, that the Goddard Space Flight Center does a lot of KM work leveraging case studies and knowledge-sharing workshops.
Other efforts are underway to ensure that lessons are transferred to the
next generation of NASA employees and the private-sector actors who are
increasingly taking over what had been traditionally done by NASA itself.
There is a fast-growing private-sector component to space exploration, and
it is critical that NASA’s lessons be transferred to these new actors as well.
The question is, are these bold new actors ready to listen?
NASA
Figure 31.2
Case
studies/
Publications
NASA Knowledge Map – categories of KM activities
Face-to-face
knowledge
services
Online tools
Knowledge
networks
Lessons
learned/
Knowledge
processes
Search/Tag
/Taxonomy
tools
SOURCE NASA website
In 2016, NASA launched the Apollo, Challenger, Columbia Lessons Learned
Program (ACCLLP) which is run out of the Kennedy Space Center. The
concern behind this is that with the passing of time, the connections to past
events recede. While the events may not be forgotten, the lessons may no
longer be so obvious to a new generation of engineers and employees,
whether within NASA or outside it. The ACCLLP aims to keep those lessons
front and centre.
Unlike many past efforts to document and share lessons learned that
were primarily aimed at an internal audience, the ACCLLP effort is reaching
out to a broader community about these programmes and their hard-won
lessons. The result isn’t traditional PowerPoint but rather a visually based
display of artefacts and a storytelling experience that generates discussion.
It isn’t just a history lesson either. The experience places a strong focus on
the lessons learned and their applications to the future of space travel
(Barlow, 2017).
A new beginning for a resilient KM
programme and a focus on continuous
improvement
As of 2018, a change in the leadership of the KM office at headquarters led
to some associated organizational changes. The CKO joined forces again
with APPEL to create APPEL Knowledge Services, consolidating what had
all along been very close links between APPEL with its training courses on
the one hand, and KM on the other hand. This close relationship is also reflected in the fact that the APPEL director is also the CKO, combining two
functions in one position.
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Case Histories
Does NASA always get it right? No, of course not. Just as NASA’s missions need to carefully balance innovation with proven approaches, and risk
with safety, budgets and schedule, so do the CKOs at the NASA Centers and
the Agency CKO. It would be misleading to say that every KM activity undertaken by NASA has been a shining success; KM is absolutely a learning
journey. While KM has been resilient and proven itself to add value and
contribute to mission success, there are persistent KM challenges to address.
For example, audits and other review mechanisms have, at times, faulted
NASA for its failure to significantly improve the utilization of its lessonslearned database (NASA, 2012). These mechanisms provide an opportunity
for the NASA KM leadership and the entire NASA KM Community to revisit its approaches and continuously strive to address KM challenges.
Opportunities for continuous improvement are precisely what the NASA
KM Community discusses and tries to address through its quarterly meetings. Since some Centers have developed more sophisticated and rigorous
approaches to capturing and sharing lessons, the NASA KM Community
quarterly meetings are the perfect place to share best practices. The goal of
these meetings is to provide a continuing mechanism to bring new members of the community up to speed and to shape the evolution of the KM
policy and activities both at headquarters and at the Centers. For example,
to address some of the issues related to the Lessons Learned database, JSC’s
chief knowledge architect has been combining data science and informatics
to create an interactive graph visualization of the lessons-learned data
(NASA, 2017).
Summary
The case history from NASA in this chapter illustrates many of the themes
in this book, not least the need for audit and continual improvement of the
KM framework over time (see Chapter 27). Barbara describes here how
many of the important evolutionary steps in NASA’s approach to KM have
come as a result of such audits, both external and internal – NASA being a
closely audited public organization. Sometimes these were regular planned
audits, sometimes one-off investigations in response to events such as the
Space Shuttle Columbia accident, but each led to a step-change improvement in NASA’s internal KM capability. What is equally striking is the adherence throughout to two basic principles: (1) a federated but coordinated
approach to KM, where accountability for KM is developed through HQ to
NASA
the operational Centers; and (2) a strong focus on value delivery. As Barbara
points out, ‘A KM activity that does not add value and that does not contribute to “mission success” does not survive very long.’ These principles (among
other factors) have resulted in a successful evolution of KM over two decades, and NASA’s KM framework can now be seen as one of the most robust
examples in the public sector.
References
ASAP (2012) Aerospace Safety Advisory Panel Annual Report for 2011, NASA,
Washington, D.C. [online] https://oiir.hq.nasa.gov/asap/documents/2011_ASAP_
Annual_Report.pdf (archived at https://perma.cc/LH6G-M6WK) [accessed
18 March 2019]
Barlow, K (2017) Protecting the future of spaceflight by preserving the
Columbia legacy, NASA, [online] https://www.nasa.gov/nesc/protecting-thefuture-of-spaceflight-by-preserving-the-columbia-legacy (archived at
https://perma.cc/7U3Z-MH64) [accessed 18 March 2019]
CAIB (2003) Report of Columbia Accident Investigation Board Vol.1, Government
Printing Office, Washington, D.C. [online] https://www.nasa.gov/columbia/
home/CAIB_Vol1.html (archived at https://perma.cc/X4E3-WXRU) [accessed
18 March 2019].
GAO (2002) NASA: Better Mechanisms Needed for Sharing Lessons Learned.
GAO-02-195, United States General Accounting Office, Washington, D.C.
[online] https://www.gao.gov/products/GAO-02-195 (archived at
https://perma.cc/MZ8Z-X7WU) [accessed 18 March 2019]
Hoffman, E (2013) Toward knowledge resilience, ASK, 49, p. 4 [online]
https://www.nasa.gov/pdf/724952main_49d_director.pdf (archived at
https://perma.cc/28MG-EQLB) [accessed 18 March 2019]
Lipka, M (2018) How did we get here? A brief history of knowledge management
evolution at NASA, LinkedIn, 2 August [online] https://www.linkedin.com/
pulse/how-did-we-get-here-brief-history-knowledge-management-michael-lipka
(archived at https://perma.cc/4Z6E-9ADJ) [accessed 18 March 2019].
NASA (2011) Knowledge Brief: Ares I-X knowledge capture and transfer, ASK the
Academy, 4 (4) [online] https://appel.nasa.gov/2011/06/10/ata_4-4_ares_
ix_knowledge_capture_transfer-html/ (archived at https://perma.cc/
5N65-2QMH) [accessed 18 March 2019].
NASA (2012) Office of Audits: Review of NASA’s lessons learned information
system, NASA Office of Inspector General, Washington, D.C. [online]
https://oig.nasa.gov/audits/reports/FY12/IG-12-012.pdf (archived at
https://perma.cc/Z67J-GJSP) [accessed 18 March 2019].
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NASA (2013) Knowledge Policy on Programs and Projects, NASA Policy Directive
7120.6 [online] https://nodis3.gsfc.nasa.gov/displayDir.cfm?t=NPD&c=7120
&s=6 (archived at https://perma.cc/N55Z-4MP9) [accessed 7 February 2019]
NASA (2016) NASA@Work Overview [online] https://www.nasa.gov/sites/default/
files/atoms/files/nasa-at-work-overview-jan2016.pdf (archived at https://perma.
cc/U3QP-4M8C) [accessed 18 March 2019]
NASA (2017) NASA expert visualizes lessons learned, CKO News, 29 August
[online] https://appel.nasa.gov/2017/08/29/nasa-expert-visualizes-lessonslearned/ (archived at https://perma.cc/WY7G-YJWC) [accessed 18 March 2019].
NASA (2018) NASA@work challenge winner creates novel approach for future
lunar landings, Johnson Space Center Roundup Reads, 21 June [online]
https://roundupreads.jsc.nasa.gov/pages.ashx/863/NASAwork%20
challenge%20winner%20creates%20novel%20approach%20for%20
future%20lunar%20landings (archived at https://perma.cc/T9WV-2NRP)
[accessed 18 March 2019]
NASA (2019) Critical Knowledge Gateway [online] https://appel.nasa.gov/
knowledge-sharing/critical-knowledge-gateway/ (archived at https://perma.
cc/5TGX-MXTR) [accessed 18 March 2019]
Prusak, L and Schwartz, M (2015) K2020 at ARC: One NASA knowledge strategy
in a federated model [online] http://docplayer.net/17438088-K2020-at-arc-onenasa-knowledge-strategy-in-a-federated-model-by-larry-prusak-and-markschwartz.html (archived at https://perma.cc/4PQG-STDC) [accessed 18 March
2019]
Rogers, E W (2011) Building the Goddard learning organization: a knowledge
management architecture of learning practices to help Goddard function more
like a learning organization [online] https://www.nasa.gov/sites/default/files/files/
KM-LOPlan2011asPosted-09032013.pdf (archived at https://perma.cc/47FLWT8J) [accessed 18 March 2019]
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32
Using the ISO
KM standard
30401:2018 to
sense-check KM
at Petroleum
Development
Oman
B Y H A N K MA L I K A N D S U L E I MA N A L TO U B I
Hank Malik is KM Programme Lead, PDO and Dr Suleiman Al Toubi
is former Asset Oil Director, PDO and visiting industry academic,
Muscat University, Oman
Context
Petroleum Development Oman (PDO) has grown rapidly over the past few
years and is seen as a forward-thinking and innovative organization, adding
value to the economic and societal development of Oman. As the leading oil
and gas producer it is the central engine of the Sultanate’s economy, but is
now increasingly supporting research into and investing in a range of
energy and social development initiatives, including:
●●
renewable energy sources including solar power;
●●
power efficiency;
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●●
sustainable social development programmes;
●●
research and development;
●●
talent schemes.
Introduction
The PDO KM Programme was launched some five years ago and was endorsed by the Executive Committee, who then appointed one of their members to become KM champion and sponsor, which helped greatly to achieve
KM success. As PDO grew in size and complexity, there was the need to put
in place a strategic and practical approach to KM:
●●
●●
that could enable us to better identify, capture, share and apply our
collective knowledge, learnings and expertise;
to help increase safety, alongside our continuous improvement journey in
projects and operations.
Some of the common pitfalls in KM are a lack of clear objectives, no clear
agreement on the scope, and failure to achieve expected outcomes. We
strongly believed in the value of a more consistent approach to KM, using
an internationally recognized benchmark or yardstick to guide us. The publication of ISO standard 30401:2018 was a timely arrival.
We reviewed the prescribed ISO standard 30401:2018 requirements in
depth and mapped them against PDO’s Enterprise KM implementation.
Wherever possible we identified examples of supporting activities. One of
our most important steps in PDO was producing a workable Enterprise
Knowledge Management Framework with a defined KM policy. This provided a good starting point for our review. In this case study we take a practitioner’s view of the ISO requirements, and we have also identified some
areas for future improvement using the standard as a guide.
The standard’s key requirements
and PDO KM reflections
Context: to understand the organization/context, the scope, the needs and
expectations of the interested parties/stakeholders, and to align to the corporate objectives/strategy.
Petroleum Development Oman
When it was initiated at PDO, knowledge management was explicitly driven
from and by the business and its shareholders. The requirements for the
creation of the KM programme were prompted directly by the company’s
executive board and received unconditional support from all its ­shareholders.
Our mandate upon launch was a strong emphasis on improved capture and
sharing of lessons learned and best practices. The aim was to gain operational efficiencies as the business grew rapidly and in complexity, while assuring acceptable health, safety and environmental performance.
Scope of the KM system/KM programme
The PDO board had recognized the KM imperative and created a succinct
set of requirements, so that there was no ambiguity on the expected outcomes of the programme. A clear Terms of Reference document was produced which included the aims, objectives, scope and key dependencies. In
addition, a clear, easy-to-read KM Charter was produced and communicated to stakeholders to gain consensus.
We were steered to start the programme with three pilots in our Major
Projects Delivery area, as this was growing rapidly. It was an area where
improved learning processes were expected to achieve good outcomes in a
high-cost environment. The three pilots were:
●●
lessons learned;
●●
onboarding of new staff;
●●
communities and collaboration.
Knowledge management system
When we first looked at the title of the ISO 30401:2018 standard, we anticipated that the title ‘Knowledge Management Systems’ would lead people
to think that it dealt with IT systems. This is happily not the case. In our
experience the standard provides the basis for an all-encompassing management framework for KM. At PDO we created the PDO KM Framework
with an accompanying KM Code of Practice, which became the definitive
standard for doing KM at PDO.
We focused on the people, learning, expertise and collaboration themes
of KM, and this was communicated consistently in all our KM engagements.
There are four core components to the framework:
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●●
learning;
●●
content;
●●
collaboration;
●●
expertise and skills.
These are supported by key KM processes including knowledge-transfer
methods which we are currently developing for acquiring, applying and retaining knowledge. This aligns well with the prescribed activities and behaviours in the standard.
One interesting observation is the reference in the standard to the handling of outdated or invalid knowledge: this was a prompt to us to review
the growing number of knowledge resources and lessons.
Knowledge conveyance and transformation
These are the activities and behaviours supporting the knowledge flows in
the KM system, eg knowledge sharing, communities, collaborative sessions,
developing content such as procedures and guidelines, and applying learning
into practice.
Within our KM framework we place emphasis on the human and learning
interactions and we introduced a series of collaboration activities such as
communities of practice and storytelling, knowledge cafés and knowledge-­
capture processes for knowledge retention.
We have written procedures and guidelines to support our KM programme and they have helped us to gain a degree of compliance and assurance in our initiatives. A great deal of effort is focused on capturing, codifying and applying lessons and then embedding them. This is supported by our
Learning Knowledge Base (LKB), which was successfully developed in-house
by our SharePoint team, and currently has over 7,000 lessons to date. An
approved Lessons Learned Knowledge Process was designed and deployed
successfully. In certain cases where valuable lessons were approved as a best
practice by the relevant technical authorities, the content has helped to support and update our engineering and operational processes. We also had
success in disseminating this knowledge through focused Learning
Knowledge Cards (featured lessons), which were effectively ‘snapshots’ of
the learning and the outcomes achieved, presented in easily digestible form.
Content management is one of the core KM components in our framework. We are compliant with the PDO policies for information management,
records and document management, and risk compliance. With our Learning
Petroleum Development Oman
Knowledge Base, we built a taxonomy for the learning content with agreed
metadata elements for tagging.
Knowledge management enablers
Identified enablers should be integrated into the KM system, covering the
prioritized domains.
In line with the ISO standard, our internal KM Code of Practice explicitly
states that enablers are key to the success of KM in PDO. In our review, we
were pleased to see that our ‘enablers’ mapped quite well to the standard`s
key areas discussed below.
Human capital
Successful KM depends on effective human capital and supporting processes. Within our KM Framework we make specific reference to identified
roles with responsibilities to support KM. In fact, before the KM team even
engages with a new PDO business, we require that these roles are allocated,
to show accountability and commitment. We aim to introduce the desired
KM behaviours into the annual performance review in the future to help
increase user buy-in.
Processes
PDO created a Learning Knowledge Procedure for the capture and applying
of lessons learned, which is now being increasingly adopted with a clear approval process. At designated stage gates in the project lifecycle it is mandatory to deliver lessons learned. Increasingly we are also now placing emphasis on the key lessons from significant incidents in order to help avoid the
same occurrences again; these can be either HSE or process based.
In addition, we are developing methods to support knowledge transfer
processes including knowledge harvesting, knowledge sharing and knowledge retention.
Technology and infrastructure
The central KM team has a home base within the newly named Information
and Digitalization Directorate (IID), which will be leading PDO’s exciting
digital transformation plans. A good example of KM supporting the digital
journey is our involvement with early cloud-based collaborative communities for forums and working groups where we use the SAP Jam platform. In
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Case Histories
addition, working closely with the SharePoint development team, a small
number of enterprise-wide solutions supporting KM processes have now
been successfully rolled out.
Governance
Right from the beginning of the PDO KM journey we placed emphasis on the
need for a robust KM governance model to be put in place to provide direction and accountability. We launched the PDO Enterprise KM Steering
Group, which had senior representation from the participating businesses
and was chaired by our KM sponsor, Dr Suleiman Al Toubi, a former southern asset director on the committee. All supporting KM documentation and
processes, including a formal PDO KM Code of Practice (CP-201), had to be
approved by the KM Steering Group before being released. This provided a
good level of corporate assurance that we were moving in the right direction.
Knowledge management culture
It is important to embed the appropriate knowledge management culture
for sustainability with supporting connections and activities.
When we designed the KM vision and early definitions for KM in PDO, we
made reference to the 4 C’s of KM:
●●
connections;
●●
collaboration;
●●
collection;
●●
culture.
Having the right culture for knowledge sharing is a must for KM success, so
we were pleased to see this emphasized in the ISO standard, with further
examples explained in Annex C. We were extremely lucky that the Omani
culture is indeed one that supports learning, collaboration and communication. Staff are comfortable to share ideas and learn lessons; overall, we
would say they have demonstrated a respectful and nurturing approach to
building and sharing our corporate knowledge. Good team and collaborative behaviours are recognized and there is a series of Executive Awards
throughout the year to encourage this. This supports a conducive culture for
learning and a sense of collective ownership for doing the ‘right thing’ for
both PDO and Oman. Having the right culture in place makes running the
KM programme feel very worthwhile.
Petroleum Development Oman
Leadership and commitment
Top management will give support and commitment.
Having supportive leaders within PDO was another very important success
factor in the growth and achievements at KM. In our experience, KM can
quickly wither and die without this senior-level support, so much so that
without it I believe you shouldn’t even consider starting a KM initiative. In
PDO we were lucky to have support from the managing director downwards and had an inspiring KM sponsor in the shape of Dr Suleiman Al
Toubi, a well-respected former asset director. He showed a genuine interest
and passion for KM and chaired the Enterprise KM Steering Group. His
networks and knowledge of the business ensured that KM would be strongly
aligned with business needs and goals.
In addition, we benefited from having a corporate functional discipline
head for KM, Said Al Shaibani. He ensured we followed the relevant PDO
corporate processes, procedures and compliance when deploying KM. This
was invaluable for ensuring that KM could be integrated and embedded successfully within PDO.
Finally, the support from local functional leads and team sponsors was
essential as we rolled out KM and engaged with staff both at head office and
in the field.
Policy
As mentioned earlier, a key policy document was the PDO KM Code of
Practice CP-201, which set out the framework, objectives, guiding principles
and criteria for success. The Code of Practice communicated mandatory
statements for KM and has become an invaluable guiding document for KM
within PDO.
Roles, responsibilities and authorities
The Code of Practice, the KM sponsor and the KM Steering Group were
unanimous on the need for key defined KM roles and responsibilities.
Having mandatory roles and responsibilities makes any KM programme
with the business much more likely to succeed. Within PDO, key roles include a KM programme manager, KM content manager, KM communications and change manager, and selected subject matter experts. In addition,
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Case Histories
a KM governance reporting structure for regular reporting on progress and
performance to the central KM team and to the KM Steering Group was put
in place.
Planning
Actions to address risk and opportunities/KM objectives and planning.
The KM Steering Group consistently ensured a documented planning approach to KM deployment at all levels of PDO. In addition, each new project
has a written charter and terms of reference. New projects start with a workshop where the scope, objectives, risks and opportunities are addressed. This
is an invaluable exercise, and is in line with PDO’s standard risk assurance
processes. Furthermore, regular communications on KM plans to the leadership and broader teams are delivered at functional town hall meetings.
Support
The resources needed, competency, training, communications.
Any KM implementation success will hinge on the level of competency in
the organization. Within the KM Framework and Code of Practice, we made
clear the importance of having appropriate KM competencies in place or
under development. We introduced two specific competencies for those staff
who wished to include KM as part of their job skills set. This was evidence
based and where appropriate was used for career development purposes.
For our pilots we created job descriptions for a number of KM roles, and
these have subsequently been refined. As part of career development, we also
introduced a KM training programme for the business, which included KM
awareness and KM certification training. From this, we are now building a
community of supportive and KM-competent focal points across PDO as
we widen the programme.
Awareness/communication
The importance of communication was also emphasized in the KM Code of
Practice and to support this, the role of the KM Communications and
Change Manager was designed. The role aims to promote KM awareness
and communications with a focus on KM insights, learnings, training and
collaboration as we roll out and embed the programme.
Petroleum Development Oman
Activities included a KM communication plan with planned activities
including Lunch and Learns, a KM newsletter, knowledge business cards
and learning knowledge cards, all branded as PDO KM collateral. When
deploying selected IT solutions, we also created short ‘how to’ videos plus
small video vignettes of the KM team in action.
KM articles on our achievements were published in the PDO corporate
magazine Al Fahal and we have received excellent support from our PDOwide Communications and External Affairs Team. The KM team regularly
delivers awareness sessions across PDO with a set of clear and consistent
messages, and increasingly we are promoting the broader benefits of KM
across Oman with the creation of the first Oman KM community of practice.
Documented information
The KM programme complies with the PDO Code of Practice and policies
for documents, records and information management, and we reference
them in our key publications and guidelines. We ensure that we comply with
the corporate controls including the security classification of documents,
access control and records lifecycle management. The concept of retention
and disposal of redundant or outdated knowledge and learning is something
we are now considering as we review the KM programme plan and future
enhancements.
Operation
To implement and control the processes needed to meet requirements.
Our KM processes are periodically reviewed in line with documentation control guidelines to ensure there is consistency across the organization. All KM
documents (Code of Practice, KM Framework and Lessons Learned Procedure)
are controlled using PDO corporate standards. Other KM implementation
and project plans are controlled via change management protocols.
Performance evaluation
Monitoring, measurement and evaluation.
In PDO, we ensure at the start of each KM engagement that a KM maturity
self-assessment is undertaken to capture the current state of KM against
best practices. This gives some indicative broad measures to benchmark
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and prioritize our campaigns against, but no detailed statistical analysis or
reporting has been undertaken so far. KM KPIs are not part of the corporate business scorecard but are included on a project basis and where KM
is deployed. These are evaluated on a quarterly basis to gauge KM implementation progress and results.
From our Learning Knowledge Base, where currently we have approximately 7,000 lessons, we can identify high-value lessons learned where benefits have been achieved either in cost savings, cost and risk avoidance, or in
time liberation.
As our KM programme matures, we will be focusing more on performance measurement, and plan to introduce consistent enterprise KPIs into
the business at corporate level.
Internal audit/management review
We have had one internal review of our KM programme by an experienced
external party who interviewed key stakeholders from both the business and
the KM team itself. The review produced very useful recommendations,
with the findings presented to the management board. In addition, we aim
to present progress at leadership team reviews and with the KM Steering
Group. We do aim to have a KM review from our internal audit team and
this new standard could be the tool to help self-assess our progress, as we
aspire to be an early path finder within the oil and gas sector and the Gulf
region. Once acceptance of the standard has matured, we may consider a
more formal accreditation process for compliance.
Improvement
Non-conformity and corrective action/continual improvement.
Naturally, as the PDO KM programme develops we aim to review and take
stock of our performance, and improve in areas that need it, as the standard
requires. It is interesting that within our lessons learned and best practices
stream (where we have achieved most success to date) we have begun to
introduce tangible improvements, embedding lessons into selected business
processes. In some cases, a key lesson, best practice captured, or KM process
could be significant enough to update a key company procedure or specification, thus demonstrating how KM can directly add value to the business
with continuous improvements.
Petroleum Development Oman
Conclusions
Using the standard as a basis for self-review helped to validate much of what
we are doing. We were pleased to conclude that PDO’s KM implementation
appears to be broadly compliant with the majority of the requirements of
ISO standard 30401:2018, ranging from a consideration of the business
context and stakeholders, strategic planning supported by key enablers,
through to leadership and support. It was relatively simple to map the range
of activities delivered in PDO KM to the requirements in the standard. The
examples and notes throughout the standard were particularly useful when
undertaking this early review.
We were fortunate in PDO that we have a comprehensive KM framework as the bedrock of our strategy and so by substituting the ISO standard’s reference to the ‘KM system’ with our usage of ‘KM Framework’, we
found it much easier to map to our key components and enablers.
Using the standard as a basis for a self-review also highlighted some useful areas for future development. One takeaway is that we aim to focus on
enhancing our activities in performance and evaluation – monitoring, measurement and evaluation. The need to measure on a frequent basis with the
help of improved analytics and digital scorecards and dashboards is something all KM programmes should aspire to, to help demonstrate the real
value KM can add to any organization. Another takeaway is the need to
focus on housekeeping redundant and outdated knowledge.
Summary
In this chapter, Hank Malik and Dr Suleiman Al Toubi describe the preliminary use of the ISO standard 30401:2018, the management systems standard for KM, to sense check the impressive KM implementation at Petroleum
Development Oman. This is an excellent example of using a standard as a
means for continual improvement of an established KM programme, in this
case in the form of an informal internal audit. PDO found that many of its
KM practices were validated by the standard, and has used the standard to
identify some areas for further development. This highlights the fact that
KM is not a one-shot ‘fire and forget’ programme, and that even mature KM
organizations need to continuously review and seek to improve their KM
framework.
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33
KM
implementation
in a global oil
and gas company
BY DA N R A N TA
KM Leader at GE
Context
The company described in this chapter as Oilco is an independent and
international oil and gas exploration and production company, with offices
all over the world. The story starts in the early 2000s – a time of
consolidation, mergers and acquisitions in the oil sector, when many
organizational leaders found themselves in charge of a decentralized
collection of autonomous business units. Each unit had their own practices
and knowledge, with multiple barriers to knowledge sharing including time
zones, language, rewards, recognition, and most importantly a dearth of
trusted relationships, based mainly on the fact that many people did not
know each other. This story explains how these barriers were gradually
dismantled within Oilco as part of their KM implementation programme.
A focus on collaboration
The genesis of KM within Oilco came when the leaders who had orchestrated many of the strategic transactions saw first-hand that workers in different parts of the world were effective, but not connected. This led to a
massive amount of ‘reinventing the wheel’ – solutions to a problem that had
Global Oil and Gas Company
been solved in one location were not being shared with other locations.
The leadership recognized the potential value of enterprise-wide knowledge
sharing as a way to meet the company’s safety, environmental and operational challenges. They felt that global collaboration within and across job
functions and business units could deliver significant cost savings and productivity benefits, especially if operations were made more consistent.
Moreover, the leadership knew that collaboration represented the ‘horizontal’ movement of knowledge across business units and that this was their
desired knowledge-sharing culture.
Connecting sharing to the business –
a bold approach
Oilco recognized that it needed an initial catalyst to show how collaborative
behaviour could benefit the employees around the world. The first attempt
was an effort to collect success stories of where employees had shared
knowledge leading to business success. After more than six months, the success story collection results were abysmal. Employees did not see why they
should take time to fill in a form documenting successful examples of knowledge sharing, and very few submissions were made. The problem was that
there was no clear connection between the desired behaviour and the bigger
prize – global knowledge sharing coupled with business value.
To overcome this, the company leadership made an astoundingly bold
decision. They told their regional leadership that participation in knowledge
sharing would be part of Oilco’s annual bonus programme. This was astounding since very few other companies would ever, even to this day, consider being this overt about the connection between collaboration and
­business value.
The result of linking knowledge sharing and the bonus programme immediately got the attention of business unit leadership and employees. The
number of knowledge-sharing success stories increased dramatically, to an
almost overwhelming degree for the small central KM team. There was another problem: what kind of rewards could match the energy and the emerging importance of knowledge sharing?
The central team quickly put a programme in place for global awards,
with award categories named in conjunction with the desired collaborative
behaviour. In retrospect, the awards were a masterful stroke that helped the
sharing activity to focus on quality. The awards went on to become highly
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coveted and represented the fact that the most significant reason employees
shared knowledge was professional pride and the fact that they wanted to
help each other.
The KM team recognized that this initial success would be fleeting at best
if there was no sustainable framework put into place to ensure that knowledge sharing was effective and yet simple enough that employees did not see
it as a burdensome part of their daily jobs. The answer to this was the disciplined and formal creation of knowledge networks (a term Oilco preferred
to the more ‘fluffy’ term ‘communities of practice’).
The link between knowledge networks
and business results
From the beginning, Oilco’s knowledge-sharing programme was linked to
the business drivers, so that collaboration between people in different regions or units would directly impact the business results. To make this linkage, the knowledge networks had to demonstrate a clear business case with
support from leadership before they could be approved, and then they had
to create a set of deliverables in the service of the business at a global or
regional level.
These two principles had a profound effect on the nature and character
of knowledge sharing at Oilco. The business alignment provided clear justification for why network members should invest their time in a knowledge
network, and ultimately led to more focused ‘purposeful collaboration’.
They also supported connectivity and horizontal integration across disparate and siloed business units and disciplines.
Oilco’s approach to building and sustaining effective networks focused
less on finding the right technology and more on guiding people to change
the way they related to one another and their work tasks, and adopting new
behaviours such as:
●●
proactively seeking answers or solutions from experts or peers;
●●
getting rid of the ‘not invented here’ mindset;
●●
actively sharing know-how;
●●
using knowledge-sharing activities as a routine way to do business.
The network portal site template was then adapted to reflect or enable these
behaviours.
Global Oil and Gas Company
Connecting people and governance
Systematically connecting people through business-focused networks became the primary driver for Oilco’s knowledge-sharing strategy. These were
networks of practitioners in specific knowledge domains, such as engineers,
geologists and drillers. The networks were supported by social technology
such as discussion forums and wikis, and were headed by a network leader,
reporting to a network sponsor. The networks enabled employees to break
down artificial barriers, build up reservoirs of trust, and engage in dialogue
and other collaborative activities to improve work performance. Network
members could exhibit professional pride by sharing their experiences to
help others mitigate risk, influence decisions and increase safety as well as
improve overall operational efficiency.
The knowledge networks were strengthened and stabilized by a set of
specific rules for every aspect of the networks. The creation of this governance framework was an ongoing journey that required regular interactions
with employees and leadership across Oilco to ensure that the governance
was both adopted, and provided clarity on (for example):
●●
●●
●●
●●
the approach to measurement of business value, through measuring the
impact of problem solving;
the approach to network creation, with a business case followed by
appointment of the network leader, followed by network launch;
the approach to continued development of the network through a series
of maturity stages;
protocols on how knowledge would be managed in the network, including
guidance on discussions, content, expertise, workgroups, and wiki articles.
One of the factors identified by Jim Collins in his book Good to Great is
what he calls the contribution of ‘relentless discipline’ in achieving breakthrough results (Collins, 2001). This was the effect of the governance
­created by Oilco’s central KM team in charge of knowledge sharing. The
disciplined and systematic approach to governance led to consistent results
and an overall system that supported collaboration and made sense to
global users.
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Visible leadership led to knowledge
network growth
Oilco began its most significant knowledge network push in late 2004. The
company’s KM team of experienced consulting advisors worked directly
with senior leadership to create and implement the ambitious governancebased knowledge-sharing model and strategy. The executive leadership support enabled the launch of the first few knowledge networks in early 2005,
representing the beginning of collaborative bridges between siloed business
units and disciplines scattered around the globe.
By year two, the number of networks had grown to nearly 60 and by year
three about 80 networks were operating. The governance in place allowed
for the efficient and consistent creation and launching of the knowledge
networks. All the networks were global in order to create the biggest reach
and greatest value. Eight years into the programme, the number of networks
had grown to about 150, with membership representing the vast majority of
all knowledge workers. Employees often belonged to multiple networks,
averaging about three to four networks per member, thanks in large part to
the consistency of each network’s look-and-feel functionality. The systematic sharing and capture that this consistency enabled, formed the cornerstone of the company’s strategy to retain critical knowledge from the most
knowledgeable people and to make it accessible to everybody, with finding
and re-using knowledge becoming a major focus. This provided a significant
boost to employee productivity.
By this time knowledge sharing at Oilco was widely driven from the top,
with executives at all levels supporting and promoting the knowledge networks and elevating the importance of knowledge sharing as it became
­embedded in the culture and the company’s DNA. In an Oilco’s employee
opinion survey, for example, knowledge sharing received the second highest
increase in employee satisfaction results, even though, when the strategy was
formulated and the programme began, most employees would likely not have
recognized terms such as ‘knowledge sharing’ and ‘knowledge networks’.
Building sustainability
Once each network was launched, the centralized support team provided
guidance and support through coaching, technical solutions and best practice
Global Oil and Gas Company
sharing across the networks. Guided by this team, Oilco developed a process
for networks to evaluate themselves against pre-determined success factors.
Knowledge network leaders met with network specialists on a regular basis
for a detailed assessment of the network’s health and business impact. These
were mandated sessions, with every network requiring at least one per year,
where solutions were discussed to increase the network’s business performance across the standard success factors. Competition through internal
benchmarking with other networks became a key success factor over time,
and this evaluation process, along with audits of network portal site effectiveness and analysis of the network business cases and KPIs, clearly increased the likelihood of continued network success.
Knowledge discussions and lesson learning
A core component of Oilco’s KM approach was connecting people through
collaborative portals so they could discuss and share best practices and lessons learned. Since about 50 per cent of the global workforce spoke English
as a second or third language, the portal sites (all in English) became the
‘great equalizer’ and employees were often more comfortable communicating in writing on the portal sites than discussing on the phone. Collaborative
portals helped technical professionals who were faced with similar problems
around the world to seek knowledge and expertise from their peers and so
make quicker, better-informed decisions.
The network portal sites, managed and monitored by the central team,
also enabled newer and less experienced employees to tap the deep well of
expertise from global subject matter experts. They could seek clarifications,
input, ideas and validation of approaches to problems, acting and operating
as part of a global company. It actually became frowned upon for an employee to act independently on a complicated work task before conferring
with the appropriate knowledge network.
The cumulative number of discussion threads surpassed thousands annually across all knowledge networks, and the number of hits across all portals
soared to more than 2 million per month as more and more network members realized the positive results of global collaboration.
Promoting knowledge re-use
As the discussions evolved, so too did Oilco’s sophistication at expanding
the impact gained from lessons learned. The central team developed a unique
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technology that enabled network leaders to share with other networks a
single discussion thread from their portal, without duplicating the thread
and while keeping the integrity and flow of the replies in a single thread.
Discussion threads were usually initiated by a network member asking for
help and advice on an operational problem, and this feature dramatically
expanded the number and global reach of potential solutions. On average,
discussions shared with related networks received twice as many responses
as those that took place within a single network.
The discussion-sharing tool was widely used and greatly enhanced the
value from lessons learned, as decisions were influenced across functions
and streams of the business. Network members could use the portal for
peer-to-peer problem solving, or broad-based learning through discussions
guided by senior practitioners and subject matter experts; or they could
search or browse through organized stores of existing knowledge and
­lessons. This not only reduced the degrees of separation between the knowledge workers, but also increased cross-organizational trust through the
demonstration of ‘human vulnerability’ that asking questions in public networks demands.
Knowledge synthesis: closed discussions
and an enterprise wiki
As discussion within the networks flourished, a natural second-order question arose – ‘What should we do with all the unstructured knowledge collected in the discussion threads?’ The two-pronged solution consisted of
closing discussions and creating an enterprise-wide wiki – both enabled by
unique technology and processes.
The central team recognized that the knowledge within online discussions should not be left to age on network portals. Many discussions contained detailed analysis and background information that represented an
extensive body of knowledge from experienced network members. The KM
team researched those discussions that were deemed to have successfully
reached their conclusion, and created a process and policy to encourage
network leaders to officially ‘close’ those discussions. These closed discussions were turned into searchable documents and added to a knowledge
network’s content library for members to re-use. This resulted in the formation of a valuable, vast and searchable repository of knowledge assets.
The next step was to begin linking them through the development of an
enterprise-wide wiki.
Global Oil and Gas Company
The wiki concept was familiar to Oilco staff, and this proved to be a
natural place to capture the insights and wisdom that had originated from
the knowledge networks, and to keep them up to date. Internally branding
the wiki sent an important message that this was the one and only place for
contextual, encyclopaedic knowledge for Oilco. To introduce the wiki to the
enterprise, the central team created a set of high-end, computer-based training modules. The team also met regularly with individuals from the business
who were appointed ‘wiki moderators’ to ensure they were aware of the
newly created and emerging wiki governance standards.
Measuring knowledge network activity
Oilco believes that ‘you manage what you measure’. Keeping detailed records of the business impact delivered by the networks served to galvanize
sponsorship and attract and sustain new members. Success stories provided
a measure of the overall benefit of knowledge sharing, while knowledge
networks also provided more specific measures of delivered value based on
their business case objectives. Some networks used non-monetary measures
for success, such as health, safety and environmental improvements, or mitigation of risk. The central team learned to be flexible with measurements to
ensure that measures could be made, so long as those measures were aligned
with the high-level business objectives of Oilco.
The overall business impact directly related to knowledge sharing measured in the hundreds of millions of dollars over a period of several years.
This was calculated by adding the business benefits from operational problems solved through the re-use of knowledge, or best practices re-used for
business gain.
Summary
Oilco worked for more than a decade with unwavering commitment and
discipline towards its vision of creating a workplace where employees continually delivered additional value through global collaboration and knowledge sharing. At Oilco, support for knowledge sharing and collaboration
came from the executive level and cascaded downward and outward
throughout the company, supported by a robust framework of knowledge
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networks, with supporting roles, technologies and governance. Oilco learned
that creating a collaborative culture is a never-ending journey with two elements at its core – shaping behaviours, and demonstrating business value.
Reference
Collins, J (2001) Good to Great: Why some companies make the leap… and others
don’t, Random House Business, New York
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34
KM
implementation
at Huawei
B Y TA N X I N D E
Former leader of the Huawei KM programme
Context
Huawei Technologies Co. Ltd is one of the world’s fastest-growing global
brands, and one of the few giant Chinese multinational companies. In 2015
the company was the world’s largest manufacturer of telecoms equipment,
and among the largest smart-phone manufacturers. One of Huawei’s
divisions designs and manufactures telecoms equipment and smart phones
(referred to in this chapter as the R&D domain), and another builds and
operates telecommunications networks (the delivery domain).
KM addresses three business issues for Huawei: the need to cope with
rapid staff growth (in the early 2010s the company was growing by 10,000
staff members per year), the need to learn rapidly from expansion into new
markets and offers, and the need to transfer knowledge from headquarters
in Shenzhen, China, to staff in projects and service teams worldwide
(referred to in this chapter as ‘front-line staff’).
As a company with more than 150,000 employees, you can’t do anything at
Huawei without someone asking you, ‘what’s the value in this?’ Only after
you’ve created value in Huawei’s business and earned your own credentials,
will others accept you. The path we’ve taken in the past several years is like
the north route to the peak of Mount Everest; which is to say, it has been
extremely challenging.
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The value of KM to Huawei
When I first took this position, I was thinking hard about how to do KM. In
the first few months, I was very unsure about the approaches that I should
take according to the KM standard at Huawei, and I struggled constantly to
find the uplifting words I needed to convince myself. Then I read a statement
quoted by one of my colleagues: ‘The value of knowledge management depends not on knowledge or on IT, but on the use of knowledge by an organization’s members.’ These words left a lasting impression on me. Our
corporate CEO also says often that ‘everything we do, we do to live’, and
these words touched me. I put them on the front page of my 2012 report to
the corporate executives and elaborated on them in a few minutes. Later, the
executives told me they thought this statement was very appropriate.
Everything that KM at Huawei has advocated in these last few years, in
every domain, boils down to the question: ‘Does what you do help those on the
front line improve their use of knowledge?’ Of course, one’s use of knowledge
must in turn help improve the quality and efficiency of one’s work.
Jack Welch said, ‘An organization’s ability to learn, and translate that
learning into action rapidly, is the ultimate competitive advantage.’ I’ve always supported this idea, but never quite found the best place to reference
it, until I visited our Nanjing research centre to discuss KM with some team
leaders, and one of them shared their experience from new employee training, touching on this point exactly. The vast majority of new employees are
straight out of university, and they all have something in common, which is
that they need a long period of time before they can work independently.
New employees have one week of orientation training, and then another
round of training with their departments. This training is not particularly
helpful in translating learning into action rapidly. In R&D, g­ enerally it takes
about six months before new employees straight out of university are ready
to do their own work independently, but this team managed to do it in less
than two months. How?
Simple: after entrance training, new employees were split into teams of
five, each team assigned to one module in a previous version of a product.
These modules already had their source code altered, bugs added, and the
goal was to have it debugged in less than 20 days. Teams were under intense
pressure during these 20 days because this time was a critical part of the
review process for graduating from training. During these 20 days there was
an expert on hand, but he/she wouldn't actively help you, of course, only
answer questions, and even then would only provide basic guidance; the rest
Huawei
was up to the employees. After these 20 days of training, new employees
would essentially no longer produce the kind of basic bugs that novices
generally produce. As long as they were able to completely debug their modules in the first 20 days, they would be able to start working on the next
version without too much worry, and they would have a thorough understanding of the system and Huawei’s coding standards. This colleague’s
story made me understand completely that our relationship with HR’s
learning and development department is interdependent, that ultimately our
goal is to accelerate the rate at which employees translate knowledge into
action. The faster this rate is, the greater our competitive advantage will be.
This is something that we can accomplish step by step.
The start of Huawei’s KM journey
Prior to the year 2000, Huawei had had an internal Bulletin Board System
(BBS). In common with many Chinese workers, Huawei employees have the
custom of taking naps during lunch breaks, but I can remember vividly that
around that time, there were a lot of people who gave up napping and instead spent the lunch period in forums online. For example, one morning I’d
be doing some software development, and I’d run into something I didn’t
know how to deal with – so what would I do? I would ask the forum and
instantly had a flood of peers responding to share their experience. But in
2003 and 2004 the company became especially serious about information
security and, unfortunately, closed the forum. I know there are still many in
R&D nostalgic for that forum.
Prior to 2008, each business unit had already started building its own
domain-specific knowledge portals, and at Huawei these kinds of spontaneous, diverse, standalone knowledge repositories were extremely common. In
2008, however, although information security was still a top priority, the
practical demands of research and development (R&D) on knowledge sharing were too great to ignore.
Why was R&D able to bring about KM? Simple: because those in R&D
naturally require knowledge to help them, equip them, and allow them to
deliver their products better and more efficiently. Soon, other departments
like marketing and global technical service (GTS) followed the footsteps of
R&D, using Web 2.0 tools to break down walls between departments and
build two knowledge-sharing platforms, one for R&D and one for nonR&D employees.
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In 2010, our software company faced a huge challenge: seeing as we offer
tailored solutions for our many telecom operators, how can we take the
knowledge and experience from our corporate HQ and deliver it quickly to
our teams at the front lines? As we were in this type of situation, we sought
consulting from Ernst & Young on KM. Knowledge management at Huawei
distinguishes between two types of knowledge: one is explicit knowledge,
the kind that can be written down and seen with the eyes; the other is tacit
knowledge, the kind that exists only in the brain. The knowledge that exists
in the brain is certainly greater and more valuable than the kind that can be
written down. Looking back, Ernst & Young’s plan focused more on the
management of explicit knowledge. Our software company went to corporate management and asked for some policy support, hoping to set a precedent in KM. Corporate management told them to go ahead and decided to
set up a corporate-level project team for KM.
In 2011, corporate management’s directive on the KM project was to
focus on finding its value. We experimented with a few development teams,
introduced consultants, made some progressive trials, and found a bit of
footing. Those in R&D at the time found these ‘project learning’ piloting
methods eye-opening; they didn’t realize that knowledge could be ‘managed’
like this, and the results were very effective.
Then we asked the consultants to offer a report to corporate management. There was a story in this report that management found very inspiring, a case study on BP near the end of 2001. BP has oil wells all over the
world. The cost of drilling wells in one oil field was close to US $600 ­million,
but through KM they succeeded in reducing that cost to $540 million on the
next field. For BP it meant additional pre-tax profits of $60 million.
Combined with our own R&D’s initial successes, this case study convinced
corporate management of the tremendous value of KM. They charged me
with organizing a full-time, corporate-level KM team, and with gradually
establishing a full-time or part-time knowledge manager (we call them
KMers) in each business department.
In 2012, we did two things. The first was to integrate our knowledge
platforms. At the time we had two separate technology platforms hosting
discussion forums for knowledge sharing: one for R&D employees, which
was built in Huawei's R&D zone and later transferred to a common zone,
and the other for non-R&D employees, also in the common zone. There was
still concern over information security, so we asked the leadership for an
executive decision to unite the two platforms and integrate knowledge from
both R&D and non-R&D. We took a lot of criticism, and there were some
Huawei
in R&D who objected, but looking back it’s now accepted as having been a
move in the right direction.
The second thing was to implement the KM methodology. In 2012, our
KM implementation team in the R&D domain focused on one development
team and delivered two pilots in the span of about a year. In the first pilot,
we tested several methods, and the business departments felt it was interesting and indeed beneficial to the quality and efficiency of their work. So when
it was time for the second pilot, the head of the relevant product development unit (PDU) decided on a complete trial and appointed a key business
employee to be a dedicated knowledge manager. This knowledge manager
led the PDU in focusing on the key problems and knowledge gaps most
likely to crop up in this version. After some analysis, we found some teams
with relevant experience and did some interviews and exchanges with them
which allowed our development team to better understand their experience
and do some focused optimization. This pilot delivered so much quality it
earned the development team’s first ever five-star rating. This case study
shows how KM can directly improve the quality of our products and the
efficiency with which we deliver them.
Going back to the BP case study mentioned earlier, according to the way
we distinguish different domains at our company, it is our delivery domain
rather than the R&D domain that has most in common with the BP case.
For example, we once had an overseas project budgeted at US $1 billion.
Where did all that cost come from? There were a few key elements. We
would install our base stations in buildings or on utility poles, each of which
we would call a ‘site’. At the time we had a project in a certain country
where it would take our engineers 20 trips or more to finish a site; it was
extremely expensive.
In fact, we already had mature, integrated solutions from our successful
experience in other countries, but the local teams didn’t understand them
and never used them. We changed to a project manager who pushed hard
for an integrated solution, and eventually got the number of trips needed to
finish a site down to eight. You might ask how much that really changes
things, 8 trips vs 22 trips. Well, every time our engineers visit a site, we take
our partner’s engineers with us, and with every visit we pay them a certain
amount of money, so essentially by cutting the number of trips to eight we
cut costs by almost two-thirds. This is just another reminder of how sharing
knowledge has a direct benefit on production and efficiency.
In 2013, we in R&D piloted KM with 10 or more product teams. At the
time there were five or six teams performing better than ever. Later we did
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an analysis and discovered that fully implementing KM was a very difficult
undertaking, the most difficult part being establishing a true understanding
and adoption of the theory and methods behind KM by our business teams.
As I just mentioned, the path we chose is a very difficult one, and at its core
this is because it is the most realistic, dealing directly with value creation.
According to plan, by the end of 2014 our KM implementation project
was approaching completion, and from then on KM would be carried out
by the business departments. From the first pilot project in R&D to various
domains in the whole company, our corporate-level KM department still
only has three or four people, but with the improvement that each domain
now has its own dedicated KMers; 30 or so people in total. In our business
departments KM is gradually taking root in R&D, sales, delivery, and even
in the operation of several overseas countries.
Going from the HQ to the frontline
Our KM is now going farther than R&D in HQ. We defined our KM goals
as ‘three ones’: it should take one minute to be able to find basic work
knowledge, one day to get questions answered in a community forum, and
one month to capture the experience of a frontline project after it completes.
In the middle of 2014, I went to one particular country where our software
company’s first ‘full IT’ delivery project was deployed. The project was successful and our clients were satisfied.
The competence centre at Huawei HQ invited a KM expert to the country to lead a ‘knowledge retrospect’, spending three days to figure out how
Huawei successfully delivered the project. At 4 pm on the third day, just as
the retrospect meeting was drawing to a close, the consultant asked if anyone had anything to say, and everyone said, ‘Everything I’ve learned was
spoken out!’
This is exactly what KM does for us in the real world: when a project is
completed well, we must use KM methods to gather up all the lessons we’ve
learned. When a project begins, we must use KM methods to identify what
difficulties and challenges the project faces, where the knowledge gaps are,
and which company resources we can call on to help us make it happen.
In the area of explicit knowledge management, we’re not quite as
­advanced as a lot of other companies. From what I’ve seen in many companies’ presentations, they’ve all done some excellent work in managing
­explicit knowledge, especially knowledge base building. At Huawei, many
Huawei
departments are already building their own knowledge bases, so our first
step wasn’t to start from here, because it would likely encounter serious resistance. The path we’re on requires that we first prove our own worth before we prove that we can do a little more. This is what we have to share
from our experience.
All in all, the past few years of KM have been difficult, because the departments we’re in are so far from the business departments, who don’t always understand KM right away. The previous success of R&D was due to
colleagues in R&D who had an interest in KM. We seized the opportunity
and leveraged the influence of consultants and gradually pushed for
­implementation.
Explicit vs tacit knowledge management
Our consultant once gave us some empirical data, telling us, ‘Out of 100 per
cent of the captured explicit knowledge, often only 5 per cent will make it
into real-world application.’ This was a great inspiration for me. If you only
do explicit knowledge management, this means that 95 per cent of your
work is wasted. The transfer of explicit knowledge comes through collection; the transfer of tacit knowledge comes through conversation. There is
an ancient Chinese saying: ‘You can learn more in one sitting of listening to
a wise man than from 10 years of reading books.’ These are wise words indeed. Therefore we should focus on learning during projects, doing what we
call ‘learning before, during, and after implementation’. This kind of learning has been project tested and is very effective. Of course, the process is
very difficult, because you have to convince people to do it, and that doing
it will be effective, which is hard. That’s why it has been so difficult to go
down this path.
The current state of KM in Huawei
By 2016 we had established KM in R&D, and in each business group we
had test cases, all basically in operation at this point. With Huawei’s current
agile development process, we have a focused KM plan for each project. For
each iteration in a product version we do an after-iteration review, and at
the final stage of a version, we do a full retrospect. This is the plan we are
piloting, and within R&D we have pushed it through universally.
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The platform is something we haven’t emphasized much. Our platform
still isn’t as ‘internet enabled’ as others, but we do focus on a few points.
First, we focus on solving real-world problems. We had a test user who
raised a question in our community, a question that had troubled him for
two months, but after just five hours in the community his question received
a complete answer. Success stories such as this are the only way users will
come to trust and rely on our community. The community generates an average of 16 million page views per month, of which 88 per cent are related
to team activity: essentially, every user will at some point join several small
teams. We’re currently focused on developing these teams into true communities of practice (CoPs). We have a standard when it comes to the CoP,
which is that more than 70 per cent of content should answer questions
about basic-level operations. A lot of people thought this standard was too
strict, but from Huawei’s perspective, we start from the ground up, and a
central tenet of the community is to help users solve business problems, or
help business teams solve problems about business innovation.
Second, we focus on people. We’ve done micro-interviews, honorary titles, medals, and special headlines, to honour our users and to self-actualize.
Every year we invite users from all over the world to discuss their needs in
our community, and take steps to implement them in our operating goals.
Finally, we focus on content building. In Huawei’s communities, ‘content
worth reading’ is one of the key elements of attracting and retaining users;
that’s why we need to constantly encourage, develop, and promote quality
content. In our communities’ monthly bulletins, we take the best and most
popular content written by our users and republish it, and even the leadership will see it. We also collect premium content on hot topics like the internet and Big Data and republish it for targeted audiences.
In 2015 we supported a technical CoP that developed extremely well,
resolving over 500 business questions and real-world problems in just half a
year, with average response times of one hour or less; all were detailed questions about hardware design. This community is run not by our KMers but
by several high-end hardware experts who saw a need within this domain
and took the initiative. It was difficult, of course, because everyone in the
company has their own KPIs and finding people with the right enthusiasm
was no easy task. This is one of our business domain’s most outstanding
CoPs ever.
This brings us back to our belief in KM at Huawei:
The value of knowledge management depends not on knowledge or on IT, but
on the use of knowledge by an organization’s members.
Huawei
Summary
This chapter illustrates many of the themes of this book as it describes the
introduction of KM into a huge and complex multinational. The link between KM and value (a strong theme in this book) runs as a thread through
this chapter, with Tan Xinde describing how he met the value challenge
head-on, like ‘climbing the North Face of Everest’. Value, as he explains,
comes when KM is applied by the front-line workers. First the idea of value
came through stories from outside the company, then through internal pilots
such as the R&D project that delivered such convincing results. It earned
this development team’s first ever five-star rating. Mr Tan’s KM team was
small, but was able to operate through a network of KM champions, or
‘KMers’ as they are referred to in the chapter. These 30 advocates have been
leading the local application of KM in the business departments, and will
take a more prominent role as KM takes root.
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35
KM
implementation
at the Singapore
Youth Olympics
BY D O R E E N TA N
Former Head Knowledge Management, Singapore Youth Olympic
Games Organizing Committee
Context
When Singapore won the bid to host the first Youth Olympic Games in
February 2008, the people were elated. The Youth Olympic Games (referred
to by Doreen as ‘the Games’) was the first innovation by the International
Olympic Committee (IOC) in the past 80 years. It would feature all the 26
sports in the Summer Olympic Programme, as well as an integrated culture
and education programme, and would be held from 14–26 August 2010. A
total of 3,600 athletes and 1,400 team officials from 205 National Olympic
Committees would participate.
It would also be the first time that Singapore had hosted an Olympiclevel Games, the previous major event having been the Southeast Asian
Games in 1973. The people of Singapore looked forward to this great
opportunity to showcase Singapore’s hardware, software and ‘heart ware’
to the rest of the world. As a nation, Singapore hoped to maximize this
one-off opportunity to learn from and retain the know-how of organizing
such a mega event, thus enhancing their ability to host future major Games.
This case study describes the creation and implementation of the
Singapore Youth Olympic Knowledge Management Programme.
Singapore Youth Olympics
To plan for and deliver the Games in August 2010, the Singapore Youth
Olympic Organizing Committee (SYOGOC) was set up in April 2008.
Compared to seven to eight years for a full-fledged Olympic Games,
SYOGOC had a much shorter time frame of 2.5 years to complete the
Games preparation. Time was short. The Games was a brand new product
with new components and service standards, and SYOGOC had no equivalent past Games to refer to. An international financial crisis was brewing in
the background. And human resources were limited.
SYOGOC had only one opportunity to deliver the Games successfully.
They had to do it right the first time. No U-turns were allowed. From the
start, SYOGOC’s leadership recognized that KM was needed to:
●●
●●
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facilitate the smooth flow and exchange of information to improve
operational efficiency across SYOGOC;
cultivate a learn-as-you go culture for SYOGOC staff to get on board
quickly and improve work processes as Games preparation progressed;
retain and transfer Games know-how and lessons learned for future
major Games to leverage.
The SYOGOC KM department was set up in June 2008 to spearhead this
initiative.
Facilitating the smooth flow and exchange
of information
The key to facilitating a smooth flow and exchange of information in such
turbulent times was standardization. All SYOGOC staff needed to speak
and write the same ‘Games language’, understand and use the same templates, follow the same information management processes, and refer to the
same updated central information sources. Information should be made as
accessible as possible for cross-referencing and updating. As SYOGOC grew
in size, staff with varying degrees of Games experience came on board at
different times. One of the challenges was getting all staff to speak and write
using the same Games jargon. To help with this, two ‘dictionary’ lists were
created, containing more than 900 acronyms and 700 technical terms, which
were categorized into subject matter areas. These lists were shared on the
network drive for the staff’s reference. Measures were put in place to ensure
that the lists were kept updated and staff were using the correct terms.
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Due to the tight preparation timeframe, things were moving very fast at
SYOGOC. Processes were developed on the fly, and so were corresponding
templates. The KM team became the major producer and standardization
body of SYOGOC templates, ranging from contact report templates to
venue operations manual templates. The release of templates for use by
SYOGOC staff was often accompanied by briefings or mass training sessions for staff, so that all were aligned in their usage.
The procurement and set-up of any KM technology would take at least
six months, and the Games preparation period was only 2.5 years, so
SYOGOC decided not to procure an IT system but instead to leverage on the
network drive for information management instead. Simple as it was, the
network drive became the default information repository across SYOGOC.
It contained both working documents and digitized records.
Document management discipline had to be instilled manually from the
start to prevent subsequent information chaos. Business units and meeting
forums were assigned folders in the network drive based on three-letter
codes. A digital file-naming convention was cascaded downwards so that
document owners and versions could be clearly identified. Folder names and
the Registry file-numbering system had to conform to the Singapore Sports
Council taxonomy so as to enable smooth post-Games knowledge transfer
back to the Sports Council.
Cultivating a learn-as-you-go culture
As the Games preparation progressed, there were new things to learn and
new activities to participate in every day. It was important for all SYOGOC
staff to be in a continuous ‘do-learn-improve-do’ mode. KM activities were
designed to cultivate a learn-as-you-go habit in conjunction with the Games
planning phases (foundation, operations planning, operational readiness
and operations).
During the Games foundation phase, the IOC invited SYOGOC staff to
observe the Beijing 2008 Olympics. After the observation trip, participants
shared their personal experiences and useful insights with their colleagues so
that they could improve their own plans and processes. The KM team developed the post-trip reporting and sharing process, resulting in the first
SYOGOC-wide sharing session in August–September 2008. Following this
session, approval was obtained from senior management to conduct
knowledge-capture workshops for each business unit at the end of the
­
Singapore Youth Olympics
SYOGOC foundation phase. The first knowledge-capture workshop took
place in November 2008, and was designed to answer the following
­questions:
●●
What have we accomplished so far?
●●
Who did we work with during this period?
●●
●●
●●
Which were the knowledge resources that we relied upon, created and
referred to, and where can they be found?
What have we learned and what can we do better the next time?
Are there any adjustments that we need to make for the operations
planning phase?
Two more workshop series of the same nature were conducted during the
operations planning phase for the Singapore Youth Olympics. All three
workshops concluded with an SYOGOC-wide sharing session designed to
highlight functional cross-dependencies and lessons learned.
Even though the SYOGOC organization structure started off with business units as building blocks, these business units would eventually morph
or divide up into functional areas that operated in different venues during
Games time. To facilitate this ‘venuization’ process, ­
knowledge-capture
workshops were also conducted for each venue during the Games operations planning phase. From the first series of venue knowledge-capture
workshops, a model venue-planning toolkit was developed and disseminated in March 2009. The toolkit detailed each micro step required during
the venue-planning process, and acted as a guidebook for all venue-planning
teams to follow. It also documented the lessons learned from various venueplanning teams. Subsequently, after every major series of venue workshops,
the venue-planning toolkit was updated. The released versions were made
available to all staff via the network drive.
During the latter part of the operations planning phase and the operations readiness phase, SYOGOC venue teams further developed their venue
plans into venue-operating manuals. This manual was the documented output of the venue-planning sessions and provided an overview of venue-level
operations and functional area-specific operations details. It also served as a
training guide for the workforce (including volunteers) who needed to operate at the venue. The KM team developed the templates for the venue operations manual as well as the venue functional area operations manuals
based on the experience gained and lessons learned during the ­venue-planning
stage, and subsequently trained staff on the usage of them.
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Besides collating process information and lessons learned from the operations staff, one-on-one interviews were also conducted with the SYOGOC
CEO, deputy CEO, chief operating officer and division directors at the end
of each knowledge-capture workshop series. Each interview was conducted
using the standard after-action review questions (Chapter 14), and captured
the senior manager’s point of view. The interviews were useful for the senior
managers as they helped them to recall and reflect on key project impacts
and cross-cutting implications. The KM team captured suggestions on how
they would manage issues the next time round.
It was not only important for SYOGOC staff to learn quickly during the
Games preparation phases, it was also essential for them to learn on the go
while the Games were under way. In order to help staff learn and improve
upon their procedures during Games time, a during-action review (DAR) process was implemented at all venues. A KM volunteer was deployed to each
venue to assist in the facilitation of the DAR, which was conducted by each
functional team at the end of each shift. At the end of each day at the venue,
the venue manager would use the collated lessons learned as a basis for his or
her end-of-day debrief to all functional heads. From there, an end-of-day report would be produced and sent to the main operations centre. Good
­practices/lessons learned that were useful across venues would be highlighted
and disseminated by the main operations centre to all venues the next day.
Retaining and transferring Games
know-how
During Games time, SYOGOC had about 22,600 staff and volunteers. After
the Games, less than 100 staff would remain to partake in dissolution
­activities. It was crucial to put in place key processes that would allow the
retention and transfer of hard-gained Games know-how to the next Games
organizers and Singapore’s sports community.
Before Games time, as planning progressed within SYOGOC, working
documents were submitted to the IOC at the end of each planning phase for
upload onto their Olympic Games KM extranet. These documents were in
turn made available to future host cities so that they could refer to them
during their own planning phases. In addition, SYOGOC hosted other
Games organizing committees via a secondment programme before and
during Games time. Secondees were assigned to various Games functional
areas to learn about actual Games operations in a hands-on manner.
Singapore Youth Olympics
During the Games, the IOC and SYOGOC jointly conducted the Obser­
vers’ Programme and Visitors’ Programme during which the next Games
organizing committees attended seminars and venue tours to learn about
SYOGOC’s planning considerations and operations. After the Games, debrief and sharing sessions to the Singaporean partner agencies, the IOC and
the Nanjing 2014 Youth Olympic Games Organizing Committee were conducted in November 2010 and January 2011. These sessions were complemented by the Singapore 2010 post-Games reports and transfer-of-­
knowledge materials that were submitted to the IOC for upload onto their
Olympic Games KM extranet.
The post-Games reports, together with the entire network drive, physical
records, media materials and senior management learning videos, were also
transferred to the relevant Singapore government agencies including the
Ministry of Community Development, Youth and Sport, Singapore Sports
Council, the National Archives of Singapore and the National Library Board
to be used as legacy materials and reference materials for future major
Games organization. The lessons learned collated from senior management
were also made available to the Singapore Civil Service College for the authoring of case studies.
In addition to the explicit documentation, the tacit knowledge and experience gained from the inaugural Youth Olympic Games were transferred in
the form of more than 100 assigned staff who returned to the Singapore
Sports Council after the Games. Both explicit and tacit knowledge gained
from the Singapore Youth Olympic Games were mobilized for the organization of the South East Asian Games held in Singapore in June 2015.
Summary
It was both easier and harder than expected to do this KM project: easier
because there were no grounded mindsets to change in the first place, but
harder because we had to implement from scratch the right processes from
the start amidst a highly challenging and fast-moving environment. What
really made it work was the people: senior management who viewed KM as
critical right from the beginning, and the divisional KM coordinators and
staff who came to believe that KM was important and embraced it as part
of their daily work life. Capturing knowledge for future generations was
important, but no one was going to participate if they did not also see immediate work benefits.
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Implementing 36
and sustaining
KM in the
Public Works
Department
Malaysia
BY ROZ N I TA OT H MA N
Former Knowledge Management Director, PWD
Context
Formed in 1872, the Public Works Department (PWD) Malaysia (in Malay,
Jabatan Kerja Raya Malaysia or JKR) is the technical government agency
responsible for the implementation and maintenance of government
infrastructure assets such as roads and bridges, air and maritime bases,
hospitals, schools, civil servant quarters and other government buildings.
It has 11 offices at the state level, three offices at the federal territory level
and a special unit in the state of Kelantan. This chapter describes the main
implementation phases of KM at PWD Malaysia between 2007 and 2017,
including the steps taken to embed and sustain KM.
Public Works Department Malaysia
PWD Malaysia is a knowledge-intensive
organization
To perform its key functions, PWD Malaysia employs a wide range of technical expertise in the field of architecture, engineering and quantity surveying.
It provides engineering services, project management and asset management
services to other ministries and government agencies. It also provides technical expert advice to central agencies, regulatory bodies and semi-government
institutions at the federal and state levels in the formulation of policies pertaining to project implementation and maintenance, and in carrying out technical audits and forensic investigations.
The department has approximately 22,000 employees, of which almost
3,700 are technical professionals composed of:
●●
civil engineers – over 2,000;
●●
quantity surveyors – over 400;
●●
mechanical engineers – over 400;
●●
electrical engineers – almost 300;
●●
architects – over 300;
●●
building surveyors – about 40.
To achieve its vision to be a world-class service provider and centre of excellence in asset management, project management and engineering services,
PWD Malaysia places significant emphasis on the development of a highly
competent workforce, the use of innovative and advanced construction technologies, and leveraging information and communication technologies (ICT).
Its new Centre of Excellence, which started operations in 2016, provides research services and training in the fields of engineering and technology.
The beginning of the KM journey
KM was initially identified as an ICT project under PWD’s ICT Strategic Plan
in 2007. However, being new and untried, KM did not succeed in acquiring
sufficient budget allocation under the ICT plan.
Then, in March 2008, KM was incorporated as an initiative under PWD’s
new Change Agenda. A champion was appointed to think of how KM
should be framed to support PWD’s work. A small task force was formed
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Case Histories
and after the overall KM strategy had been presented to the top management, activities were carried out to promote awareness and understanding
of KM, to develop a KM framework and roadmap, to plan the implementation, and to run a pilot.
In 2010, the PWD Strategic Framework incorporated KM as one of the
organization’s strategic initiatives to support the learning and growth aspects of its employees in meeting organizational goals. This was translated
into a number of enterprise-wide KM efforts aimed at improving the knowledge culture and competencies in managing the knowledge resources that
are critical to ensure excellent delivery of projects.
In 2009, a series of workshops was held with representatives from various branches to carry out a knowledge-mapping exercise, which involved
identifying knowledge resources, locating where they were throughout the
organization, and mapping the knowledge flows to examine where as well
as how those knowledge resources are used and shared. This provided input
for the KM framework and roadmap, with strategies and approaches to
overcome the following barriers:
a Knowledge silos – the hierarchical structure of PWD Malaysia, divided
into various divisions and units, had led to knowledge silos. Useful
information or knowledge tended to remain hidden or unreachable to
others.
b Brain drain – the number of experienced technical personnel who would be
retiring and leaving the organization was increasing. As such, PWD Malaysia
was facing a significant risk of losing critical knowledge, particularly tacit
knowledge, which needed to be retained and transferred to the younger
generation.
c Incomplete information – departmental circulars, guidelines and manuals
were inconsistently applied due to misinterpretation and confusion. Since
the HQ and state offices are geographically separated, employees at the
operational level often found difficulties in seeking opinions and
clarifications from the process owners or experts who were located at
HQ. They also had few opportunities to give ideas and feedback to the
offices that prepared the documents.
d Undocumented project knowledge – solutions to problems unearthed
during discussions among project team members were not well
documented or shared, resulting in lost opportunities for project teams to
share experiential knowledge and avoid repeating the same mistakes.
Often, project teams were disbanded after project completion and team
Public Works Department Malaysia
members were immediately posted to work on other projects. There was
little time allotted for them to reflect and document their learning
experience.
e Lack of organizational learning – valuable knowledge acquired in projects
remained locked in the heads of individual employees as too much
emphasis was given to individual learning rather than collective learning,
resulting in knowledge gaps that affected their efficiency. Knowledgesharing (KS) activities across departments were lacking or the techniques
and tools used were ineffective.
During the first two years of KM implementation, the department embarked
on a quick-win initiative that focused on improving the accessibility of critical knowledge needed in the project delivery stage. This was intended to
demonstrate the value of KM to the different stakeholders.
In 2011, before expanding into a full-fledged formal KM programme, the
KM team conducted a KM readiness assessment. The assessment highlighted
that the KM team needed to work on several key factors including getting
visible support and commitment from top management, maintaining a dynamic strategic alignment between KM initiatives and the organization’s
vision and mission, establishing a rewards and recognition programme, continuous organization-wide engagement activities, and the introduction of a
performance measurement system. These factors were taken into consideration in developing subsequent major KM initiatives.
Another assessment was undertaken following changes in the organization
structure and strategic focus after the review of the department’s strategic
plan in 2016. An organization-wide knowledge audit was initiated to reassess
the department’s knowledge needs, to take stock of knowledge resources, and
to identify knowledge issues across the organization. Intervention plans were
identified and implemented to address issues pertaining to managing knowledge of experts, capturing and harvesting knowledge, enhancing and maintaining critical knowledge, and building a learning culture.
KM initiatives
The department took an iterative and cumulative approach to rolling out
new KM initiatives, making sure the prior initiatives were bedded down
before embarking on a new one.
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1. Handbook on enterprise content and knowledge
management (2009)
The handbook was published to raise awareness and generate interest in
KM among PWD employees at all levels. It introduced the concept of KM,
its value proposition to the organization and employees, and the key factors
to ensure successful implementation of KM in PWD Malaysia.
2. Online knowledge repository (2010)
To address wide concerns about the lack of support for knowledge sharing,
priority was given to making critical knowledge resources available and
easily accessible. Hence, as a pilot, knowledge resources related to site management and supervision were collected by the team and shared via an online repository, an online Practical Site Management Guide developed on a
wiki platform. The wiki enabled flexibility and ease in developing the
knowledge base in a collaborative manner. The content development teams,
from a wide array of disciplines, were led by subject matter experts (SMEs),
who ensure the relevancy, accuracy, completeness and currency of the content. Content development and review workshops were organized periodically to give them time to focus on the content quality. End users of the
guide were also included in these workshops to elicit feedback and input
where appropriate.
The positive results obtained in terms of adoption rate and an increase in
the number of users provided enough confidence to extend this model to
other organizational knowledge domains and the online repository was renamed as JPEDIA in 2012. With strong support, especially from the director
general, JPEDIA has, over the years, attracted more and more users, and the
content shared has increased exponentially.
3. E-learning (2012)
Malaysia’s public sector training institute, INTAN, encourages government
agencies to share knowledge via its online learning platform called EPSA. To
date, PWD Malaysia has contributed 10 e-learning courses to EPSA, which are
shared nationwide. The development of e-learning courses requires skillsets in
instructional design and the use of multimedia tools for graphics design and
Public Works Department Malaysia
animation, so the team members involved were trained in those aspects for the
content design. To ensure a smooth implementation of e-learning initiatives, a
governance structure defining clear roles and responsibilities has been institutionalized.
At the time of writing (2019), the department is in the process of piloting
a mobile learning application to deliver onboarding courses to new hires,
aimed at accelerating their learning curves and preparing them for the work
they will be assigned to.
4. Exit interviews (2013)
The year 2013 saw many baby boomer employees reaching retirement age
and more were expected to be leaving in the coming years. Realizing the
high risk of tacit knowledge loss the department would be facing, selected
soon-to-be retired directors were interviewed. During the interviews, which
were video recorded, they not only shared major project experiences acquired through their years of service but also the knowledge resources that
they had helped develop. These videos are also uploaded to the public sector’s online learning platform.
5. Communities of practice (2013)
In 2013, PWD Malaysia embarked on an initiative to cultivate communities
of practice (CoPs), which in our environment are peer networks where professionals share knowledge and experience and provide support for solving
problems and challenges. Initially, five CoPs were established and this has
since increased to 10.
Although participation is on a voluntary basis, the setting up of CoPs was
done in a structured and formal manner, with official appointment letters
for CoP leaders, coordinators, SMEs and core team members stating their
roles and responsibilities. Apart from organizing meetings and knowledgesharing activities, the CoPs also collect knowledge related to their domain to
enrich the knowledge base in JPEDIA. They use an online platform, named
JCoP, to discuss work-related issues. The KM team introduced gamification
elements, such as rankings and points, into the JCoP platform, and this has
contributed to its success. Active knowledge contributors receive certificates
of appreciation from top management during the department’s annual KM
event.
In 2018 the KM team carried out a ‘health’ assessment on the CoPs to
identify actions that needed to be taken in order to sustain and strengthen
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them. At the time of writing, the department is in the process of developing
a CoP maturity model and a health-check guide.
6. Project lessons learned (2015)
The amount of knowledge that PWD generates from projects at their various stages is overwhelming. Actions are taken to capture, codify and share
the project learning, and ensure it is reused and leveraged in other projects.
To ensure project lessons are captured by all throughout the ­organization, the
top management has mandated every branch and state director to document
lessons learned from any two of their projects each year. The project management offices (PMOs) at the branches and state offices have been tasked
to coordinate and facilitate lessons-learned workshops for their own project
teams, often with the help of the KM team.
The structured approach developed for capturing and documenting project
lessons was piloted in four projects before it was formalized and published in
the PWD Malaysia Project Lessons Learned Practical Guide.
Project lessons-learned reports are submitted to the KM Office for vetting
and uploaded to JPEDIA. Relevant SMEs are engaged to review crucial lessons and update related knowledge resources if improvements to existing
processes and practices are necessary. Efforts are also being taken to analyse
the captured lessons learned to identify necessary actions that will prevent
recurrences of mistakes and/or to repeat successes in future projects.
7. KM toolbox (2016)
The KM toolbox is a collection of key KM tools and techniques that are
widely used in PWD Malaysia. It includes peer assist, after-action review,
post-implementation review, knowledge café, communities of practice, fish
bowl, storytelling, and exit interview. The tools are described in easy-to-read
format using visual illustrations and are published in separate booklets
which are placed in the ‘box’. These are used in training sessions conducted
for new knowledge managers.
8. Expert tech talks (2017)
SMEs are expected by the department to actively share their knowledge. The
Expert Tech Talk is a KM initiative that produces videos of talks given by
SMEs, which are also uploaded to the public sector’s online learning platform for sharing.
Public Works Department Malaysia
Key challenges for KM
The human dimension
PWD Malaysia is very dependent on the expertise of its professional staff.
With the growing awareness that tacit knowledge makes up as much as
80 per cent of the vital knowledge that an organization needs to sustain its
competitiveness, there is a dire need to harvest, recycle and renew as much
as possible of this type of knowledge. However, much of the unspoken and
unrecorded information/knowledge can remain locked up in the minds of
individuals if they have poor verbal or written communication skills.
A survey carried out at the start of our journey in 2007 revealed that employees did not share their knowledge because they perceived knowledge as power
and believed that if they built up their personal knowledge, they would be better
regarded and seen as indispensable. Some also feared that if they shared they
would not be recognized or worse still, someone else would take credit for their
knowledge. Some were not comfortable to share knowledge because of a lack
of trust and a culture of blaming others for mistakes and failures.
To overcome these obstacles, the KM programme has focused heavily
over the past decade on cultivating a knowledge-sharing culture and creating a learning-friendly environment.
The organizational dimension
As mentioned, PWD Malaysia has offices in all of Malaysia’s states and districts, and across the federal territories. Given the geographically dispersed
nature and hierarchical structure of the organization, the speed and flow of
information and knowledge can be inhibited. Tightly defined job descriptions
and procedures dictate the way work is organized, resulting in information
silos. These are underlying factors that have discouraged employees who possess critical knowledge from sharing their knowledge with others.
The creation of JPEDIA has significantly improved knowledge accessibility and knowledge sharing within the department, by providing a means to
short-circuit these geographic and structural barriers to sharing.
The technical dimension
Poor practices in managing content had frequently led to problems where
desired information was outdated or unavailable. Hence, the creation of
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content was not enough. The KM team organized quarterly content review
workshops for SMEs. The wide use of social media tools and mobile apps
has also greatly helped to promote and create awareness across the department of the availability of useful knowledge, and updates to the department’s knowledge resources.
How KM was sustained
KM governance
One of the biggest strengths of the PWD KM programme lies in the governance framework that was established in 2010. A KM office (KMO) was officially set up to plan, execute and monitor the KM programme based on the
approved KM framework and roadmap. Every branch and state office appoints knowledge managers to champion and facilitate knowledge sharing
at the respective offices. Specific roles and responsibilities are assigned to
them. Quarterly meetings are organized for the knowledge managers to
gather and discuss knowledge-related issues and to monitor KM implementation across the department.
KPIs are set to ensure KM goals – aligned to the organizational goals –
are met. The KPIs are cascaded down to the branch and state levels and the
achievements are measured, monitored and reported monthly. This has
helped to secure buy-in and support from all levels within the organization,
from the top to the bottom.
KM competencies
PWD believes strongly that people with KM responsibilities must be given the
right competencies. Knowledge managers require the necessary competencies
to support knowledge sharing, eg facilitating knowledge-sharing events, capturing knowledge and designing knowledge transfer processes. Knowledge
managers come and go, either because they are relocated to somewhere else or
leave the department due to retirement. Changes in personnel mean retraining
has to be provided quickly so that the new knowledge managers can do
their job.
Besides the basic KM training provided by the KMO, knowledge managers
are also expected to participate in KM seminars and conferences organized
in-house and externally. They are also encouraged to go for KM certification
Public Works Department Malaysia
programmes to give them a foundation in KM principles and practice. To
date, there are 18 certified knowledge managers in the department.
Change management
Roadshows and KM talks are part of the change management plan that is
continuously being executed by the KM Office. Apart from these, KM events
involving top ranks in the department are regularly organized. Top management’s strong support is critical in getting buy-in from the employees.
Knowledge-related activities are regularly communicated using a wide
variety of media. We place great emphasis on influencing employees’ behaviours and attitudes so that they are more willing and motivated to seek,
share and use knowledge. This is achieved by continually demonstrating to
them how sharing knowledge will benefit them personally and help them
improve their job performance.
Adaptive KM approaches
Taking into consideration the different generations that make up today’s
workforce, ranging from the baby boomers to the millennials, Gen Z and
their successors, the KM initiatives take into account each generation’s preferences in sharing knowledge and learning styles. Since many employees are
nearing retirement, knowledge loss has started to become a big concern.
Hence, many of our KM efforts are now focused on ways to effectively
transfer tacit knowledge in ways that suit the baby boomer generation.
For the millennials and later generations, innovative technology and social media tools are actively deployed to make the process of knowledge
transfer attractive and effective. However, these tools cannot replace the
traditional face-to-face interactions that are crucial in building trust and
camaraderie, and in overcoming barriers to knowledge sharing.
Areas of future improvement
The KM journey at PWD Malaysia is also a continuous learning journey.
Among others, the following areas of future improvement for KM have been
identified:
407
408
Case Histories
●●
●●
●●
●●
Learning culture. Specifically, the need to improve the culture of encouraging
question asking and responding to questions asked. Questions posted in
JCoP need to be answered quickly and in depth. Subject matter experts need
to make time for this and be able to provide fact-based opinions.
Quality of content. There is a need to further improve the critical knowledge
content to ensure it is continuously reviewed for consistency, reliability,
currency and accuracy throughout its entire lifecycle.
Critical knowledge flows. The critical knowledge flows need to be reviewed
on an ongoing basis so that new barriers are identified and removed.
Incentives for participation and contribution. Participation in knowledgesharing activities can be further improved by putting in place mechanisms
to reward and recognize employees who share their knowledge. Employees’
appraisals and performance reviews need to take into account their
contributions to the organizational knowledge base.
Summary
The KM journey at PWD Malaysia has been one of careful, step-by-step
implementation, focusing on real pain points to the department’s core business, and always paying attention to the professional expertise it depends on
and the effectiveness of the infrastructure projects that it undertakes. We can
see how the KM team rolled out each new initiative carefully, embedded it,
and then went back periodically to review and renew it. The way in which
they built and then supported their network of KM champions is an impressive illustration of how to embed KM initiatives by handing off initiatives
into the business, and by ensuring the competencies for KM roles are first
built and then sustained.
409
Summary
This book is now complete. If your knowledge management journey has
paralleled the structure of this book, then your KM implementation is also
complete, KM is fully embedded in your organizational operations, and you
are starting to engage actively with the broader KM landscape.
You should feel proud of yourself – you have successfully done what
Machiavelli said (in the quote in our introduction) was most difficult, perilous
and uncertain. You have introduced a new order of things. You have introduced a new management discipline to your organization. You have succeeded
where many have failed – you have implemented Knowledge Management.
We hope that this book has been helpful to you in your journey, and has
guided you away from the pitfalls and presented you with approaches you
could copy, case studies you could learn from, and templates you were able
to apply.
Now is the time for you to pay some of this knowledge back. Conduct a
learning review of your KM implementation programme, perhaps using ISO
30401:2018 as a reference framework, and identify the lessons that will be
useful both to future KM programmes, and other change programmes in
your own organization. Share and publish these lessons widely so they can
help others who will follow in your footsteps, because we can be sure of one
thing: no matter how difficult, perilous and uncertain the introduction of
knowledge management may be, the topic is important enough that knowledge management implementation will remain a priority for organizations
around the globe for decades to come.
410
G LO S S A RY
A3 Report
A structured document following a process for
reviewing, analysing and documenting learning about
product failures and product design improvements.
After-Action Review
A short, structured meeting, where a team reviews a
recent work activity and draws out lessons for the
future. This process is generally used for short-term
activities such as tasks within a project.
Ambient Findability
Ensuring that relevant knowledge resources pop up
proactively at the point or in the context where they are
needed. This means anticipating where relevant
resources will be needed and engineering a ‘push’ of
content to users at that point in the process.
Artificial Intelligence
An umbrella term to describe a range of computerbased technologies to help machines perform tasks
normally conducted by humans – such as natural
language recognition, interpreting visual images,
machine translation, autonomous driving, automated
decision making. See also Chatbot, Machine Learning,
Semantic Search.
Autoclassification Tools
Software tools that automatically assign tags or
Taxonomy topics to information and knowledge
resources. They can work by suggesting tags or topics
to users, or they can be fully automated, working in the
background without human intervention.
Baton Passing
A facilitated process for transferring knowledge from
one team to another team conducting the same type of
work.
Before-Action Review
A facilitated discussion before a project or activity cycle
commences, to identify prior learning and knowledge
needs that are relevant to the project.
Benefits Mapping
A systematic and visual way of demonstrating the
connections between knowledge management
interventions and positive business outcomes.
Glossary
Best Practice
A practice or way of doing something that has been
identified and validated as the best currently known
way of doing it in a specific context.
Big Data
A broad term referring to the processing and analysis of
very large datasets from multiple sources, to gain
meaningful and actionable insights for the business. See
also Data.
Blog
An online software application that shows entries in
order of greatest recency. Useful for recording
knowledge and insights from projects and activities as
they happen.
Business Intelligence
Supporting decision making through gathering and
analysing information from the environment, to avoid
risks and create possibilities for change.
Chatbot
A computer programme, powered by Artificial
Intelligence, that is designed to simulate human
conversation. Chatbots are increasingly being used to
replace call centre operators on standard types of
service enquiry.
Cloud Computing
The transition to storing data, content and software
applications on remote, hosted internet servers and
platforms, rather than on internally managed machines
and data centres.
Codified Knowledge
Knowledge that is recorded in text, audio, video, images
or algorithms. Arguably also known as Explicit
Knowledge.
Community of Practice
A group of people who work on a common type of
activity or practice area, and who share knowledge
regularly on their practice, either in person or virtually,
to help each other perform better.
Community of Purpose
Similar to a Community of Practice, but focused on a
common purpose, process or objective shared by the
members. The community focuses on helping members
address the business goals represented by the
community.
Competence
A combination of technical knowledge, skills and values
that give somebody the ability to be effective in a role
or function.
411
412
Glossary
Content Management
The application of processes and systems to managing
information content in support of organizational needs,
whether it be web content, documents, records, or other
forms of Explicit Knowledge.
Culture
Distinctive patterns of behaviours, assumptions and
values expressed within a community or organization.
Because they are embedded through habits, they are
difficult to manage directly, or change through simple
appeals to reason, but must be supported through a
systematic change programme, putting in place new
processes, roles and enablers.
Data
Individual measurements, observations and facts, which
may be combined and ordered into information, or
interpreted to form insights. See also Big Data.
Dialogue
A style of conversation that stresses exploration of
different perspectives and achieving mutual
understanding, not necessarily agreement.
Digital Transformation
A programme of changing the way an organization
operates and delivers value to its customers, using Big
Data and digital technologies such as Artificial
Intelligence and Machine Learning.
Embedding
A set of interventions intended to ensure that new ways
of working become permanent.
Enterprise Search
Specialist
A role responsible for ensuring that the search
technology exploits the Taxonomy effectively, supports
the Information Architect’s design objectives, and helps
users find and access information and knowledge
resources useful to them.
Enterprise Taxonomist
A role responsible for developing, implementing and
maintaining enterprise Taxonomies to support the
findability, access and re-use of knowledge resources.
Enterprise Taxonomy
Management System
A software application that supports the centralized
management of multiple Taxonomies, Metadata
elements and other reference vocabularies, and acts as a
single source of vocabulary for a number of different
information systems.
Expert System
A system that embeds the knowledge and decisionmaking rules of experts into algorithms and workflows
in a software application.
Glossary
Expertise
An umbrella term for the specialist knowledge of
experts. It can refer to a wide variety of forms of
knowledge, such as deep technical expertise, historical
knowledge of how things were done in the past, highly
developed skills, deep Tacit Knowledge based on
experience, and the ability to coordinate and
communicate effectively with teams.
Explicit Knowledge
Knowledge that is, or is capable of being, recorded in
text, audio, video, images or algorithms. Arguably also
known as Codified Knowledge.
Governance
Enabling effective administration, oversight and
accountability of an organizational function through
a combination of structures, roles, policies and
processes.
Human Capital
The stock of knowledge, competences, values and social
attributes possessed by an organization, which enables
it to be effective at what it does. Human capital is one
form of Intangible Asset.
Information
A collation, presentation and analysis of Data, which
tells you something, or factual content that is
communicated to you.
Information Architect
A role responsible for designing the information and
knowledge environment in a system such as a Portal or
Knowledge Base so that information resources can be
easily navigated and retrieved.
Innovation
Introducing significantly improved products and
services through the creation of new knowledge, and
the implementation and validation of ideas,
experimentation and problem solving.
Intangible Assets
Assets of an organization that cannot be quantified and
put on a balance sheet in the same way as tangible
assets such as cash, facilities or equipment. Examples of
intangible assets are reputation, goodwill, customer
capital, human capital, intellectual property or
capabilities. Some forms of knowledge are an important
kind of intangible asset, if they can be owned and
controlled by the organization. See also Knowledge
Assets and Knowledge Resources.
413
414
Glossary
KNAC
Knowledge Asset Creation process – a five-step process
developed by Siemens for creating synthesized
knowledge assets around a particular topic or product.
Knowledge
A human or organizational resource enabling effective
decisions and action in context:
‘Knowledge can be individual, collective or
organizational. There are diverse views on the scope
covered within knowledge, based on context and
purpose. Examples of knowledge include insight,
knowhow, etc. Knowledge is acquired through learning
or experience’ (ISO 30401:2018). See also Explicit
Knowledge, Intangible Asset, Knowledge Asset,
Knowledge Resource and Tacit Knowledge.
Knowledge Analyst
A role responsible for retrieving, collating and
synthesizing knowledge resources around a specific
topic from different Knowledge Bases, and preparing
briefings for internal or external customers.
Knowledge Assets
Assets are things of value that can be owned and
controlled by an organization or individual.
Knowledge assets refer to discrete, identifiable items of
knowledge that help to make an organization effective
at what it does. Knowledge assets cover a wide range
of knowledge types, from Explicit to Tacit. They can
include intellectual property, skills, competencies,
methodologies, and practices, whether codified or not.
Organizational knowledge assets exclude experiencebased knowledge, technical expertise, and knowledgecarrying relationships, since these cannot be owned or
fully controlled by the enterprise. To describe the full
range of knowledge types, we prefer Knowledge
Resources.
Knowledge Audit
A general term referring to a systematic evaluation of
knowledge resources, knowledge gaps, knowledge
flows, and knowledge management processes, with the
aim of making recommendations for improvement.
Often part of the detailed planning process for a KM
implementation.
Knowledge Bank,
Knowledge Base
A place where the Explicit Knowledge of an
organization or a community of practice is collected.
Glossary
Knowledge Café
A facilitated large-scale meeting where small group
sharing conversations take place at café-style tables.
Typically, each table has a host to facilitate the
conversation and at the end of each conversation cycle,
the other participants at the table split up and join a
different table with a different group. Knowledge cafés
are good at bringing multiple perspectives to bear on
complex problems or challenges, and at improving
networking and relationship building.
Knowledge Capture,
Knowledge
Documentation
Processes for documenting some elements of Tacit
Knowledge into codified form as Explicit Knowledge.
Knowledge Engineer
A role with accountability for capturing knowledge
from a team, department or division.
Knowledge Exchange
A meeting where many people come to discuss and
learn from each other. In a knowledge exchange
everyone is a contributor and everyone a learner.
Knowledge Handover
A facilitated process for transferring lessons from a
project team that has completed a project to other
teams that may need that knowledge.
Knowledge
Management
Management with regard to knowledge. A systematic
and strategic approach to maximizing the value of the
collective know-how of an organization. ‘Knowledge
management uses a systemic and holistic approach to
improve results and learning, and includes optimizing
the identification, creation, analysis, representation,
distribution and application of knowledge to create
organizational value’ (ISO 30401:2018).
Knowledge Management
Champion
A colleague who has been given responsibilities for
supporting KM activities in their part of the business,
usually as an additional role on top of their normal
functional role.
Knowledge Management
Framework
Part of a management framework or management
system with regard to knowledge. The system elements
include: the organization’s KM culture, structure,
governance and leadership, roles and responsibilities,
technology, processes and operations.
415
416
Glossary
Knowledge
Management Plan
A document that captures the KM goals, knowledge
needs, knowledge gaps, knowledge sources and
knowledge acquisition strategy, knowledge creation
roles, KM responsibilities and processes for a given
project or activity.
Knowledge Manager
Someone whose primary accountability is making sure
that the knowledge of their part of the organization is
managed for business benefit.
Knowledge Map
A visual representation of where knowledge resources
are located in an organization and how they relate to
key functional areas and activities, and/or a visual
representation of knowledge flows and dependencies
across an organization.
Knowledge
Organization
A set of processes to organize knowledge resources in
an organization so that they can be effectively managed,
accessed, and used.
Knowledge Owner
The person responsible for managing the contents,
accuracy, completeness and currency of the Knowledge
Base for any particular area of knowledge.
Knowledge Resources
A broader term than Knowledge Assets to cover all the
forms of knowledge that can help an organization
achieve its goals effectively, whether they be fully
owned or controlled (Knowledge Assets) or whether
they are owned by the individuals who work for the
organization (eg experience, deep expertise, knowledgecarrying relationships).
Knowledge Retention
A set of processes to retain important knowledge in the
organization while individual people come and go.
Often focused on Tacit Knowledge.
Knowledge Synthesis
Compiling and distilling knowledge from many sources
into a single coherent set of guidance for easy reference.
Learning
Improving the way things are done as a result of
acquiring new insight and knowledge.
Glossary
Learning Historian
A role responsible for creating a learning history
through interviews, data gathering, analysis and
creation of a narrative that distils learning from a
particular activity, series of activities, or event, and gives
guidelines on application of the lessons.
Lessons Database
A database in which to store, categorize and retrieve
lessons learned.
Lessons Learned
A term used to describe pieces of knowledge that have
been learned through a business activity. These lessons
are most valuable if they are expressed as advice for the
future, and given in the words of people with practical
experience. Lessons are not fully ‘learned’ until they
have been embedded in new ways of doing things.
Lessons Management
System
A system to manage the capture, validation and
application of lessons learned. Usually incorporates a
Lessons Database.
Machine Learning
An application of Artificial Intelligence that helps
computers learn from experience using feedback loops,
statistical models and general rules bases, without
having to be explicitly programmed on those lessons.
Metadata
Data that describes the attributes of data or
documents, for example, title, author, date of
creation, topic, structure, security classification.
Metadata helps in the management of content and
supports giving access to content, eg through search.
Taxonomy is a form of metadata that aids search and
discovery of content.
Microblogging Tools
Tools that support sharing of information and
knowledge through short messages and updates. Twitter
is the most famous kind of open microblogging tool,
while Yammer is a well-known enterprise
microblogging tool.
Packaging
Compiling knowledge into a coherent format so that it
can be presented to the knowledge customer to
maximize the ease of re-use. See also Knowledge
Synthesis.
Partnering
A structured approach to identifying and engaging with
partners, negotiating responsibilities and contributions,
and recognizing partners’ constraints and priorities.
417
418
Glossary
Peer Assist
A structured, facilitated meeting or workshop where
people are invited from other business units, or other
businesses, to provide their experience, insights and
knowledge to a team who have requested help in
solving a problem or addressing a challenge.
Peer Review
A structured, facilitated meeting or workshop where
people are invited from other business units, or other
businesses, to review the work of another team.
People Finder
A knowledge directory matching people’s names to
knowledge domains to help staff find out ‘who knows
what’ in an organization. Also sometimes referred to as
a ‘Yellow Pages’.
Pilot
A limited-scale project to test out the KM Framework
in a part of the organization, and to demonstrate the
value of KM to business stakeholders. A pilot should
also produce insights leading to the refinement of the
KM Framework.
Policy
A clear statement of what is expected from employees
in relation to a specific activity area, spelling out the
guiding principles, roles and accountabilities, and
supporting instructions.
Portal
An online site that gives access to Knowledge Bases,
software applications and collaboration tools.
Professional Support
Lawyer
A role within law firms to provide advice, access to
precedents and know-how, providing training and
support for client pitches.
Proof of Concept
A very small-scale activity to demonstrate the value of
KM to management stakeholders.
Q&A Forum
A discussion forum (often but not exclusively emailbased) structured around questions and answers. This
can be a powerful means of exchanging knowledge
within a community of practice. Community members
can raise questions within the forum, which are
answered by their peers around the world.
Record Keeping,
Records Management
Systematic processes for keeping formal records of
official decisions, activities and transactions, for the
purposes of management control, accountability,
regulatory compliance, and preservation of
organizational memory.
Glossary
Resource Mapping
A structured and visual method of identifying the
resources required by a KM implementation, and of
who will be responsible for contributing those
resources.
Retrospect
A structured and facilitated meeting at the end of a
project or major activity cycle, to capture the
knowledge and learning before the team disbands.
Roll-out
The process of extending a new way of working across
an organization.
Search-Based
Application
A software application that uses the search engine to
proactively deliver highly targeted content to specific
users at a point of need.
Semantic Search
An application of search that uses the semantics of
search queries rather than simple word matches against
an index, to understand the intent of a search query and
provide relevant results. Semantic search can be
considered a branch of Artificial Intelligence, using
Natural Language Programming, text analytics, and
sometimes ontologies to interpret queries and suggest
relevant results.
Social Network
Analysis
A method of mapping the interactions between people
in a team, community or organization, to assess the
level of connectivity, and to identify any interventions
to improve the flow of knowledge and information.
Social Media
Online software applications that are designed to
encourage and facilitate social interactions.
Strategic Knowledge
Areas
Knowledge-based capabilities that are critical to an
organization’s effectiveness and competitiveness.
Subject Matter Expert
Someone in a community or a function who has
ownership or stewardship of one area of knowledge,
and who manages that area on behalf of the community
or organization.
Tacit Knowledge
Knowledge which is held in people’s heads and bodies,
and which enables them to perform important tasks,
which may or may not be possible to write down, and
of which the knowledge holder might not be fully
aware.
419
420
Glossary
Tag Cloud
A cluster of commonly used keywords in a collection of
resources, where the size of the font indicates the
frequency of use of that keyword.
Tagging System
A system that allows users to add keywords to an
information or knowledge resource.
Taxonomy
A structured, controlled vocabulary used to describe
what documents or discussions are about. Taxonomies
are part of Metadata, and are used to support search
and retrieval of relevant content. Taxonomies can also
be used to describe expertise topics associated with
individuals and communities.
Taxonomy Facet
A distinct vocabulary within the taxonomy that focuses
on a specific attribute of a knowledge resource, for
example the type of document, the activity referenced,
the entities involved.
Validate
To make sure something, such as a lesson or other piece
of knowledge, is valid and defensible, and can therefore
be applied in future as a good practice.
Wiki
A set of online pages that can be directly and
collaboratively edited by readers through a web
browser interface.
Wikithon
A facilitated event where a group of Knowledge
Owners or Community of Practice members gather to
synthesize a collective Knowledge Base on a wiki
platform.
Yellow Pages
See People Finder.
421
INDEX
Note: Numbers within main headings are filed as spelt out; acronyms are filed as presented.
Page locators in italics denote information within a Figure or Table.
accessibility analysis 124
ACCLLP 359
active community members 137
active workflow systems 155
activity cycle time 92–93, 110
activity metrics 264, 267, 269, 271, 273
advocacy 228–29
Aerospace Safety Advisory Panel
(ASAP) 353, 356–57
after-action reviews 151–52, 198, 396, 404
agile methodology 16, 26, 326, 389
Al Fahal 371
Al Shaibani, Said 369
Al Toubi, Dr Suleiman 368, 369
Amadeus 331
Amazon 328, 331
ambient findability 170, 175
Aon Insurance 94
APPEL (Knowledge Services) (APPL) 352,
353, 355, 359
Appreciative Inquiry 149
APQC 311, 325
Ares I-X 353, 356
army 162, 172, 180, 319
Artificial Intelligence (AI) 170, 327, 328,
329–36
ASHEN framework 117–18
‘Ask Anglo’ 139
ASK Magazine 352, 353, 358
A3 reports 152, 155–56
ATLAS 51
attitudes 68, 203, 206–07
audience segmentation 192–94
audits 12, 27–28, 41, 115–25, 182, 185–86,
188, 302, 306–08, 355
PWD, Malaysia 401
autoclassification tools 175
automation 328, 331, 334, 336
awards schemes 270–71, 298–99, 308, 368,
375–76
awareness training 258, 259
Bangladesh retrospect 240
BASAbali 163
Baton-Passing process 140–41
BBC 175
before-action reviews 172
benchmarking 80, 295–96, 306–07, 308,
311, 371–72
see also awards schemes
benefits mapping 85–89, 97
benefits measurement 37–38
best practice 10, 13, 62, 133, 158, 159, 206
Big Data 327, 328
blogs 28, 41, 154, 155, 174, 193, 207, 243
Boeing 330, 333
bonus programmes 98, 206, 233, 270,
375–76
bottom up approach 23, 28, 77–78, 133,
163–64, 183, 193
BP 53, 90–91, 96, 169, 197, 236, 286, 386, 387
see also Browne, John
Braganza and Möllenkramer 35, 37
brain drain 400
British Energy 299
Browne, John 14, 169, 197
budgets 77–84
Bulletin Board Systems 385
business cases 53, 248, 376
business-critical activity 242
business drivers (focus) 34–35, 48–49,
179–80, 238–49
see also organizational context
business intelligence 13
business skills 66
business sponsors 244, 247
business value 37–38, 56, 77, 82, 140, 241,
247, 351, 377, 384
targets 95–98
CAIB 353, 354, 355, 357
case studies 275, 339–408
celebrating success 208, 259–60
challenging 202
champions 33, 72, 208, 227–38, 256, 258,
259, 304, 323
Huawei 391
PDO 364
422
Index
champions (continued)
PWD Malaysia 399, 406, 408
see also senior management; team leaders
(programme managers)
change management 41–42, 52–53, 59,
61–62, 67, 189–99, 207–11, 284,
398–408
see also culture change
Chartered Institute of Library and
Information Professionals
(CILIP) 302
charters 143, 294, 365, 370
Chase, Rory 298
chatbots 158, 329, 330, 331, 334, 336
check sheets 253
CKO (Chief Knowledge Officer/
Architect) 354, 355, 357, 358,
359–60
closing implementation programme
285–89
cloud-based platforms 327–28, 367
coaching 69, 218, 246, 259
Coca Cola 93
Codes of Practice, PDO CP-201 365, 367,
368, 369, 371
codified knowledge 16, 17
cognitive bias 149, 305, 308
collaboration 11, 202, 368, 374–75
Columbia Space Shuttle 350, 353, 354,
355, 359
see also CAIB
communication 11–12, 38, 207–11, 217–18,
258, 346, 370–71
see also communications lead;
conversation; discussion; discussion
forums; face-to-face discussions;
influencing skills; language
communication packs 209
communication plans 209–10, 371
communications lead 69
communities of practice (CoP) 40, 92,
123, 136–38, 208, 221, 234–35,
252, 294
Huawei 390
Mars 344–45
metrics 266–67, 268
NASA 353, 355, 358, 360
PDO 366
PWD Malaysia 403–04
see also knowledge networks
communities of purpose 343, 344, 345, 346
community leaders 137
community members 137–38
community sponsors 137
community sub-groups 138
competences 43, 59–60, 92, 327, 334–36,
370, 406–07
see also skills
competitive behaviour 202, 206
complacency 203, 206
compliance metrics 265, 267, 271
comprehensive knowledge resources
audits 120, 121
conference calls 244
conferences 259, 299, 305, 311, 315,
341–42, 348, 406
connecting people 9, 11, 15–17, 131,
368, 377
Conoco Archimedes awards 271
ConocoPhillips 158
consistency 110, 122, 129, 155, 165, 346
consultancies 312–23, 386
consulting projects 321, 322–23
content 15–17, 67, 127, 145–56, 160–64,
182–83, 296, 366–67, 390, 408
content warrant 184–86
continuity 279–80
continuous improvement 13, 359–60, 372,
394–96
contracts 318–20
control, taxonomies 181
conversation 15–17, 66, 134–44, 191, 208,
235, 275, 316–17, 389
coordination 11–12
CoP see communities of practice (CoP)
corporate communications
department 101, 102
corporate librarians 108, 109, 160
costs 92, 106
cosying up 195, 198
‘could follow’ knowledge 159, 160
critical activities 342–43
critical knowledge flows 408
Critical Knowledge Gateway
(NASA) 353, 358
Crossrail 92–93
cultural archetypes mapping 203–04, 205
cultural dimensions mapping 201–03,
204–05
cultural drivers 205–06
culture 126–27, 368
culture analysis 217
culture change 15, 32, 33, 57, 61–62,
189–99, 200–11, 266
culture mapping 201–05
current state KM assessment 51–52,
293–309
customer knowledge 48–49, 350–62
customer satisfaction 94–95
customer trap 38
Index
data management 108–09, 331–32
see also Big Data
data managers 109
databases 148–49
deal making 195–96, 198
debate 135
debriefs 135, 396–97
defensiveness 202, 205
dialogue 135–44
dictionary lists 393–94
digital file-naming 394
digital transformation 325–37
digital voice recorders 154
directors of KM see KM team leaders
discussion 143
discussion forums 142, 155, 176, 234, 252,
260, 377, 386
disempowerment 202, 205
dishonesty 202, 205
doctrine manuals 158, 162
document management 9, 12, 16–17, 118,
122, 145–56, 179–88, 371, 394, 396
see also terms of reference documents
draft KM frameworks 52
Dumitriu, Petru 306
Dunning-Kruger effect 305–06, 313
during-action reviews 396
e-learning 402–03
editathons 162
embedding KM 35, 190, 223, 250–54, 348
empowerment 202
enablers of KM 15, 38–39, 78–79, 367–68
Engineers Without Borders 260
Enterprise KM Steering Group (PDO) 368,
369, 370, 372
enterprise search 174–75
enterprise search specialists 171–72
enterprise social media 142–43
enterprise taxonomies 171–72, 174, 181, 313
enterprise taxonomists 171–72, 182
enterprise taxonomy management
systems 176
enterprise wikis 380–81
EPSA 402–03
Ernst & Young 386
Ethiopian Airlines 330
evaluating bids 322–23
events 235–36, 239
evidence-based knowledge
organization 184–85
excellence culture 203
Executive Awards (PDO) 368
exit interviews 403
expectation setting 155, 169, 314–15
experience 119, 123
‘expert squeeze’ 332
expert systems 146–47, 150
Expert Tech Talks (PWD Malaysia) 404
expertise 332
explicit knowledge 386, 388–89, 397
Exploration Systems Mission Directorate
(NASA) 356
external appointments 58–59
external audits (auditors) 306–07, 308
external KM frameworks 293–309
external support 310–24
face-to-face discussions 140–42, 209, 232,
351–52, 407
Facebook 331
facet analysis 182, 184–87
facilitators (facilitation skills) 66, 135,
137–40, 141, 142, 149, 153, 314,
404, 406
lessons-learned 147–48
fail fairs 260
favour asking 196, 198
federated approach 351
field of dreams trap 38
financial management 127–28
Finnish Parliament vision 49
‘five whys’ 152
Fluor 139–40, 260–61
Food and Agriculture Organization (UN) 52–53
forcing tactic 197, 198
forgetting behaviours 202, 206
functional heads 254
future-tense questions 149
gap analysis 51, 124, 173, 253
Gather awards 271
General Motors 93, 158, 161–62
generational differences 407
generic KM frameworks 294–95
Give awards 271
Goddard Learning Plan 354–55
Goddard Space Flight Center (GSFC) 353,
354–55, 358
Google 169, 328, 329
governance 15, 39, 79, 129, 131–32, 251,
254–55
discussion 143
documentation 155–56
financial management 128
knowledge finding and re-use 176–77
knowledge synthesis 165–66
Oilco 377
PDO 368
PWD Malaysia 406
423
424
Index
Government Accounting Office 355
Grab awards 271
grass roots see bottom up approach
growth 49, 61–62, 242, 341–49
Guards Formations 180
Guts awards 271
handbook on enterprise content and
knowledge management (PWD
Malaysia) 402
hard metrics 266
Heineken 93
Hewlett-Packard 177
high-level pilots 243
high-performance cultures 169
high-value knowledge 37
honesty 202
hourly billing systems 206
HR department 101, 102, 254
HSE management 109–10, 367
Huawei 383–91
human capital 367
IBM 98
Immigration and Customs Authority of
Singapore 335–36
impact metrics 91–95, 266, 267, 268, 269,
271, 273, 343, 345–46
implementation 22–30, 40–41, 56, 57, 65,
67, 85–99, 225–89
Huawei 383–91
and knowledge resources audit 117–20
Mars 341–49
Public Works Department Malaysia ­
398–408
Singapore Youth Olympics 392–97
implementation pitfalls 31–44
implementation planning 212–23
inattentional blindness 305
incentives 32, 33, 62, 168–69, 206, 408
incomplete information 400
individual KM processes roll-out 24
individual knowledge synthesis 161–62
inductions 164, 170
influencing skills 59, 67, 189–99
information access metric 91
information architects 171, 172, 186–87
information architecture 12, 180, 182–83,
186–87
Information and Digitalization
Directorate 367
information management functions 108–09
information managers 109
information security policies 12, 58, 108,
169–70, 205, 385–86
initiation meeting, partnerships 105–07
innovation 10, 13, 49, 92–93, 101, 383–91
inspiring tactics 194–95, 198
INTAN 402–03
intangible assets 8, 272
internal appointments 57–58, 59
internal audits (self-auditing) 304–06,
308, 372
interviews 150–51, 396
see also exit interviews
invitation to tender 322
invoking authority 197, 198
ISO 301
ISO Standard 9001 300
ISO Standard 30401:2018 7–8, 15, 19,
126, 129, 256, 265, 287–88, 300–02,
303–04
PDO 363–73
IT skills (department) 67, 101, 102
JCoP 403, 408
Johnson Knowledge Online 356
Johnson Space Center (JSC) 355, 356, 360
Joint Inspection Unit (UN) 306–07
JPEDIA 163, 402, 403, 404, 405
KM, defined 7–9
KM framework 56, 126–33, 157–66, 218,
222, 254, 287–89, 294–95, 365–66
KM framework template 129–32
KM Offices (KMOs) 359, 404, 406, 407
KM paradigm shift 206–07
KM principles 15–18, 47–48
KM stars (HP) 177
KM supply chain 14, 18, 129, 145, 334
KM toolbox (PWD Malaysia) 404
KM4Dev 311
KMUnity 234–35
KNAC 162
knower behaviour 202, 203, 205
knowledge analysts 170
knowledge assets 142, 162, 239, 344
‘knowledge bank’ 71
knowledge base administration teams
160–61
knowledge base publishers 148
knowledge bases 133, 148–49, 165, 246,
268–69, 334
knowledge briefs 253
knowledge brokering 228, 229, 230
knowledge cafés 138, 366, 404
knowledge capture
Mars 16–17, 39–40, 128, 145–56, 343,
345, 346, 348
NASA 352, 356
Index
PDO 366
SYOGOC 394–95, 396
knowledge centres 170
knowledge domain experts see knowledge
owners
knowledge elicitation 147
knowledge engineers 146–47
knowledge exchange process 142, 162
knowledge fairs 259–60
knowledge finding and re-use 17, 167–78,
183, 379–80
knowledge handover process 141
knowledge inventory audits 12
knowledge managers 69, 191–92, 327,
406–07
Knowledge Map & Toolbox (NASA) 353,
358–59
knowledge maps 120–21, 185, 186, 353,
358–59
knowledge networks 376–81
Knowledge OnLine 260
knowledge organization 67, 179–88, 219
knowledge owners 160, 161
see also subject matter experts
knowledge pull/push 139
knowledge resource 115, 332
knowledge resource maps 185
knowledge resources audit 41, 115–25, 182,
185–86, 188
knowledge retention 9, 12, 155, 192, 220,
239, 396–97
knowledge sharing 197, 314, 352, 375–76, 405
Huawei platforms 385–88, 390
knowledge silos 35, 176, 400
knowledge synthesis 17, 157–66, 380–81
knowledge systems 40–41, 179–88
knowledge systems maps 182–83
knowledge transactions 16–17
knowledge transfer 15–16, 28, 92, 220, 315,
333–34
see also content; conversation; document
management; knowledge retention
knowledge treasure hunts 258
KPIs 246, 372, 389, 390, 406
Kraft Foods 93
language 11, 59, 66, 208, 209, 393
leadership 32, 369, 378
see also senior management
learn-as-you-go culture 394–96
learner behaviour (culture) 202, 203, 408
learning 12–13, 180, 368, 401, 402–03
learning from experience 10, 13
learning functions 109–10
learning historians 148
Learning Knowledge Base (PDO)
366–67, 372
Learning Knowledge Cards 366, 371
Learning Knowledge Procedure 367
legal sector 131–32
lessons-capture meetings 239
lessons learned 147–49, 155, 219–20, 239,
275, 319, 379, 397
metrics 267, 269
Lessons Learned Information System
(LLIS) 352, 353
Lessons Learned Knowledge Process
(PDO) 366
lessons management systems 155
librarians 108, 109, 160–61
LinkedIn 311, 315
Lion Air 330
local pilot project managers 245
logos 209, 346
lurkers 138
machine learning 327, 328, 329, 332
Major Projects Delivery area (PDO) 365–73
MAKE awards 298, 299
Making Mobile Gov Wiki 162
management reviews 372
manufacturing sector 133
market share 93–94
Mars 78, 93, 212, 341–49
Masters Forums 352
maturity levels, organizational 81–83
maturity metrics 266–67, 271, 273
maturity models 295–98
MCAS software 330
memory 12
mentors 16, 58, 60, 61, 67, 122, 123, 312
metadata 67, 79, 155, 176, 182, 367
metaphors 61–63
methods 118, 122
metrics 155, 187, 247, 261, 263–73, 371–72
impact 91–95, 343, 345–46
knowledge networks (Oilco) 381
see also benefits measurement
micro-blogging 28, 243
Microsoft 328, 330
MIKE award 298
milestones 213
Military Police 180
Mind Gym (Bailey & Black) 194–97
minimum viable product (MVP) 243–44
Ministry of Community Development, Youth
and Sport (Singapore) 397
‘must follow’ knowledge 159
425
426
Index
NASA (National Aeronautics and Space
Administration) 256–57, 306,
350–62
NASA KM Community 353, 358, 360
NASA Knowledge Map 353, 358–59
NASA Portal & Engineering Network
CoP 353, 355
NASA@Work 353, 356
National Archives of Singapore 397
National Health Service (NHS) 172
National Library Board (Singapore) 397
Natural Language Processing 329
natural talent 119–20, 123–24
need to know behaviours 202, 205
need to share behaviours 202
needs assessment 105
network portal sites (Oilco) 379–80
new recruits 231
Newman, Victor 140
non-monetary awards 270–71
‘not invented here’ syndrome 203
Nuclear Regulatory Commission (US) 92
objections to KM 274–76
objectives 85–99, 107
Observers’ Programme and Visitors’
Programme (SYOGOC) 397
oil industry 131
see also BP; Oilco
Oilco 374–82
online librarians 160–61
online Q&As 139–40, 142
openness 202
operational costs 92
operational excellence 48, 392–97
operational phase 27, 293–37
Operations Forum 244
opportunistic implementation 23, 24
opportunity 192
Orange 94
organizational context 320, 364–65
see also business drivers (focus)
organizational involvement 321
organizational learning 401
organizational maturity levels 81–83
Orissa cyclone 240
outsourcing 287, 313, 319
over-enthusiasm 276–78
overloading 231
ownership 232–33
page-level maps 183
pages 183
partner disciplines (departments) 18–20, 32,
100–11, 254
partnering (partnership) 103–10
PDO (Petroleum Development Oman) 303,
363–73
Peer Assist process 26, 141, 236, 239, 246,
305, 343, 404
peer networks 310–12
people-finder systems 142
performance management 233, 235, 270–71
see also awards schemes
performance metrics 265, 267, 268, 269,
271, 273, 371–72
personality trap 60–61
Pillsbury 38
pilots see trials and pilots approach
‘planner’s droop’ 214
planning 25–26, 89–90, 173, 212–23, 370
see also communication plans
policy 169–70, 255–58
NASA 353, 355, 357–58
PDO 364, 366, 369
policy owners 108
portals 164–65
positive perception 191, 192, 193
Post-it notes 78, 89, 107, 140, 203–04, 213,
214
Practical Site Management Guide (PWD
Malaysia) 402
practice owners see knowledge owners
pre-designed framework implementation 23
primary vendors 316
process 15, 33, 39, 79, 131–32, 251, 367
financial management 127
knowledge finding and re-use 172–73
knowledge synthesis 161–63
PDO 371
process owners see knowledge owners
product quality 93
professional associations 311
professional support lawyers 171
programme managers see team leaders
project-based KM frameworks 132
project costs 92
project cycle time 92–93
project deliverables 247
Project Lessons Learned Practical Guide
(PWD Malaysia) 404
project management 68, 109–10
Project Management Challenge (NASA) 358
project management offices 404
project managers 68–69, 170, 245
project metrics 267
project planning templates 213–14
proof-of-concept exercises 29–30, 33, 62, 69,
196, 209, 219–20, 238–44, 246, 317
protection 192
Public Works Department Malaysia 163,
398–408
Index
pull and push 17, 18, 344–45
PWD Strategic Framework 400
Q&A forums 139–40, 142, 311
quality management 109–10, 129
Quality Management Standard 303
quarterly meetings 406
question asking 149, 150, 151, 152, 153,
195, 198
quick-wins 28, 33, 59, 83, 120, 241, 401
RAG analysis 123–24
reactive questioning approach 149
reasoning 194, 198
recognition 233, 235
recording technology 154
records managements 12, 108–09
reference documents (resources) 245–46, 259
relationships 119, 122–23
remembering behaviours 202
repetitive business activity 242
reporting 135, 223, 271–73
see also A3 reports
request access feature 169
requirements creep 321
requirements settings 320–22
resource mapping 104–05, 107, 213–16,
234, 246, 370
respectful negotiation 107
retrospects 152–53, 240, 272–73, 388
RFI (requests for information) 319–20
risk analysis 124, 246
risk management 8, 109–10, 134
ROI 95–96
roles 15, 32, 33, 39, 79, 259
communities of practice 137–38
financial management 127
KM champions 231, 232
knowledge finding and re-use 170–72
knowledge synthesis 160–61
PDO 369–70
team 68–69
roll-out phase 26–27, 250–62, 344
roll-out workshops 222
safety management 8, 134
sales volume 93–94
SAP Jam 367
scheduled questioning 150
scope (scoping KM projects) 50, 245,
317–23, 365
search technology (applications) 175, 183, 187
secondment programmes 396
segmentation 192–94
self-auditing (internal audits) 304–06,
308, 372
self-funding trap 83
senior management 30, 33, 36, 71–76, 101,
276–77, 313, 347
service quality 93
SharePoint 274, 275, 366, 368
Shell 158, 163
short-termism 203, 206
‘should follow’ knowledge 159, 160
Siemens 38, 162, 270, 331
SIKM Leaders Community 311
simple taxonomies 181
Singapore Army 172
Singapore Civil Service College 397
Singapore Sports Council 397
Singapore 2010 post-Games reports 397
Singapore Youth Olympic Organizing
Committee (SYOGOC) 392–97
single taxonomy hierarchy 181
skills 66–68, 118, 122, 313, 314,
334–36, 347
see also competences
skills matrices 68
small talk (social chatter) 135
SMART objectives 90–91
SMEs see subject matter experts (SMEs)
social cohesion 135
social media 39, 142–43, 193, 209, 406, 407
see also Facebook
social proof (silent allies) 193–94, 196–97,
198, 247
socialization opportunities 123
soft metrics 266
South East Asian Games 397
Space Shuttle Program Tacit Knowledge
Capture Project (2008) 356
specialist skills 313, 314
sponsors 71–73, 103, 244, 247, 254, 368
‘squirrel’ behaviour 204, 205
staff surveys 269–70
stakeholder buy-in ladder 189–91, 192 –93,
209, 261
stakeholders 42–43, 100–11, 189–99,
209–10, 217–18, 277, 279, 281–82
standard operating procedures (SOPs) 118, 122
standardization 13, 93, 122, 306, 393, 394
Standards Australia 300
standards development 300–04
see also ISO Standard 30401:2018
Standards Institution of Israel 300
standards warrant 184, 185
steering teams (groups) 74, 104
PDO 368, 369, 370, 372
storage technology 154–55
strategic knowledge assessment 50–51
strategic patience 203
strategic principles 47–48
427
428
Index
strategy 25, 47–54, 56
stretch targets 169
subject matter experts (SMEs) 137, 147, 163,
179, 369, 379, 380, 402, 404, 408
see also knowledge managers; knowledge
owners
success celebrations 208, 259–60
succession planning 61, 123, 165, 280
summarizing 139, 141, 151
supply and demand see pull and push
support 228, 229
surveys 269–70
SYOGOC see Singapore Youth Olympic
Organizing Committee (SYOGOC)
system integrators 316, 317, 318
tacit knowledge 16, 17, 124, 135, 136,
148, 332
Huawei 386, 389
PWD Malaysia 400, 403, 405, 407
Space Shuttle Program Tacit Knowledge
Capture Project (2008) 356
SYOGOC 397
tag clouds 174
tagging systems 174, 185
targeted knowledge resources
audits 120, 121
tax authorities 116
taxonomies 12, 93, 133, 142, 171–72,
174–76, 180–88, 313, 394
see also dictionary lists
taxonomy facets 181–82
Tay 330
team leaders 43, 55–63
team size 64–65
teams 43, 64–70, 216–17, 235, 245, 246,
286–87, 346–47
see also knowledge base administration
teams
Tearfund 240
technology 15, 32, 33–34, 39, 79, 129,
131–32, 219, 251
documentation 153–55
financial management 127
Huawei 385
knowledge discussion 142–43
knowledge finding and re-use 174–76,
183
knowledge synthesis 163–65
MVP 243
PDO 367–68
PWD Malaysia 405–06
SYOGOC 394
see also Artificial Intelligence (AI);
automation; blogs; digital
transformation; e-learning; JPEDIA;
machine learning; request access
feature; technology projects;
technology testing;
technology vendors; wikis
technology projects 321, 323
technology testing 220–21
technology vendors 219, 294, 316–17,
318–20, 322, 323
Teleos 298
tendering process 317–23
terms of reference documents 221, 232, 233,
245, 365, 370
testing see trials and pilots approach
timescales 81–84
top down implementation 23
Toyota 152, 253
tracking roll-out phase 261
training 218, 234, 246, 258–59, 311,
330–31, 348, 352–53, 370, 384–85
transcription services 154
trials and pilots approach 22, 24, 26, 27–30,
62, 90, 196, 201, 221–22, 238–49
Huawei 387–88
undocumented project knowledge 400–01
United Nations 52–53, 306–07
United States (US) 92, 162
use cases 186–87, 321
user warrant 184, 185
value 37–38, 56, 77, 82, 140, 241, 247, 351,
377, 384
targets 95–98
values 68, 203
vendors 219, 294, 316–17, 318–20, 322, 323
venue-planning toolkit (SYOGOC) 395
videos 154, 196–97, 371
Virtual PM Challenge (NASA) 358
vision 49, 106
voice-recognition software 154
web portals 164–65
Web 2.0 385
Whiffen, Paul 240
‘wider sell’ 191–92
wiki moderators 381
Wikipedia 162, 163–64
wikis 148–49, 163–64, 380–81, 402
wikithons 162–63
win/ lose conversations 135
wireframes 183
work processes 40–41
workshops 173, 203–04, 212–13, 222, 311,
348, 394–95, 396, 400
World Bank 71, 134, 207–08
writing skills 67
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