Case Studies in Knowledge Management

389 Pages·2005·6.73 MB·English

by  Jennex, Murray

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Murray E. Jennex
San Diego State University, USA
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Library of Congress Cataloging-in-Publication Data
Case studies in knowledge management / Murray Jennex, editor.
p. cm.
Includes bibliographical references and index.
ISBN 1-59140-351-0 (hardcover) -- ISBN 1-59140-352-9 (softcover) -- ISBN 1-59140-353-7
(ebook)
1. Knowledge management--Case studies. I. Jennex, Murray, 1956-
HD30.2.C378 2005
658.4'038--dc22
2005004515
British Cataloguing in Publication Data
A Cataloguing in Publication record for this book is available from the British Library.
All work contributed to this book is new, previously-unpublished material. The views expressed in
this book are those of the authors, but not necessarily of the publisher.
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Preface .........................................................................................................................vii
Section I:
Knowledge Management in Support of Organizational Learning
Chapter I.
Learning from Simple Systems: The Case of JPL 101.................................................1
Lynne P. Cooper, Jet Propulsion Laboratory, USA
Rebecca L. Nash, Jet Propulsion Laboratory, USA
Tu-Anh T. Phan, Jet Propulsion Laboratory, USA
Teresa R. Bailey, Jet Propulsion Laboratory, USA
Chapter II.
A Knowledge Management Case Study in Developing, Documenting, and
Distributing Learning ................................................................................................ 23
Brigette McGregor-MacDonald, Marsh Inc., UK
Section II:
Knowledge Management in Support of Retaining Organizational Knowledge
Chapter III.
A Case Study on Assessing the Readiness of Professional Services Company to
Build an Organizational Memory Information System.............................................. 36
Hani Abdel-Aziz, Cairo University, Egypt
Khaled Wahba, Cairo University, Egypt
Chapter IV.
Rebuilding Core Competencies When a Company Splits: A Case Study of Assessing
and Rebuilding Expertise ............................................................................................ 51
Gail Corbitt, California State University, Chico, USA
Section III:
Knowledge Management Strategy
Chapter V.
Exploring the Impacts of Knowledge (Re)Use and Organizational Memory on the
Effectiveness of Strategic Decisions: A Longitudinal Case Study............................. 66
Afsoun Hatami, London School of Economics, UK
Robert D. Galliers, Bentley College, USA
Chapter VI.
Governance of Strategies to Manage Organizational Knowledge: A Mechanism to
Oversee Knowledge Needs.......................................................................................... 83
Suzanne Zyngier, Monash University, Australia
Frada Burstein, Monash University, Australia
Judy McKay, Swinburne University of Technology, Australia
Chapter VII.
Challenges in Developing a Knowledge Management Strategy for the Air Force
Material Command....................................................................................................104
Summer E. Bartczak, Air Force Institute of Technology, USA
Ellen C. England, Air Force Institute of Technology, USA
Section IV:
Knowledge Management in Support of Projects
Chapter VIII.
Knowledge Management in a Project Climate..........................................................130
Elayne Coakes, University of Westminster, UK
Anton Bradburn, University of Westminster, UK
Cathy Blake, Taylor Woodrow, UK
Chapter IX.
Where Knowledge Management Resides within Project Management ................... 138
Jill Owen, Monash University, Australia
Frada Burstein, Monash University, Australia
Section V:
Knowledge Management is Support of Knowledge Transfer
Chapter X.
Organizational Knowledge Sharing Based on the ERP Implementation of
Yongxin Paper Co., Ltd..............................................................................................155
Zhang Li, Harbin Institute of Technology, China
Tian Yezhuang, Harbin Institute of Technology, China
Li Ping, Harbin Institute of Technology, China
Chapter XI.
Supporting Research and Development Processes Using Knowledge Management
Methods..................................................................................................................... 165
Thomas Hahn, Profactor Produktionsforschungs GmbH, Austria
Bernhard Schmiedinger, Profactor Produktionsforschungs GmbH, Austria
Elisabeth Stephan, Profactor Produktionsforschungs GmbH, Austria
Chapter XII.
Know-CoM: Decentralized Knowledge Management Systems for Cooperating
Die- and Mold-Making SMEs....................................................................................186
Florian Bayer, Martin-Luther-University Halle-Wittenberg, Germany
Rafael Enparantza, Centro Technológico Tekniker, Spain
Ronald Maier, Martin-Luther-University Halle-Wittenberg, Germany
Franz Obermair, Profactor Produktionsforschungs GmbH, Austria
Bernhard Schmiedinger, Profactor Produktionsforschungs GmbH, Austria
Section VI:
Issues in Knowledge Management
Chapter XIII.
Reserve Bank of New Zealand: Journey Toward Knowledge Management ............. 211
Yogesh Anand, Reserve Bank of New Zealand, New Zealand
David J. Pauleen, Victoria University of Wellington, New Zealand
Sally Dexter, Victoria University of Wellington, New Zealand
Chapter XIV.
A Comparative Case Study of Knowledge Resource Utilization to Model
Organizational Learning..........................................................................................235
Colin White, Deloitte Consulting, USA
David Croasdell, University of Nevada, Reno, USA
Chapter XV.
Implementing Knowledge-Enabled CRM Strategy in a Large Company:
A Case Study from a Developing Country ................................................................249
Minwir Al-Shammari, University of Bahrain, Bahrain
Chapter XVI.
Why Knowledge Management Fails: Lessons from a Case Study............................279
Ivy Chan, The Chinese University of Hong Kong, Hong Kong
Patrick Y.K. Chau, The University of Hong Kong, Hong Kong
Chapter XVII.
Infosys Technologies, Limited..................................................................................289
Nikhil Mehta, Auburn University, USA
Anju Mehta, Auburn University, USA
Chapter XVIII.
Keeping the Flame Alive: Sustaining a Successful Knowledge Management
Program ....................................................................................................................315
Eliot Rich, University of Albany, USA
Peter Duchessi, University of Albany, USA
Section VII:
Knowledge Management Outcomes
Chapter XIX.
Knowledge Management for Healthcare: Using Information and Communication
Technologies for Decision Making .......................................................................... 328
A.N. Dwivedi, Coventry University, UK
Rajeev K. Bali, Coventry University, UK
R.N.G. Naguib, Coventry University, UK
Chapter XX.
Productivity Impacts from Using Knowledge............................................................344
Murray E. Jennex, San Diego State University, USA
About the Authors.....................................................................................................358
Index ........................................................................................................................369
vii
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Knowledge Management (KM) has been growing in importance and popularity
as a research topic since the mid 1990s. This is sufficient time for many organizations
to implement KM initiatives and KM systems (KMS). This book presents twenty cases
investigating the implementation of KM in a number of business and industry settings
and a variety of global settings. The purpose of this book is to fill a deficiency that I’ve
observed while teaching KM. KM is being taught in specialized courses and as a topic
included in Decision Support Systems (DSS), Enterprise Information Systems (EIS),
and Management Information Systems (MIS) issues courses. The deficiency I’ve ob-
served is in moving discussions of KM from a focus on theory to the more practical
focus of how to implement KM to help organizations improve their performance. Exist-
ing course materials do include some short cases and/or vignettes discussing KM in
business settings, but I haven’t found any source that has multiple, detailed teaching
cases. This book is meant to fill that void.
The cases contained in this book are presented as teaching cases. All have
discussion questions and are written in a style that students can easily read and under-
stand. Also, additional sources and support materials are included where appropriate.
The book includes cases from many different countries in an attempt to appeal to as
wide an audience as possible. Cases are included from Australia, Austria, Bahrain,
China, Egypt, Germany, Great Britain, Hong Kong, India, New Zealand, and the United
States. Additionally, a variety of business situations are presented including banking,
consulting, engineering, government agencies, manufacturing, military, project man-
agement, software development, and public utilities. Also, several different related
processes and technologies are discussed. Related processes include organizational
learning (OL) and organizational memory (OM). Technologies include Customer Rela-
tionship Management (CRM), Enterprise Resource Planning (ERP), Data Warehousing,
networking, and Intranets. Finally, several issues are addressed including knowledge
capture, knowledge sharing, knowledge transfer, knowledge representation, organiza-
tional culture, management support, KM/KMS success, KM sustainability, retaining
worker knowledge, creating learning organizations, and management support.
viii
WHAT IS KM?
There are many definitions of KM but this book combines the KM and OM litera-
ture to define KM as the process of selectively applying knowledge from previous
experiences of decision-making to current and future decision making activities with
the express purpose of improving the organization’s effectiveness. This definition
allows us to define the goals of KM as:
• Identify Critical Knowledge
• Acquire Critical Knowledge in a Knowledge Base or Organizational Memory
• Share the stored Knowledge
• Apply the Knowledge to appropriate situations
• Determine the effectiveness of using the applied knowledge
• Adjust Knowledge use to improve effectiveness
WHY OM AND OL?
Why is OM, and OL included in a book on knowledge management? Jennex and
Olfman (2002) found that the three areas are related and have an impact on organiza-
tional effectiveness. KM and OM are observed to be manifestations of the same pro-
cess in different organizations. User organizations ‘do’ knowledge management; they
identify key knowledge artifacts for retention and establish processes for capturing it.
OM is what IT support organizations ‘do’; they provide the infrastructure and support
for storing, searching, and retrieving knowledge artifacts. OL results when users utilize
captured knowledge. That OL may not always have a positive effect is examined by the
monitoring of organizational effectiveness. Effectiveness can improve, get worse, or
Figure 1. The KM/OM/OL Model (Jennex & Olfman, 2002)
Impact to Organizational Effectiveness
EEEffectiveness
Access and Use Memory to perform actions
Management Org that affect Organizational Performance
Learning Knowledge Users
Evaluate Events for Use of Applicable
Monitor Organizational Effectiveness Memory to perform actions that affect
and AdjustKnowledge Requirements Organizational Performance
as needed

Knowledge
Engineers
System
Designers/IT
KM OM
Drives Users to put Information
and Knowledge into their OMS
Identify and Acquire Store, Retrieve, and Search
Knowledge for future use Memory Base
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remain the same. How effectiveness changes influences the feedback provided to the
organization using the knowledge.
WHAT IS A KMS?
The cases in this book address the implementation of Knowledge Management
Systems (KMS). However, KMS is a term that does not have a consensus definition.
Yes, we know what the initials KMS stand for and we have an understanding of what a
system is. The IPO model: Inputs, Processes, Outputs, defines a basic system that
when we add feedback, is a fair description of a KMS in a learning organization. We get
further insight into what an information system is from Alter (1999) who defines an
information system as humans or machines limited to processing information by per-
forming six types of operations: capturing, transmitting, storing, retrieving, manipulat-
ing, and displaying. This is further refined by Churchman (1979, p. 29) who defines a
system as “a set of parts coordinated to accomplish a set of goals;” and that there are
five basic considerations for determining the meaning of a system:
• system objectives, including performance measures
• system environment
• system resources
• system components, their activities, goals and measures of performance
• system management.
Churchman (1979) also noted that systems are always part of a larger system and
that the environment surrounding the system is outside the system’s control, but influ-
ences how the system performs. These definitions are useful but don’t fully describe a
KMS. Reviewing the literature provides definitions that range from purely technical to
something that includes organizational issues. These definitions are summarized be-
low.
Alavi and Leidner (2001, p. 114) defined a KMS as “IT-based systems developed
to support and enhance the organizational processes of knowledge creation, storage/
retrieval, transfer, and application.” They observed that not all KM initiatives will
implement an IT solution, but they support IT as an enabler of KM. Maier (2002)
expanded on the IT concept for the KMS by calling it an ICT (Information and Commu-
nication Technology) system that supported the functions of knowledge creation, con-
struction, identification, capturing, acquisition, selection, valuation, organization, link-
ing, structuring, formalization, visualization, distribution, retention, maintenance, re-
finement, evolution, accessing, search, and application. Stein and Zwass (1995) define
an Organizational Memory Information System (OMIS) as the processes and IT compo-
nents necessary to capture, store, and apply knowledge created in the past on deci-
sions currently being made. Jennex and Olfman (2004) expanded this definition by
incorporating the OMIS into the KMS and adding strategy and service components to
the KMS.
Additionally, we have different ways of classifying the KMS and/or KMS tech-
nologies where KMS technologies are the specific IT/ICT tools being implemented in
the KMS. Alavi and Leidner (2001) classify the KMS/KMS tools based on the Knowl-
edge Life Cycle stage being predominantly supported. This model has 4 stages, knowl-