4. Case Studies in
Knowledge
Management
Table of Contents
Preface .........................................................................................................................vii
SectionI:
KnowledgeManagementinSupportofOrganizationalLearning
ChapterI.
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
ChapterII.
AKnowledgeManagementCaseStudyinDeveloping,Documenting,and
DistributingLearning ................................................................................................ 23
Brigette McGregor-MacDonald, Marsh Inc., UK
SectionII:
KnowledgeManagementinSupportofRetainingOrganizationalKnowledge
ChapterIII.
ACaseStudyonAssessingtheReadinessofProfessionalServicesCompanyto
BuildanOrganizationalMemoryInformationSystem .............................................. 36
Hani Abdel-Aziz, Cairo University, Egypt
Khaled Wahba, Cairo University, Egypt
ChapterIV.
RebuildingCoreCompetenciesWhenaCompanySplits:ACaseStudyofAssessing
andRebuildingExpertise ............................................................................................ 51
Gail Corbitt, California State University, Chico, USA
5. SectionIII:
KnowledgeManagementStrategy
ChapterV.
ExploringtheImpactsofKnowledge(Re)UseandOrganizationalMemoryonthe
EffectivenessofStrategicDecisions:ALongitudinalCaseStudy ............................. 66
Afsoun Hatami, London School of Economics, UK
Robert D. Galliers, Bentley College, USA
ChapterVI.
GovernanceofStrategiestoManageOrganizationalKnowledge:AMechanismto
OverseeKnowledgeNeeds .......................................................................................... 83
Suzanne Zyngier, Monash University, Australia
Frada Burstein, Monash University, Australia
Judy McKay, Swinburne University of Technology, Australia
ChapterVII.
ChallengesinDevelopingaKnowledgeManagementStrategyfortheAirForce
MaterialCommand .................................................................................................... 104
Summer E. Bartczak, Air Force Institute of Technology, USA
Ellen C. England, Air Force Institute of Technology, USA
SectionIV:
KnowledgeManagementinSupportofProjects
ChapterVIII.
KnowledgeManagementinaProjectClimate .......................................................... 130
Elayne Coakes, University of Westminster, UK
Anton Bradburn, University of Westminster, UK
Cathy Blake, Taylor Woodrow, UK
ChapterIX.
WhereKnowledgeManagementResideswithinProjectManagement ................... 138
Jill Owen, Monash University, Australia
Frada Burstein, Monash University, Australia
SectionV:
KnowledgeManagementisSupportofKnowledgeTransfer
ChapterX.
OrganizationalKnowledgeSharingBasedontheERPImplementationof
YongxinPaperCo.,Ltd. ............................................................................................. 155
Zhang Li, Harbin Institute of Technology, China
Tian Yezhuang, Harbin Institute of Technology, China
Li Ping, Harbin Institute of Technology, China
6. ChapterXI.
SupportingResearchandDevelopmentProcessesUsingKnowledgeManagement
Methods ..................................................................................................................... 165
Thomas Hahn, Profactor Produktionsforschungs GmbH, Austria
Bernhard Schmiedinger, Profactor Produktionsforschungs GmbH, Austria
Elisabeth Stephan, Profactor Produktionsforschungs GmbH, Austria
ChapterXII.
Know-CoM:DecentralizedKnowledgeManagementSystemsforCooperating
Die-andMold-MakingSMEs .................................................................................... 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
SectionVI:
IssuesinKnowledgeManagement
ChapterXIII.
ReserveBankofNewZealand:JourneyTowardKnowledgeManagement ............. 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
ChapterXIV.
AComparativeCaseStudyofKnowledgeResourceUtilizationtoModel
OrganizationalLearning .......................................................................................... 235
Colin White, Deloitte Consulting, USA
David Croasdell, University of Nevada, Reno, USA
ChapterXV.
ImplementingKnowledge-EnabledCRMStrategyinaLargeCompany:
ACaseStudyfromaDevelopingCountry ................................................................ 249
Minwir Al-Shammari, University of Bahrain, Bahrain
ChapterXVI.
WhyKnowledgeManagementFails:LessonsfromaCaseStudy............................ 279
Ivy Chan, The Chinese University of Hong Kong, Hong Kong
Patrick Y.K. Chau, The University of Hong Kong, Hong Kong
ChapterXVII.
InfosysTechnologies,Limited .................................................................................. 289
Nikhil Mehta, Auburn University, USA
Anju Mehta, Auburn University, USA
7. ChapterXVIII.
KeepingtheFlameAlive:SustainingaSuccessfulKnowledgeManagement
Program .................................................................................................................... 315
Eliot Rich, University of Albany, USA
Peter Duchessi, University of Albany, USA
SectionVII:
KnowledgeManagementOutcomes
ChapterXIX.
KnowledgeManagementforHealthcare:UsingInformationandCommunication
TechnologiesforDecisionMaking .......................................................................... 328
A.N. Dwivedi, Coventry University, UK
Rajeev K. Bali, Coventry University, UK
R.N.G. Naguib, Coventry University, UK
ChapterXX.
ProductivityImpactsfromUsingKnowledge ............................................................ 344
Murray E. Jennex, San Diego State University, USA
AbouttheAuthors ..................................................................................................... 358
Index ........................................................................................................................ 369
8. Preface
vii
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.
9. 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
viii
Figure 1. The KM/OM/OL Model (Jennex & Olfman, 2002)
Learning
OMKM
Drives Users to put Information
and Knowledge into their OMS
Monitor Organizational Effectiveness
and AdjustKnowledge Requirements
as needed
Identify and Acquire
Knowledge for future use
Store, Retrieve, and Search
Memory Base
Evaluate Events for Use of Applicable
Memory to perform actions that affect
Organizational Performance
Org
Impact to Organizational Effectiveness
EEEffectiveness
Access and Use Memory to perform actions
that affect Organizational Performance
Knowledge Users
Management
System
Designers/IT
Knowledge
Engineers
10. 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-
ix
11. edge creation, knowledge storage/retrieval, knowledge transfer, and knowledge appli-
cation and it is expected that the KMS will use technologies specific to supporting the
stage for which the KMS was created to support. Marwick (2001) classifies the KMS/
KMS tools by the mode of Nonaka’s (1994) SECI model (Socialization, Externalization,
Combination, and Internalization) being implemented. Borghoff and Pareschi (1998)
classify the KMS/KMS tools using their Knowledge Management Architecture. This
architecture has 4 classes of components: repositories and libraries, knowledge worker
communities, knowledge cartography/mapping, and knowledge flows; with classifica-
tion being based on the predominant architecture component being supported. Hahn
and Subramani (2001) classify the KMS/KMS tools by the source of the knowledge
being supported: structured artifact, structured individual, unstructured artifact, or
unstructured individual. Binney (2001) classifies the KMS/KMS tools using the Knowl-
edge Spectrum. The Knowledge Spectrum represents the ranges of purposes a KMS
can have and include: transactional KM, analytical KM, asset management KM, pro-
cess-based KM, developmental KM, and innovation and creation KM. Binney (2001)
does not limit a KMS/KMS tool to a single portion of the Knowledge Spectrum and
allows for multi-purpose KMS/KMS tools. Zack (1999) classifies KMS/KMS tools as
either Integrative or Interactive. Integrative KMS/KMS tools support the transfer of
explicit knowledge using some form of repository and support. Interactive KMS/KMS
tools support the transfer of tacit knowledge by facilitating communication between
the knowledge source and the knowledge user. Jennex and Olfman (2004) classify the
KMS/KMS tools by the type of users being supported. Users are separated into two
groups based on the amount of common context of understanding they have with each
other resulting in classifications of: process/task based KMS/KMS tools or generic/
infrastructure KMS/KMS tools.
While I tend to favor a more holistic/Churchmanian view of systems and the KMS
and like to classify the KMS by the amount of context needed by the users to effec-
tively use knowledge, others are equally happy with these other KMS definitions and
classification schemes. It is not the point of this book to settle the debate; in fact, many
of the enclosed cases use definitions different than the holistic. KM is a young disci-
pline and it will have multiple definitions of key terms for a while as we go through
growing pains in establishing our definitions. That is okay, but for us to mature we
need to settle on some of our fundamental definitions. Defining a KMS is one of those
fundamental definitions we need to agree on. This is needed for our practitioners, and
to some degree, our researchers. Practitioners need to speak a common language to
each other and to their clients. The KMS is one of those concepts that clients expect us
to understand. It is hoped that the cases in this book, when taken as a whole, provide
support for the holistic definition as the KMS discussed are varied in their components
and purpose.
ORGANIZATION OF SECTIONS
This book is organized into seven sections, each dedicated to an area of KM
research. The following paragraphs describe these sections.
Section 1 looks at using KM in support of OL and contains two cases. The first
case is from Lynne P. Cooper, Rebecca L. Nash, Tu-Anh T. Phan, and Teresa R. Bailey
and describes a KMS used in the United States’ Jet Propulsion Laboratory to help new
x
12. employees learn about the organizational culture. The second case is from Brigette
McGregor-MacDonald and describes the KMS used in Marsh, Inc. to help employees
learn and pass on their knowledge to other employees. Both cases look at key issues
and discuss the importance of management support in sustaining the KM effort.
Section 2 explores using KM to support the retention of organizational knowl-
edge in organizations where the work forces are in transition. Hani Abdel-Aziz, and
Khaled Wahba discuss the use of OM to capture knowledge in an Egyptian Profes-
sional Services company that had a high rate of employee turnover. Gail Corbitt dis-
cusses the issues affecting knowledge loss and the creation of two financial divisions
when HP split into HP and Agilent. These papers find that the processes used to
capture knowledge are critical. Additionally, issues such as corporate culture, techni-
cal infrastructure, and training are discussed
Section 3 discusses the importance of a KM strategy in the implementation of a
KM initiative. Afsoun Hatami and Robert D. Galliers look at the long term impacts of
strategy on the success of an OM system used to support decision making. Suzanne
Zyngier, Frada Burstein, and Judy McKay discuss the use of corporate governance as
a method of implementing KM strategy in Australia’s Science and Technology Devel-
opment Organization. Summer E. Bartczak and Ellen C. England discuss the issues
involved in developing a KM strategy for the United States’ Air Force Material
Command’s KM initiative. These cases also explore the impact of leadership and the
use of a strategic framework in the development of a KM strategy.
Section 4 discusses the use of KM in the support of projects and project manage-
ment. Elayne Coakes, Anton Bradburn, and Cathy Blake, discuss the use of KM to
capture and use best practices in the British construction firm Taylor Woodrow to
improve project performance. Jill Owen and Frada Burstein look at where knowledge
resides in an Australian consulting firm and how the firm uses this knowledge to im-
prove project performance. Both cases discuss the importance of understanding knowl-
edge transfer dynamics to improve the flow of knowledge within a project team.
Section 5 discusses KM in support of knowledge transfer. Zhang Li, Tian
Yezhuang, and Li Ping, discuss the dynamics of using a Enterprise Resource Planning
system to capture and transfer knowledge in a Chinese manufacturing firm. Thomas
Hahn, Bernhard Schmiedinger, and Elisabeth Stephan look at the use of communities of
practice and other techniques to improve the transfer of knowledge in and between
Austrian small and medium sized manufacturing firms. Florian Bayer, Rafael Enparantza,
Ronald Maier, Franz Obermair, and Bernhard Schmiedinger discuss the use of Know
Com to facilitate the decentralized control of the flow of knowledge between small and
medium sized German die and mould makers.
Section 6 discusses a variety of issues associated with the implementation of KM
and a KMS. Yogesh Anand, David J. Pauleen, and Sally Dexter discuss the develop-
ment and sustainability of the KM initiative in the New Zealand Reserve Bank. Colin
White and David Croasdell discuss issues in representing knowledge in Enterprise
Resource Planning Systems at Nestle USA, Colgate-Palmolive, Xerox, and Chevron-
Texaco. Minwir Al-Shammari discusses issues in using a Data Warehouse and a Cus-
tomer Relationship Management system to capture and transfer knowledge in a Middle
Eastern telecommunications company. Ivy Chan and Patrick Y.K. Chau explore why a
KM initiative failed in a Hong Kong manufacturing and export firm. Nikhil Mehta and
Anju Mehta discuss issues faced by India’s Infosys Technologies, Limited. Eliot Rich
xi
13. and Peter Duchessi discuss the issues involved in sustaining the KM initiative at the
United States’ System Management Solutions International.
Section 7 discusses how to determine KM outcomes. A.N. Dwivedi, Rajeev K.
Bali, and R.N.G. Naguib discuss a general KM framework for the British healthcare
industry and how to manage KM successfully. Murray E. Jennex discusses how the
use of knowledge can impact individual and organizational productivity.
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