Managing Knowledge in the Digital Firm

1
Managing Knowledge inthe Digital Firm
Chapter 11
2
Objectives

1. What is knowledge management? Why do businesses
   today need knowledge management programs and
   systems for knowledge management?
2. What types of systems are used for
   enterprise-wide knowledge management? How do they
   provide value for organizations?
3. How do knowledge work systems provide value for
   firms? What are the major types of knowledge work
   systems?

3
Objectives

• What are the business benefits of using
  intelligent techniques for knowledge management?
• What major management issues and problems are
  raised by knowledge management systems? How can
  firms obtain value from their investments in
  knowledge management systems?

4
Management Challenges

• Designing knowledge systems that genuinely
  enhance organizational performance
• Identifying and implementing appropriate
  organizational applications for artificial
  intelligence

5
The Knowledge Management Landscape
Important Dimensions of Knowledge

• Knowledge
• Wisdom
• Tacit knowledge
• Explicit knowledge

6
The Knowledge Management Landscape
U.S enterprise knowledge management software
revenues, 2001-2006
Figure 11-1
7
The Knowledge Management Landscape
Important Dimensions of Knowledge

• Knowledge
• Is a firm asset
• Has different forms
• Has a location
• Is situational

8
The Knowledge Management Landscape
Organizational Learning and Knowledge Management

• Organizational learning Creation of new standard
  operating procedures and business processes
  reflecting experience
• Knowledge management Set of processes developed
  in an organization to create, gather, store,
  disseminate, and apply knowledge

9
The Knowledge Management Landscape
The knowledge management value chain
Figure 11-2
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The Knowledge Management Landscape
The Knowledge Management Value Chain

• Knowledge acquisition
• Knowledge storage
• Knowledge dissemination
• Knowledge application

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The Knowledge Management Landscape
The Knowledge Management Value Chain

• Chief Knowledge Officer (CKO) Senior executive
  in charge of the organization's knowledge
  management program
• Communities of Practice (COP) Informal groups
  who may live or work in different locations but
  share a common profession

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Types of Knowledge Management Systems
Types of Knowledge Management Systems

• Enterprise Knowledge Management Systems General
  purpose, integrated, and firm-wide systems to
  collect, store and disseminate digital content
  and knowledge
• Knowledge Work Systems (KWS) Information systems
  that aid knowledge workers in the creation and
  integration of new knowledge in the organization
• Intelligent Techniques Datamining and artificial
  intelligence technologies used for discovering,
  codifying, storing, and extending knowledge

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Types of Knowledge Management Systems
Major types of knowledge management systems
Figure 11-3
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Enterprise-Wide Knowledge Management Systems
Structured Knowledge Systems

• Structured knowledge
• Semistructured knowledge
• Knowledge repository
• Knowledge network

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Enterprise-Wide Knowledge Management Systems
Enterprise-wide knowledge management systems
Figure 11-4
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Enterprise-Wide Knowledge Management Systems
KWorlds knowledge domain
Figure 11-5
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Enterprise-Wide Knowledge Management Systems
KPMG knowledge system processes
Figure 11-6
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Enterprise-Wide Knowledge Management Systems
Window on Technology

• DaimlerChrysler Learns to Manage
• Its Digital Assets
• What are the management benefits of using a
  digital asset management system?
• How does ADAM provide value for DaimlerChrysler?

19
Enterprise-Wide Knowledge Management Systems
Organizing Knowledge Taxonomies and Tagging

• Taxonomy Method of classifying things according
  to a predetermined system
• Tagging Once a knowledge taxonomy is produced,
  documents are tagged with proper classification

20
Enterprise-Wide Knowledge Management Systems
Hummingbirds integrated knowledge management
system
Figure 11-7
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Enterprise-Wide Knowledge Management Systems
Knowledge Networks

• Key Functions of an Enterprise Knowledge Network
• Knowledge exchange services
• Community of practice support
• Auto-Profiling Capabilities
• Knowledge management services

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Enterprise-Wide Knowledge Management Systems
The problem of distributed knowledge
Figure 11-8
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Enterprise-Wide Knowledge Management Systems
AskMe Enterprise knowledge network system
Figure 11-9
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Enterprise-Wide Knowledge Management Systems
Portals, Collaboration Tools, and Learning
Management Systems

• Teamware Group collaboration software running on
  intranets that is customized for teamwork

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Enterprise-Wide Knowledge Management Systems
Portals, Collaboration Tools, and Learning
Management Systems

• Learning Management Systems (LMS) Tools for the
  management, delivery, tracking, and assessment of
  various types of employee learning

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Enterprise-Wide Knowledge Management Systems
Window on Management

• Managing Employee Learning New Tools, New
  Benefits
• What are the management benefits of using
  learning management systems?
• How do they provide value to Alyeska and APL

27
Knowledge Work Systems
Knowledge Workers and Knowledge Work

• Knowledge workers perform 3 key roles
• Keeping the organization current in knowledge as
  it develops in the external world
• Serving as integral consultants regarding the
  areas of their knowledge, the changes taking
  place, and opportunities
• Acting as change agents

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Knowledge Work Systems
Requirements of knowledge work systems
Figure 11-10
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Knowledge Work Systems
Examples of Knowledge Work Systems

• Computer-aided design (CAD)
• Virtual reality systems
• Virtual Reality Modeling Language (VRML)
• Investment workstations

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Intelligent Techniques
Capturing Knowledge Expert Systems

• Knowledge Base Model of human knowledge
• Rule-based Expert System Collection in an AI
  system represented in the the form of IF-THEN

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Intelligent Techniques
Capturing Knowledge Expert Systems

• AI shell programming environment
• Inference Engine strategy used to search
  through the rule base
• Forward Chaining strategy for searching the
  rules base that begins with the information
  entered by user and searches the rule base to
  arrive at a conclusion

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Intelligent Techniques
Rules in an AI program
Figure 11-11
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Intelligent Techniques
Inference engines in expert systems
Figure 11-12
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Intelligent Techniques
Capturing Knowledge Expert Systems

• Backward Chaining Strategy for searching the
  rule base in an expert system that acts as a
  problem solver
• Knowledge Engineer Specialist who elicits
  information and expertise from other
  professionals and translates it into set of rules
  for an expert system

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Intelligent Techniques
Examples of Successful Expert Systems

• Galeria Kaufhof
• Countrywide Funding Corp.

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Intelligent Techniques
Organizational Intelligence Case-Based Reasoning

• Case-based Reasoning (CBR) Artificial
  intelligence technology that represents knowledge
  as a database of cases and solutions

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Intelligent Techniques
How case-based reasoning works
Figure 11-13
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Fuzzy Logic Systems
Fuzzy Logic Systems

• Rule-based AI
• Tolerates imprecision
• Uses nonspecific terms called membership
  functions to solve problems

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Fuzzy Logic Systems
Implementing fuzzy logic rules in hardware
Figure 11-14
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Neural Networks
Neural Networks

• Hardware or software emulating processing
  patterns of biological brain
• Put intelligence into hardware in form of a
  generalized capability to learn

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Neural Networks
How a neural network works
Figure 11-15
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Genetic Algorithms
Genetic Algorithms

• Problem-solving methods
• Promote evolution of solutions to specified
  problems
• Use a model of living organisms adapting to their
  environment

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Genetic Algorithms
The components of a genetic algorithm
Figure 11-16
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Genetic Algorithms
Hybrid AI Systems

• Integration of multiple AI technologies into a
  single application
• Takes advantage of best features of technologies

45
Intelligent Agents
Intelligent Agents

• Software program that uses built-in or learned
  knowledge base to carry out specific, repetitive,
  and predictable tasks for an individual user,
  business process, or software application

46
Intelligent Agents
Intelligent agent technology at work
Figure 11-17
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Management Issues for Knowledge Management Systems
Implementation Challenges

• Insufficient resources available to structure and
  update the content in repositories
• Poor quality and high variability of content
  quality because of insufficient mechanisms
• Content in repositories lacks context, making
  documents difficult to understand

48
Management Issues for Knowledge Management Systems
Implementation Challenges

• Individual employees not rewarded for
  contributing content, and many fear sharing
  knowledge with others on the job
• Search engines return too much information,
  reflecting lack of knowledge structure or taxonomy

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Management Issues for Knowledge Management Systems
Implementing knowledge management projects in
stages
Figure 11-18
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Obtaining Value from Knowledge Management Systems
Obtaining Value from Knowledge Management Systems

1. Develop in stages
2. Choose a high-value business process
3. Choose the right audience
4. Measure ROI during initial implementation
5. Use the preliminary ROI to project
   enterprise-wide values

51
Chapter 11 Case Study
Can Knowledge Systems Help Procter Gamble Stay
Ahead of the Pack?

1. Analyze PGs business strategy using the value
   chain and competitive forces models.
2. What business and technology conditions caused
   PG to change its business strategy? What
   management, organization, and technology problems
   did PG face?

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Chapter 11 Case Study
Can Knowledge Systems Help Procter Gamble Stay
Ahead of the Pack?

• What is the role of knowledge management in
  supporting PGs business strategy? Explain how
  knowledge management systems help PG execute its
  business strategy.
• How successful has PG been in pursuing its
  business strategy and using knowledge management?
  How successful do you think that strategy will be
  in the future? Explain your answer.