Managing Knowledge in the Digital Firm Chapter 11 Managing Knowledge in the Digital Firm

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

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?

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

Important Dimensions of Knowledge The Knowledge Management Landscape Important Dimensions of Knowledge Knowledge Wisdom Tacit knowledge Explicit knowledge

U.S enterprise knowledge management software revenues, 2001-2006 The Knowledge Management Landscape U.S enterprise knowledge management software revenues, 2001-2006 Figure 11-1

Important Dimensions of Knowledge The Knowledge Management Landscape Important Dimensions of Knowledge Knowledge: Is a firm asset Has different forms Has a location Is situational

Organizational Learning and Knowledge Management 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

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

The Knowledge Management Value Chain The Knowledge Management Landscape The Knowledge Management Value Chain Knowledge acquisition Knowledge storage Knowledge dissemination Knowledge application

The Knowledge Management Value Chain 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

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

Major types of knowledge management systems Figure 11-3

Structured Knowledge Systems Enterprise-Wide Knowledge Management Systems Structured Knowledge Systems Structured knowledge Semistructured knowledge Knowledge repository Knowledge network

Enterprise-wide knowledge management systems Figure 11-4

KWorld’s knowledge domain Enterprise-Wide Knowledge Management Systems KWorld’s knowledge domain Figure 11-5

KPMG knowledge system processes Enterprise-Wide Knowledge Management Systems KPMG knowledge system processes Figure 11-6

DaimlerChrysler Learns to Manage Its Digital Assets 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?

Organizing Knowledge: Taxonomies and Tagging 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

Hummingbird’s integrated knowledge management system Enterprise-Wide Knowledge Management Systems Hummingbird’s integrated knowledge management system Figure 11-7

Key Functions of an Enterprise Knowledge Network 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

The problem of distributed knowledge Enterprise-Wide Knowledge Management Systems The problem of distributed knowledge Figure 11-8

AskMe Enterprise knowledge network system Enterprise-Wide Knowledge Management Systems AskMe Enterprise knowledge network system Figure 11-9

Portals, Collaboration Tools, and Learning Management Systems Enterprise-Wide Knowledge Management Systems Portals, Collaboration Tools, and Learning Management Systems Teamware: Group collaboration software running on intranets that is customized for teamwork

Portals, Collaboration Tools, and Learning Management Systems 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

Managing Employee Learning: New Tools, New Benefits 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

Knowledge Workers and Knowledge Work 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

Requirements of knowledge work systems Figure 11-10

Examples of Knowledge Work Systems Computer-aided design (CAD) Virtual reality systems Virtual Reality Modeling Language (VRML) Investment workstations

Capturing Knowledge: Expert Systems 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

Capturing Knowledge: Expert Systems 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

Intelligent Techniques Rules in an AI program Figure 11-11

Inference engines in expert systems Intelligent Techniques Inference engines in expert systems Figure 11-12

Capturing Knowledge: Expert Systems 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

Examples of Successful Expert Systems Intelligent Techniques Examples of Successful Expert Systems Galeria Kaufhof Countrywide Funding Corp.

Organizational Intelligence: Case-Based Reasoning Intelligent Techniques Organizational Intelligence: Case-Based Reasoning Case-based Reasoning (CBR): Artificial intelligence technology that represents knowledge as a database of cases and solutions

How case-based reasoning works Intelligent Techniques How case-based reasoning works Figure 11-13

Tolerates imprecision Fuzzy Logic Systems Fuzzy Logic Systems Rule-based AI Tolerates imprecision Uses nonspecific terms called membership functions to solve problems

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

Hardware or software emulating processing patterns of biological brain 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

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

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

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

Integration of multiple AI technologies into a single application Genetic Algorithms Hybrid AI Systems Integration of multiple AI technologies into a single application Takes advantage of best features of technologies

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

Intelligent agent technology at work Intelligent Agents Intelligent agent technology at work Figure 11-17

Implementation Challenges 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

Implementation Challenges 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

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

Obtaining Value from Knowledge Management Systems Develop in stages Choose a high-value business process Choose the right audience Measure ROI during initial implementation Use the preliminary ROI to project enterprise-wide values

Can Knowledge Systems Help Procter & Gamble Stay Ahead of the Pack? Chapter 11 Case Study Can Knowledge Systems Help Procter & Gamble Stay Ahead of the Pack? Analyze P&G’s business strategy using the value chain and competitive forces models. What business and technology conditions caused P&G to change its business strategy? What management, organization, and technology problems did P&G face?

Can Knowledge Systems Help Procter & Gamble Stay Ahead of the Pack? Chapter 11 Case Study Can Knowledge Systems Help Procter & Gamble Stay Ahead of the Pack? What is the role of knowledge management in supporting P&G’s business strategy? Explain how knowledge management systems help P&G execute its business strategy. How successful has P&G 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.