Presentation on theme: "Managing Knowledge in the Digital Firm"— Presentation transcript:
1 Managing Knowledge in the Digital Firm Chapter 11Managing Knowledge in the Digital Firm
2 ObjectivesWhat 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?
3 ObjectivesWhat 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 performanceIdentifying and implementing appropriate organizational applications for artificial intelligence
5 Important Dimensions of Knowledge The Knowledge Management LandscapeImportant Dimensions of KnowledgeKnowledgeWisdomTacit knowledgeExplicit knowledge
7 Important Dimensions of Knowledge The Knowledge Management LandscapeImportant Dimensions of KnowledgeKnowledge:Is a firm assetHas different formsHas a locationIs situational
8 Organizational Learning and Knowledge Management The Knowledge Management LandscapeOrganizational Learning and Knowledge ManagementOrganizational learning: Creation of new standard operating procedures and business processes reflecting experienceKnowledge management: Set of processes developed in an organization to create, gather, store, disseminate, and apply knowledge
9 The knowledge management value chain The Knowledge Management LandscapeThe knowledge management value chainFigure 11-2
10 The Knowledge Management Value Chain The Knowledge Management LandscapeThe Knowledge Management Value ChainKnowledge acquisitionKnowledge storageKnowledge disseminationKnowledge application
11 The Knowledge Management Value Chain The Knowledge Management LandscapeThe Knowledge Management Value ChainChief Knowledge Officer (CKO): Senior executive in charge of the organization's knowledge management programCommunities of Practice (COP): Informal groups who may live or work in different locations but share a common profession
12 Types of Knowledge Management Systems Enterprise Knowledge Management Systems: General purpose, integrated, and firm-wide systems to collect, store and disseminate digital content and knowledgeKnowledge Work Systems (KWS): Information systems that aid knowledge workers in the creation and integration of new knowledge in the organizationIntelligent Techniques: Datamining and artificial intelligence technologies used for discovering, codifying, storing, and extending knowledge
13 Major types of knowledge management systems Figure 11-3
17 KPMG knowledge system processes Enterprise-Wide Knowledge Management SystemsKPMG knowledge system processesFigure 11-6
18 DaimlerChrysler Learns to Manage Its Digital Assets Enterprise-Wide Knowledge Management SystemsWindow on TechnologyDaimlerChrysler Learns to ManageIts Digital AssetsWhat are the management benefits of using a digital asset management system?How does ADAM provide value for DaimlerChrysler?
19 Organizing Knowledge: Taxonomies and Tagging Enterprise-Wide Knowledge Management SystemsOrganizing Knowledge: Taxonomies and TaggingTaxonomy: Method of classifying things according to a predetermined systemTagging: Once a knowledge taxonomy is produced, documents are tagged with proper classification
21 Key Functions of an Enterprise Knowledge Network Enterprise-Wide Knowledge Management SystemsKnowledge NetworksKey Functions of an Enterprise Knowledge NetworkKnowledge exchange servicesCommunity of practice supportAuto-Profiling CapabilitiesKnowledge management services
22 The problem of distributed knowledge Enterprise-Wide Knowledge Management SystemsThe problem of distributed knowledgeFigure 11-8
24 Portals, Collaboration Tools, and Learning Management Systems Enterprise-Wide Knowledge Management SystemsPortals, Collaboration Tools, and Learning Management SystemsTeamware: Group collaboration software running on intranets that is customized for teamwork
25 Portals, Collaboration Tools, and Learning Management Systems Enterprise-Wide Knowledge Management SystemsPortals, Collaboration Tools, and Learning Management SystemsLearning Management Systems (LMS): Tools for the management, delivery, tracking, and assessment of various types of employee learning
26 Managing Employee Learning: New Tools, New Benefits Enterprise-Wide Knowledge Management SystemsWindow on ManagementManaging Employee Learning: New Tools, New BenefitsWhat are the management benefits of using learning management systems?How do they provide value to Alyeska and APL
27 Knowledge Workers and Knowledge Work Knowledge Work SystemsKnowledge Workers and Knowledge WorkKnowledge workers perform 3 key roles:Keeping the organization current in knowledge as it develops in the external worldServing as integral consultants regarding the areas of their knowledge, the changes taking place, and opportunitiesActing as change agents
28 Requirements of knowledge work systems Figure 11-10
29 Examples of Knowledge Work Systems Computer-aided design (CAD)Virtual reality systemsVirtual Reality Modeling Language (VRML)Investment workstations
30 Capturing Knowledge: Expert Systems Intelligent TechniquesCapturing Knowledge: Expert SystemsKnowledge Base: Model of human knowledgeRule-based Expert System: Collection in an AI system represented in the the form of IF-THEN
31 Capturing Knowledge: Expert Systems Intelligent TechniquesCapturing Knowledge: Expert SystemsAI shell: programming environmentInference Engine: strategy used to search through the rule baseForward 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
32 Intelligent Techniques Rules in an AI programFigure 11-11
33 Inference engines in expert systems Intelligent TechniquesInference engines in expert systemsFigure 11-12
34 Capturing Knowledge: Expert Systems Intelligent TechniquesCapturing Knowledge: Expert SystemsBackward Chaining: Strategy for searching the rule base in an expert system that acts as a problem solverKnowledge Engineer: Specialist who elicits information and expertise from other professionals and translates it into set of rules for an expert system
35 Examples of Successful Expert Systems Intelligent TechniquesExamples of Successful Expert SystemsGaleria KaufhofCountrywide Funding Corp.
36 Organizational Intelligence: Case-Based Reasoning Intelligent TechniquesOrganizational Intelligence: Case-Based ReasoningCase-based Reasoning (CBR): Artificial intelligence technology that represents knowledge as a database of cases and solutions
37 How case-based reasoning works Intelligent TechniquesHow case-based reasoning worksFigure 11-13
38 Tolerates imprecision Fuzzy Logic SystemsFuzzy Logic SystemsRule-based AITolerates imprecisionUses nonspecific terms called membership functions to solve problems
39 Implementing fuzzy logic rules in hardware Fuzzy Logic SystemsImplementing fuzzy logic rules in hardwareFigure 11-14
40 Hardware or software emulating processing patterns of biological brain Neural NetworksNeural NetworksHardware or software emulating processing patterns of biological brainPut intelligence into hardware in form of a generalized capability to learn
41 How a neural network works Neural NetworksHow a neural network worksFigure 11-15
42 Problem-solving methods Genetic AlgorithmsGenetic AlgorithmsProblem-solving methodsPromote evolution of solutions to specified problemsUse a model of living organisms adapting to their environment
43 The components of a genetic algorithm Genetic AlgorithmsThe components of a genetic algorithmFigure 11-16
44 Integration of multiple AI technologies into a single application Genetic AlgorithmsHybrid AI SystemsIntegration of multiple AI technologies into a single applicationTakes advantage of best features of technologies
45 Intelligent AgentsIntelligent AgentsSoftware 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 agent technology at work Intelligent AgentsIntelligent agent technology at workFigure 11-17
47 Implementation Challenges Management Issues for Knowledge Management SystemsImplementation ChallengesInsufficient resources available to structure and update the content in repositoriesPoor quality and high variability of content quality because of insufficient mechanismsContent in repositories lacks context, making documents difficult to understand
48 Implementation Challenges Management Issues for Knowledge Management SystemsImplementation ChallengesIndividual employees not rewarded for contributing content, and many fear sharing knowledge with others on the jobSearch engines return too much information, reflecting lack of knowledge structure or taxonomy
49 Implementing knowledge management projects in stages Management Issues for Knowledge Management SystemsImplementing knowledge management projects in stagesFigure 11-18
50 Obtaining Value from Knowledge Management Systems Develop in stagesChoose a high-value business processChoose the right audienceMeasure ROI during initial implementationUse the preliminary ROI to project enterprise-wide values
51 Can Knowledge Systems Help Procter & Gamble Stay Ahead of the Pack? Chapter 11 Case StudyCan 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?
52 Can Knowledge Systems Help Procter & Gamble Stay Ahead of the Pack? Chapter 11 Case StudyCan 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.