1、12.1 2006 by Prentice Hall12Chapter 12.2 2006 by Prentice Hall Assess the role of knowledge management and knowledge management programs in business Define and describe the types of systems used for enterprise-wide knowledge management and demonstrate how they provide value for organizations Define
2、and describe the major types of knowledge work systems and assess how they provide value for firms OBJECTIVES12.3 2006 by Prentice Hall Evaluate the business benefits of using intelligent techniques for knowledge management Identify the challenges posed by knowledge management systems and management
3、 solutionsOBJECTIVES (Continued)12.4 2006 by Prentice Hall Challenge: Coordinating the flow of unstructured information and documents among multiple product development groups Solutions: Documentum eRoom software to manage product development documents Develop new business processes for document rou
4、ting Illustrates the role of knowledge and document management systems for coordinating teams and achieving operational excellenceCott Corporation Case12.5 2006 by Prentice HallTHE KNOWLEDGE MANAGEMENT LANDSCAPE U.S Enterprise Knowledge Management Software Revenues 2001-2006 Figure 12-1Source: Based
5、 on the data in eMarketer, “Portals and Content Management Solutions,” June 2003.12.6 2006 by Prentice Hall Data: Flow of captured events or transactions Information: Data organized into categories of understanding Knowledge: Concepts, experience, and insight that provide a framework for creating, e
6、valuating, and using information. Can be tacit (undocumented) or explicit (documented)THE KNOWLEDGE MANAGEMENT LANDSCAPE 12.7 2006 by Prentice HallKnowledge is a Firm Asset: Intangible asset Requires organizational resources Value increases as more people share it Wisdom: The collective and individu
7、al experience of applying knowledge to the solution of problem; knowing when, where, and how to apply knowledgeTHE KNOWLEDGE MANAGEMENT LANDSCAPE Important Dimensions of Knowledge (Continued)12.8 2006 by Prentice Hall Tacit or explicit Know-how, craft, and skill Knowing how to follow procedures; why
8、 things happen Knowledge has a Location: Cognitive event Social and individual bases of knowledge Sticky, situated, contextual THE KNOWLEDGE MANAGEMENT LANDSCAPE Knowledge has Different Forms:Important Dimensions of Knowledge (Continued)12.9 2006 by Prentice Hall Conditional Contextual THE KNOWLEDGE
9、 MANAGEMENT LANDSCAPE Knowledge is Situational:Important Dimensions of Knowledge (Continued)12.10 2006 by Prentice Hall Organizational learning: Adjusting business processes and patterns of decision making to reflect knowledge gained through information and experience gatheredOrganizational Learning
10、 and Knowledge Management THE KNOWLEDGE MANAGEMENT LANDSCAPE 12.11 2006 by Prentice Hall Knowledge acquisition Knowledge storage Knowledge dissemination Knowledge application Building organizational and management capital: collaboration, communities of practice, and office environments The Knowledge
11、 Management Value ChainTHE KNOWLEDGE MANAGEMENT LANDSCAPE 12.12 2006 by Prentice HallThe Knowledge Management Value Chain Figure 12-2THE KNOWLEDGE MANAGEMENT LANDSCAPE 12.13 2006 by Prentice Hall Types of Knowledge Management SystemsFigure 12-3THE KNOWLEDGE MANAGEMENT LANDSCAPE 12.14 2006 by Prentic
12、e HallENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS Figure 12-412.15 2006 by Prentice Hall Knowledge repository for formal, structured text documents and reports or presentations Also known as content management system Require appropriate database schema and tagging of documents Examples: Database of
13、 case reports of consulting firms; tax law accounting databases of accounting firms Structured Knowledge System ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS 12.16 2006 by Prentice HallKWorlds Knowledge Domains ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS Figure 12-512.17 2006 by Prentice HallKPMG Kn
14、owledge System Processes ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS Figure 12-612.18 2006 by Prentice Hall Knowledge repository for less-structured documents, such as e-mail, voicemail, chat room exchanges, videos, digital images, brochures, bulletin boards Also known as digital asset management s
15、ystems Taxonomy: Scheme of classifying information and knowledge for easy retrieval Tagging: Marking of documents according to knowledge taxonomySemistructured Knowledge SystemsENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS 12.19 2006 by Prentice HallHummingbirds Integrated Knowledge Management System
16、 ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS Figure 12-712.20 2006 by Prentice HallENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS Online directory of corporate experts, solutions developed by in-house experts, best practices, FAQs Document and organize “tacit” knowledge Also known as expertise locati
17、on and management systemsKnowledge Network Systems12.21 2006 by Prentice HallENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS Knowledge exchange services Community of practice support Autoproofing capabilities Knowledge management services Key features can include: Knowledge Network Systems (Continued)1
18、2.22 2006 by Prentice HallThe Problem of Distributed Knowledge ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS Figure 12-812.23 2006 by Prentice HallAskMe Enterprise Knowledge Network System ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS Figure 12-912.24 2006 by Prentice HallENTERPRISE-WIDE KNOWLEDGE MAN
19、AGEMENT SYSTEMS Enterprise knowledge portals: Access to external sources of information Access to internal knowledge resources Capabilities for e-mail, chat, discussion groups, videoconferencing 12.25 2006 by Prentice HallENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS Provides tools for the management
20、, delivery, tracking, and assessment of various types of employee learning and training Integrates systems from human resources, accounting, sales in order to identify and quantify business impact of employee learning programs Learning Management System (LMS): 12.26 2006 by Prentice HallKNOWLEDGE WO
21、RK SYSTEMS Knowledge workers key roles: Keeping the organization current in knowledge as it develops in the external worldin technology, science, social thought, and the arts Knowledge workers: Create knowledge and information for organization 12.27 2006 by Prentice HallKNOWLEDGE WORK SYSTEMS Servin
22、g as internal consultants regarding the areas of their knowledge, the changes taking place, and opportunities Acting as change agents, evaluating, initiating, and promoting change projects Knowledge Workers and Knowledge Work (Continued)12.28 2006 by Prentice HallRequirements of Knowledge Work Syste
23、msFigure 12-10KNOWLEDGE WORK SYSTEMS 12.29 2006 by Prentice Hall Information system that automates the creation and revision of industrial and manufacturing designs using sophisticated graphics softwareComputer-Aided Design (CAD): Interactive graphics software and hardware that create computer-gener
24、ated simulations that emulate real-world activities or photorealistic simulations Virtual Reality Systems: KNOWLEDGE WORK SYSTEMS 12.30 2006 by Prentice Hall Powerful desktop computer for financial specialists, which is optimized to access and manipulate massive amounts of financial dataInvestment W
25、orkstation: KNOWLEDGE WORK SYSTEMS Examples of Knowledge Work Systems (Continued)12.31 2006 by Prentice HallINTELLIGENT TECHNIQUES Identification of underlying patterns, categories, and behaviors in large data sets, using techniques such as neural networks and data miningKnowledge Discovery: Compute
26、r-based systems based on human behavior, with the ability to learn languages, accomplish physical tasks, use a perceptual apparatus, and emulate human expertise and decision makingArtificial Intelligence (AI) technology: 12.32 2006 by Prentice HallExpert system: An intelligent technique for capturin
27、g tacit knowledge in a very specific and limited domain of human expertise Knowledge base: Model of human knowledge that is used by expert systems Series of 200-10,000 IF-THEN rules to form a rule base INTELLIGENT TECHNIQUES AI shell: The programming environment of an expert system12.33 2006 by Pren
28、tice Hall Rules in an AI ProgramFigure 12-11INTELLIGENT TECHNIQUES 12.34 2006 by Prentice Hall The strategy used to search through the rule base in an expert system. Common strategies are forward chaining and backward chainingInference engine: INTELLIGENT TECHNIQUES A strategy for searching the rule
29、 base in an expert system that begins with the information entered by the user and searches the rule base to arrive at a conclusion Forward chaining: 12.35 2006 by Prentice HallINTELLIGENT TECHNIQUES A strategy for searching the rule base in an expert system that acts like a problem solver by beginn
30、ing with hypothesis and seeking out more information until the hypothesis is either proved or disproved Backward chaining: A specialist who elicits information and expertise from other professionals and translates it into a set of rules for an expert system Knowledge engineer: 12.36 2006 by Prentice
31、 HallInference Engines in Expert Systems INTELLIGENT TECHNIQUES Figure 12-1212.37 2006 by Prentice Hall Knowledge system that represents knowledge as a database of cases and solutions Searches for stored cases with problem characteristics similar to the new case and applies solutions of the old case
32、 to the new caseCase-Based Reasoning (CBR): INTELLIGENT TECHNIQUES 12.38 2006 by Prentice Hall Rule-based technology that can represent imprecise values or ranges of values by creating rules that use approximate or subjective values Used for problems that are difficult to represent by IF-THEN rules
33、Fuzzy Logic SystemsINTELLIGENT TECHNIQUES 12.39 2006 by Prentice HallHow Case-based Reasoning Works INTELLIGENT TECHNIQUES Figure 12-1312.40 2006 by Prentice HallImplementing Fuzzy Logic Rules in Hardware INTELLIGENT TECHNIQUES Figure 12-14Source: James M. Sibigtroth, “Implementing Fuzzy Expert Rule
34、s in Hardware,” Al Expert, April 1992. copyright 1992 Miller Freeman, Inc. Reprinted with permission. 12.41 2006 by Prentice Hall Hardware or software that emulates the processing patterns of the biological brain to discover patterns and relationships in massive amounts of data Use large numbers of
35、sensing and processing nodes that interact with each other INTELLIGENT TECHNIQUES 12.42 2006 by Prentice Hall Uses rules it learns” from patterns in data to construct a hidden layer of logic that can be applied to model new data Applications are found in medicine, science, and business INTELLIGENT T
36、ECHNIQUES Neural Networks (Continued)12.43 2006 by Prentice HallHow a Neural Network Works INTELLIGENT TECHNIQUES Figure 12-15Source: Herb Edelstein, “Technology How-To: Mining Data Warehouses,” InformationWeek, January 8, 1996. Copyright 1996 CMP Media, Inc., 600 Community Drive, Manhasset, NY 1203
37、0. Reprinted with permission.12.44 2006 by Prentice Hall Adaptive computation that examines very large number of solutions for a problem to find optimal solution Programmed to “evolve” by changing and reorganizing component parts using processes such as reproduction, mutation, and natural selection:
38、 worst solutions are discarded and better ones survive to produce even better solutions INTELLIGENT TECHNIQUES 12.45 2006 by Prentice HallThe Components of a Genetic Algorithm INTELLIGENT TECHNIQUES Figure 12-16Source: Dhar, Stein, SEVEN METHODS FOR TRANSFORMING CORPORATE DATA INTO BUSINESS INTELLIG
39、ENCE (Trade Version), 1st copyright 1997. Electronically reproduced by permission of Pearson Education, Inc., Upper Saddle River, New Jersey.12.46 2006 by Prentice Hall Integration of multiple AI technologies (genetic algorithms, fuzzy logic, neural networks) into a single application to take advant
40、age of the best features of these technologiesIntelligent Agents: Software programs that work in the background without direct human intervention to carry out specific, repetitive, and predictable tasks for an individual user, business process, or software applicationINTELLIGENT TECHNIQUES Hybrid AI
41、 system:12.47 2006 by Prentice HallIntelligent Agents in P&Gs Supply Chain Network INTELLIGENT TECHNIQUES Figure 12-1712.48 2006 by Prentice Hall Proprietary knowledge can create an “invisible competitive advantage” Management Opportunities: MANAGEMENT OPPORTUNITIES, CHALLENGES AND SOLUTIONS 12.49 2
42、006 by Prentice Hall Insufficient resources are available to structure and update the content in repositories. Poor quality and high variability of content quality results from insufficient validating mechanisms. Content in repositories lacks context, making documents difficult to understand. Manage
43、ment Challenges: MANAGEMENT OPPORTUNITIES, CHALLENGES AND SOLUTIONS 12.50 2006 by Prentice Hall Individual employees are 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 o
44、r taxonomy.MANAGEMENT OPPORTUNITIES, CHALLENGES AND SOLUTIONS Management Challenges: (Continued)12.51 2006 by Prentice HallDevelop in stagesChoose a high-value business process Choose the right audienceMeasure ROI during initial implementationUse the preliminary ROI to project enterprise-wide values Solution Guidelines: MANAGEMENT OPPORTUNITIES, CHALLENGES AND SOLUTIONS Five important steps in developing a successful knowledge management project: 12.52 2006 by Prentice HallImplementing Knowledge Management Projects in Stages Figure 12-18MANAGEMENT OPPORTUNITIES, CHALLENGES AND SOLUTIONS
