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10.1 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm 10 MANAGING KNOWLEDGE FOR THE DIGITAL.

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Presentation on theme: "10.1 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm 10 MANAGING KNOWLEDGE FOR THE DIGITAL."— Presentation transcript:

1 10.1 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm 10 MANAGING KNOWLEDGE FOR THE DIGITAL FIRM Chapter

2 10.2 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Why do businesses today need knowledge management programs and systems for knowledge management?Why do businesses today need knowledge management programs and systems for knowledge management? Define and describe the types of systems used for enterprise-wide knowledge management and demonstrate how they provide value for organizations?Define and describe the types of systems used for enterprise-wide knowledge management and demonstrate how they provide value for organizations? Identify the challenges posed by knowledge management systems and management solutions.Identify the challenges posed by knowledge management systems and management solutions. OBJECTIVES

3 10.3 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm How can businesses use expert systems and case-based reasoning to capture knowledge?How can businesses use expert systems and case-based reasoning to capture knowledge? How can organizations benefit from using use neural networks and other intelligent techniques?How can organizations benefit from using use neural networks and other intelligent techniques? OBJECTIVES

4 10.4 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Designing knowledge systems that genuinely enhance organizational performanceDesigning knowledge systems that genuinely enhance organizational performance Identifying and implementing appropriate organizational applications for artificial intelligenceIdentifying and implementing appropriate organizational applications for artificial intelligence MANAGEMENT CHALLENGES

5 10.5 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Important Dimensions of Knowledge Distinction between data, info, knowledge and wisdom –Data –Data: flow of events or transactions captured by organizations –Information –Information: to turn data into useful info, a firm must expend resources to organize data into categories of understanding, such as monthly, daily, or regional reports –Knowledge –Knowledge: to transform info into knowledge, a firm must expend additional resources to discover patterns, rules, and contexts where the knowledge works –Wisdom –Wisdom: is thought to be the collective and individual experience of applying knowledge to the solution of problems. Wisdom involves where, when and how to apply knowledge

6 10.6 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm How do firms obtain knowledge ? They create and gather knowledge using a variety of organizational learning mechanism Organizational learning Through trial and error, careful measurement of planned activities, feedback from customers and the environments. in general, organizations create new standard operating procedures and business processes that reflects their experience. Knowledge management Set of business processes developed in the organization Creates, gathers, stores, maintains, and disseminates knowledgeCreates, gathers, stores, maintains, and disseminates knowledge Knowledge management increases the ability of the org to learn from its environment and to incorporate knowledge into its business processesKnowledge management increases the ability of the org to learn from its environment and to incorporate knowledge into its business processes KNOWLEDGE MANAGEMENT IN THE ORGANIZATION Organizational Learning and Knowledge Management

7 10.7 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Knowledge Assets. Management theorists believe that these know. assests are as important for competitive advantage, than physical assetsOrganizational knowledge regarding how to efficiently and effectively perform business processes and create new products and services that enables the business to create value. Management theorists believe that these know. assests are as important for competitive advantage, than physical assets Chief Knowledge Officer (CKO) Senior executive in charge of organization’s knowledge management program. They help design programs and systems to find new sources of knowledge or to make better use of existing knowledge in organizational and management processes KNOWLEDGE MANAGEMENT IN THE ORGANIZATION Organizational Learning and Knowledge Management

8 10.8 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Communities of practice (COPs)Communities of practice (COPs) –are informal social networks of professionals and employees within and outside the firm who have similar work-related activities and interests TaxonomyTaxonomy –A scheme for classifying info and knowledge in such a way that it can be easily accessed (like a table of contents in a book) Organizational knowledge can be captured and stored using case-based Reasoning. Ex: engagement-based (case-based) Ex: Accounting and consulting firms have developed structured document and engagement-based (case-based) repositories of reports from consultants who are working with particular clients. The reports typically are created after the consulting engagement is completed and include detailed descriptions of the consulting objective Organizational Learning and Knowledge Management KNOWLEDGE MANAGEMENT IN THE ORGANIZATION

9 10.9 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Tacit (network) Knowledge Expertise and experience not formally documented which resides in the minds of individual employeesExpertise and experience not formally documented which resides in the minds of individual employees Structured internal knowledge(explicit knowledge) - Structured internal knowledge (explicit knowledge) that exists in formal documents External knowledge of competitors,products and markets - External knowledge of competitors, products and markets Best Practices Successful solutions or problem-solving methods developed by specific organization or industrySuccessful solutions or problem-solving methods developed by specific organization or industry KNOWLEDGE MANAGEMENT IN THE ORGANIZATION Systems and Infrastructure for Knowledge Management

10 10.10 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Organizational Memory Stored learning from organization’s historyStored learning from organization’s history Used for decision making and other purposesUsed for decision making and other purposes KNOWLEDGE MANAGEMENT IN THE ORGANIZATION Systems and Infrastructure for Knowledge Management

11 10.11 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm IT Infrastructure for Knowledge Management KNOWLEDGE MANAGEMENT IN THE ORGANIZATION Figure 10-1

12 10.12 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Consists of creating or processing informationConsists of creating or processing information Divided into knowledge workers and data workersDivided into knowledge workers and data workers INFORMATION AND KNOWLEDGE WORK SYSTEMS Information Work

13 10.13 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Office systems Computer sys, designed to inc the prod of info workers in the off Manage and coordinate work of data and knowledge workersManage and coordinate work of data and knowledge workers Connect work of local information workers with all levels and functions of organizationConnect work of local information workers with all levels and functions of organization Connect organization to external worldConnect organization to external world Example: Word processing, voice mail, and imagingExample: Word processing, voice mail, and imaging INFORMATION AND KNOWLEDGE WORK SYSTEMS Distributing Knowledge: Office and Document Management Systems

14 10.14 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm INFORMATION AND KNOWLEDGE WORK SYSTEMS The Three Major Roles of Offices Figure Coordination of the work of loc professional and info workers 2. Coord work in the org across levels and function 3. They couple the org to the ext env

15 10.15 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Document imaging systems Convert documents and images into digital formConvert documents and images into digital form Can be stored and accessed by the computerCan be stored and accessed by the computer Knowledge repository Collection of Documented int & ext knowledge in a single location for more efficient management & utilization by the org. Using these tools, knowledge from many diff sources that can be documented in the forms of memo, presentations, and articles can be digitized and placed in a central location for easy storage and retrievalCollection of Documented int & ext knowledge in a single location for more efficient management & utilization by the org. Using these tools, knowledge from many diff sources that can be documented in the forms of memo, presentations, and articles can be digitized and placed in a central location for easy storage and retrieval Typical Office Systems INFORMATION AND KNOWLEDGE WORK SYSTEMS

16 10.16 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm INFORMATION AND KNOWLEDGE WORK SYSTEMS Components of an Imaging System Figure 10-3

17 10.17 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm INFORMATION AND KNOWLEDGE WORK SYSTEMS Web Publishing and Document Management Figure 10-4

18 10.18 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Knowledge Work Systems (KWS) Aid knowledge workers in creation and integration of new knowledgeAid knowledge workers in creation and integration of new knowledge Specialized tools for specific types of knowledge workSpecialized tools for specific types of knowledge work User-friendly interface User-friendly interface Creating Knowledge: Knowledge Work Systems INFORMATION AND KNOWLEDGE WORK SYSTEMS

19 10.19 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Changes in the Construction Project Management Process INFORMATION AND KNOWLEDGE WORK SYSTEMS Figure 10-5

20 10.20 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Requirements of Knowledge Work Systems INFORMATION AND KNOWLEDGE WORK SYSTEMS Figure 10-6

21 10.21 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Computer-aided design (CAD)Computer-aided design (CAD) – automates the creation and revision of designs, using computers and sophisticated graphics software Virtual reality systemsVirtual reality systems –Interactive graphics software and hardware that create computer-generated simulations that provide sensations that emulate sensations real-world activities Virtual Reality Modeling Language (VRML)Virtual Reality Modeling Language (VRML) –A set of specifications for interactive three-dimensional modeling on the WWW. Users can download a three- dimensional data over the Internet, and virtual world designed using VRML from a server over the Internet using their Web browser Investment workstationsInvestment workstations –powerful desktop comp for financial specialists, which is optimized to access and manipulate massive amounts of financial data Examples of Knowledge Work Systems INFORMATION AND KNOWLEDGE WORK SYSTEMS

22 10.22 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm GroupwareGroupware Intranets and Enterprise Knowledge EnvironmentsIntranets and Enterprise Knowledge Environments Enterprise information / knowledge portals Application that enables companies to provide users with a single gateway to internal and ext sources of informationEnterprise information / knowledge portals Application that enables companies to provide users with a single gateway to internal and ext sources of information Teamware Group collaboration software that is customized for team- work. Consists of intranet-based applications for building a work teamTeamware Group collaboration software that is customized for team- work. Consists of intranet-based applications for building a work team Sharing Knowledge: Group Collaboration Systems and Enterprise Knowledge Environments INFORMATION AND KNOWLEDGE WORK SYSTEMS

23 10.23 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm An Enterprise Information Portal INFORMATION AND KNOWLEDGE WORK SYSTEMS Figure 10-7

24 10.24 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Effort to develop computer-based systems that behave as humansEffort to develop computer-based systems that behave as humans Includes natural language, robotics, perceptive systems, expert systems, and intelligent machinesIncludes natural language, robotics, perceptive systems, expert systems, and intelligent machines ARTIFICIAL INTELLIGENCE What is Artificial Intelligence?

25 10.25 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Artificial Intelligence:Artificial Intelligence: types of systems that would be able to learn languages and use a perceptual apparatus. –Stores information in active form –Creates mechanism not subjected to human feelings –Eliminates routine and unsatisfying jobs –Enhances organization’s knowledge base –Generates solution to specific problems Why Business is Interested in Artificial Intelligence ARTIFICIAL INTELLIGENCE

26 10.26 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm The Artificial Intelligence Family ARTIFICIAL INTELLIGENCE Figure 10-8 Knowledge management also includes a diverse group of intelligent techniques, such as : - data mining focus on discovering knowledge - expert systems and fuzzy logic distilling knowledge in the form of rules for a computer program - genetic algorithms discovering optimal solutions for problems that are too large and complex for human beings to analyze

27 10.27 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Knowledge engineer Specialist eliciting information and expertise from other professionalsSpecialist eliciting information and expertise from other professionals Translates information into set of rules for an expert systemTranslates information into set of rules for an expert system A knowledge engineer is similar to a traditional systems analystA knowledge engineer is similar to a traditional systems analyst ARTIFICIAL INTELLIGENCE Building an Expert System

28 10.28 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Knowledge BaseKnowledge Base Rule-based Expert SystemRule-based Expert System Rule BaseRule Base Knowledge FramesKnowledge Frames Capturing Knowledge: Expert Systems ARTIFICIAL INTELLIGENCE

29 10.29 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Rules in an AI Program ARTIFICIAL INTELLIGENCE Figure 10-9

30 10.30 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm AI shellAI shell Inference EngineInference Engine Forward ChainingForward Chaining Backward ChainingBackward Chaining Capturing Knowledge: Expert Systems ARTIFICIAL INTELLIGENCE

31 10.31 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm ARTIFICIAL INTELLIGENCE Figure 10-10

32 10.32 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Knowledge engineer Specialist eliciting information and expertise from other professionalsSpecialist eliciting information and expertise from other professionals Translates information into set of rules for an expert systemTranslates information into set of rules for an expert system A knowledge engineer is similar to a traditional systems analystA knowledge engineer is similar to a traditional systems analyst ARTIFICIAL INTELLIGENCE Building an Expert System

33 10.33 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Galeria KaufhofGaleria Kaufhof Countrywide Funding Corp.Countrywide Funding Corp. ARTIFICIAL INTELLIGENCE Examples of Successful Expert Systems

34 10.34 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Case-based Reasoning (CBR) Captures and stores collective knowledgeCaptures and stores collective knowledge Represents knowledge as database of cases and solutionsRepresents knowledge as database of cases and solutions Organizational Intelligence: Case-Based Reasoning ARTIFICIAL INTELLIGENCE

35 10.35 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm ARTIFICIAL INTELLIGENCE Figure Case database NOYES Successful? System modifies the solution to better fit the problem System finds closest fit and retrieves solution System stores problem and successful solution in the database System asks user additional questions to narrow the search System searches database for similar cases User describes the problem

36 10.36 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Hardware or software emulating processing patterns of biological brainHardware or software emulating processing patterns of biological brain Put intelligence into hardware in form of a generalized capability to learnPut intelligence into hardware in form of a generalized capability to learn Neural Networks OTHER INTELLIGENT TECHNIQUES

37 10.37 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Inference Engines in Expert Systems ARTIFICIAL INTELLIGENCE Figure 10-12

38 10.38 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm ARTIFICIAL INTELLIGENCE Figure 10-13

39 10.39 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Biological Neurons of a Leech OTHER INTELLIGENT TECHNIQUES Figure 10-14

40 10.40 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Rule-based AIRule-based AI Tolerates imprecisionTolerates imprecision Uses nonspecific terms called membership functions to solve problemsUses nonspecific terms called membership functions to solve problems Fuzzy Logic OTHER INTELLIGENT TECHNIQUES

41 10.41 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Implementing Fuzzy Logic Rules in Hardware OTHER INTELLIGENT TECHNIQUES Figure 10-15

42 10.42 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Problem-solving methodsProblem-solving methods Promote evolution of solutions to specified problemsPromote evolution of solutions to specified problems Use a model of living organisms adapting to their environmentUse a model of living organisms adapting to their environment Genetic Algorithms OTHER INTELLIGENT TECHNIQUES

43 10.43 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm The Components of a Genetic Algorithm OTHER INTELLIGENT TECHNIQUES Figure 10-16

44 10.44 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Integration of multiple AI technologies into a single applicationIntegration of multiple AI technologies into a single application Takes advantage of best features of technologiesTakes advantage of best features of technologies Hybrid AI Systems OTHER INTELLIGENT TECHNIQUES

45 10.45 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Software programsSoftware programs Use built-in or learned knowledge base to carry out specific, repetitive, and predictable tasksUse built-in or learned knowledge base to carry out specific, repetitive, and predictable tasks Intelligent Agents OTHER INTELLIGENT TECHNIQUES

46 10.46 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm OTHER INTELLIGENT TECHNIQUES Figure 10-17

47 10.47 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm 10 MANAGING KNOWLEDGE FOR THE DIGITAL FIRM Chapter

48 10.48 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Where, when, and how to apply knowledge is referred to as:Where, when, and how to apply knowledge is referred to as: –wisdom. –information. –data. –knowledge. Multiple Choice Questions ( 6 Questions)

49 10.49 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm An informal group of people that may deliver work in many different locations, but who share, professional interest is called:An informal group of people that may deliver work in many different locations, but who share, professional interest is called: –community of practice. –communities of discovery. –communities of interest. –communities of knowledge. Multiple Choice Questions

50 10.50 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm CAD systems require:CAD systems require: –processing nodes. –neural networks. –graphics and powerful modeling capabilities. –groupware. Multiple Choice Questions

51 10.51 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm When capturing tactic knowledge, which of the following technologies would NOT be used?When capturing tactic knowledge, which of the following technologies would NOT be used? –Virtual reality –Expert systems –Fuzzy logic systems –Case-based reasoning Multiple Choice Questions

52 10.52 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm These types of systems would be able to learn languages and use a perceptual apparatus.These types of systems would be able to learn languages and use a perceptual apparatus. –Artificial intelligence –Fuzzy logic. –CAD –Intelligent agents Multiple Choice Questions

53 10.53 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Organizational knowledge can be captured and stored using:Organizational knowledge can be captured and stored using: –case-based reasoning. –neural networks. –user-defined techniques. –backward chaining. Multiple Choice Questions

54 10.54 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Because of their complexity and intangible benefits, knowledge-management systems represent only a minor area of information systems investment.Because of their complexity and intangible benefits, knowledge-management systems represent only a minor area of information systems investment. –True – False True-False Questions (6 Questions)

55 10.55 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Knowledge is both an individual attribute and a collective attribute of a firm.Knowledge is both an individual attribute and a collective attribute of a firm. –True –False True-False Questions

56 10.56 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Knowledge storage generally involves the creation of wisdom.Knowledge storage generally involves the creation of wisdom. –True – False True-False Questions

57 10.57 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Architects, engineers, and medical workers use precise simulations of objects provided by virtual reality systems.Architects, engineers, and medical workers use precise simulations of objects provided by virtual reality systems. –True – False True-False Questions

58 10.58 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Best practice is a scheme for classifying information and knowledge in such a way that it can be easily accessed.Best practice is a scheme for classifying information and knowledge in such a way that it can be easily accessed. –True –False True-False Questions

59 10.59 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm The majority of knowledge workers do not rely on office systems to increase productivity in the office.The majority of knowledge workers do not rely on office systems to increase productivity in the office. –True –False True-False Questions


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