SESSION 10 MANAGING KNOWLEDGE FOR THE DIGITAL FIRM

1. SESSION 10 MANAGING KNOWLEDGE FOR THE DIGITAL FIRM

2. KNOWLEDGE MANAGEMENT IN THE ORGANIZATION Organizational learning • Creation of new standard operating procedures and business processes Knowledge management • Set of processes • Creates, gathers, stores, maintains, and disseminates knowledge

3. KNOWLEDGE MANAGEMENT IN THE ORGANIZATION Systems and Infrastructure for Knowledge Management Knowledge Base • Structured internal knowledge (explicit knowledge) • External knowledge of competitors, products and markets • Tacit knowledge • Informal internal knowledge which resides in the minds of employees and has not been formally documented in a structured form

4. KNOWLEDGE MANAGEMENT IN THE ORGANIZATION Systems and Infrastructure for Knowledge Management Organizational Memory • Stored learning from organization’s history • Used for decision making and other purposes

5. Figure 11-1 KNOWLEDGE MANAGEMENT IN THE ORGANIZATION IT Infrastructure for Knowledge Management

6. INFORMATION AND KNOWLEDGE WORK SYSTEMS Information Work • Consists of creating or processing information • Carried out by workers who are divided into • knowledge workers who primarily create knowledge and information • data workers who primarily process and disseminate information

7. Distributing Knowledge: Office and Document Management Systems • Office systems: any application of IT that intends to increase productivity of information workers in the office. • Manage documents • Support scheduling for individuals and groups • Support communicating • Manage data • Example: Word processing, voice mail, and imaging

8. Distributing Knowledge: Office and Document Management Systems Document imaging systems • A way to reduce problems stemming from paper work flow • Convert documents and images into digital form • Can be stored and accessed by the computer

9. Figure 11-3 Distributing Knowledge: Office and Document Management Systems Components of an Imaging System

10. Creating Knowledge: Knowledge Work Systems Knowledge Work Systems (KWS) • Information systems that aid knowledge workers in creation and integration of new knowledge • Knowledge work is segmented into highly specialized fields and each field has a different collection of KWS.

11. Figure 11-6 Creating Knowledge: Knowledge Work Systems Requirements of Knowledge Work Systems

12. Creating Knowledge: Knowledge Work Systems Examples of Knowledge Work Systems • Computer-aided design (CAD) • Virtual reality systems • Investment workstations

13. Sharing Knowledge: Group Collaboration Systems and Enterprise Knowledge Environments • Groupware: a tool that provides functions and services that support the collaborative activities of work groups • Intranets and Enterprise Knowledge Environments • Enterprise information portals

14. Figure 11-7 Sharing Knowledge: Group Collaboration Systems and Enterprise Knowledge Environments An Enterprise Information Portal

15. Sharing Knowledge: Group Collaboration Systems and Enterprise Knowledge Environments • Intranet for applications requiring publication of documents by a small number of authors and with relatively static information • Groupware for applications requiring extensive coordination and management

16. ARTIFICIAL INTELLIGENCE What is Artificial Intelligence? • Effort to develop computer-based systems that behave as humans

17. Figure 11-8 ARTIFICIAL INTELLIGENCE The Artificial Intelligence Family

18. ARTIFICIAL INTELLIGENCE Why Business is Interested in Artificial Intelligence • Stores information in active form • Creates mechanism not subjected to human feelings • Eliminates routine and unsatisfying jobs • Enhances organization’s knowledge base by generating solution to specific problems that are too massive and complex to be analyzed by human beings

19. ARTIFICIAL INTELLIGENCE Expert Systems:Knowledge intensive computer program that captures the expertise of human in limited domains of knowledge How Expert Systems Work • Knowledge Base • Rule Base • Knowledge Frames

20. Figure 11-9 ARTIFICIAL INTELLIGENCE Rules in an AI Program

21. Figure 11-10 ARTIFICIAL INTELLIGENCE Frames to Model Knowledge

22. ARTIFICIAL INTELLIGENCE Drawbacks of Expert Systems • Only certain classes of problems can be solved • Knowledge base of expert systems cannot learn or change over time. Keeping knowledge base up to date is a problem. • Can represent only limited forms of knowledge: IF-THEN knowledge • They are most effective in automating lower level clerical functions

23. ARTIFICIAL INTELLIGENCE Organizational Intelligence: Case Based Reasoning Case-based Reasoning (CBR) • Artificial intelligence technology • Represents knowledge as database of cases and solutions

24. Figure 11-12 ARTIFICIAL INTELLIGENCE How Case-Based Reasoning Works

25. OTHER INTELLIGENT TECHNIQUES Neural Networks • Hardware or software emulating processing patterns of biological brain How Neural Networks work • The network is fed a training set of data for which the inputs produce a known set of outputs and conclusions. Computer learns the correct solution by example • Address the problems in pattern classification, prediction and financial analysis, and control and analysis

26. Figure 11-15 OTHER INTELLIGENT TECHNIQUES A Neural Network

27. OTHER INTELLIGENT TECHNIQUES Genetic Algorithms • Problem-solving methods • Promote evolution of solutions to specified problems • Use a model of living organisms adapting to their environment

28. OTHER INTELLIGENT TECHNIQUES Hybrid AI Systems • Integration of multiple AI technologies into a single application • Takes advantage of best features of technologies

29. OTHER INTELLIGENT TECHNIQUES Intelligent Agents • Software programs • Use built-in or learned knowledge base to carry out specific, repetitive, and predictable tasks or make decisions on the user’s behalf.