BCIS 401 Information Systems for Management

1. BCIS 401 Information Systems for Management Knowledge Management Dr. J. Affisco Fall 2001

2. Why Knowledge Management? • Knowledge is the property of the individual • Successful practices rarely transferable • Knowledge is embedded and hard to extract • Large amounts of time spent “reinventing the wheel”

3. Why Knowledge Management? Fortune 500 companies wasted $12 billion in 1999 as employees duplicated one another’s work 90% of 800 North American and European Companies were working on some aspect of knowledge management Ford estimated that in 1997-99 knowledge management initiatives resulted in cost savings or additional revenues of $914 million

4. Why Knowledge Management? Chevron estimates it has saved more than $650 million since 1991 by sharing best practices among mangers in charge of energy use at its oil refineries Texas Instruments reports savings of more than $1 billion by disseminating best practices throughout its 13 semiconductor plants By late 1999 1/3 of top 1,000 largest U.S. companies had begun knowledge mgt. initiatives; by 2003 more than half will have done so.

5. Types of Knowledge • Explicit Knowledge • Easily collected and organized • Transferred through digital means • Tacit Knowledge • Personal context-specific • Process knowledge • Hard to formalize and communicate BCIS 401

6. Knowledge Management Strategies • Sets forth criteria for choosing • What knowledge a firm plans to pursue • How firm will capture and share it • Generally determined through strategic audit • What sorts of knowledge are critical to support business positioning • Who needs to have what information? • When do they need to know it?

7. Knowledge Management Processes • Generating • Organizing • Developing • Distributing BCIS 401

8. Generating • Identifying the desired content • Getting people to contribute ideas • On-line discussions • Submitting deliverables that have emerged from other work BCIS 401

9. Generating • Buy or Rent • Research and Development • Shared Problem Solving • Adaptation • Communities of Practice BCIS 401

10. Organizing • Organizing collected data so it can be represented and retrieved electronically • Knowledge sharing systems or tools • Knowledge bases • Navigational devices • User interfaces • Taxonomies BCIS 401

11. Organizing - Knowledge Bases • Unfiltered • Archive documents directly • Many-to-many communication without intervention by others • Filtered • Content screened, distilled, and approved for use by recognized experts • Material continually refreshed to maintain its currency BCIS 401

12. Developing • Selection and further refinement of material to increase its value for users • Subject matter experts review work done by others such as editors • Results include • Final content/form of expert material • Knowledge objects BCIS 401

13. Distributing • How people get access to material • User friendliness • Encouraging use and reuse of knowledge • Types of systems • Push - Sends large masses of information out to users • Pull - Users call on the knowledge base to draw material out • Targeted Push - Proactively deliver material that is context sensitive

14. Types of Decision Support • Decision Support Systems • Expert Systems/Knowledge Based DSS • Group Decision Support Systems • Executive Support Systems BCIS 401

15. Decision Support Systems

16. Phases of Decision Making Process • Intelligence • Design • Choice BCIS 401

17. Intelligence • Searching the environment for conditions calling for decisions • Raw data are obtained, processed, & examined for clues that may identify problems. BCIS 401

18. Design • Inventing, developing, & analyzing possible courses of action. • This involves processes to • Understand the problem • Generate solutions • Test solutions for feasibility BCIS 401

19. Choice • Selecting a particular course of action from those available • A choice is made and implemented BCIS 401

20. Levels of Org Decision Making Information Characteristics Task VariableStrat. Plan. Mgt. Control Operational Control Accuracy LowHigh Level of DetailAggregateDetailed Time Horizon Future Present Frequency of UseInfrequent Frequent Source External Internal Scope of Info.WideNarrow Type of InfoQualitativeQuantitative Age of Info. Older Current

21. A MIS/DSS Framework

22. Three DSS Levels Specific DSS DSS Generator DSS Tools

23. Relating DSS Levels and Roles Manager (user) Specific DSS Intermediary DSS Generator DSS Builder Technical Supporter Toolsmith DSS Tools

24. Data Base Model Base DBMSMBMS DSS DGMS Task Environment User DSS Components

25. DSS Development Process Systems Development Process Builder and User agree on small significant sub- problem. • Analysis - What application is to be supported? Design and develop an initial system to support decision making required by sub-problem. • Design - What is the best way to support application? • Construction - Build the designed system. Use the system for a short period of time. Evaluate the system. Modify the system. Incrementally expand the system. • Implementation - Apply the system.

26. Expert Systems

27. Definition Expert Systems are special-purpose computer programs which use knowledge and reasoning to perform complex tasks in a specific problem domain at a level of performance usually associated with an expert in the domain. BCIS 401

28. Purpose Originally designed to replace domain experts. Today viewed as Knowledge-based Decision Support Systems System supports Managerial Decision Making with the capability to process knowledge in addition to quantitative data. BCIS 401

29. Components of ES Knowledge Base Inference Engine User Interface BCIS 401

30. Expert Systems Architecture

31. Knowledge Base • Repository of domain-specific knowledge • Knowledge needs to be represented and employed in a form that can be used for reasoning. • Knowledge structures • Facts • Rules • Frames BCIS 401

32. Facts • General statements of truth that may be either temporary or permanent knowledge BCIS 401

33. Rules • Knowledge structure of the form “if-then” • The “if statement” represents a premise. • The “then statement” represents a conclusion. • As rules are processed, if the premise is true then the conclusion indicates some action to be taken. • A rule is proved when the premise of the rule matches known facts.

34. Frames • A way of packaging knowledge about one object. • Are composed of slots in which data or characteristics associated with specific objects are stored. • Frames are organized in a hierarchy which allows for sharing of knowledge through the property of heredity. BCIS 401

35. Rules vs Frames • Frames are especially efficient for packaging knowledge and handling the storage and retrieval of that knowledge. • Rules work best at making deductions. BCIS 401

36. Inference Engine • Its task is to process the domain knowledge contained in the knowledge base to arrive at a solution to the problem. • Inference engine combines facts and rules through an inference process to arrive at conclusions. • Inference techniques • Forward chaining • Backward chaining

37. Forward Chaining • Begins with known facts and the rule set and attempts to deduce new facts which may eventually lead to the deduction of the goal. • Inference engine cycles through the rules until one is found whose premises matches a fact. This rule is then proved or fired, and the conclusion is added to the fact base. • Process continues until the implication of the conclusions reached are sufficient to provide a solution.

38. Backward Chaining • Inference processes work backwards from the goal. • Inference takes the goal as a hypothesis and then seeks to prove a series of subgoals working backward from the goal. • This is done recursively until all subgoals that are required for the goal’s existence are proven. BCIS 401

39. Group Decision Support Systems

40. GROUP DECISION-SUPPORT SYSTEM (GDSS) INTERACTIVE COMPUTER-BASED SYSTEM FACILITATES SOLUTION OF UNSTRUCTURED PROBLEMS BY DECISION MAKERS WORKING AS GROUP * BCIS 401

41. TOOLS OF GDSS • ELECTRONIC QUESTIONNAIRES • ELECTRONIC BRAINSTORMING • IDEA ORGANIZERS • QUESTIONNAIRE TOOLS • TOOLS FOR VOTING, SETTING PRIORITIES * BCIS 401

42. TOOLS OF GDSS • STAKEHOLDER IDENTIFICATION & ANALYSIS TOOLS • POLICY FORMATION TOOLS • GROUP DICTIONARIES * BCIS 401

43. ELECTRONIC MEETING SYSTEM (EMS) COLLABORATIVE GDSS USES INFORMATION TECHNOLOGY TO MAKE GROUP MEETINGS MORE PRODUCTIVE FACILITATES COMMUNICATION DECISION MAKING * BCIS 401

44. HOW GDSS ENHANCED DECISION MAKING • IMPROVED PRE-PLANNING • INCREASED PARTICIPATION • OPEN, COLLABORATIVE ATMOSPHERE • IDEA GENERATION FREE OF CRITICISM • EVALUATION OBJECTIVITY • IDEA ORGANIZATION & EVALUATION * BCIS 401

45. HOW GDSS ENHANCED DECISION MAKING • SETTING PRIORITIES & DECISION MAKING • DOCUMENTATION OF MEETINGS • ACCESS TO EXTERNAL INFORMATION • PRESERVATION OF ORGANIZATIONAL MEMORY * BCIS 401

46. An Illustration of the Use of GDSS

47. The Problem • Plant Location • In practice, a cross-functional team of senior executives typically makes plant location decisions. • In arriving at this decision the team looks at a number of conflicting variables and factors, both quantitative and qualitative. BCIS 401

48. The Objective • To provide training for executives in plant location strategic decision making so as to improve their performance when faced with such a decision. BCIS 401

49. The Scenario • A general scenario describing the industry, competitive environment, government and legal environment, and position of various other stakeholders is provided prior to the group support sessions. • The exercise proceeds in two phases BCIS 401

50. Phase I • The executive group is broken into three role playing groups • Corporate management • State and local government • Environmental stakeholders • A more specific scenario in terms of the firm’s products and processes is distributed with instructions to read it from the point of view of their role playing group.