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Principles of Decision Support Systems

Introduction to Decision Support Systems. Principles of Decision Support Systems. Abe Feinberg California State University, Northridge. 1. Managers and Managerial Work. Managing within an Organization

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Principles of Decision Support Systems

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  1. Introduction to Decision Support Systems Principles of Decision Support Systems Abe Feinberg California State University, Northridge 1

  2. Managers and Managerial Work • Managing within an Organization • Definition: A System of Resources Structured by Power Centers to Achieve some Objectives within an Environment • Orientation: Public <---> Private • Size of the Organization • Durability of the Organization 2

  3. Structuring the Resources INPUTS ORGANIZATION OUTPUTS Money Funds Monetary Resources Material Resources Human Resources Materials Products People Services Knowledge Knowledge Resources Knowledge 3

  4. Organizational Aspects • Power Centers • Organizational Purposes or Objectives • Organizational Environment: External and Internal 4

  5. Managerial Functions • Planning • Organizing • Commanding • Coordinating • Controlling 5

  6. Mangerial Roles • Informational • Interpersonal • Decisional: Entrepreneur; Disturbance Handler; Resource Allocator; and Negotiator 6

  7. Types of Knowledge • Descriptive: Information or Data • Examples: Demand for Service, Inventories, Personnel Records • Procedural: How to do something or steps to follow to do something or an Algorithm 7

  8. Decisions • What is Decision Making? • Choosing among Alternatives? • Generating Alternatives? • Selecting a Course of Actions? • Handling Risk? • All of the Above!! 8

  9. Decision Context • Organizational Setting: Planning vs. Control • Emergent vs. Established Situation • Timing of Decisions • Organizational Design: Centralized vs. Decentralized • Decision Type: Strategic or Tactical 9

  10. Decision Structuredness • Programmed • Structured • Semi-Structured • Unstructured • The Degree of Structuredness Can Change over Time • Negotiated vs. Unilateral Decisions 10

  11. Contributions of DSS’s • Answering What-If Questions • Assessing Potential Outcomes • Aiding Negotiations • Providing Consistent Decisions • Evaluating and Limiting Risk 11

  12. Some DSS examples • Forecasting Demand for Service • Staffing • Resource Allocation • Project Management • Vehicle Routing • Waste Disposal 11A

  13. DECISION MAKING AND COMPUTERIZED SUPPORT • Management Support Systems (MSS)Computerized technologies • Objectives • Support managerial work • Support decision making 12

  14. Management Support SystemsAn Overview Emerging and Advanced Computer Technologies for Supporting Managerial Problem Solution • Changing Organizational Structure • Enabling Business Transformation • Changing Management Methods 14

  15. Managers and Decision Making:Why Computerized Support? • Competition • Speed • The MANAGERS are always responsible for decision making 15

  16. Factors AffectingDecision Making • Technology / Information / Computers • Structural Complexity / Competition • International Markets / Political Stability / Consumerism • Changes, Fluctuations 16

  17. Managers and Computerized Support • Information Technology: vital to the business • Support technologies extensively implemented 17

  18. Computer Applications Evolving from Transaction Processing Systems (TPS) and MIS to Proactive Applications (DSS) New modern management tools in • Data access • Online analytical processing (OLAP) • Internet / Intranet / Web for decision support 18

  19. Need for Computerized Decision Support and the Supporting Technologies • Speedy computations • Overcome cognitive limits in processing and storage • Cognitive limits may restrict an individual’s problem-solving capability • Cost reduction • Technical support • Quality support • Competitive edge 19

  20. Decision Support Technologies Management Support Systems (MSS) • Decision Support Systems (DSS) • Group Support Systems (GSS) • Enterprise (Executive) Information Systems (EIS) • Enterprise Resource Planning (ERP) and Supply-Chain Management (SCM) • Knowledge Management Systems • Expert Systems (ES) • Artificial Neural Networks (ANN) • Hybrid Support Systems • Intelligent DSS 19

  21. Decision Support Framework Type of Control Tech Supp. Needs Type of Decision Operational Managerial Strategic Control Control Control MIS, OR, TP Fin. Mgt., Distribution Structured Semi-structured Unstructured A/R, order entry Budget Analysis DSS Budget Prep., Facility Layout Project Sched. Build New Facility, Quaity Assurance Scheduling Brochure Design DSS ES, N Nets Negotiating, Recruiting New Tech. Devel., Social Resp. Planning MIS Mgt. Science EIS, ES Neural Nets. DSS, ES, EIS Mgt. Science Tech Support Needed 21

  22. Unstructured problem has no structured phases • Semistructured problem has some (or some parts with) structured phases • Structuredproblem has all structured phases • Procedures for obtaining the best solution are known • Objectives are clearly defined • Management support systems can be useful 22

  23. Unstructuredproblems often solved with human intuition • Semistructured problems in between Solve with standard solution procedures and human judgment • A Decision Support System can help managers understand problems in addition to providing solutions • Goal of DSS:Increase the effectiveness of decision making 23

  24. Computer Support for Structured Decisions • Since the 1960s • Repetitive in nature • High level of structure • Can abstract and analyze them, and classify them into prototypes • Solve with quantitative formulas or models • Management Science (MS) / Operations Research (OR) 24

  25. Management Science Scientific approach to automate managerial decision making1. Define problem2. Classify problem3. Construct mathematical model4. Find and evaluate potential solutions5. Choose and recommend a solutionModeling: Transforming the real-world problem into an appropriate prototype structure 25

  26. Decision Support Systems Concept • DSS are interactive computer-based systems, which help decision makers utilize data and models to solve unstructured problems • Decision support systems couple the intellectual resources of individuals with the capabilities of the computer to improve the quality of decisions. It is a computer-based support system for management decision makers who deal with semi-structured problems • Content-free expression • There is no universally accepted definition of DSS Umbrella term vs. narrow definition (specific technology) 26

  27. Major DSS Characteristics DSS Example for Mineral Exploration • Initial risk analysis (management science) • Model scrutiny using experience, judgment, and intuition • Initial model mathematically correct, but incomplete • DSS provided very quick analysis • DSS: flexible and responsive. Allows managerial intuition and judgment 27

  28. Why Use DSS? Perceived benefits • decision quality • improved communication • cost reduction • increased productivity • time savings • improved customer and employee satisfaction 28

  29. Major Reasons • Unstable economy • Difficulty in tracking numerous business objectives • Increased competition • Electronic commerce • Existing systems did not support decision making • IS Department is too busy • Special analysis • Need accurate information • Organizational winner • New or timely information needed • Mandated by management • Cost reductions • End-user computing 29

  30. Group Support Systems (GSS) • Decisions often made by groups • Supports groupwork, anytime, anyplace Also called • Groupware • Electronic meeting systems • Collaborative computing 30

  31. Executive Information (Support) Systems (EIS, ESS) • Organizational view • Information needs of executives / managers • Customized user seductive interface • Timely and effective tracking and control • Drill down • Filter, compress, and track critical data / information • Identify problems / opportunities 31

  32. EIS • Mid-1980s - large corporations • Now global • Affordable to smaller companies • Serves managers as enterprise-wide systems 32

  33. Expert Systems (ES) • Experts solve complex problems • Experts have specific knowledge and experience • Expert systems mimic human experts • ES performance comparable to or better than experts in a specialized and usually narrow problem area 33

  34. Intelligent Agents • Help automate various tasks • Increase productivity and quality • Learn how you work 34

  35. Artificial Neural Systems • Artificial Neural Networks (ANN): • Mathematical models of the human brain • ANN learn patterns in data • ANN can work with partial, incomplete, or inexact information 35

  36. Knowledge Management Systems (KMS) • Capture and reuse knowledge at the organizational level • Knowledge repository for storage • Organizational impacts can be dramatic 36

  37. ERP and SCM • Enterprise Resource Planning (Management) • Supply Chain Management including Customer Resource Management (CRM) • Enterprise-level cost cutters 37

  38. Cutting Edge Intelligent Systems • Genetic AlgorithmsWork in an evolutionary fashion • Fuzzy LogicContinuous logic (NOT just True / False) • Intelligent AgentsIn search engines, e-mail, electronic commerce 38

  39. Hybrid Support Systems • Combines MSS technologies • Use strengths of each • Goal: successful solution of the managerial problem • Tools support each other • Tools can add intelligence to traditional MSS 39

  40. Computerized Decision Aids Evolution and Attributes • Computerized procedures development aids decision making • Early: Calculations • Intermediate: Find, organize and display information • Current: Decision relevant computations, displays and interactions • Starting: Complex fuzzy decision support, collaborative decision making and machine learning 40

  41. DSS supports specific questions • Raw Data & Status • General Analysis • Repres. & Causal Models • Solution Suggestions/ Evals. • Solution Selection What is …? What is or Why? What will be? Why? What if? What if? 41

  42. Evolutionary View of CBIS 1. Time Sequence • mid-1950s Transaction Processing Systems (TPS) • 1960s MIS • 1970s Office Automation Systems DSS • 1980s DSS Expanded Commercial applications of expert systems Executive Information Systems • 1990s Group Support Systems Neural Computing Integrated, hybrid computer systems 42

  43. 2. Computer evolved over time 3. Systemic linkages in how each system processes data into information Relationship among these and other technologies 43

  44. Relationship Among Technologies • Each technology unique • Technologies interrelated • Each supports some aspects of managerial decision making • Ever expanding role of information technology improving management • Interrelationship and coordination evolving 44

  45. Summary • DSS has many definitions • Complexity of managerial decision making is increasing • Computer support for managerial decision making • Several MSS technologies including hybrids 45

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