B. Information Technology (IS) CISB434: Decision Support Systems

1. B. Information Technology (IS)CISB434: Decision Support Systems Chapter 3 Decision Making, Systems, Modeling & Support

2. Learning Objectives • Explore the concepts of decision making • Examine the four phases of decision making • intelligence • design • choice • implementation • Examine how DSS support for decision making can be provided in practice

3. Decision Making, Systems, Modeling & Support Concept of Decision Making

4. Decision MakingDefinition • Decision Making • A process of choosing among two or more alternative courses of action for the purpose of attaining a goal or goals • Synonymous to and part of the whole process of Management

5. Decision MakingCharacteristics • Groupthink • Decision makers are interested in evaluating what-if scenarios • Experimentation with the real system • may result in failure • possible only for one set of conditions at a time • can be disastrous

6. Decision MakingCharacteristics • Changes in the decision making environment • may occur continuously, leading to invalidating assumptions about the situation • may affect decision quality by imposing time pressure on the decision maker

7. Decision MakingCharacteristics • Collecting information and analyzing a problem takes time and expensive • difficult to determine when to stop and make a decision • Insufficient information to make an intelligent decision • Information overload

8. Decision MakingDecision Making Vs. Problem Solving • Is decision making similar to problem solving? • Problem Solving • A process in which one starts from an initial state and proceeds to search through a problem space to identify a desired goal • Solving a problem by making decisions

9. Decision MakingDisciplines • Behavioral • anthropology, law, philosophy • political science, psychology, sociology • Scientific • computer science, decision analysis, economics • sciences, engineering, mathematics, statistics • Each discipline contributes a unique valid view of how people make decisions

10. Decision MakingDisciplines: Successful Decisions • Effectiveness • The degree of goal attainment • Doing the right things-outcome • Efficiency • The ratio of output to input • Appropriate use of resources • Doing the things right-process?approach?

11. Decision MakingDecision Styles • The manner in which a decision maker thinks and reacts to problems • includes perceptions, cognitive responses, values, and beliefs • Consequently, people do not follow the same steps of decision making

12. Decision MakingDecision Styles • Decision making styles • Heuristic vs Analytic • Autocratic vs Democratic • Consultative • Combinations of these styles • e.g. analytic and autocratic

13. Decision MakingDecision Styles & Decision Makers • Different decision styles require different types of support • Individual decision makers need access to • data • experts who can provide advice • Groups need collaboration tools

14. Models • DSS analysis is usually performed on a model rather on the real system • Model • a simplified representation or abstraction of reality

15. Models Model Classes • Iconic or scale model • a scaled physical replica of a system • e.g. a model of an airplane • Analog model • an abstract, symbolic model of a system • behaves like the system but looks different • e.g. organization charts show structure, authority, and responsibility relations • Mental model • descriptive representations of decision making situations formed in the head and thought about • the process of thinking through scenarios • to consider utility of and risk in each potential alternative

16. Models Model Classes • Mathematical (quantitative) model • A system of symbols and expressions that represent a real situation • e.g. an equation representing heat transfer between bodies • Most DSS analyses are performed with mathematical or other quantitative models

17. The Benefits of Models • Model manipulation is much easier than manipulating a real system • Models enable the compression of time • The cost of modeling analysis is much lower • The cost of making mistakes during a trial-and-error experiment is much lower when models are used than with real systems • With modeling, a manager can estimate the risks resulting from specific actions within the uncertainty of the business environment

18. The Benefits of Models • Mathematical models enable the analysis of a very large number of possible solutions • Models enhance and reinforce learning and training • Models and solution methods are readily available on the Web • Many Java applets are available to readily solve models

19. Decision Making, Systems, Modeling & Support The Phases of Decision Making

20. Decision-Making ProcessPhases

21. Decision-Making ProcessPhases • Intelligence phase • The initial phase of problem definition in decision making • Design phase • Involves finding possible alternatives in decision making and assessing their contributions • Choice phase • An alternative is selected • Implementation phase • Involves actually putting a recommended solution to work

22. Decision-Making Process The Intelligence Phase • Problem (or opportunity) identification • Issues that may arise during data collection • Data are not available • Obtaining data may be expensive • Data may not be accurate or precise enough • Data estimation is often subjective • Data may be insecure • Important data that influence the results may be qualitative

23. Decision-Making Process The Intelligence Phase • Problem (or opportunity) identification • Issues that may arise during data collection • Information overload • Outcomes (or results) may occur over an extended period • If future data is not consistent with historical data, the nature of the change has to be predicted and included in the analysis

24. Decision-Making Process The Intelligence Phase • Problem classification • The conceptualization of a problem • in an attempt to place it in a definable cate-gory • possibly leading to a standard solution approach • Problem decomposition • Dividing complex problems into simpler subproblems may help in solving the com-plex problem • Problem ownership • The jurisdiction (authority) to solve a pro-blem

25. Decision-Making Process The Design Phase • The design phase involves finding or developing and analyzing possible courses of action • Understanding the problem • Testing solutions for feasibility • A model of the decision-making problem is constructed, tested, and validated

26. Decision-Making Process The Design Phase • Modeling involves conceptualizing a problem and abstracting it to quanti-tative and/or qualitative form • Models have • Decision variables • Principle of choice

27. Decision-Making Process The Design Phase • Decision variables • A variable in a model that can be changed and manipulated by the decision maker • Decision variables correspond to the decisions to be made, such as • quantity to produce • amounts of resources to allocate • etc.

28. Decision-Making Process The Design Phase • Principle of choice • The criterion for making a choice among alternatives • For example • Are we willing to assume high risk? • Or do we prefer a low-risk approach

29. Decision-Making Process The Design Phase • Normative models • Models in which the chosen alternative is the best of all possible alternatives • Basically optimizing all possibilities • Optimization • A process of examining all the alternatives and proving that the one selected is the best

30. Decision-Making Process The Design Phase • Suboptimization • An optimization-based procedure • that does not consider all the alternatives for or impacts on an organization • Suboptimal decision • A decision made in one part, without con-sidering the other parts of an organization • But (considered) optimal from that part

31. Decision-Making Process The Design Phase • Descriptive model • A model that describes things as they are • e.g. Simulation, an imitation of reality • Narrative is a story that helps a decision maker uncover the important aspects of the situation and leads to better under-standing and framing

32. Decision-Making Process The Design Phase • Good enough or Satisficing • Willingness to settle for a satisfactory solution • “Something less than the best” • Satisficing • a process by which one seeks a solution that will satisfy a set of constraints • satisficing seeks a solution that will work well enough • in contrast to optimization, which seeks the best possible solution

33. Decision-Making Process The Design Phase • Reasons for satisficing • Time pressures • Ability to achieve optimization • Recognizing that the marginal benefit of a better solution is not worth the marginal cost to obtain it

34. Decision-Making Process The Design Phase • Develop (generate) alternatives • In optimization models, alternatives may be generated automatically by the model • In most MSS situations it is necessary to generate alternatives manually • a lengthy, costly process • Issues such as when to stop generating alternatives are very important • The search for alternatives occurs after the criteria for evaluating the alternatives are determined • The outcome of every proposed alter-native must be established

35. Decision-Making Process The Design Phase • Measuring outcomes • The value of an alternative is evaluated in terms of goal attainment • Risk • A decision maker must attribute a level of risk to the outcome of each potential alter-native being considered

36. Decision-Making Process The Design Phase • Scenario • A statement of assumptions about the operating environment of a particular system at a given time • a narrative description of the decision-situation setting • Scenarios are especially helpful in simulations and what-if analyses

37. Decision-Making Process The Design Phase • Scenarios play an important role in MSS because they • Help identify opportunities and problem areas • Provide flexibility in planning • Identify the leading edges of changes that management should monitor • Help validate major modeling assumptions • Allow the decision maker to explore the behavior of a system through a model • Help to check the sensitivity of proposed solutions to changes in the environment

38. Decision-Making Process The Design Phase • Possible scenarios to consider • The worst possible scenario • The best possible scenario • The most likely scenario • The average scenario

39. Decision-Making Process The Design Phase • Errors in decision making • The model is a critical component in the decision-making process • A decision maker may make a number of errors in its development and use • Validating the model before it is used is critical • Gathering the right amount of information, with the right level of precision and accuracy is also critical

40. Decision-Making Process The Choice Phase • Solving a decision-making model involves searching for an appropriate course of action • Analytical techniques (solving a formula) • Algorithms (step-by-step procedures) • Heuristics (rules of thumb) • Blind searches

41. Decision-Making Process The Choice Phase • Analytical techniques • methods that use mathematical formulas • to derive an optimal solution directly • or to predict a certain result • mainly in solving structured problems

42. Decision-Making Process The Choice Phase • Algorithm • a step-by-step search • in which improvement is made at every step • until the best solution is found

43. Decision-Making Process The Choice Phase • Heuristics • Informal, judgmental knowledge of an expert about an application area • that constitutes the rules of good judgment

44. Decision-Making Process The Choice Phase • Heuristics encompasses the knowledge of how to • solve problems efficiently and effectively • plan steps in solving a complex problem • improve performance, • and so forth

45. Decision-Making Process The Choice Phase • Sensitivity analysis • A study of the effect of a change in one or more input variables on a proposed solution • to determine the robustness of an alternative • Slight changes in the parameters do not cause significant changes to the chosen alternative

46. Decision-Making Process The Choice Phase • What-if analysis • A process that involves querying a computer the effect of changing some of the input data or parameters • To explore the effects of changes to parameters

47. Decision-Making Process The Implementation Phase • Some generic implementation issues important in dealing with • Resistance to change • Degree of support of top management • User training

48. Decision-Making Process The Implementation Phase

49. Decision Making, Systems, Modeling & Support DSS Support for Decision Making

50. How Decisions SupportedIntelligence Phase • The ability to scan external and internal information sources for opportunities and problems • to interpret what the scanning discovers • Web tools and sources are extremely useful for environmental scanning