Chapter 2: DECISION MAKING, SYSTEMS, MODELING, AND SUPPORT

1. Chapter 2: DECISION MAKING, SYSTEMS, MODELING, AND SUPPORT Decision Support Systems and Intelligent Systems, 7th

2. Decision Making: Introduction and Definitions • Characteristics of decision making: • Groupthink • Decision makers are interested in evaluating what-if scenarios • Experimentation with the real system may result in failure • Experimentation with the real system is possible only for one set of conditions at a time and can be disastrous • Changes in the decision making environment may occur continuously, leading to invalidating assumptions about the situation

3. Decision Making: Introduction and Definitions(cont.) • Changes in the decision making environment may affect decision quality by imposing time pressure on the decision maker • Collecting information and analyzing a problem takes time and can be expensive. It is difficult to determine when to stop and make a decision • There may not be sufficient information to make an intelligent decision • Information overload

4. Decision Making: Introduction and Definitions(cont.) • Working Definition of Decision making The process of choosing among two or more alternatives courses of action for the purpose of attaining a goal or goals.

5. Decision Making: Introduction and Definitions(cont.) • Decision Making and Problem Solving • Phases of the decision process • Intelligence • Design • Choice • 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. It includes the 4th phase of the decision process • Implementation • Monitoring ? Is it the fifth phase?

6. Systems • A system is a collection of objects such as people, resources, concepts, and procedures intended to perform an identifiable function or to serve a goal • System Levels (Hierarchy): All systems are subsystems interconnected through interfaces

7. Systems (con.) • Structure • Inputs: are elements that enter the system • Processes: are all the necessary to convert or transform inputs into outputs. • Outputs: are the finished products or the consequences of being in the system. • Feedback :is a flow of information from the output component to the decision-maker concerning the system’s output or performance. Based on the outputs, the decision-maker, may decide to modify the inputs, the processes, or both. the decision-maker compares the output to the expected output and adjusts the input and possibly the processes to move close to the output targets.

8. Systems (con.) • The environment:Is composed of several elements that lie outside in in the sense that they are not inputs, output, or processes. However they affect the system’s performance and consequently the attainment of its goals. Environmental elements can be social, political, legal, physical, or economic . • Boundary:A system is separated from its environment by boundary. Input Processes Output boundary Environment

9. Systems (con.)

10. System Types • Closed system • Independent • Takes no inputs • Delivers no outputs to the environment • Black Box: is one which inputs and outputs are well defined, but the process itself is not specified. Such as transaction processing system (TPS). • Open system • Very dependent on it environment. • Accepts inputs from the environment. • Delivers outputs to environment

11. An Information System • Collects, processes, stores, analyzes, and disseminates information for a specific purpose • Is often at the heart of many organizations • Accepts inputs and processes data to provide information to decision makers and helps decision makers communicate their resultsSystem performance measures • Effectiveness : The degree of goal attainment (e.g. total sales) . Doing the right things • Efficiency : The ratio of output to input. Appropriate use of resources. Doing the things right

12. Models • Model: is a simplified representation or abstraction of reality • Four groups of models: • Iconic model A scaled physical replica • Analog model An abstract, symbolic model of a system that behaves like the system but looks different • Mental model The mechanisms or images through which a human mind performs sense-making in decision making • Mathematical (quantitative) model A system of symbols and expressions that represent a real situation

13. Models (cont.) • 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

14. Models (cont.) • With modeling, a manager can estimate the risks resulting from specific actions within the uncertainty of the business environment • 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

15. REALITY Examination Intelligence Phase  Verification of the Model Design Phase Verification, Testing of Proposed Solution  Choice Phases SUCCESS Implementation of Solution  FAILURE Phases of the Decision-Making Process

16. Phases of the Decision-Making Process (con.) • Intelligence phase The initial phase of problem definition in decision making • Design phase The second decision-making phase, which involves constructing model of decision making problem, finding possible alternatives in decision making and assessing their contributions

17. Phases of the Decision-Making Process (cont.) • Choice phase The third phase in decision making, in which an alternative is selected • Implementation phase The fourth decision-making phase, involving actually putting a recommended solution to work

18. Decision Making: The Intelligence Phase 1- Problem (or opportunity) identification: some 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 may be insecure • Information overload • Outcomes (or results) may occur over an extended period

19. Decision Making: The Intelligence Phase (cont.) 2- Problem classification The conceptualization of a problem in an attempt to place it in a definable category, possibly leading to a standard solution approach 3- Problem decomposition Dividing complex problems into simpler subproblems may help in solving the complex problem 4- Problem ownership The jurisdiction (authority) to solve a problem

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

21. Decision Making: The Design Phase (cont.) • Modeling involves conceptualizing a problem and abstracting it to quantitative and/or qualitative form • A proper balance between the level of model simplification and the representation of reality must be obtained because the cost-benefit trade-off. • The process of modeling is a combination of art and science.

22. Decision Making: The Design Phase (cont.) • Models have: • 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, and so on • Principle of choice The criterion for making a choice among alternatives

23. Decision Making: The Design Phase (cont.) • Models can be: • Normative models Models in which the chosen alternative is demonstrably the best of all possible alternatives • Optimization The process of examining all the alternatives and proving that the one selected is the best • Suboptimization An optimization-based procedure that does not consider all the alternatives for or impacts on an organization

24. Decision Making: The Design Phase (cont.) • Descriptive model A model that describes things as they are. It is mathematically based. • Simulation An imitation of reality • Narrative It is a story that helps a decision maker uncover the important aspects of the situation and leads to better understanding and framing

25. Decision Making: The Design Phase (cont.) • Good enough or satisficing • Satisficing A process by which one seeks a solution that will satisfy a set of constraints. In contrast to optimization, which seeks the best possible solution, satisficing simply seeks a solution that will work well enough • Reasons for satisficing: • Time pressures • Lack the ability to achieve optimization • Recognition that the marginal benefit of a better solution is not worth the marginal cost to obtain it

26. Decision Making: The Design Phase (cont.) • Developing (generating) alternatives: • In some situation, the alternatives may be generated automatically by the model • In most 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 usually occurs after the criteria for evaluating the alternatives are determined • The outcome of every proposed alternative must be established

27. Decision Making: The Design Phase (cont.) • Measuring outcomes • The value of an alternative is evaluated in terms of goal attainment • Risk • One important task of a decision maker is to attribute a level of risk to the outcome associated with each potential alternative being considered

28. Decision Making: The Design Phase (cont.) • 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

29. Decision Making: The Design Phase (cont.) • Scenarios play an important role 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

30. Decision Making: The Design Phase (cont.) • Possible scenarios • The worst possible scenario • The best possible scenario • The most likely scenario • The average scenario

31. Decision Making: The Design Phase (cont.) • 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

32. Decision Making: 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

33. Decision Making: The Implementation Phase • Generic implementation issues include: • Resistance to change • Degree of support of top management • User training

34. How decisions are supported