DSS - LESSON 2 - Decisions and Decision Makers.ppt
- 1. 1 Lesson 2: Decisions and Decision Makers
- 2. 2 Question!!!!!! • Assume now you are having some problems. • • What will you do to solve your problem? • Any specific method/steps? • Are they trying to get the optimum solution ?
- 3. 3 2-1: Decision Makers: Who Are They? • Before focusing on the decision maker, we need a working model of what he is trying to accomplish. • The decision maker plays a schizophrenic role since he is considered both a step in the process and also a participant.
- 4. 4 Example of a Decision-Making Process
- 5. 5 Classes of Decision Makers Many different types of DSSs exist because there are many different types of decision makers.
- 6. 6 Decision Maker Classifications • Individual decision makers can be a single person or a computer system. • Multiple decision makers can be: – groups where all members have a say in the decisions, – teams where members support a single decision maker, or – organizational where global agreement is needed.
- 7. 7 Classification of Decision Structures
- 8. 8 2-2: Decision Styles • Style is the manner in which a manager makes decisions. • The effect of a particular style depends on problem context, perceptions of the decision maker, and his own set of values. • The complexity of these intertwine in the formation of decision style. The basic classes of styles are illustrated on the next slide.
- 10. 10 Decision Style Categories • Directive – combines a high need for problem structure with a low tolerance for ambiguity. Often these are decisions of a technical nature that require little information. • Analytical – greater tolerance for ambiguity and tends to need more information. • Conceptual – high tolerance for ambiguity but tends to be more a “people person”. • Behavioral – requires low amount of data and demonstrates relatively short-range vision. Is conflict- averse and relies on consensus.
- 11. 11 Decision Style in DSS Design • Key issues are the decision maker’s reaction to stress and the method in which problems are usually solved. • For example, to best serve a directive type who does not handle stress well, the interface needs to allow the decision maker to control the system without tedious input • . • For an analytic type, the DSS needs to allow access to many data sources which the decision maker will analyze.
- 12. 12 2-3: Decision Effectiveness • A good decision results in attainment of the objective within the constraints imposed. • Most decision models suggest that the decision maker must balance the forces acting upon the process and contend with the dynamics of them. • These forces can be of a several natures: Personal Emotional Economic Contextual Emergent Organizational
- 13. 13 Forces Acting Upon A Decision Maker
- 14. 14 2-4: How Can a DSS Help? Some common types of support provided by a DSS: • Explores multiple perspectives of a decision • Generates multiple and higher quality alternatives • Explores multiple strategies • Facilitates brainstorming • Provides guidance and reduction of bias • Increases ability to tackle complex problems • Improves response time • Discourages premature decision-making • Provides control over multiple sources of data
- 15. 15 2-5: Why are Decisions So Hard? The four key areas that determine the relative difficulty of a decision are: 1. Structure – in general, the more structure, the less information required 2. Cognitive limitations – the human mind is limited to handling 5 to 9 distinct pieces of information
- 16. 16 2-5: Why are Decisions So Hard? (cont.) The four key areas that determine the relative difficulty of a decision are: 3. Uncertainty – the amount is based on how complete and accurate the information is 4. Alternatives and multiple objectives – the selection of one alternative may impede the progress towards a different goal
- 17. 17 Continuum/Range of Decision Structures
- 18. 18 2-6: A Typology of Decisions No two decisions are alike, but they can be categorized: • Negotiation-based decisions can be classified as routine, creative, or negotiated. • Activity-based decisions can be typed as entrepreneurial, adaptive, or planning. • Strategy-based decisions can be grouped into computational, judgmental, inspirational, or compromise.
- 20. 20 2-7: Decision Theory and Simon’s Model Keen and Scott Morton categorized decision theory into five perspectives. 1. Rational manager perspective 2. Process-oriented perspective 3. Organizational procedures perspective 4. Political perspective 5. Individual difference perspective
- 21. 21 Simon’s Model of Problem Solving Simon proposed a three-phase model of problem solving: 1. Intelligence phase – the decision maker looks for indications that a problem exists 2. Design phase – alternatives are formulated and analyzed 3. Choice phase – one of the alternatives is selected and implemented
- 22. 22 Simon’s Model of Problem Solving
- 23. 23 2-8: Rational Decision Making • Many decision strategies (next slide) attempt to find optimal solutions. • In many circles, this is considered to be rational behavior. • It is not always possible to optimize. Some problems have only qualitative solutions. Others may be quantitative but have multiple objectives at odds with others. • In such situations, rational behavior would be to choose a “good” solution.
- 24. 24 Modeling and Analysis Strategies Satisficing strategies: – Simulation – Forecasting – “What if” analysis – Markov analysis – Complex queuing methods – Environmental impact analysis Optimizing strategies: – Linear programming – Goal programming – Simple queuing models – Investment models – Inventory models – Transportation models
- 25. 25 2-9: Bounded Rationality • Simon argued that people don’t always optimize because it is often impractical to consider all possible solutions to a problem. • He notes that we often “simplify reality” by looking for a solution that is acceptable, a strategy he called satisficing. • When people make rational decisions that are bounded by often uncontrollable constraints, he notes that they are operating inside bounded reality.
- 26. 26 Optimizing Versus Satisficing Optimizing strategies search here Satisficing strategies search here
- 27. 27 Bounded Reality and DSS Design • Left alone, a decision maker preconceives the structure of a desired solution before the search for it begins. • By using a DSS, the decision maker can learn to avoid placing too many constraints too early on the solution. • In short, using a DSS would at least “loosen the bounds”. • Using a DSS can also help the decision maker solve the problem rather than simply treating the problem’s symptom.
- 28. 28 2-10: The Process of Choice • In Simon’s model, the choice phase represents the climax of the decision process. • It is important, however, to NOT focus all the energy here because it will not do justice to the other phases. • The choice phase focuses mainly on decisions of the semistructured and unstructured types where there is uncertainty.
- 29. 29 Normative versus Descriptive Choice • In normative models of decision making, choice is the theory in itself. In a behavioral or descriptive model, choice is one step in a process. • A DSS will handle uncertainty by assigning probabilities to the expected decision outcome -- an activity more a part of a normative rather than behavioral process.
- 30. 30 2-11: Cognitive Processes Decision makers face a formidable task if they are to overcome all the factors contributing to cognitive limitations: – Humans can only retain a few bits of information in short-term memory. – Decision makers display differing intelligence. – Some decision makers tend to restrict their search. – Decision makers that employ concrete thinking tend to be limited information processors.
- 31. 31 2-11: Cognitive Processes (cont.) Decision makers face a formidable task if they are to overcome all the factors contributing to cognitive limitations: – Propensity for risk varies among decision makers. – Decision maker’s level of aspiration is positively correlated with desire for information. – In general, older decision makers appear to be more limited than younger ones.
- 32. 32 Perception This is a special type of cognitive limitation. Common perception blocks are: – Difficulty in isolating the problem. – Delimiting the problem space too closely. – Inability to see the problem from different perspectives. – Stereotyping. – Cognitive saturation or overload.
- 33. 33 Judgment • Although numerous strategies exist for evaluation of solution alternatives, judgment appears to be the most favored. • Compared to detailed analysis, judgment is faster, more convenient, and less stressful. • When applied in isolation, however, judgment may be nothing but a guess. • One reason why it may not be used exclusively is that it relies heavily on the decision maker’s recollection, which may fail.
- 34. 34 2-12: Biases and Heuristics In Decision Making • We all have “rules of thumb” that we rely on in making decisions. Another term for such rules is heuristics. • Heuristic search techniques follow a series of steps based on “rules” developed by experience. • These searches can often provide solutions very close to those found by exhaustive search.
- 35. 35 Advantages of Heuristics in Problem Solving • Simple to understand • Easy to implement. • Requires less conception time. • Requires less cognitive effort. • Can produce multiple solutions.
- 36. 36 Appropriate Uses of Heuristics in Problem Solving • Input data are inexact or limited. • High computation time for an optimal solution. • Problems are solved frequently and repeatedly. • Symbolic processing is involved. • A reliable, exact method is not available. • Optimization is not economically feasible.
- 38. 38 Initial Heuristic Solution Rule: start at home, go to closest city
- 39. 39 Modified Heuristic Solution Rule: no crossing any connection, no backtracking
- 40. 40 Heuristic Bias Sometimes the use of heuristics can hamper finding a solution. The four major categories of bias are: 1. Availability – people tend to estimate probability based on past experience, which may not be representative. 2. Adjustment and anchoring – people often pick a starting value and then adjust up and down from it. They tend to underestimate the need for adjustments.
- 41. 41 Heuristic Bias (cont.) Sometimes the use of heuristics can hamper finding a solution. The four major categories of bias are: 3. Representativeness – people tend to misestimate probabilities of belonging to a group. 4. Motivational – incentives often lead decision makers to estimate probabilities that do not reflect their true beliefs.
- 42. 42 2-13: Effectiveness and Efficiency Effectiveness of DSS: – Easier access to information – Faster problem recognition and identification – Easier access to computing tools – Greater ability to evaluate large choice sets Efficiency from DSS: – Reduction in decision costs – Reduction in decision time – Better quality in feedback supplied
- 43. 43 References • http://www.computerworld.com/softwaretopics/software/apps/story/0,10801,72327,00.html • DSS emerged from a data processing world of routine static reports, according to Clyde Holsapple, professor in the decision science department of the College of Business and Economics at the University of Kentucky in Lexington. "Decision-makers can't wait a week or a month for a report," he says. • DSS journal • http://www1.elsevier.com/homepage/sae/orms/dss/menu.htm • Example of DSS http://www.rap.ucar.edu/projects/rdwx_mdss/mdss_description.html • http://ag.arizona.edu/AREC/cull/culling.html
- 44. 44 Additional Info 1(Project)- Why use excel • Solver, simulation, and databases queries are available in other software packages with more advanced options. • However, combining these analysis tools with Excel functionality extends the capabilities of the entire DSS application • Examples -
- 45. 45 Additional Info 2(project)- Recording Macros • Macros are technically defined as units of VBA code. • Macros can be thought of as a way to automate a series of actions in a spreadsheet application. • Steps: – Preparation – Record – Stop – Play