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Decision Analysis

Decision Analysis

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Decision Analysis

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  1. Amirkabir University of TechnologyComputer Engineering & Information Technology Department Decision Analysis Dr. Saeed Shiry

  2. Definitions • A decision is a choice between alternatives based on estimates of the values of those alternatives. • Supporting a decision means helping people working alone or in a group gather intelligence, generatealternatives and make choices • Supporting the choice making process involves supporting the estimation, the evaluation and/or the comparison of alternatives

  3. Human decision-making • H. A. Simon is considered a pioneer in the development of human decision-making models. His basic model depicts human decision-making as a three-stage process. These stages are: • Intelligence:The identification of a problem (or opportunity) that requires a decision and the collection of information relevant to the decision • Design:Creating, developing, and analyzing alternative courses of action • Choice:Selecting a course of action from those available.

  4. Decision-Making Phases and Steps • Intelligence • Data Gathering Observation of reality and collecting of any relevant qualitative and quantitative data is done for the general situation of interest. • Problem Recognition Based on the interpretation of collected data, a well focused problem statement and general objective is defined. • Design • Model Formulation Using the well-focused problem, a predefined model is instanced with a set of courses of action, outcomes criteria, set of uncontrolled events and parameters, and the relationships between these variables. If a predefined model is unavailable, a new model must be developed. • Model Analysis Face validity and pilot test of the model is conducted to reduce any potential source of significant error. • Choice • Generation & Evaluation With a validated model, all courses of action are evaluated (or dynamically generated) and what-if, sensitivity, and goal-seeking analysis are conducted, in terms of the outcomes criteria. • Selection Best course of action is finally suggested, using an optimization, satisfaction criteria, or other approach.

  5. Elements for rational decision making • Elements for rational decision making • Identify the goalto be achieved by the decision • Identify the options available to the decision maker • Evaluate the likely outcomesif each option is chosen • Decide which option is best • … And then Do it! • Decision makers need support with all elements

  6. Why are decisions hard? • Because of its complexity; uncertainty surrounding the subject, to think about interests of various groups, Having limited information: • it needs a structure to keep the problem to be analyzed: decision tree and influence diagram.

  7. Why are decisions hard? • Because of inherent uncertainty: example: introducing a new product to the market. • A decision maker may work toward multiple objective but progress in one direction. A trade off between benefit in one area against cost in other areas. • Different perspectives may lead to different conclusions. More than one person is involved in decision making.

  8. What is a good decision? • A simple answer: it is the one that gives the best outcome. • You may make a decision after careful consideration of the available information and through deliberation about the goals and possible outcomes, however still have an unlucky outcome: such as stock market. DSS helps you make a decision with eyes open! You can do better with structure and guidance

  9. Decision Analysis • Decision Analysis providers structure and guidance for thinking systematically about hard decisions. • To help a decision maker take action with confidence gained through a clear understanding of the problem.

  10. Subjective judgment • While management science and operational research ignore subjective judgment, decision analysis approach include it.

  11. Decision Analysis Process • Identify the decision situation (find the exact problem): minimizing cost? Maximizing profit? Minimizing risks? • Identify alternatives • Decompose and model the problem: model of problem structure, Model of uncertainty, Model of preference. • Choose the best alternative • Sensitivity analysis • Is further analysis needed? If YES repeat step 1,2 and 3 • Implement the chosen alternative

  12. Decision Process

  13. Decision Analysis • Once a decision making problem is understood and defined it is time to analyze it. • You might wonder if the decisions you make are suitable for decision analysis. If you are looking for a way to structure your decisions to make them more organized and easier to explain to others, you definitely should consider using formal decision analysis.

  14. Influence Diagrams • Influence diagrams present a decision in a simple, graphical form. • Decisions, chance events and payoffs (values) are drawn as shapes (called nodes) and are connected by arrows (called arcs) which define their relationship to each other. • In this way, a complex decision may be reduced to a few shapes and lines. • Influence diagrams are excellent for showing the relationship between events and the general structure of a decision clearly and concisely.

  15. Influence Diagrams • The term influence refers to the dependency of a variable on the level of another variable. • The variables are connected by arrows which indicate the direction of influence. Rectangle: Decision Variable Circle: uncontrollable or intermediate variable Oval: result (outcome) variable, intermediate or final

  16. Influence Diagrams • The shape of arrow indicate the type of relationship: • Certainty • Uncertainty • Random (Risk variable) • Dereference (between outcome variables): Interest Collected Amount In CDs Price Sales ~ Demand Sales A double lined arrow

  17. Example • Unit Sold = 0.5 x amount used in advertisement • Expenses = unit cost x units sold + fixed cost • Consider the following profit model: • Profit = income – expenses • Income = unit sold x unit price Unit Price Income • ~ amount used in advertisement Units Sold Profit Units Cost Expenses Fixed Cost

  18. Income Unit Price ~ Amount used in advertisement Units Sold Profit Expense Unit Cost Fixed Cost Example: An Influence Diagram for the Profit Model

  19. Decision Trees • Decision trees are a comprehensive tool for modeling all possible decision options. • While influence diagrams produce a compact summary of a problem, decision trees can show the problem in greater detail. • Decision trees describe events in chronological order but can be much larger than influence diagrams.

  20. Decision Trees • It utilizes a network of two types of nodes: decision (choice) nodes, and states of nature (chance) nodes • Square represents decisions to be made. • Circles represents chance events. Chance nodes, are random variables and they represent uncertain quantities that are relevant to the decision problem. • Branches from a square correspond to the choices available to the decision maker. • Branches from a circle represent the possible outcome of a chance event. • The consequence is specified at the ends of the branches.

  21. Example • Venture capitalist's situation in decision weather to invest in a new business. • Objective: to make money. Venture Succeeds Large Return On Investment Invest Venture Fails Funds Lost Typical Return Earned on Less Risky Investment Do not Invest

  22. Interpretation of Decision Trees • The options represented by branches from a decision node must be such that the decision maker can choose only one option. • Each chance node must have branches that correspond to a set of mutually exclusive and collectively exclusive outcomes ( only one of them can happen, No other possibilities exit) • A Decision Tree must show all the possible paths that the decision maker might follow through time. Including all possible decision alternatives. • Some times the nodes might occur in a time sequence. • The sequence of decisions is shown in the tree from left to right.

  23. Modeling Decisions • Given a complicated problem, how should we begin? • A critical first step is to identify elements of the situation: • Values and Objectives, • Decisions to make, • Uncertain events, • Consequences

  24. Values refer to the thing that matter to you. What is value for a farmer? What is values for a scientist? Objective is a specific thing that you want to achieve. An individual’s objective taken together make up his or her values. A persons values are the reason for making decisions. Every decision situation involves a specific context and that context determines what objectives need to be considered. A requisite decision model includes all of the objectives that matter within the decision context at hand. Values and Objectives

  25. Money Making: A special Objective • Money Making is an important objective because it allows us to do thing that we want to do: eat, afford housing and clothing, travel, live comfortably,… • For corporations money is a primary objective. However many situations may require a trade-off between making money and some other objective. • Example: Consider a hospital that performs organ transform. Wealthy people can pay more to move up in the queue. Hospital can use this extra money to buy new equipments to help needy people. But moving wealthy patient may have risks to the lives of other people. In this case hospital will probably think to forget the wealthy people money.

  26. Example: Selecting a Supercomputer for a Company • Objectives: • Minimize Cost: Five year Cost, Cost of improved performance. • Maximize performance: Speed, Throughput, Memory size, Disk Size, On site performance, • Satisfy User needs: Installation date, Ease of use, Software compatibility, Mean time between failure. • Satisfy organizational needs: Square footage, Water cooling, Operator Tools, Telecommunications, Vendor support. • Satisfy Management issues: Vendor Health, Commitment to supercomputer.

  27. Decisions to Make • Identifying the immediate decision to make is a critical step in understanding difficult decision situation. • Sequential decisions • In many cases there is no single decision to make, but several sequential decisions. • Example: A manufacture may decide weather or not to introduce a product, then whether to produce it or subcontract it, then where to market it ,… • Dynamic Decisions: A decision in future may depend on sequences of decisions taken already.

  28. Uncertain Events • Many important events has to be taken without knowing exactly what will happen in the future. • It is important to know at each decision exactly what information is available and what remains unknown. • The possible things that can happen in the resolution of uncertain events are called outcomes. • Many different uncertain events might be considered in a decision situation but only some are relevant!

  29. Consequences • After the last decision has been made and the last uncertain event has been resolved, the decision maker’s fate is finally determined. • It may be a matter of profit or loss. • How far in the horizon should we consider?

  30. Homework 2 • A) Study the concept of Time Value of Money and make a report on it. • Analyze the decision situation weather to invest in Bank Parisan (19% investment rate) or purchase a house? • B) Papers From: Encyclopedia of Decision Making and Decision Support Technologies Read and write a summary for 2 papers out of following: • The Analytic Hierarchy Process: Structuring, Measurement, and Synthesis • Context in Decision Support Systems Development • Contextualization in Decision Making and Decision Support The Summary should be written in Persian. Hand over it to Papers TA by next week.

  31. Homework 3 • A) Solve the question handed in paper. • B) Papers From: Encyclopedia of Decision Making and Decision Support Technologies Read and write a summary for 1 papers out of following: • Diagrammatic Decision-Support Modeling Tools in the Context of Supply Chain Management • Fuzzy Decision Trees • Influence Diagrams as a Tool for Decision Support System Design The Summary should be written in Persian. Hand over it to Papers TA by next week.