Decision Making

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Decision Making

  1. 1. Decision Making Prepared By : Mahesh M Kelkar
  2. 2. <ul><li>The process of identifying problems and opportunities and resolving them. </li></ul><ul><li>Decisions can be made depending on: </li></ul><ul><ul><li>The scope of the decision, and </li></ul></ul><ul><ul><li>The design and structure of the problem and role of self in the decision matrix. </li></ul></ul>DECISION MAKING
  3. 3. Programmability Uncertainty Risk Conflict Decision Scope Characteristics of decision making
  4. 4. DECISION MAKING Intelligence Design Choice Implementation
  5. 5. Intelligence Phase <ul><li>Searching the environment for conditions calling for decisions </li></ul><ul><li>Data inputs obtained, processed, examined for clues to identify problems or opportunities </li></ul><ul><li>Identify problems for opportunity situations requiring design and choice. </li></ul><ul><li>Scanning the environment, intermittently or continuously, is important. </li></ul><ul><ul><li>objectives </li></ul></ul><ul><ul><li>search and scanning procedures </li></ul></ul><ul><ul><li>data collection </li></ul></ul><ul><ul><li>problem identification </li></ul></ul><ul><ul><li>problem classification </li></ul></ul><ul><ul><li>problem statement </li></ul></ul>
  6. 6. HOW DO YOU DO AN INFLUENCE FACTOR ANALYSIS? Decision making Specific Environment to problem General Environment Technological Political-Legal Sociocultural Demographic Economic Technological Political-Legal Sociocultural Demographic Economic
  7. 7. DECISION MAKING INFLUENCE FACTORS Economic Demographic Sociocultural Political-Legal Technical Decision Making Sources of Influence
  8. 8. DESIGN PHASE <ul><li>Inventing (Innovation), developing, and analyzing possible courses of action </li></ul><ul><li>This involves processes to understand the problem, to generate solutions and test solutions for feasibility: </li></ul><ul><ul><li>Formulate a model. </li></ul></ul><ul><ul><li>Set criteria for choice. </li></ul></ul><ul><ul><li>Search for alternatives </li></ul></ul><ul><ul><li>Predict and measure outcomes </li></ul></ul>
  9. 9. <ul><li>Select an alternative from those available </li></ul><ul><li>Select and implement a choice: </li></ul><ul><ul><li>Solution to the model </li></ul></ul><ul><ul><li>sensitivity analysis </li></ul></ul><ul><ul><li>selection of best (good) alternatives(s) </li></ul></ul><ul><ul><li>plan for implementation (action) </li></ul></ul>CHOICE & IMPLEMETATION PHASE
  10. 11. Decision Making Concepts <ul><li>Four dimensions of decision types:: </li></ul><ul><ul><li>I. Knowledge of Outcomes </li></ul></ul><ul><ul><li>II. level of structure/programmability </li></ul></ul><ul><ul><li>III. Criteria for the decision </li></ul></ul><ul><ul><li>IV. Level of decision impact </li></ul></ul>
  11. 12. Decision Making Concepts I: Knowledge of Outcomes <ul><li>Outcome - what will happen if a particular alternative or course of action is chosen </li></ul><ul><li>Knowledge of outcomes is important with multiple alternatives </li></ul><ul><li>Three types of knowledge with respect to outcomes are usually distinguished: </li></ul><ul><ul><li>Certainty </li></ul></ul><ul><ul><li>Risk </li></ul></ul><ul><ul><li>Uncertainty </li></ul></ul>
  12. 13. <ul><li>Certainty </li></ul><ul><ul><li>Complete and accurate knowledge of outcome of each alternative. There is only one outcome for each alternative. </li></ul></ul><ul><li>Risk </li></ul><ul><ul><li>Multiple outcomes for each alternative and a probability can be assigned to each </li></ul></ul><ul><li>Uncertainty </li></ul><ul><ul><li>Multiple outcomes for each alternative and a probability cannot be assigned to each </li></ul></ul>Decision Making Concepts I: Knowledge of Outcomes
  13. 14. Decision Making under Risk <ul><li>Risk is when multiple outcomes of each alternative is possible and a probability of occurrence can be associated with each </li></ul><ul><li>In such cases, the general rule is to pick the one that has the highest expected value </li></ul><ul><li>Expected value is defined as the product of the outcome and the probability of the outcome </li></ul><ul><li>Expected value = outcome x probability </li></ul>
  14. 15. Decision Making Under Uncertainty <ul><li>Uncertainty is the situation where the outcomes are known, but the probabilities are unknown </li></ul><ul><li>One solution is to somehow assign the probabilities and then convert it to a problem under risk. </li></ul><ul><li>Other decision rules are to minimize regret and to use the maximum and minimum criteria. </li></ul><ul><li>Uses Bayesian decision theory which recommends maximizing subjective expected utility , and on decision analysis which uses decision trees, payoff matrices, and influence diagrams to implement Bayesian Decision Theory. </li></ul>
  15. 16. Decision Making Process Input Output Decision Final o/p prediction Individual in Decision Making No Decision taken problems sensor Innovation Environment Sensors Problem
  16. 17. <ul><li>Decisions can only be implemented on things which can be changed </li></ul><ul><li>Decisions are frequently associated with ‘action’ </li></ul>DECISION MAKING FACTS
  17. 18. <ul><li>Determine objectives, problems </li></ul><ul><li>Identify courses of action available to achieve / rectify </li></ul><ul><li>Collect Information to assess available options </li></ul><ul><li>Select criteria for evaluation purposes </li></ul><ul><li>Evaluate information acquired </li></ul><ul><li>Select preferred course of action / strategy </li></ul><ul><li>Implement chosen option / strategy </li></ul><ul><li>Monitor results - post analysis </li></ul>DECISION MAKING PROCESS Innovation at each step
  18. 19. THANK YOU

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