BA 341 14th Edition Lecture 14 Outline of Last Lecture I Break Even Analysis II Example 1 III Example 2 IV Multiproduct Case Example 1 V Multiproduct Case Example 2 Outline of Current Lecture VI Decisions VII Decision Trees VIII Decision making under uncertainty IX Decision Making under Risk Current Lecture Decision Making Tools Why are Decisions so hard The problems involved are complex It often involves uncertainty and risks May involve multiple conflicting objectives difficult to convince other parties May involve multiple stakeholders with different views and preferences Different perspectives may lead to different conclusions What constitutes a good decision Structure the problem o Gather all the data and identify stakeholders o Understand problem objectives and key factors o Identify available resources costs constraints Analyze the problem o Develop measures of performance o Develop a model that connects resources and actions to objectives These notes represent a detailed interpretation of the professor s lecture GradeBuddy is best used as a supplement to your own notes not as a substitute o Carefully examine each alternative based on logic o Implement and monitor solution success Decision Trees Popular tool for decision analysis Very flexible applies to a variety of decisions A graphical display of the decision process indicating decision alternatives states of nature and their probabilities and outcomes payoffs Symbols commonly used o square decision node from which different alternatives can be selected decision point o circle state of nature chance or uncertain node An Example A company seeks to introduce a new product family This requires the construction of either a large or a small manufacturing plant The market for the product can be either favorable or unfavorable Decision making under uncertainty Assume a decision environment characterized by complete uncertainty cannot assess probabilities of uncertain outcomes e g introduction of a new innovative product Some possible decision methods o MaxiMax Optimistic maximizes the maximum outcome for every alternative o MaxiMin Pessimistic maximizes the minimum outcome for every alternative o Equally likely assumes that each state of nature is equally likely to occur maximizes the average outcome for every alternative From the earlier example Let s construct the payoff table associated with this decision How do we apply the MaxiMax method Choose the maximum number in each column For Maximax approach 200 000 For Maximin approach 0 For Equally Likely approach 40 000 Decision Making under Risk Assume that information on the probabilities of uncertain outcomes is available In this case decisional alternatives can be assessed based on the expected monetary value EMV o EMV alternative i payoff for 1st state of nature x probability 1st state of nature payoff for last state of nature x probability last state of nature Alternative with max EMV is best Back to the example Assume the following payoff table What are the EMVs of the 2 alternatives o A1 200000 x 65 180000 x 35 67 000 o A2 100000x 65 20000 x 35 58 000 What is the best option o The best option is A1 Putting it all together The corresponding decision tree is
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