BUS 660 – lecture aid2

BUS 660 – lecture aid2 - BUS 660 lecture...

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BUS 660 – lecture aid Decision Analysis Models Introduction Decision analysis models generally present expected results associated with several possible alternatives that face the decision maker so that the alternative with the best-expected result can be chosen. An important point to keep in mind is that decision analysis models should be used only when the number of alternatives is finite . Another point to note is that decision analysis models sometimes deal with situations in which there is uncertainty and risk, and their goal is then to reduce, or eliminate when possible, the risk. A final important point is that decision analysis models are usually used to make a one- time decision, but the method can be extended to address dynamic or sequential decisions made at multiple points in time. One advantage of decision analysis models is that most of these models can actually be solved manually by hand, perhaps with the use of a calculator. In more complicated situations, one can use Excel© to perform the calculations. There are also other more sophisticated tools that can be used for very complex decision analysis models. One such tool is Palisade's PrecisionTree (http://www.palisade.com/precisiontree/default.asp), which is an Excel© add-on. The Typical Structure of Decision Analysis Models Most decision analysis models are characterized by the following four elements: 1) Alternatives - options or courses of action. 2) States of nature - scenarios, usually future scenarios. 3) Probabilities - of the states of nature. 4) Payoffs - that quantify the outcomes of the various alternatives for each state of nature. The following illustrates the approach using a concrete example: Consider the case where two types of toasters were manufactured: Model A (realizing a gross profit of $5/toaster) and Model B (realizing a gross profit of $8/toaster). The business is humming along nicely and the owner is really delighted with the $14,400/month (or $172,800/year) profit that will be realized in 2005. The marketing analyst, Jean, follows the toaster market carefully, and has developed long-range scenarios for the years 2010-2013 (next four years). It turns out that the market for toasters is highly dependent on the average disposable household income, a fact that she determined using a regression analysis. Jean has found out from delving into long-range financial forecasts that three scenarios are relevant to toaster demand in the next 4 years : PROBABILITY AVERAGE MONTHLY DEMAND FORECAST (Toaster Units) 2010 2011 2012 201 Model A Model B Model A Model B Model A Model B Model A Scenario 1 0.3 2,400 1,200 2,600 1,300 2,800 1,400 3,000 Scenario 2
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BUS 660 – lecture aid2 - BUS 660 lecture...

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