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 bestexpected 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 ExcelÂ© 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 ExcelÂ© addon.
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 longrange scenarios
for the years 20102013 (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 longrange 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
This preview has intentionally blurred sections. Sign up to view the full version.
View Full Document
This is the end of the preview.
Sign up
to
access the rest of the document.
 Spring '10
 SheilaD.FournierBonilla
 TED, decision analysis models

Click to edit the document details