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ITM 501
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Information Technology Management

ITM 501

Selcuk Savas

Fall

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September 22, 2012
ITM501: Chapter 9 Notes
- Decision analysis: an analytic and systematic approach to the study of decision making
- A good decision is based on logic, considers all possible decision alternatives, examines all
available info about the future, and applies the decision modeling approach
- A bad decision that is not based on logic, does not use all available info, does not consider all
alternatives, and does not employ appropriate decision modeling techniques
- 5 steps of decision making:
o Clearly define the problem at hand
o List all possible decision alternatives
o Identify the possible future outcomes for each decision alternative
o Identify the payoff (usually profit or cost) for each combination of alternatives and
outcomes
o Select one of the decision analysis modeling techniques discussed in this chapter. Apply
the decision model, and make your decision
- Decision alternative: a course of action that is available to the decision maker
- Outcomes are also known as states of nature
- Payoffs can also be nonmonetary (i.e. # of units sold, # of workers needed)
o Payoffs are also called conditional values
o Conditional values or payoffs: a consequence or payoff, normally expressed in a
monetary value, which occurs as a result of a particular alternative and outcome
- Decision table or payoff table: all decision alternatives are listed down the left side of this table,
and all the possible outcomes are listed across the top while the body of the table contains the
actual payoffs
- The types of decision models available for selection depend on the environment in which we are
operating and the amount of uncertainty and risk involved
- 3 decision making environments:
o Decision making under certainty: decision makers know for sure the payoff for every
decision alternative; the consequences of every alternative is known
Typically means there is 1 outcome for each alternative
o Decision making under uncertainty: decision makers have no info at all about the
various outcomes; probabilities for each outcome to occur are not known
o Decision making under risk: decision makers have some knowledge regarding the
probability of occurrence of each outcome; probabilities are known but they could be
precise or an estimate
Decision makers attempt to identify the alternative that optimizes their
expected payoff
Decision analysis models for business problems in this environment typically
employ 1 of 2 criteria:
Maximization of expected monetary value Minimization of expected opportunity loss
- An environment of decision making under uncertainty exists when a manager cannot assess the
probabilities of the different outcomes with confidence, or when virtually no probability data
are available
o 5 different decision-making criteria to handle such situations:
Maximax
Selects the decision alternative that maximizes the maximum payoff
over all alternatives
First locate maximum payoff for each alternative and then select the
alternative with the highest value among these maximum payoffs
Also called optimistic criterion
Maximin
Takes an extremely conservative view on the future; exact opposite to
maximax
Called pessimistic criterion
Finds the alternative that maximizes the minimum payoff over all
decision alternatives
First locate the minimum payoffs for each alternative and then select
the alternative with the highest value among those minimum payoffs
Criterion of realism
Also called Hurwicz
Offers a compromise between optimistic and pessimistic decisions
Use a parameter called the coefficient of realism to measure the
decision maker’s level of optimism regarding the future
o Coefficient is denoted by α, has a value between 0 and 1
o An α value of 0 implies that the decision maker is totally
pessimistic about the future while an α value of 1 implies that
the decision maker is totally optimistic about the future
o Advantage is that it allows the decision maker to build in
personal feelings about relative optimism and pessimism
Realism payoff for alternative = α x maximum payoff for alternative + (1-
α) x minimum payoff for alternative
Because the realism payoff is just a weighted average for the maximum
and minimum payoffs, this criterion is also called the weighted average
criterion
Α = 0.5 implies a strictly neutral person
Equally likely
This criterion finds the decision alternative that has the highest average
payoff
First we calculate the average payoff for each alternative and then pick
the alternative with the maximum average payoff Minimax regret
This criterion is based on opportunity loss
Opportunity loss also called regret: the difference between the optimal
payoff and the actual payoff received
It’s the amount lost by not picking the best alternative
This criterion finds the alternative that minimizes the maximum
opportunity loss within each alternative
To use this, first need an opportunity loss table and it’s done by
determining the opportunity loss of not choosing the best alternative
for each outcome; to do so, subtract each payoff for a specific outcome
from the best payoff for that outcome
Once the opportunity loss table is constructed, we first locate the
maximum opportunity loss (regret) for each alternative and then pick
the alternative with the smallest value among these maximum regrets
o In these criteria, we assume that all payoffs represent profits
If the payoffs represent cost, some of the criteria would need to be changed and
an easy option is to convert costs in a payoff table to profits by multiplying all
cost values by -1
o First 4 criteria can be computed directly from decision/payoff table whereas the
minimax regret criterion requires the use f opportunity loss table
- When the probability of occurrence of each outcome can be assessed, the problem environment
is called decision making under risk
o One of the most popular methods of making decisions under risk is : selecting the
alternative with

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