Summary Quantitative Business Analyses 2.4
Topic T1
Chapter 8: Decision Analysis
Introduction
Decision analysis = analytic and systematic approach to the study of decision
making.
A good decision can be defined as one that is based on logic, considers all possible
decision alternatives, examines all available information about the future, and applies
the decision modeling approach.
A bad decision does not consider all alternatives.
Five steps in decision analysis
1. Clearly define the problem at hand
2. List all possible decision alternatives
3. Identify the possible future outcomes for each decision alternative
4. Identify the payoff for eah combination of alternatives and outcomes
5. Select one of the decision analysis modeling techniques, apply the decision
model and make your decision
Types of decision-making environments
Three different decision-making environments:
1. Decision-making under certainty: knowing for sure the payoff for every decision
alternative.
2. Decision-making under uncertainty: decision makers have no information at all
about the various outcomes, they do not know the probability that a specific
outcomes will occur
3. Decision-making under risk: decision makers have some knowledge regarding
the probability of occurrence of each outcome, could be a precise measure or an
estimate. Identify the alternative that optimizes the expected payoff.
Decision making under uncertainty
Five different decision-making criteria to handle such situations:
1. Maximax: optimistic approach
Selects the decision alternative that maximizes the maximum payoff over all
alternatives. First locate max payoff of each alternative and then select the
alternative with the highest value.
2. Maximin: pessimistic approach
Locates minimum payoff of each alternative and then selects alternative with
the highest minimum payoff.
3. Criterion of realism: uses weighted average approach
Uses coefficient of realism: has a value between 0 and 1. Allows decision maker
to build in personal feelings about relative optimism and pessimism. Formula:
Realism payoff for alternative = α × (maximum payoff for alternative) + (1- α)
× (minimum payoff for alternative)
Alpha of 0.5 is neutral person, the lower is pessimistic and higher is optimistic.
4. Equally likely: selects highest average alternative
5. Minimax regret: based on opportunity loss
Difference between optimal payoff and actual payoff received. Amount lost by
not picking the best alternative.
Topic T1
Chapter 8: Decision Analysis
Introduction
Decision analysis = analytic and systematic approach to the study of decision
making.
A good decision can be defined as one that is based on logic, considers all possible
decision alternatives, examines all available information about the future, and applies
the decision modeling approach.
A bad decision does not consider all alternatives.
Five steps in decision analysis
1. Clearly define the problem at hand
2. List all possible decision alternatives
3. Identify the possible future outcomes for each decision alternative
4. Identify the payoff for eah combination of alternatives and outcomes
5. Select one of the decision analysis modeling techniques, apply the decision
model and make your decision
Types of decision-making environments
Three different decision-making environments:
1. Decision-making under certainty: knowing for sure the payoff for every decision
alternative.
2. Decision-making under uncertainty: decision makers have no information at all
about the various outcomes, they do not know the probability that a specific
outcomes will occur
3. Decision-making under risk: decision makers have some knowledge regarding
the probability of occurrence of each outcome, could be a precise measure or an
estimate. Identify the alternative that optimizes the expected payoff.
Decision making under uncertainty
Five different decision-making criteria to handle such situations:
1. Maximax: optimistic approach
Selects the decision alternative that maximizes the maximum payoff over all
alternatives. First locate max payoff of each alternative and then select the
alternative with the highest value.
2. Maximin: pessimistic approach
Locates minimum payoff of each alternative and then selects alternative with
the highest minimum payoff.
3. Criterion of realism: uses weighted average approach
Uses coefficient of realism: has a value between 0 and 1. Allows decision maker
to build in personal feelings about relative optimism and pessimism. Formula:
Realism payoff for alternative = α × (maximum payoff for alternative) + (1- α)
× (minimum payoff for alternative)
Alpha of 0.5 is neutral person, the lower is pessimistic and higher is optimistic.
4. Equally likely: selects highest average alternative
5. Minimax regret: based on opportunity loss
Difference between optimal payoff and actual payoff received. Amount lost by
not picking the best alternative.
