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Making DecisionsChapter OutlineDecision making with CertaintyDecision making with UncertaintyDecision making with RiskSequential decisionsCase Study

This chapter discusses the ways in which managers can approach decision making. It starts with the idea that managers work in complex and uncertain conditions, and they need some structure to help with their decisions. We describe several ways of giving this structure, starting with simple maps and moving on to payoff matrices and decision trees. These structures can help analyse problems in different circumstances, including certainty, uncertainty and risk.

Chapter Outline

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Decision making with Certainty

With decision making under certainty there is only one event. The mangers compare outcomes and choose the alternative that gives the best.

In reality, even decisions under certainty can be difficult. Most decisions contain subjectivity , and even when managers know all the circumstances – which is almost impossible – they are still unlikely to agree on the best decision.

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With decision making under uncertainty there are several possible events, but se do not know which will occur or cannot even give them probabilities. The usual way of tackling these problems is to use decision criteria. We illustrated these with Laplace, Wald and Savage criteria, but there are many others for different circumstances.Laplace decision criterion :-As we cannot give probabilities to the events, the Laplace criterion says that we should treat them as equally likely. The procedure is as follow :1. For each alternative find the mean value of the outcomes.2. Choose the alternative with the best average outcome.Wald decision criterion:-This decision criterion assumes that decision makers are cautions – or even pessimistic – and want to avoid big potential losses. The steps are :1. For each alternative find the worst outcome.2. Choose the alternative from the best of these worst

outcomes.

Decision Making with Uncertainty

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Savage decision criterion :-This decision criterion is based on regrets which is the difference between actual outcome and best possible outcome. It is essentially pessimistic and minimises the maximum regret, with the following steps :1. For each event find the best possible outcome.2. Find the regret for every entry in the column, which is the

difference between the entry itself and the best entry in the column.

3. Put the regrets found in Step 2 into a ‘regret matrix’. There should be at lest one zero in each column (for the best outcome) and regrets are always positive.

4. For each alternative find the highest regret (that is, the highest number in each row).

5. Choose the alternative with the best (that is, lowest) of these highest regrets.

Steps 1 to 3 build a regret matrix, and the steps 4 and 5 apply

the Wald criterionto the regret matrix.

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Limitations for decision criterion mentioned earlier:-

Both the Wald and Savage Criteria effectively recommend their decision based on one outcome – the worst for Wald and the that leads to the highest regret for Savage. So the choice might be dominated by a few atypical results. The Laplace criterion is the only one that uses all values to make its recommendation.

Decision criteria are useful tools – and their strength is now necessarily in identifying the best alternative, but to give structure to a problem, show relationships, and allow an informed debate of options.

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Decision Making with Risk

With decision making under risk there are several possible events and we can give each a probability. The expected value for each alternative is :∑ (probability of event occurring × outcome)For decision making with risk there are two steps :1. Calculate the expected value for each alternative.2. Choose the alternative with the best expected value (that is,

the highest value off gains, and the lowest value for costs).

Utilities :Expected values are easy to use but they have some drawbacks. In particular, they do not always reflect real preferences. Utilities are useful in principle, but it is very difficult to define a reasonable function. Each individual and organisation has a different view of the value of money and works with a different utility function. You might notice that you feel confident and risk-raking in the morning and conservative and risk-averse in the afternoon. In principle, though, when we can establish a reasonable utility function, the process of choosing the best alternative is the same as with expected values, but with expected utilities replacing expected values.

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Sequential Decisions

There are many circumstances where managers are not concerned with a single decision, but have to consider a series of related decisions. We can describe sequential decisions with the help of decision trees.

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Chapter outline

This chapter discusses the ways in which managers can approach decision making. It starts with the idea that managers work in complex and uncertain conditions, and they need some structure to help with their decisions. We describe several ways of giving this structure, starting with simple maps and moving on to payoff matrices and decision trees. These structures can help analyse problems in different circumstances, including certainty, uncertainty and risk.