Decision Analysis: Decision analysis is a set of quantitative decision making techniques for decision situations in which uncertainty exists.
Now, uncertainty can be classified into two ways/ types:
1. Subjective Probability: Subjective probability is the degree of belief to occurrence of the event.
2. Objective Probability: Objective probability is the probability which can be derived either based on historical occurrences or based on experimentation. Alternatively can be derived from statistical formula.
Consistency requirement: If the probability of an event A is 0.65, then the probability of event B must be 0.35.
i.e. P(A) + P(B) = 1
Mathematically, if A, B ...view middle of the document...
Let’s say that you have $ 1000 to invest for a one year period. One alternative is to open a savings account paying 6% interest and another is to invest in a government treasury bond paying 10% interest. Both investment are secure and guaranteed, but as treasury bond will pay a higher return, you may choose that one.
Type 2: Decision Making Under Risk: In decision making under risk, the decision maker knows the probability of occurrence of each outcome. For example, that the probability of being dealt a club is 0.25. The probability of rolling a 5 on a die is 1/6. In decision making under risk, the decision maker attempts to maximize his or her expected well-being. Decision theory models for business problems in this environment typically employ two equivalent criteria: maximization of expected monetary value and minimization of expected loss.
Type 3: Decision Making Under Uncertainty: In decision making under uncertainty the decision maker does not know the probabilities of the various outcomes. As an example, the probability that a BNP personnel will be president of Bangladesh 25 years from now is not known. Sometimes it is impossible to assess the probability of success of a new undertaking or product.
Decision Making Under Risk
Decision making under risk is a probabilistic decision situation. Several possible states of nature may occur, each with a given probability.
There are three types of methods or criteria available, which could be of help to the decision maker.
1. Expected Monetary Value: EMV is the weighted sum of possible payoffs for each alternative.
i.e. EMV (alternative i ) = (Payoff of first state of nature) x ( Probability of first state of nature)
+(Payoff of second state of nature)x(Probability of second state of nature)
+ …. + (Payoff of last state of nature)x(Probability of last state of nature).
Example: 1 Mc Douglas a national chain fast food restaurant, has been offering a traditional selection of hamburgers, French fries, soft drinks etc. The company want to introduce breakfast items to the menu.
Breakfast items are relatively easy to prepare and would not require a large capital outlay for additional cooking equipment. Most important such items would be sold in the morning when the demand for the company’s traditional products has been very week. However, because
a. Many people are known to skip breakfast and
b. The company does not know how competitors may react, the demand for the new products is uncertain.
So, they consider three levels of customer demand- strong, average and weak.
There are two alternative acts available to Mc Douglas
A1 : Introduce breakfast items.
A2 : Do not introduce breakfast items.
And three possible states of nature
S1 : Strong demand
S2 : Average demand