The decision-tree approach is useful analytical technique in capital budgeting to evaluate risky investment proposal involving sequential decisions. The technique enables the decision maker to study the various decisions points in relation to subsequent chance, events and choose, from among the alternatives, in an objective and consistent manner. Since the format of the problem of the investment decision has an appearance of a tree with branches, the method is known as decision-tree method.
The decision-tree shows the magnitude, probability and inter-relationship of all possible out-comes of an investment proposal. In a nut-shell, a decision-tree is a graphic display of the relationship between a present decision and future events, future decisions and their consequences. It contains squares and circles. The square represent decision points and the circles represent chance events modes.
Steps involved in decision tree analysis
The following are the important steps involved in constructing and using a decision- tree in capital budgeting :
(i) To identify and define the investment proposal.
(ii) To identify the decision alternatives. For example, if a company is considering setting up a plant, it has the option of setting up a large plant, a medium size plant or a small plant initially and expand it later on or no plant at all.
(iii) To draw various branches of the tree showing the decision points, chance events and other data.
(iv) To enter on the decision-tree branches the relevant data such as the projected cash-flows, probabilities and the expected payoffs.
(v) To analyze the result and by backward induction determine optimal decisions at various decision points and eliminate alternative branches on the basis of dominance.
The following example will illustrate the procedure. Suppose a firm has an investment proposal requiring an outlay of US $1,00,000. If the proposal is successfully implemented, the expected cash-inflows will amount to US $1,40,000. However, if the proposal fails, the firm will suffer a loss of US $15,000 on account of expenses, etc., for initiating the proposal. The life of the proposal is estimated to be 1 year and its salvage value is nil. Now, Estimated Profit = US $1,40,000 – 1,00;000 – 15,000 = US $25,000
Probability of Success = .5
Probability of Failure = .5
The expected pay off has been computed by the backward induction method and shown against chance node 2 as + US $5,000 being a positive amount the investment is worthwhile.
Advantages/Usefulness of Decision Tree Analysis
Decision tree is a useful method of risk analysis, the probability of occurrences for various outcomes and the inter-relationship between the outcomes. It is useful in the following circumstance:
(1) The decision-tree approach is very useful in handling the sequential investments. Working backwards from the future to the present-the decision maker is able to eliminate unprofitable branches and ascertain optimum decision at various decision points.
(2) This approach clearly brings out the implicit assumptions and calculations for all to see, question and revise.
(3) The decision-tree enables a decision maker to visualize assumptions and alternatives in a graphic form, which is usually much easier to understand.
Disadvantages of Decision Tree analysis
Some disadvantages are also associated with Decision Tree analysis approach. The diagrams tend of Decision Tree analysis become more and more complicated with the inclusion of more alternative variables and by looking into a very distant future. Complications increase still further if the analysis is extended to include interdependent alternatives and variables. They make the decision-tree diagram cumbersome and complex and calculations become very time consuming and difficult.