The Application of Decision Trees by Companies and its Advantages and Disadvantages
Management science uses different ways of approach to solve management problems. Management science which is also referred to as decision analysis is part of a core of business. Decision analysis is a method used in the business firm to help managers resolve uncertainties in making investment decisions. It helps them make choices, take risks, and gain information that is needed. The decision tree can be simple or complex. It shows a combination of choice with different possible events. The usage of decision trees has helped various companies to determine the best alternative, which yields the greatest monetary gain. An example of a decision tree applied in real life is by the Oglethorpe Power Corporation (OPC). It was used in deciding whether to invest in a major transmission system. Firstly, three groups were established. The first group consists of a senior management team which helps review ideas, recommendations and make a decision based on the approach. Then, we have the analytical team which is responsible for conducting the analysis and analyse the ideas and recommendations given. The last group consists of the OPC experts who helps solve specific topics which have been brought up during the analysing process. The first step in decision analysis was identifying the problems that may arise accurately which were conducted by the analytic team. Major decisions, uncertainties, flaws and any values of concern were listed as a problem at OPC. These problems were transferred onto a bigger picture to help create an influence diagram and a clear decision tree which is shown in Diagram 3 below. The decision they had to make was whether to build the transmission line, upgrade the facilities or control the new facilities. The three decisions lead to 18 different alternatives altogether based on the decisions as shown in Diagram 1.

Diagram 1 shows, the 18 alternatives altogether based on the three decisions.
Their main problem was to choose an alternative among the three on the Line decision. There were three alternatives based on the line decision, an integrated transmission system (ITS), no ITS and a no line system. There were five uncertainties OPC faced, construction cost, demand power, competitive situation, OPC share and spot price. These uncertainties accounted to 405 different probabilities. OPC then chose to calculate these decisions based on the net present value over nominal transmission line policy.
After addressing the key issues and problems, the second step was to conduct quantitative analysis. A model was produced to help calculate the final value measure given the probability of each variable. A value model was calculated based on the equation, VALUE MODEL = final value + savings. Savings is calculated by subtracting the cost form the revenue. Moreover, TOTAL REVENUE = contract revenue + spot revenue + wheeling revenue + operating savings. SPOT REVENUE is the spot amount * spot price. The equations are represented in DPL code.
After the value model has been created, sensitivity analysis is conducted to determine the important uncertainties which affects the decision. Data value is made simpler by dividing the variable into two groups; sensitive, which are treated by probability steps in decision analysis and insensitive, which are set to nominal or expected values. However, research was conducted that sensitive analysis was not needed in this study as the five major uncertainties were considered as sensitive variables.
Probabilistic analysis was carried out next to assign probability to each outcome. There were five major uncertainties that were mentioned earlier, a probability distribution was carried for each of these events in a discrete or continuous manner. Unfortunately, due to the lack of time OPC had, probability assessments had to be conducted quickly. OPC experts then joined in to give inputs on specific