Reference no: EM13923500

Introduction:

Decision trees are superb tools for helping you to select between several courses of action. They provide a highly effective structure in which you can lay out options and investigate the possible outcomes of choosing those options. They also help you to form a balanced picture of the risks and rewards associated with each possible course of action.

Key Points for Decision Trees

Decision trees provide an effective method of decision making because they:

1. Visibly lay out the problem so that all options can be tested;

2. Allow you to fully analyze possible consequences of making any given decision;

3. Provide a framework to quantify the values of outcomes and the probabilities of achieving them; and,

4. Help you to make the best decisions on the basis of current information and best guesses.

As with all decision making methods, decision tree analysis should be used in conjunction with common sense - decision trees are just one important part of your decision making tool kit.

In this case study you will be using the information from below to create a PrecisionTree[1] for Festus Temperature Controls Case Study. They need your help to first display the various options open to them, then to analyze these options and to recommend a course of action. Read the information carefully. It contains all of the information that you need to create your PrecisionTree. The analysis is, of course, up to you. But do it completely.

Remember the output for this case study is to be in the form of a mini report similar to the other reports that you have produced. Thus you will have an executive summary (200 words), the body of the report with the PrecisionTree (copied from Excel), and the concluding statement (75 words) and citation section. The mini report should be between 5 to 9 pages in length.

Festus Temperature Controls Case Study

Randy Cliff, manager of Festus (Missouri) Temperature Controls Company has a good problem. His company has been experiencing unexpected growth since 2009 and now has some extra plant capacity that he needs to use. The company is considering a short manufacturing run for either two types of new products, a temperature sensor or a pressure sensor. Randy's chief sales manager has assured him that either product will be successful in the marketplace, however Randy is not sure that his team will be able to develop them successfully in the short time allocated.

The sales manager believes that there is a probability of 65% that the potential revenue of $1.5 million from selling the temperature sensor, and probability of 35% that the potential revenue of $750,000 from selling the pressure sensor. Both of these amounts are net of the production costs, but do not include the development costs for either.

If the development is unsuccessful for a product, then there will be no sales, and the development cost will be totally lost. Randy estimates that the development cost for the temperature sensor would be $155,000 and for the pressure sensor the cost will be $26,000.

Randy has asked you to help his senior management team figure out the pros and cons of these several options to their product line. To do this you will create a PrecisionTree, analyze the tree using the maximax, maximin, and the other decision-making techniques presented to you during week nine chat, and help the company decide which way to proceed based on the expected monetary value and good old common sense.

Calculating The Value of Uncertain Outcome Nodes

Where you are calculating the value of uncertain outcomes (probability nodes on the diagram), do this by multiplying the value of the outcomes by their probability. The total for that node of the tree is the total of these values.

For instance, if the probability of an outcome (positive or negative) is 35% and the value for that node is $200,000 then you multiply $200,000 times .35 and the value of this node is: $70,000.