The best possible alternatives and potential payoff for a new product

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Decision trees can be used to determine the best possible alternatives and potential payoff for a new product or solving other management problems where uncertainty is present.

Your task is to build a decision tree based on the following scenario.

OM, Inc., a manufacturer of widgets, is considering the possibility of producing a new super-duper widget. However, they cannot decide between using an automatic 3D printing manufacturing technique or producing the widgets by traditional methods. This new project will require OM, Inc. to either purchase a high-end 3D printer or hire and train four additional employees. The market for the new widget could be either favorable or unfavorable. Ultimately, OM, Inc. can also decide not to develop the new widget.

Sales for favorable customer acceptance would be 20,000 widgets selling for $1,900 each. With unfavorable acceptance, sales of the widgets would only be 4,000 widgets at a selling price of $1,900 each. The initial setup cost of the 3D printing system is $2,000,000; however, the hiring and training of the four new employees would cost only $400,000. In the end, manufacturing costs are $1,700 for each widget when manufacturing without 3D printing and $1,500 each when 3D printed.

The probability of favorable acceptance of the new widgets is .30; the probability of unfavorable acceptance is .70.

Before you start building your decision tree, review the How to Build a Decision Tree in Excel OM example presentation narrated by the course developer, Dr. Bob Walton. Make sure to also review the videos in 3.1 Readings, Presentations & Videos. There is also more information in your textbook on Decision trees and the use of the OM Software in Module A.

Use Excel OM to build a decision tree. Make sure you carefully review the “Instructions & Example” provided in the OM plugin, and the example in your book. Submit your Excel decision tree along with a short explanation of what decision should be made by the company and how you arrived at your answer.

Sample Solution

Here’s how you can build the decision tree:

  1. Open Excel and activate the OM add-in.
  2. Create a new decision tree by clicking on the “Decision Tree” icon in the OM toolbar.
  3. Define the first decision point: This will be “Develop New Widget?” with two branches: “Yes” and “No.”
  4. Under the “Yes” branch, create two decision points:
    • The first decision point will be “Manufacturing Method?” with two branches: “3D Printing” and “Traditional.”
    • Under the “3D Printing” branch, add a chance node with two branches: “Favorable Market” (probability 0.30) and “Unfavorable Market” (probability 0.70).
    • Under the “Traditional” branch, add the same chance node with the same probabilities.
  5. Under each outcome of the chance nodes, add terminal nodes to represent the final outcomes:
    • For “Favorable Market” under both manufacturing methods, calculate the profit by subtracting the costs (initial setup + production cost per unit) from the revenue (sales).
    • For “Unfavorable Market” under both methods, do the same.
  6. Repeat steps 4 and 5 for the “No” branch of the first decision point, but instead of adding manufacturing method decisions, simply add terminal nodes representing the decision not to develop the widget.
  7. Calculate the expected value of each decision point by taking the average of the values of its branches, weighted by their probabilities.
  8. Analyze the decision tree: The decision with the highest expected value at the first decision point (“Develop New Widget?”) will be the optimal choice for OM, Inc.

Explanation of the results:

By following these steps, you will build a decision tree that visually represents the different options and potential outcomes for OM, Inc. By calculating the expected values of each decision point, you can identify the option with the highest expected profit. This will then guide OM, Inc. in making the optimal decision.

Additional notes:

  • Be sure to carefully review the “Instructions & Example” provided in the OM plugin and the example in your textbook for detailed instructions on using the specific features of Excel OM for building decision trees.
  • Consider incorporating sensitivity analysis to see how the optimal decision might change under different assumptions about costs, prices, and probabilities.

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