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.

Sample Solution

. Setting Up the Tree:

  • Open Excel and activate the OM add-in.
  • Create a new decision tree using the “Decision Tree” icon in the OM toolbar.

2. Defining Decision Points:

  • Add the first decision point titled “Develop New Widget?” with two branches: “Yes” and “No.”

3. Exploring Manufacturing Methods:

  • Under the “Yes” branch, add a new decision point titled “Manufacturing Method?” with two branches: “3D Printing” and “Traditional.”

4. Incorporating Market Uncertainty:

  • Under both “3D Printing” and “Traditional” branches, add a chance node titled “Market Acceptance.” This node will have two branches: “Favorable” (probability 0.3) and “Unfavorable” (probability 0.7).

5. Calculating End Values:

  • Under each outcome of the “Market Acceptance” node, add terminal nodes representing the final outcomes. Calculate the profit for each terminal node considering:
    • Favorable Market: Revenue – Initial setup cost – Production cost per unit
    • Unfavorable Market: Revenue – Initial setup cost – Production cost per unit

6. Don’t Develop Decision:

  • Under the “No” branch of the first decision point, add a single terminal node representing the decision not to develop the widget. Assign a value of 0 (no profit) to this node.

7. Analyzing Expected Values:

  • At each decision point, calculate the expected value by taking the average of the values of its branches, weighted by their probabilities.

8. Choosing the Optimal Path:

  • The decision point with the highest expected value at the “Develop New Widget?” level will be the recommended option for OM, Inc.

Additional Notes:

  • Consider sensitivity analysis to assess how the optimal decision might change under different assumptions about costs, prices, and probabilities.
  • Utilize the “Instructions & Example” provided in the OM plugin and the examples in your textbook for detailed guidance on using specific features of Excel OM for this purpose.

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