Building a Decision Tree
Building a Decision Tree: A decision tree 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 involves building 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 using 3D printing. 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. In the end, OM, Inc., can also decide not to develop the new widget.
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Sales for favorable acceptance by customers would be 25,000 widgets selling for $90 each. With unfavorable acceptance, sales of the widgets would only be 8,000 widgets at a selling price of $90 each. The cost of the 3D printing system is $600,000. The hiring and training of four new employees would cost only $400,000. In the end, manufacturing costs should drop from $60 for each widget when manufacturing without 3D printing to $50 each when 3D printed.
The probability of favorable acceptance of the new widget is .40; the probability of unfavorable acceptance is .60.
Before you start building your decision tree, review the How to Build a Decision Tree in Excel OM
Sales for favorable acceptance by customers would be 25,000 widgets selling for $90 each. With unfavorable acceptance, sales of the widgets would only be 8,000 widgets at a selling price of $90 each. The cost of the 3D printing system is $600,000. The hiring and training of four new employees would cost only $400,000. In the end, manufacturing costs should drop from $60 for each widget when manufacturing without 3D printing to $50 each when 3D printed.
The probability of favorable acceptance of the new widget is .40; the probability of unfavorable acceptance is .60.
Before you start building your decision tree, review the How to Build a Decision Tree in Excel OM
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