## Completing a Decision Tree

As the project manager of the new GFB Project, you have to decide whether to create a new Web application in-house or send the project out to a developer. The developer you would use (if you were to outsource the work) quotes the project cost at \$175,000. Based on previous work with this company, you are 85 percent certain they will finish the work on time.

Your in-house development team quotes the cost of the work as \$165,000. Again, based on previous experience with your in-house developers, you feel 75 percent certain they can complete the work on time. Now let's apply what we know to a decision tree:

• Buy or build is simply the decision name.

• The cost of the decision if you "buy" the work outside of your company is \$175,000. If you build the software in-house, the cost is \$165,000.

• Based on your probability of completion by a given date, you apply the 85-percent certainty to the "strong" finish for the buy branch of the tree. Because you're 85 percent certain, you're also 15 percent uncertain; this value is assigned to the "weak" value on the buy branch. You complete the same process for the build branch of the tree.

Figure 11-7

Decision trees analyze the probability of events and calculate decision values.

Figure 11-7

Decision trees analyze the probability of events and calculate decision values.

• The value of the decision is the percentage of strong and weak applied to each branch of the tree.

• The best decision is based solely on the largest value of all possible decisions.