1.
The primary problem in the Bill Galen Development Company case is in deciding whether to hire a consultant or not. This is the decision that has to be made first before the other decisions follow sequentially. After the company has made its decision the other decisions that must be responded to include the application for the variance, whether to purchase the option and in purchasing the property.
3.
The data used in the decision tree can be explored through the first decision on whether to hire the consultant or not;
A decision not to hire the consultant has no costs. The next decision node has three options, do nothing, buy land and purchase option. In the case of doing nothing, the cost is zero and the decision tree ends there. The buying land option has the cost of $300,000 and the purchase option has the cost of $20,000. Both decisions to buy the land and the purchase option lead to applying for variance with the cost of $30,000. There is a 0.4 chance of approval and 0.6 chance of denial. If the option chosen was buying the land, then the cost of building will be $500,000 and the selling price will be $950,000. As such, in the case of buying the land the profit made will be $120,000 {950000(sale)-300000(buying land) – 30000(variance) – 500000(building)} the sale minus total costs incurred in the process. If the variance was rejected then the sale would have been for $260,000. As such a loss of 70,000 would have been made, {260000(sale)-300000(buying land) – 30000(variance)}. If the decision made was purchasing option and the variance was approved, then the cost of buying the land would have been $300,000, building $500,000 and the sale $950,000. As such, the profit made would have been $100,000 {950000(sale)-20000(purchase option)-(300000(buying land) – 30000(variance) – 500000(building)}. If the variance was rejected then the loss made would have been $50,000; the combined cost of purchase and option and an application for variance.
On the other hand, of the company decides to hire a consultant then the consultant can either predict an approval or a denial of the variance. As such, the key issue at this stage is establishing the posterior probabilities for both the denial and approval of the application made for the variance. The posterior probability for the consultant to predict approval is .7 and the probability for denial is 0.3. Once these are established, the rest of the decision tree is similar to the one without a consultant except for the inclusion of the $5,000 consultant fee.
4.
The expected returns for each of the possible strategies are clearly outlined in the decision tree and begin with a 0, 120000, -30000, 100000, -50000, -5000, 115000, -75000, 95000, 55000, and 5000. The strategy with the maximum loss has a loss of $75,000 and followed the decision path of Not hiring a consultant, Buying land and applying for variance, the variance is rejected and they are forced to sell. The optimal strategy follows the following decision strategy, hiring the consultant, a prediction of approval, buying the land and applying for valiance with a 0.7 probability of approval that leads to an $115,000 profit. I recommend this strategy considering its high profit potential.
6.
7.
The information prepared in steps 1-5 show that the design situation is simply sequential choices that culminate in a particular end and are influenced by external factors such as the variance approval.
I would just follow the procedure according the optimal strategy of hiring the consultant, a prediction of approval, buying the land and applying for valiance with a 0.7 probability of approval that leads to an $115,000 profit.
