Executive Summary
Choosing the best evaluation value alternative can a difficult process, taking into consideration the relatively huge pool of options available, integrated with improbability based on the likely value and affordability. This paper will look to use the evaluation value method to provide a value of the intervention when the outcomes are averaged over several players. The ‘expected-outcome decision maker’ selects the treatment with the most effective outcome when averaged over a collection of others. In the first problem, the impact from the computation revealed the benefit of selling the property due to the benefit accrued from the average expected outcome. Hence Bill is recommended to sell the property. For the second problem, the average expected outcome revealed the importance for Bill to pay to get the information for an appropriate decision. This is recommended as it would prove beneficial to Bill. In the last problem, the tree provided figures that impacted on the decision to be made. It is recommended that military cuts were beneficial.
Decision Analysis Case Study
In the given problem Bill is faced by a difficult decision. He expected to sell his business once he reached the age of 67 years-old. However, currently at the age of 57 years-old he is faced by dilemma to sell his business because he has received a good offer and there is uncertainty in the business. Therefore, to solve this problem Bill has to construct a decision tree to solve the problem and the expected value approach was used in coming up the better of the two alternative. In summation, Bill should determine if he should keep his business or sell it.
Expected value approach is a concept that is often used in statistical analysis. It uses a weight average approach of multiplying the possible outcome and its probability of the expected outcome. In the given problem the expected value approach was calculated as follows for the two alternatives:
Not to Sell
| Outcome | Probability | |
| 2.27 | 0.01 | 0.0227 |
| 2.69 | 0.09 | 0.2421 |
| 2.08 | 0.04 | 0.0832 |
| 1.76 | 0.36 | 0.6336 |
| 0.98 |
Sell
| Outcome | Probability | |
| 1.64 | 0.075 | 0.123 |
| 1.95 | 0.075 | 0.14625 |
| 3.27 | 0.05 | 0.1635 |
| 2.53 | 0.05 | 0.1265 |
| 2.13 | 0.125 | 0.26625 |
| 2.13 | 0.125 | 0.26625 |
| 1.09 |
Understanding the implications of the expected value calculation in the above example showed that if Bill decided not to sell the average expected outcome was $0.98 million whereas if he decided to sell the property the average expected outcome was $1.09 million. Therefore, for this decision it was particularly favorable for selling the property.
Question 2
In the given problem Bill’s competitor will have to borrow money and perform an appraisal. This will take a couple of months. Therefore, gives Bill an opportunity to perform market research. Given the data collected I performed a regression analysis to determine the correlation between price versus units and price and square feet. This information was particularly important to determine the price of property with regards other properties in other cities. The following were the results of the regression analysis
The scatter plots were linearly scattered and the R square values for price versus units and price and square feet were R2 =0.695 and R2=0.71 respectively. From the above values one is able to deduce that the both independent variables unit andsquare feet are strongly correlated with the dependent variable price.
I believe it matters whether Bill’s competitor is bluffing about building another facility if Bill does not sell to him. In order to prove if this true a decision tree is designed and an expected value calculation performed.
Is Bluffing
| Outcome | Probability | |
| 2.27 | 0.02 | 0.0454 |
| 2.69 | 0.18 | 0.4842 |
| 0.5296 |
Is Not Bluffing
| Outcome | Probability | |
| 2.08 | 0.08 |
0.1664 |
| 1.76 | 0.72 | 1.2672 |
| 1.4336 |
The results indicate that if Bill’s competitor was bluffing average expected outcome was $0.53 million whereas if Bill’s competitor was not bluffing the average expected outcome was $1.43 million. Therefore, the two decisions had a huge variance between them. I believe should pay as much as he can to get the information because the information will enable him arrive at a better decision. Secondly, the disparities between are huge therefore making the wrong decision can be extremely costly.
Question 3
Bills decision-making process was worsened by the fact that there would be a few military cuts over the next few years. This reduced Bill’s revenue. The information obtained from primary sources would ultimately make a difference in his decision making process as majority of Bill’s customers were military personnel (80%) and he would therefore suffer significant losses as a result if he did not tread carefully. Bill’s future plans had not incorporated the idea of probable military cuts thus the information obtained was relevant in the decision making process.
Military cuts
| outcome | probability | |
| 2.08 | 0.1 | 0.208 |
| 2.27 | 0.1 | 0.227 |
| 0.435 |
No military cuts
| outcome | probability | |
| 2.69 | 0.9 | 2.421 |
| 1.76 | 0.9 | 1.584 |
| 4.005 |
I am therefore strongly convinced by the figures above that the information that military cuts were to be made had a significant implication on his decision line. The expected outcome without military cuts is $4.005 and with military cuts $0.435.Once again, the discrepancies between the two outcomes are enormous thus wrong decision making would be fatal.
Conclusion
The paper was able to use decision analysis of evaluation value method to decide on the most effective outcome. The effective outcome is based on an average of set of values. The paper used a case study where Bill had to use the most effective expected value method that would prove beneficial in the long run. Where in the first problem the method advised him to sell it, the second problem allows him to borrow money as it would be of benefit to him despite the risks involved while in the third problem, Bill is recommended to take military cuts considering the risks involved. This method has proved to be of value to users so as to avoid losses that would cripple the Bill’s business.
