# BestServers.com Case Study: PV, IRR, MIRR, sensitivity analysis

See attached file.

BestServers.com has developed a powerful new server that would be used for corporations' internet activities. It would cost $9 million to buy the equipment necessary to manufacture the server, and $3.5 million of net operating working capital would be required. The servers would sell for $24,000 per unit, and BestServers believes that variable costs would amount to $17,500 per unit. The company's fixed costs would also rise by $1 million per year. It would take one year to buy the required equipment and set up operations, and the server project would have a life of 4 years. Conditions are expected to remain stable during each year of the operating life, i.e., unit sales, the sales price, and costs would be unchanged. If the project is undertaken, it must be continued for the entire 4 years. Also, the project's returns are expected to be highly correlated with returns on the firm's other assets.

The equipment would be depreciated over a 5-year period using MACRS rates (Use Table 6.3 on page 176 of Ross, Westerfield and Jaffe). The estimated market value of the equipment at the end of the project's 4-year life is $2,000,000. BestServers' tax rate is 36%. Its cost of capital is 10% for average risk projects, defined as projects with a coefficient of variation for NPV between 0.8 and 1.2. Low risk projects are evaluated with a WACC of 8%, and high risk projects at 13%. 1000 units per year. Based upon the information provided, please complete the following:

1. Develop a spreadsheet model and use it to find the project's NPV, IRR, MIRR, and payback period (assume the project is of average risk).

2. Conduct a sensitivity analysis (also known as What-If Analysis) for the project to determine the sensitivity of NPV to changes in the sales price, variable costs per unit, and number of units sold (Use the What-If Analysis feature in Excel). Set these variablesâ'values at 10% and 20% above and below their base case values. Include a graph in your analysis. See Chapter 7 of Ross, Westerfield and Jaffe for additional information on sensitivity analysis. Below is an example of the information to be collected for each variable.

3. Conduct a scenario analysis for the project:

Compute the NPV of the project assuming the 'worse case' conditions, with sales price being 20% lower, variable cost per unit being 20% higher, and number of units sold being 20% lower than the assumptions in the base case. Would you accept the project under the 'worse case' conditions? Why or why not?

Compute the NPV of the project assuming the 'best case' conditions, with sales price being 20% higher, variable cost per unit being 20% lower, and number of units sold being 20% higher than the assumptions in the base case. Would you accept the project under the â??best caseâ? conditions? Why or why not?

4. Compute a probability distribution analysis for the project. Assume that there is a 25% probability of â??best caseâ? conditions for the project, a 25% probability of 'worst case' conditions for the project, and a 50% probability of base case conditions. Using the probability distribution, compute the expected NPV, variance and standard deviation of NPV, and the coefficient of variation of NPV for the project. Based upon the coefficient of variation, is the project of low, average, or high risk? Refer to Chapter 11 of Ross, Westerfield and Jaffe for additional information on probability distribution.

5. If the project appears to be more or less risky than an average project, find its risk-adjusted NPV, IRR, MIRR, and payback using our base case cash flows and the appropriate WACC (if the coefficient of variation of the expected project is above 1.2, use the high risk WACC; if the coefficient of variation for the project is less than 0.8, use the low risk WACC).

Based upon this analysis, would you recommend that BestServers.com accept the project? Please justify your answer.

#### Solution Summary

BestServers.com Case Study is examined. The expert calculates the PV, IRR, MIRR and provides a sensitivity analysis.