Scenario 2

You are part of the capital budgeting team at Global Bike U.S. (GBI).  The production team has requested funding for equipment which will increase the company’s capability to manufacture bicycles efficiently. Market analysis indicates that GBI will be able to sell at least 30% more bicycles than it currently manufactures, so increasing manufacturing capacity by up to 30% will equate to increased revenues. As per company policy, the purchasing department sent out an RFQ to equipment vendors globally. The three qualifying quotes are shown below in Table 1.

Your job is to analyze which proposal is most beneficial to GBI. Projects with negative net present value are not acceptable and should be rejected. Standard policy in your department has been to recommend the bid with the highest profitability index. Depreciation life is used for calculating NPV.

Assume sale (salvage value) will go into a like-kind exchange and will not trigger additional taxes.

Obviously your analysis of the capital budgeting project is based on several estimates. Therefore, your team has discussed the shortcomings of discrete data modeling results for capital budgeting questions. The team would like to explore stochastic modeling and use of Monte Carlo simulations with the intention to get a more accurate feel for possible outcomes and provide “ready-made” sensitivity analysis. Thus, you will use the stochastic modeling capabilities built into MS Excel in your analysis. As a benchmark, you will also complete the analysis as if the inputs and output were discrete to compare to your stochastic model.

stochastic-modeling-Scenario 2