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Tuning-In on the Market: The Financial Impact of Project Delays in Product Development

June 23rd, 2010

logo_microtuneClient: Microtune Inc.
Team: Andrew Bass, Chris Ginder, Shan Zaidi
Faculty Advisor: Dr. Siems
Year: 2009
Documents: Final Report (Word), Final Presentation (PPT)

The problem our team faced was how to account for the financial impact of project delays in product development. Microtune had a product in the market and a new product was under consideration to replace the existing product. The goal was to determine the value of the new product to the firm. In order to generate a cost/benefits analysis for the implementation of a product we developed a series of models in Excel to account for various uncertainties.

A beta distribution was generated for the implementation process and we were able to generate a most likely scenario for the availability time of a new product. We noticed there would be financial advantages to selling a new product, but also realized that costs must be taken into account. A Monte Carlo simulation was used with 15,000 iterations to determine the most likely cost for the product implementation.  Our team also developed a replacement function which we used to approximate the rate of cannibalization for product #2. The next step was to generate a sales data sheet to get a picture of the financial implications of the product cannibalization process. We were given a range of parameters which we displayed in three sales data scenarios: best case, mean result, and worst case. The sales datasheets allowed us to see revenue and profit for a ten year horizon.

In the net present value calculation, the monthly profits were discounted at a rate we calculated in the financial portion of the model. We were able to generate a matrix containing nine possible income possibilities. We noticed that under good conditions the implementation can be highly profitable; however, if things go wrong then the company can lose money on the project. All of the scenarios are reliant on user definable parameters, but given accurate data the model can produce a comprehensive picture of the possible project outcomes.

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