2 Pages Posted: 21 Oct 2008
A regional director of a consulting firm must decide how to compete for a major consulting contract. Appshop can take a level payment contract, a lower level payment with a prospective bonus given high performance, or bid on an RFP where a significant reward is given contingent on the client's savings. The case can be used to introduce Monte Carlo simulation modeling and to build skills in structuring a decision tree in a spreadsheet. It affords an opportunity to simulate alternative risk profiles and to discuss their comparative advantages.
Bonuses, gain-sharing, competitive pricing—these ideas were attractive and simple enough, but they made negotiating a contract much more challenging for Eric Clark, director of the Central Region for Appshop, Inc. Clark was in the throes of settling terms and deciding whether and how to do the OS-7 project, a major implementation of Oracle software in all seven international locations of a large multinational company (the “client”). Appshop had recently completed a successful implementation of Oracle financials in the client's Dallas headquarters. Appshop had met or exceeded all stated objectives, and would continue to support corporate Oracle applications for the client.
Appshop was the largest independent full-service Oracle consulting, applications-management, and outsourcing company. Privately held, Appshop had annual revenues of $ 25 million. Clark was responsible for growing the client base and selling additional professional services, as well as managing existing clients headquartered within his region. The client had told Clark that it would like Appshop to do all the consulting for the OS-7 project. Clark and a team of consultants spent two weeks working on the strategy, scope, and timeline for the roll-out. Based on that analysis, Appshop calculated that the project would require 1,000 hours of work per month for 24 months from a variety of contracted professionals and support personnel, which would result in a total cost to Appshop of $ 140 an hour. Because of their wide experience in doing these implementations, Clark and his team were confident that this level of effort would result in a completed and running implementation. How much the implementation would save the client and how pleased the client would be with its performance were yet to be determined.
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Keywords: decision analysis, structuring, software, Monte Carlo simulation, consulting team, risk analysis, decision trees
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