Despite nearly 50 years of attempts at reform, the US defense acquisition system continues to deliver weapon systems over budget, behind schedule, and with performance shortfalls. Why has acquisition reform failed? Three potential contributors were identified in the literature: the misalignment of incentives, a lack of a systems view, and a lack of objective evaluation criteria. This thesis considers these problems in the context of the most recent effort to transform the defense acquisition enterprise, evolutionary acquisition. First, game theory was employed to analyze the incentives of participants in the defense acquisition enterprise regarding the use of immature technology. It was found that there is a tragedy of the commons at work where acquisition programs serve as a common resource for stakeholders to meet their goals. The result is that participants are incentivized to use immature technology in contradiction of evolutionary acquisition policies. Second, the cost and performance of evolutionary acquisition in the context of the defense acquisition system was analyzed using a discrete event simulation. What was found was that evolutionary acquisition may lead to better performance from fielded systems and lower cost programs but also that the cost of operating the acquisition system as whole may actually rise. Finally, a method using price indices was developed to translate the gain in buying power resulting from improvements to the defense acquisition system into a monetary valuation. This allows for the application of options analysis to determine whether or not it is cost effective to pursue a potential improvement. A comparison with a more traditional approach revealed that simply using the NPV of cost savings may significantly understate value.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/28171 |
| Date | 06 March 2008 |
| Creators | Pennock, Michael James |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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