Probalistic Approaches to Quantity Determination and Cost Evaluation in System Acquisition.

摘要

Quantity uncertainty is a very real problem experienced in the acquisition of systems. Particularly when the systems have a diverse customer base and contracts span several years, exact quantities can be difficult to estimate. Typically, program managers guess at the most probable quantity and use that estimate to drive the Request For Proposals (RFP) and subsequent source selection. When the actual quantity purchased differs from the estimate, additional source selections or renegotiations are needed, usually driving up the unit price in the process. Two alternative probabilistic methods are presented that deal with this problem, with the effect of reducing the quantity uncertainty risk. One substitutes a probabilistically estimated quantity (PEQ) for the most probable quantity, often called the best estimated quantity (BEQ) in government acquisition. The second, called the Probabilistic Evaluation of Price (PEP), abandons the estimate altogether in favor of requiring bid prices for all possible quantities. These bid prices are then combined probabilistically into an overall evaluation price. The two methods are presented with the help of a simple example, and the lessons learned from implementation in a major joint program are included to address advantages and limitations gleaned from actual experience.