Simulation Modeling for Cost Estimation

Abstract

What do a group of statisticians have to contribute to the subject of good costing practices, and in particular the United States Postal Service (USPS) costing methodology? Credible cost estimates require the collection of high quality information as component inputs. Deciding what information to collect lies in the province of the economist, but exactly how to collect that information, when to collect it, how much of it to collect, as well as a significant part of the overall evaluation of the quality of the information itself, lies in the province of the statistician.²

The authors acknowledge the contribution of many individuals to both the design and construction of the model. Paul R. Kleindorfer and Michael A. Crew were instrumental to the design of the underlying economic models. Without the inputs from the United States Postal Service, provided by Ross Bailey, John Reynolds and their staff, there would be no data on which to run the model. The members of the LINX DQS team turned the Postal data into formats amenable for input to the economic models. Many discussions with both the Postal Rate Commission and the General Accounting Office helped steer the modeling in relevant directions.