Estimating Procurement Cost Growth Using Logistic and Multiple Regression

Cost Growth in Department of Defense (DoD) major weapon systems has been an on-going problem for more than 30 years. Previous research has demonstrated the use of a two-step logistic and multiple regression methodology to predicting cost growth produces desirable results versus traditional single-step regression. This research effort validates, and further explores the use of a two-step procedure for assessing DoD major weapon system cost growth using historical data. We compile programmatic data from the Selected Acquisition Reports (SARs) between 1990 and 2001 for programs covering all defense departments. Our analysis concentrates on cost growth in procurement dollar accounts for the Engineering and Manufacturing Development phase of acquisition. We investigate the use of logistic regression in cost growth analysis to predict whether or not procurement cost growth will occur in a program. If applicable, the multiple regression step is implemented to predict how much procurement cost growth will occur. Our study considers all seven SAR categories within the procurement accounts engineering, schedule, estimating, support, quantity, economic, and other, but we refrain from analyzing these categories individually. Consequently, we focus on the total procurement cost growth incurred from these five categories during the Engineering and Manufacturing Development phase of acquisition.

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