Abstract
Past research shows that schedule growth within the acquisition community is difficult to predict and often adversely affects the cost and performance characteristics within the program. Determining the correct schedule duration is difficult principally in the beginning stages of the program where many uncertainties lie. This uncertainty along with the large investment in human capital, facilities, and materials within the Engineering and Manufacturing Development phase of acquisition magnifies the effect of schedule growth on the program.
This study extends a two-step modeling procedure used previously to assess cost growth for major defense acquisition programs using historical data. Through the operations of both logistic and multiple regression, this research develops statistical models to predict if a program will experience schedule growth and, if applicable, to determine the expected percentage of schedule slip. Programmatic data from the Selected Acquisition Reports (SAR) between the timeframe of 1990 and 2003 is used to build the resultant regression equations.