Using Pre-Milestone B Data to Predict Schedule Duration for Defense Acquisition Programs

Accurately predicting a realistic schedule for a defense acquisition program is a difficult challenge considering the inherent risk and uncertainties present in the early stages of a program. Through the application of multiple regression modeling, we provide the program manager with a statistical model that predicts schedule duration from official program initiation, which occurs at Milestone B, to the initial operational capability of the program’s deliverable system. Our model explains 42.9% of the variation in schedule duration across historical data from a sample of 56 defense programs from all military services. Statistically significant predictor variables include whether a program is a new effort or modification to an existing program, the year of Milestone B start as it relates to changes in defense acquisition reform policy, and the amount of raw funding (adjusted for inflation) prior to Milestone B for a program. Our final and strongest predictor variable, percentage of the total RDT&E (Research Development Test and Evaluation) funding profile allocated at Milestone B, indicates that increased percentage of RDT&E funding for pre-Milestone B technology risk reduction may shorten a program’s schedule duration to initial operational capability.

[1]  Edward D. White,et al.  Investigating Schedule Slippage , 2005 .

[2]  Michael J Sullivan,et al.  Defense Acquisitions: Assessments of Selected Weapon Programs , 2015 .

[3]  Jeffrey A. Drezner,et al.  An Analysis of Weapon System Acquisition Schedules , 1990 .

[4]  Cristina T. Chaplain Space Acquisitions: DOD Delivering New Generations of Satellites, but Space System Acquisition Challenges Remain , 2011 .

[5]  Edward D. White,et al.  Extending Cost Growth Estimation to Predict Schedule Risk , 2006 .

[6]  Shahryar Sarkani,et al.  Improving Program Success Through Systems Engineering Tools in Pre-Milestone B Acquisition Phase , 2013 .

[7]  Louis R. Rodrigues Joint Strike Fighter Acquisition: Development Schedule Should be Changed to Reduce Risks , 2000 .

[8]  R. Cook Detection of influential observation in linear regression , 2000 .

[9]  A. Hossain,et al.  A comparative study on detection of influential observations in linear regression , 1991 .

[10]  J. Neter,et al.  Applied Linear Statistical Models (3rd ed.). , 1992 .

[11]  V. Barnett,et al.  Applied Linear Statistical Models , 1975 .

[12]  Edward D. White,et al.  R&D Budget-Driven Cost and Schedule Overruns , 2004 .

[13]  Gary Christle,et al.  Cost Implications of Design/Build Concurrency , 2011 .

[14]  Jonathan D. Ritschel,et al.  Time Phasing Aircraft R&D Using the Weibull and Beta Distributions , 2015 .

[15]  William M. Cashman Why Schedules Slip: Actual Reasons for Schedule Problems Across Large Air Force System Development Efforts. , 1995 .