A Macro-Stochastic Model for Improving the Accuracy of Department of Defense Life Cycle Cost Estimates

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A Macro-Stochastic Model for Improving the Accuracy of Department of Defense Life Cycle Cost Estimates

Journal of Cost Analysis and Parametrics

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https://www.iceaaonline.com/ready/wp-content/uploads/2020/07/1941658X.2013.767073.pdf

Abstract:

The authors present a prognostic cost model that is shown to provide significantly more accurate estimates of life cycle costs for Department of Defense programs. Unlike current cost estimation approaches, this model does not rely on the assumption of a fixed program baseline. Instead, the model presented here adopts a stochastic approach to program uncertainty, seeking to identify and incorporate top-level (i.e., macro) drivers of estimating error to produce a cost estimate that is likely to be more accurate in the real world of shifting program baselines. The predicted improvement in estimating accuracy provided by this macro-stochastic cost model translates to hundreds of billions of dollars across the Department of Defense portfolio. Furthermore, improved cost estimate accuracy could reduce actual life cycle costs and/or allow defense acquisition officials the ability to make better decisions on the basis of more accurate assessments of value and affordability.

Authors:

Major Erin Ryan, Ph.D., is an Assistant Professor in the Department of Systems Engineering and Management at the Air Force Institute of Technology (AFIT). In addition to his Ph.D. in Systems Engineering from AFIT, Maj Ryan also holds degrees in Electrical Engineering from the University of Washington and National Security Studies from New Mexico State University. Major Ryan’s principal experience to date has been in the intelligence and space communities, serving as the Contracting Officer’s Technical Representative or Program Manager for multiple space-related programs. His principal research interests are stochastic modeling, decision analysis, life cycle cost estimating, and space architectures.

Dr. Christine Schubert Kabban is an Assistant Professor of Statistics in the Department of Mathematics and Statistics at AFIT. She received her Ph.D. in Applied Mathematics from AFIT and returned to AFIT after five years in the Department of Biostatistics at VCU. Her research interests include classification and detection methods, ROC surfaces and diagnostic testing, information fusion, and multi-level modeling.

Dr. David Jacques (Lt Col, USAF-Ret), is an Associate Professor of Systems Engineering on the faculty at AFIT. He holds a Ph.D. and M.S. in Aeronautical Engineering from AFIT, and a B.S. in Mechanical Engineering from Lehigh University. Dr. Jacques is currently curriculum chair for Graduate Systems Engineering at AFIT. His research interests are in the areas of concept definition and evaluation, architecture modeling, and optimal system design. Varied applications of his research involve experimental test of multi-UAV cooperative control and autonomous munition concepts, and networked sensor approaches to chem/bio detection within a building.

Lieutenant Colonel Jonathan D. Ritschel, Ph.D., is an Assistant Professor and Director Cost Analysis Program in the Department of Systems Engineering and Management at AFIT. He received his BBA in Accountancy from the University of Notre Dame, his M.S. in Cost Analysis from AFIT, and his Ph.D. in Economics from George Mason University. Lt Col Ritschel’s research interests include public choice, the effects of acquisition reforms on cost growth in DOD weapon systems, research and development cost estimation, and economic institutional analysis.