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

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Bibliographic Details
Title: A Macro-Stochastic Model for Improving the Accuracy of DoD Life Cycle Cost Estimates
Authors: Erin T. Ryan, Christine M. Schubert, David R. Jacques, Jonathan D. Ritschel
Contributors: The Pennsylvania State University CiteSeerX Archives
Source: http://www.dtic.mil/ndia/2012system/ttrack714662_Paper.pdf.
Collection: CiteSeerX
Description: The authors welcome opportunities to share the data used to formulate this model. Please contact the primary author for any questions on this paper or to obtain source data. This research was sponsored by the Office of the Secretary of Defense. The authors present a prognostic cost model that is shown to provide significantly more accurate estimates of life cycle costs for DoD 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 DoD portfolio. Furthermore, improved cost estimate accuracy could reduce 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.
Document Type: text
File Description: application/pdf
Language: English
Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.387.131; http://www.dtic.mil/ndia/2012system/ttrack714662_Paper.pdf
Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.387.131
http://www.dtic.mil/ndia/2012system/ttrack714662_Paper.pdf
Rights: Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Accession Number: edsbas.73EA973D
Database: BASE
Description
Abstract:The authors welcome opportunities to share the data used to formulate this model. Please contact the primary author for any questions on this paper or to obtain source data. This research was sponsored by the Office of the Secretary of Defense. The authors present a prognostic cost model that is shown to provide significantly more accurate estimates of life cycle costs for DoD 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 DoD portfolio. Furthermore, improved cost estimate accuracy could reduce 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.