A Macro-Stochastic Model for Improving the Accuracy of DoD Life Cycle Cost Estimates: Enhanced with Text Analytics by PageKicker Robot Jellicoe

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.Enhanced with text analytics by PageKicker robot Jellicoe.