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A Year-Over-Year Forecasting Methodology for the Prediction of Program Unit Cost for Major Defense Acquisition Programs

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Abstract of Praxis A Year-Over-Year Forecasting Methodology for the Prediction of Program Unit Cost for Major Defense Acquisition Programs Cost growth in defense weapons acquisition programs has a history going back to the 1960’s. Over the course of several decades, very little relief has been received that mitigates the issue of high cost growth. Uncertainty in engineering design, which leads to uncertainty in engineering management, increases risk which frequently leads to cost overruns. The current best practices recommendation adopted by the Department of Defense is to employ a knowledge-based approach to weapons acquisition program management. The goal of utilizing a knowledge-based approach is to reduce uncertainty caused by knowledge gaps. Other efforts to address the issue of cost growth management entail increasing available data and characterizing cost growth patterns by system type and branch of service. Statutory measures, such as the Nunn-McCurdy Act, have also been employed that can result in contract cancellation when cost growth exceeds set thresholds. Defense leaders suggest that data-driven decision making that supports a continuous improvement philosophy may aid with reducing cost growth. This work employs a unit cost growth prediction model that utilizes knowledge-based metrics as predictors. The model employs a data inclusive methodology. Other predictor variables utilized correlate to proven cost growth influencers. Last, the model allows for quantitative, year-over-year cost growth forecasting which can support annual data-driven decision making.

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