Date of Award


Document Type


Degree Name

Master of Science


Department of Mathematics and Statistics

First Advisor

Edward D. White III, PhD


Military and civil space acquisitions have received much criticism for their inability to produce realistic cost and schedule estimates. This research seeks to provide space systems cost estimators with a forecasting tool for space system cost and schedule growth by identifying factors contributing to growth, quantifying the relative impact of these factors, and establishing a set of models for predicting space system cost and schedule growth. The analysis considers data from both Department of Defense (DoD) and National Aeronautics and Space Administration (NASA) space programs. The DoD dataset includes 21 space programs that submitted developmental Selected Acquisition Reports between 1969 and 2006. The analysis uses multiple regression to assess 22 predictor variables, finding that communications missions, ground equipment, firm-fixed price contracts, and increased program manager tenure are all predictive of lower cost growth for military space systems. The NASA analysis includes 71 satellites and spacecraft developed between 1964 and 2004. The analysis uses a two-stage logistic and multiple regression approach to analyze 31 predictor variables finding that smaller programs (by total cost), more massive spacecraft, microgravity missions, and space physics missions are predictive of higher cost growth. For schedule growth, the study finds that larger programs and those developed by the Jet Propulsion Laboratory, Northrop Grumman, or international developers are predictive of increased schedule growth, whereas those programs developed by Johns Hopkins University are predictive of reduced schedule growth.

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DTIC Accession Number