Analyzing Factors That Contribute to Cost Overruns on Department of Defense (DoD) Contractor Programs
Open Access DepositedThe Department of Defense (DoD) is the key to the United States’ National Security. The organizational body is responsible for being a safeguard for U.S. citizens and an integral alliance to our allies. However, the DoD has been plagued by costly overruns on defense programs that are funded to provide armaments that allow our military the ability to respond to and protect against national and international threats. These costly overruns have plagued the Department of Defense (DoD), as early as 1977 with high occurrences of cost overruns on more than 500 major defense programs resulting in tens of billions of dollars spent over the past 25 years on weapons systems that were over budget, delivered late, or canceled (Smith, 2022). The overruns limit future research and development, impede the country’s defense capabilities, and disrupts the financial balance that affects taxpayers, healthcare, education, and transportation. This study examines DoD contract cost overruns by identifying and analyzing significant contributing factors and applying machine learning models to determine the likelihood of these overruns. The dataset for this research incorporated 524 records (262 overruns and 262 non- overruns) of various DoD contracts into four different supervised machine learning algorithms: logistic regression, gradient boosting, support vector machines, and random forest. The results outline which machine learning algorithm performed best using the induced dependent (overrun) and independent (factors) variables.
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FunchesAllen_gwu_0075A_17108.pdf | 2025-04-09 | Open Access |
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