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Developing A Cost Overrun Predictive Model for Complex Systems Development Projects Open Access

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While system complexity is on the rise across many product lines, the resources required to successfully design and implement complex systems remain constrained. Because financiers of complex systems development efforts actively monitor project implementation cost, project performance models are needed to help project managers predict their cost compliance and avoid cost overruns. This dissertation presents a cost overrun predictive model for complex systems development projects. The dissertation is based on a research undertaken to develop the cost overrun predictive model using five known drivers of complex systems development cost: system performance, technology maturity, schedule, risk, and reliability.The dissertation demonstrates how large-scale system development project managers and systems engineers can use the model to support decision making aimed at achieving compliance with the Nunn-McCurdy cost overrun requirements. Sixty-nine aerospace and defense systems development projects were analyzed using logistic regression leading to the development of the predictive model. Model variables include system performance, Technology Readiness Levels (TRL), risk, schedule, and reliability. The final model predictability accuracy was 62.1% for significant cost overrun and 83.3% for no significant cost overrun respectively, within the statistical boundaries of the research. Overall, the model is inconclusive on 10 cases, predicts 29 cases as significant cost overruns and 30 cases as on budget. For the aerospace projects, the model is inconclusive 7.14% of the cases; predicts 35.71% of the cases as significant cost overruns; and predicts 57.14% of the cases as no significant overrun outcomes. For defense projects, the model is inconclusive 19.51% of the cases; predicts 46.34% of the cases as significant cost overruns; and 34.15% of the cases as no significant cost overrun outcomes. Therefore, the model predicts more cost overruns for the defense projects than for the aerospace projects. Specifically the model predicts approximately 36% significant cost overruns for aerospace projects and 46% for defense projects. The model identifies schedule and reliability as the key determinants of whether or not a large complex systems development project will experience cost overrun, within constraints of the data. Projects that achieve both the defined schedule and reliability thresholds will have the lowest level of probability for a cost overrun outcome. That is, projects that fail to meet the requirements of the schedule and reliability criteria are more likely to experience significant cost overruns, within the statistical boundaries of the model. Interestingly, the model demonstrates that the TRL threshold alone is not adequate for preventing a cost overrun. However, the interaction between TRL and system performance parameters decreases the probability of a cost overrun.

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