System Dynamic Modeling as Applied to Coast Guard Cutter Home Porting Decisions: Innovating Systems Engineering Processes in Federal Agencies to Engage Stakeholders, Stimulate Local Economies and Benefit the Public Good

Thesis (Master's)--University of Washington, 2019The U.S Coast Guard uses a codified Systems Engineering process to determine the best location for new Coast Guard cutters. This process, called the Cutter Homeport Decision Process (CHDP), quantifies stakeholder input and evaluations of potential ports to make the best homeporting decision. The goal of this study is to use System Dynamic (SD) modeling, specifically using Causal Loop Diagrams and Stock and Flow Diagrams, as a tool to conduct a port-to-port comparison of Coast Guard Cutter home porting. In doing so this study strives to support the Coast Guard in making even more informed, quantifiable cutter home porting decisions. The process of SD modeling involves robust stakeholder engagement and alinement of assumptions to bring together a model that provides quantitative information of a dynamic system’s behavior over time. In this case, a SD model is designed to show the difference between final Coast Guard Cutter operational days given a home port co-located with a maintenance hub versus a remotely located home port. The model is specifically applied to Fast Response Cutter, the Coast Guard’s newest surface asset. The model behavior and design were verified by subject matter experts; the results were validated by SME’s and also comparted to limited real world data. The study then looks at the economic benefit brought to these different home ports by Coast Guard personnel stationed there. Ultimately this study finds that there is a statistically significant difference between the operational days achieved by a cutter co-located with its maintenance hub versus one that is remote. The co-located maintenance hub has more operational days per year than the remote cutter. Also, in the case of the home ports analyzed by this study, the difference in economic impact is minimal. This study recommends co-location of the cutter with its maintenance hub to maximize operational effectiveness. This study also recommends use of SD modeling for analyzing this decision, and similar decisions, as a powerful tool for stakeholder engagement and alignment. Using SD modeling in this context can support better financial decisions, better use of resources and better support of the American public. This research strives to expand SD modeling into the federal arena and in doing so, support the public good