Systems engineering has continued to evolve over the last few decades from document-based system design and tracking of requirements to what is now commonly known as Model-Based Systems Engineering (MBSE). MBSE is an evolutionary approach in the discipline of systems engineering where rules, descriptive interconnectivity, and physics-based digital models of the structure and behavior of systems replace drawings and documents as a mechanism to manage, develop and integrate system requirements and architecture. By combining processes, tools, methods, and data, MBSE captures a representation of a system or system of systems to help identify risk-informed investment opportunities. Thus, stakeholders can be assured they are making best-value trades across an architecture at a level of fidelity not available with prior analysis methods. Using a common MBSE framework, developers and operators of space systems can leverage existing systems engineering artifacts, including requirements specifications, system performance metrics, and even physics-based models to optimize ground- and space-based elements of a systems architecture. Since MSBE enables manipulation and evaluation of multiple assumptions across an individual system architecture or across a system-of-systems architecture, stakeholders are assured the final architecture is optimized for a variety of use cases instead of locked by a single set of assumptions. This paper describes an example of one such MBSE implementation, used to execute trade studies for operational parameters of a COTS-based GEO SSA sensor suite. This example demonstrates the feasibility of using MBSE as an approach to creating a shared architecture analysis framework, with standardized assumptions and algorithm inputs that can be established to support analysis by multiple customers in order to reach conclusions that will have broad acceptance on operationally relevant timelines.