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Standardized design approaches such as those embodied by concurrent design facilities have many benefits, such as increased efficiency of the design process, but may also have hidden costs. Specifically, when their standardized organizational decomposition is a poor fit for the particular design problem, important design trades might be missed or poor decisions made. Before we can understand how this lack of fit impacts the design process, we must be able to empirically observe and measure it. To that end, this paper identifies measures of "fit" from the literature along with attributes likely to impact design process performance, then evaluates the measures to determine how well the measures can detect and diagnose potential issues. The results provide comparative insights into the capabilities of existing fit measures, and also build guidance for how the systems engineering and design community can use insights from the "fit" literature to inform process improvement. [ABSTRACT FROM AUTHOR]

This paper develops the concept of representational uncertainty to frame a critical challenge in systems engineering. Representational uncertainty arises in complex systems problems when the correct system representation cannot practically be known until some initial work has been undertaken. Drawing on empirical evidence from two very different system design problems, we illustrate the nature and prevalence of representational uncertainty in systems engineering practice. Our findings show that errors in the system representation may lead to wasted design work that explores the wrong tradespaces, expects the wrong value from design choices, and organizes work on the wrong set of decomposed subproblems. We find that mitigating representational uncertainty requires design processes that incorporate discovery of the system properties through a "reality check" early in the design process. We consider the implications for systems engineering processes and tools, and highlight directions for future research. [ABSTRACT FROM AUTHOR]