Investigation of Leading Indicators for Systems Engineering Effectiveness in Model-Centric Programs

Abstract

Acquisition programs increasingly use model-centric decision-making approaches, generating and using digital assets throughout the life cycle. This transformation is resulting in new digital artifacts, revised processes, and more frequent reviews using models rather than documents. Accordingly, how engineering effectiveness is assessed must evolve. Systems engineering leading indicators provide visibility into expected project performance and potential future states. Visibility into the future state has not traditionally been part of a measurement process, and the leading indicators provide a forward-looking perspective. Prior research transformed lagging engineering metrics to systems engineering leading indicators; however, these are predicated on traditional systems engineering practice that uses document-driven processes and major milestone reviews. The research investigates adaptation and extension of existing systems engineering leading indicators for model-centric programs and how program leaders can use these to proactively assess systems engineering effectiveness in model-centric programs. The potential impact of this ongoing research is twofold: to better provide visibility into projected future state through use of leading indicators in model-centric programs, and to enhance the insights provided by the leading indicators as new digital artifacts enrich systems practice. This paper shares the approach and interim findings of the investigation.