Structural Equation Modeling for Efficient Mission Formulation

The purpose of the NASA Pre-Phase A project life cycle phase is, “To produce a broad spectrum of ideas and alternatives for missions from which new programs/projects can be selected, and to determine the feasibility of [the] desired system, develop mission concepts, draft system-level requirements, assess performance, cost, and schedule feasibility; identify potential technology needs, and scope.”[1]. In this early stage of planning NASA's science missions, a key goal is to maximize “science per dollar” efficiency. This means making the most out of limited financial resources. To achieve this, it's crucial to define the minimum science requirements necessary for the mission. If these requirements are too ambitious, the mission's “science per dollar” efficiency drops, and valuable scientific opportunities might be missed. Overly ambitious science requirements can also lead to unnecessary cost risks, jeopardizing the mission proposal's success and reducing the overall scientific return. Therefore, it's essential to strike a balance in setting these requirements. Another crucial part of early mission planning is efficiently identifying the essential science requirements to ensure maximum efficiency of the formulation effort itself. This paper presents a versatile framework for efficiently identifying minimum science requirements using Structural Equation Modeling (SEM). This approach is applicable across all five divisions of NASA's Science Mission Directorate: Astrophysics, Biological and Applied Sciences, Earth Science, Heliophysics, and Planetary Science. Additionally, we share initial results from implementing this method in early mission concept formulation at the Jet Propulsion Laboratory.