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Decision‐makers use system dynamics models to understand how model structure causes problematic behaviors, and how the structure should be changed to improve performance. However, understanding problem behavior and designing policies can be complicated without analytical tools. Existing methods focus on feedback loops that drive dynamic behavior. We propose a new method, Analysis of Dynamic Models by Optimization (ADMO), which focuses on understanding the causes of well‐defined problems and on guiding system and policy design. Unlike existing methods, ADMO can evaluate the influence of exogenous variables and nonlinearities, leading to new understandings of endogenous behavior and providing insights for policy design. ADMO can be employed with any model, including differential equation, agent‐based, discrete event, or hybrid, requiring minimal effort. Two cases demonstrate …