Decisions are made, actions are taken, and the world is changing constantly as a result. The consequences of past decisions create the information that affects future decisions in an iterative, continuous set of feedback processes. To better comprehend real-world systems, change, and complex interactions, identifying and understanding feedback is paramount. The system dynamics (SD) approach, part of the operations research field and identified by systems philosophers as part of the first three waves of systems thinking, emerged out of servomechanisms engineering and control theory. It has been applied to understand and manage a wide range of complex problems in natural, engineered, and social systems. The SD approach combines the theory of information feedback, human decision making, and computer simulation to create a computer-aided approach to policy analysis and design. The SD approach favors a point of view that originates from within—an endogenous approach—to explain and propose alternatives for change in complex systems. Feedback and endogeneity, core concepts in system dynamics, enable closed-loop thinking to understand complex systems which go beyond open-loop thinking and reveal, in a holistic way, not only how, but also why things change over time. Additionally, SD uses a broad system boundary to provide such endogenous structural explanations of system behavior, and embracesmethodological pluralism in order to evolve, adapt, and take advantage of advances in computer processing speed and storage, data availability and analysis, and social science research and analytical methods.