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System Dynamics Modeling is a structured approach for modeling stocks, flows and feedbacks in complex systems. It supports scenario analysis, policy testing and strategic decision-making by simulating and visualizing cause–effect chains. Typical applications include corporate strategy, supply chain and product dynamics.
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Executable approach: can be applied and produces an outcome.
What organizes, connects, or makes decisions possible.
System dynamics modeling represents feedback, delays, and stocks to study how complex systems behave over time.
Jay W. Forrester developed the approach at MIT in the 1950s by combining control engineering with management research.
Describe stocks, flows, and feedback loops, define their relationships, and simulate how the system evolves under different assumptions.
A quantity that accumulates or depletes through inflows and outflows.
A loop in which an outcome influences its own cause.
The time between a change and its visible effect.
Models help test side effects and long-term developments before real measures are implemented.
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