InteractiveMap of Operations Research
Back to Networks, Games & Systems
MethodIntermediate04.09
Networks, Games & Systems

System Dynamics & Feedback Models

Model feedback loops, delays, and policy resistance.

Overview

System Dynamics & Feedback Models focuses on model feedback loops, delays, and policy resistance. In the map of OR, it connects Stocks and flows, Feedback loops, Delays to decisions that must be modeled, solved, explained, and revised as evidence changes.

System dynamics complements optimization by simulating stocks, flows, feedback, delays, and nonlinear behavior in complex organizations. The practical use case is clearest in Public policy, Healthcare, Sustainability, Operations strategy, where the method helps turn constraints and tradeoffs into a decision artifact someone can inspect.

Core ideas

Stocks and flows

Stocks and flows is a core checkpoint for System Dynamics & Feedback Models: define it concretely, attach units or rules where possible, and test whether stakeholders interpret it the same way.

Feedback loops

Feedback loops is a core checkpoint for System Dynamics & Feedback Models: define it concretely, attach units or rules where possible, and test whether stakeholders interpret it the same way.

Delays

Delays is a core checkpoint for System Dynamics & Feedback Models: define it concretely, attach units or rules where possible, and test whether stakeholders interpret it the same way.

Policy resistance

Policy resistance is a core checkpoint for System Dynamics & Feedback Models: define it concretely, attach units or rules where possible, and test whether stakeholders interpret it the same way.

How to use it

  1. 1Start with Public policy: write the decision, time horizon, actors, and objective in operational language.
  2. 2Translate the problem into Stocks and flows, Feedback loops, and Delays; define units and data sources for each one.
  3. 3Build a small instance of System Dynamics & Feedback Models that can be solved or simulated by hand inspection before using full production data.
  4. 4Compare the recommendation against a baseline policy, not just against mathematical optimality.
  5. 5Document assumptions, sensitivity results, and the conditions under which the recommendation should be revisited.

Applications

Public policyHealthcareSustainabilityOperations strategy
  • Public policy: compare feasible policies, quantify the operating tradeoffs, and make the assumptions behind the recommendation visible.
  • Healthcare: compare feasible policies, quantify the operating tradeoffs, and make the assumptions behind the recommendation visible.
  • Sustainability: compare feasible policies, quantify the operating tradeoffs, and make the assumptions behind the recommendation visible.
  • Operations strategy: compare feasible policies, quantify the operating tradeoffs, and make the assumptions behind the recommendation visible.

Common pitfalls

  • Applying System Dynamics & Feedback Models because the label sounds appropriate while leaving the actual decision boundary vague.
  • Treating Stocks and flows as a technical detail instead of a modeling choice that affects the recommendation.
  • Reporting one answer without showing sensitivity to demand, capacity, costs, or behavioral assumptions.
  • Ignoring implementation details such as data quality, explainability, ownership, and how users will override bad recommendations.

Resources