Causal Loop Diagrams

Causal Loop Diagrams (CLDs) are visual tools used in systems thinking to map the causal relationships and feedback loops within complex systems. They consist of variables connected by arrows that indicate causal influences, with polarity (positive or negative) showing how changes propagate through the system. CLDs help identify reinforcing and balancing feedback loops that drive system behavior over time.

Also known as: CLDs, Causal Diagrams, Feedback Loop Diagrams, System Dynamics Diagrams, Causal Maps

Why learn Causal Loop Diagrams?

Developers should learn CLDs when working on projects involving complex systems, such as software ecosystems, business processes, or socio-technical systems, to understand interdependencies and emergent behaviors. They are particularly useful in system dynamics modeling, requirements analysis, and designing resilient architectures where feedback effects are critical, such as in DevOps pipelines, user engagement systems, or resource management applications.

Learning Resources

• course: Introduction to Causal Loop Diagrams - MIT System Dynamics
• tutorial: Causal Loop Diagrams Explained - The Systems Thinker
• course: Systems Thinking and Modeling with Causal Loop Diagrams - Coursera
• docs: Causal Loop Diagram Guide - Insight Maker
• article: Feedback Loops in Software Development - Martin Fowler