A causal loop diagram (CLD) is a visual model of hypothesized cause-and-effect relationships among variables. Arrows show causal influence, link polarities show whether variables move in the same or opposite direction relative to a baseline, and closed paths identify feedback loops.
CLDs are used to explain patterns over time, surface assumptions, compare stakeholder mental models, and locate possible interventions. They are qualitative unless translated into equations and tested as a simulation model.
Example
More service backlog can increase work pressure. Pressure may increase shortcuts, which reduce quality and create repeat demand. Repeat demand then adds to backlog, forming a reinforcing loop.
Learn how to construct and validate one in Causal Loop Diagrams: A Practical Guide.