think-causal-loop-diagrams

Causal Loop Diagrams

People narrate systems as one-directional chains and silently drop the loop-back. "More users, so more revenue" omits "...which funds acquisition, which brings more users" - the cycle that actually drives the behavior. This skill performs one distinct move: close the feedback loops and sign them. Trace each cycle back to its start so it closes, give every link a polarity (does a rise in A raise (+) or lower (-) B), and label the whole loop reinforcing (R) when the signs multiply to net-positive (it amplifies: a vicious or virtuous spiral) or balancing (B) when they multiply to net-negative (it counteracts: goal-seeking, or oscillation when delayed). Then read likely behavior off the structure: which loop dominates, and therefore whether the system spirals, seeks a goal, or oscillates. The output is a signed causal loop diagram framed as a structured argument about dynamics - not a prediction. It corrects a specific, well-evidenced failure (people misperceive feedback); it does not claim to predict the system or to teach systems thinking wholesale.

When to Use

• A variable plausibly feeds back on itself through a cycle (growth funds growth; a fix recreates its problem; relief of a constraint re-attracts the load).
• The puzzle is why does this keep accelerating / stalling / overshooting and undershooting - behavior that a linear story cannot explain.
• You want an inspectable, signed structure (R/B loops with polarities) before reasoning about leverage or intervention.

When NOT to Use

• A single accumulation, no loop (one stock, net flow, no cycle): use think-stocks-and-flows-reasoning. That skill reasons about one quantity from its net flow; it does not close or sign a loop.
• You only need to name that feedback exists as one structural layer among events, patterns, and structure: use think-iceberg-model. It names feedback as a structure item but does not close, sign, or diagram loops.
• Forward, one-directional consequences that fan out and do not loop back: use think-futures-wheel. It is an acyclic consequence tree by construction - no loop, no polarity.
• The structure is genuinely open-loop / linear. If the chain does not actually feed back, forcing a loop manufactures false feedback. Say "no closed loop found - this is a linear chain" and stop; do not invent a loop to fill the diagram.
• Teaching general systems thinking, hunting leverage points, or wholesale systems mapping - out of scope (separate catalog rows). This skill does one move: close and sign loops, then read dominance.