Causal Loop Diagram (CLD)

A systems thinking tool mapping variables and reinforcement (+)/balancing (-) loops to understand complex feedback systems.

🎯 What Problem It Solves

In business or policy, we often face growth plateaus or policy resistance. CLD helps visualize feedback loops and delays to find leverage points.

🧠 Thinking Logic & Core Concepts

Variables interact in closed loops. We identify: 1. Reinforcing Loops (R, self-multiplying, like viral marketing), and 2. Balancing Loops (B, self-limiting, like market saturation).

📋 Newbie Step-by-Step Guide

1. Identify Variables: List key factors (ad spend, users, quality).
2. Connect with Directions: Use (+) for same-direction change (users -> referrals) and (-) for opposite (users -> server delay -> quality).
3. Identify Loops: Trace closed paths. Even number of (-) loops are Reinforcing (R), odd number are Balancing (B).
4. Mark Delays: Add double-lines on slow connections.
5. Find Leverage: Focus on variables that can ease balancing loop constraints.

💡 Classic Example

[Bike Sharing Market Case]

• Loop 1 (R): More bikes -> More users -> More revenue -> More bikes.
• Loop 2 (B): More bikes -> More broken/illegally parked bikes -> Government complaints -> Fines & restrictions -> Fewer bikes.
• Leverage Point: Invest in smart geo-fencing and maintenance to reduce illegal parking, easing the balancing loop.