systems-thinking

Systems Thinking

Analyze complex systems through feedback loops, leverage points, and system dynamics.

Core Concepts

Feedback Loops

Reinforcing (Positive) Loops: Amplify change in one direction

Growth → Success → More Resources → More Growth

Balancing (Negative) Loops: Seek equilibrium

Temperature ↑ → Thermostat → Cooling → Temperature ↓

Meadows' 12 Leverage Points

Intervention points ranked by effectiveness (most to least powerful):

Level	Leverage Point	Example
12	Paradigms	Mental models underlying the system
11	Goals	System purpose and direction
10	Self-organization	Ability to evolve structure
9	Rules	Incentives, constraints, permissions
8	Information flows	Who has access to what data
7	Reinforcing loops	Amplifying feedback
6	Balancing loops	Stabilizing feedback
5	Delays	Time between action and response
4	Material stocks/flows	Physical resources
3	Buffer sizes	Stabilizing capacity
2	Structure	Physical connections
1	Parameters	Numbers and constants

System Archetypes

Fixes that Fail: Quick fix creates side effects Shifting the Burden: Symptomatic solution undermines fundamental solution Limits to Growth: Initial success hits constraints Tragedy of the Commons: Individual benefit depletes shared resource

Analysis Workflow

1. Boundary Definition: Scope, internal vs external, timescale
2. Element Mapping: Variables, stocks, flows
3. Relationship Identification: Causal connections, +/- classification
4. Loop Detection: Feedback paths, dominant loops
5. Leverage Point Analysis: High-impact intervention points

Causal Loop Notation

A --[+]--> B   (same direction)
A --[-]--> B   (opposite direction)
R = Reinforcing, B = Balancing

Common Pitfalls

• Linear thinking (ignoring B→A)
• Event focus (symptoms vs structures)
• Boundary errors (too narrow/wide)
• Delay blindness