Systems Thinking and Mental Models

May 17, 2024

Systems Thinking and Mental Models 🧠

Key Concepts

Two Ways of Looking at the World

  • In Parts: Traditional way, breaking down complex systems into individual components.
    • Example: School subjects like English, math, biology, etc.
  • As a Whole: Considering the connections and relationships between different parts.
    • Aristotle: The whole is more than the sum of its parts.
    • Importance of connections and relationships in understanding complex systems.

Systems Thinking

  • Definition: Understanding problems as a whole and identifying the causes, not just treating symptoms.
  • Six Mental Models: Tools to understand systems thinking.

1. Linear vs Non-Linear Organization

  • Linear Thinking: Sequence-based, if A happens then B happens, typical in traditional thinking (e.g., Excel spreadsheets).
  • Non-Linear Thinking: Cycles and interconnections, A affects B affects C which in turn affects A.
    • Example: Documentary "The Biggest Little Farm"
      • Interconnected problems and solutions on a farm.
      • Ducks eating snails that affect crops, snails fertilizing soil, etc.

2. Stock and Flow

  • Stock: The items or entities in a system (e.g., animals, plants, soil, water, money).
  • Flow: The actions that change the stock levels (e.g., selling products, buying resources).
    • Simplifies understanding of systems.

3. Iceberg Model

  • Four Levels of Reality:
    1. Events: Observable occurrences (e.g., snail infestation).
    2. Patterns of Behavior: Trends over time (recurrent issues).
    3. Systems: Underlying structures causing patterns.
    4. Mental Models: Beliefs and values shaping the system.
  • Example: Farm dealing with pests and biodiversity.
    • Addressing the underlying mental model leads to sustainable solutions.

4. Finding the Bottleneck

  • Definition: The system is only as strong as its weakest part.
  • Application:
    • Identifying delays or points where the system gets stuck.
    • Using the 80/20 rule to prioritize issues.

5. Second Order Thinking

  • First Order Thinking: Simple cause and effect (if A then B).
  • Second Order Thinking: Considering the broader implications (if A, then B, which might cause C).
    • Questions to Ask:
      1. What are the likely outcomes?
      2. Which outcomes are expected to occur?
      3. What is the probability of being right?
    • Application: Helps guide research and decision-making.

6. Building a Feedback Loop

  • Importance: Design a system to provide information and data to understand progress.
  • Steps:
    1. Define your goal.
    2. Articulate the assumptions for achieving the goal.
    3. Choose appropriate measurements.
  • Example: Decision-making process using mental models and feedback.
    • Tracking decisions, assessing outcomes, and refining mental models.

Conclusion

  • Systems thinking offers a holistic approach to problem-solving by understanding the connections and relationships within a system.
  • Mental models provide frameworks to identify causes, predict outcomes, and design effective solutions.