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Systems Thinking and Mental Models
May 17, 2024
Systems Thinking and Mental Models ðŸ§
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
:
Events
: Observable occurrences (e.g., snail infestation).
Patterns of Behavior
: Trends over time (recurrent issues).
Systems
: Underlying structures causing patterns.
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
:
What are the likely outcomes?
Which outcomes are expected to occur?
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
:
Define your goal.
Articulate the assumptions for achieving the goal.
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.
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