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390 readings

Reading 1: The Jim Hines Method

Jim HInes Method

Purpose

  • A step-by-step approach to solve complex, dynamic problems using systems thinking and system dynamics modeling.

  • Based on MIT/WPI teaching materials by Jim Hines (nicknamed the “Standard Method”).

Types of Complexity

  • Detail complexity: lots of parts but predictable (e.g., building an airplane).

  • Dynamic complexity: things that change over time, involve feedback, delays, nonlinearities, multiple stakeholders → what system dynamics focuses on.

The 11 Steps

  1. List variables – what can change over time (measurable ↑↓).

  2. Reference modes – sketch expected/hoped/feared behaviors of key variables over time.

  3. Problem statement – short, clear description of the issue (no solutions yet).

  4. Dynamic hypothesis – draft causal loop/stock-flow diagrams that explain the behaviors.

  5. Identify feedback loops (reinforcing = positive, balancing = negative).

  6. Identify key stocks in the loops (e.g., population, resources).

  7. Collect data for key stocks.

  8. Simulate a first key stock (start small).

  9. Add feedback for the first stock.

  10. Quick analysis/validation – does model match reference modes?

  11. Repeat steps 5–10 iteratively.

Key Ideas

  • Reference mode vs. real data: reference mode = your mental model (before looking at actual data).

  • Feedback examples:

    • Reinforcing → exponential growth (e.g., rhinos increase).

    • Balancing → goal-seeking (e.g., population levels off at carrying capacity).

  • Always build gradually, test constantly, and refine your mental model.

👉 Quiz tip: Be able to list the 11 steps in order and explain difference between reinforcing vs. balancing loops.

📘 Reading 2: Introduction to Systems and Systems Thinking

introduction-to-systems-and-sys…

What is a System?

  • A set of parts (elements/stocks) + their relationships → forms a whole with a function.

  • Must interact and depend on each other (vs. a “collection,” like spices on a rack).

  • Examples: body, climate, transportation.

Types of Systems

  • Simple: predictable, few parts (goldfish in a bowl).

  • Complicated: solvable, may require expertise, stable outcomes (computer, school schedules).

  • Complex Adaptive (CAS): many parts, nonlinear, feedback, unpredictable, self-organizing, adaptive (immune system, democracy).

  • Chaotic: no clear patterns (weak connections, randomness).

Systems Thinking (definition)

  • A set of skills for:

    • Identifying/understanding systems,

    • Predicting behaviors,

    • Finding leverage points to influence them.

  • Not about control, but about seeing connections, feedbacks, and trade-offs.

Core Concepts

  • Stocks: measurable parts (population, happiness, temp).

  • Flows: inputs/outputs that change stocks.

  • Feedback loops:

    • Balancing (negative): stabilizes system (thermostat, body temp).

    • Reinforcing (positive): amplifies change (interest in a bank account, vicious/virtuous cycles).

  • Boundaries: define what’s in/out of the system (important for framing).

  • Mental models: assumptions/worldviews that shape how we see systems.

Tools (common quiz material!)

  • Iceberg/Tree model: events → patterns → structures → mental models.

  • Causal loop diagrams: show variable relationships (+ or –).

  • Change-over-time graphs: trends/patterns.

  • Rich pictures: unstructured diagrams showing system complexity.

  • Scenario analysis: imagine different futures.

  • Leverage points (Meadows): 12 places to intervene in a system; deepest leverage = paradigms, goals, mindsets.

Key Systems Thinking Questions (Box 2):

  • What are the patterns/trends?

  • What feedbacks are at play?

  • What’s the boundary of the system?

  • Where can small shifts make a big difference?

  • What trade-offs/unintended consequences exist?

👉 Quiz tip: Be ready to compare simple/complicated/complex systems, define stocks, flows, feedback, and recall the iceberg model and leverage points.

✅ Quick Memory Hacks

  • Hines 11 Steps → “Variables Refer Problems Dynamically; Loops Stocks Data Simulate Add Validate Repeat.”

  • System types → “Simple goldfish, Complicated computer, Complex immune system, Chaotic mess.”

  • Feedback → Reinforce = runaway, Balance = stabilize.

  • Iceberg → Events → Patterns → Structures → Mental Models (tip vs. root cause).