Summary: Thinking in Systems (by Donella H. Meadows)

Niklas Hemmer
7 min readOct 10, 2021

The main argument of the book:
Everything in this world is made of systems. While we cannot fully understand systems, we can observe them and study their patterns and behaviors. Combined with an open mind, this will allow us to figure out how we can design and redesign our systems and how we can live with them.

Part 1: System Structure and Behavior

1.1 The Basics:

  • A system is an interconnected set of elements that is coherently organized in a way to serve a particular function/purpose.
  • It must always consist of three things: (1) elements, (2) interconnections, and (3) a function or purpose.
  • The structure of these three things leads to a behavior. If you freeze the behavior at a specific moment in time you will see an event.
  • The most important determinant of behavior is a system’s purpose. It has the largest influence as the system will always try to achieve its purpose.
  • While interconnections are also very important, elements usually have the least effect on the system. They can be changed easily.

Example: A football team is a system with elements such as players, coaches, field, and ball. Its interconnections are, for example, the rules of the game, the coach’s strategy, and the players’ communication. The purpose is to win games. This leads to behavior on the pitch, i.e., performances over time and events, i.e., results on matchday.

1.2 Stocks and Flows:

  • The behavior of a system breaks down into stocks and flows.
  • A stock is the foundation of any system. It is an accumulation of information or material that has built up over time. For instance, the population, your self-confidence, or money in your bank account.
  • These stocks change over time through the actions of a flow. While inflows add something to the stock, outflows subtract something from it.
  • Example: More births increase the population while deaths decrease the population.

1.3 Feedback Loops:

  • These flows constantly change over time when the stock changes. This is what we call a feedback loop. We have to distinguish between two different feedback loops:
  • Balancing Feedback Loops stabilize the stock level based on the difference between the actual and desired level of stock. These loops try to keep a stock at a given value or within a certain range of values.
    Example: Take your bank account. The bank account itself is the stock, your income is the inflow, and your expenses are the outflow. Now, you receive your bank statement and see that you lost money. There is a discrepancy between your actual and your desired fortune. You decide to work more hours to earn more money (inflow) and stabilize your bank account.
  • Reinforcing Feedback Loops reinforce the direction of change. They generate more input into stock the more is already there. These are vicious and virtuous cycles.
    Example: The more money you have in the bank, the more interest you earn, the more money you have in the bank, and so on…
  • It is worth noting that both feedback loops often work together. For instance, the fertility rate is a reinforcing feedback loop (R). The more people there are, the more babies there are, and so on. While this could lead to exponential growth, there is also a balancing feedback loop (B): mortality rate.

Part 2: Systems and us

2.1 Characteristics of a well-functioning system:

  1. Resilience
    The ability of a system to survive and persist in a variable, highly dynamic environment; the ability to recover from a setback due to an outside force. It’s important to have tight feedback loops to react quickly
  2. Self-organization
    The ability of a system to structure itself, to learn, to diversify. With just a few organizing principles, self-organization can lead to the creation of new structures, new ways of doing things.
  3. Hierarchy
    Systems are organized in such a way as to create a larger system, i.e., subsystems within a system. There is a risk of too much control or discrepancies between the overall goal and goals of subsystems.

2.2 Mistakes in Systems Thinking:

The following is a warning list of how our mental models fail to take into account the complexity of the real world.

“Our knowledge is amazing; our ignorance even more so.”

  1. Beguiling Events
    We fool ourselves by seeing a system’s output as a series of events. Instead, we should put an event into its historical context to understand the system structure.
  2. Linear minds in a nonlinear world
    Many relationships in systems are not linear but nonlinear. Their relative strengths shift in disproportionate amounts as the stocks in the system shift.
  3. Nonexistent Boundaries
    There are no separate systems. Everything is connected. Where to draw (artificial) boundaries around a system depends on the purpose of the discussion.
  4. Layers of Limits
    There will always be limits to growth. When one factor ceases to be limiting, growth occurs, and the growth itself changes the relative scarcity of factors until another becomes limiting.
  5. Ubiquitous Delay
    Delays are ubiquitous in every system, e.g., the delay between catching an infectious disease and getting sick enough to be diagnosed. Overshoots, oscillations, and collapses are caused by delays.
  6. Bounded Rationality
    People make quite reasonable decisions based on the information they have. But they don’t have perfect information. Therefore, the bounded rationality of each actor in a system may not lead to the best decision for the system as a whole.

2.3 System traps and opportunities:

  • Some systems are structured in a way that produces problematic behavior. Meadows calls these patterns of problematic behavior archetypes.
  • The destruction they cause is often blamed on a particular person (element), but it is actually a consequence of the system structure. Standard responses such as blaming, or firing, won’t help which is why these archetypes are traps.

Example: Drift to Low Performance
We have a bias to remember negative past performances. If you allow these biases to influence your standards, your goals erode, drifting toward low performance.
— Solution:
Keep performance standards absolute. Or, even better, use the best performances as a benchmark.

Part 3: Creating Change

3.1 Top 5 Leverage Points to change a system (from best to worst)

  1. Transcending Paradigms
    Stay unattached to any specific paradigm, realizing that no paradigm is “true”. Accept that we have a tremendously limited understanding of an immense and amazing universe that is far beyond human comprehension.
    If no paradigm is right, you can choose the one that will help to achieve your purpose.
  2. Paradigms — The mindset out of which the system — its goals, structure, rules, delays, parameters — arises
    Paradigms are the sources of systems. From them, from shared social agreements, come system goals and information flows and everything else. How do you change paradigms? Keep pointing at the anomalies and failures of the old paradigm. Speak and act, loudly and with assurance, from the new one. Insert people with the new paradigm in places of public visibility and power.
  3. Goals — The purpose or function of the system
    The goal is a crucial determinant of every system. Everything below the goal, e.g., physical stocks, information flows, will be twisted to conform to a goal.
  4. Self-Organization — The power to add, change, or evolve system structure
    A system that can evolve can survive almost any change, by changing itself. We have to write clever rules for self-organization. These rules govern how, where and what the system can add onto and subtract from itself under what conditions.
  5. Rules — Incentives, punishments, constraints:
    Rules are high leverage points. If you want to understand the system’s deepest malfunctions, pay attention to the rules and to who has power over them.

3.2 Guidelines for living in a world of systems:

  • Get the beat of the system — watch how it behaves, analyze it before acting
  • Expose your mental models to the light of the day — make your model and your assumptions visible; challenge it and think like a scientist
  • Honor, respect, and distribute information — you should not distort, delay, or withhold information
  • Use language with care and enrich it with systems concepts
  • Pay attention to what is important, not just what is quantifiable — not everything is quantifiable; assess the quality, cohesion, or freedom of a system
  • Make feedback policies for feedback systems — the best feedback policies not only contain feedback loops but meta-feedback loops
  • Go for the good of the whole — don’t maximize parts of the system while ignoring the whole
  • Listen to the wisdom of the system — before you try to make things better, pay attention to what’s already there
  • Locate responsibility in the system — understand who is responsible for an action and who experiences the consequences
  • Stay humble — stay a learner
  • Celebrate complexity — beyond that, celebrate and encourage self-organization, disorder, variety, and diversity
  • Expand time horizon — consider the short- and long-term
  • Defy the disciplines — put together people from different fields
  • Expand the boundary of caring
  • Don’t erode the goal of goodness — don’t weigh the bad news more heavily than the good; keep the standards absolute