Cover of book Thinking in Systems: A Primer

Thinking in Systems: A Primer

by: Donella H. Meadows

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136 Highlights | 10 Notes
  • … systems thinking transcends disciplines and cultures, and when it is done right, it overarches history as well.
  • Once you start to see the events of the day as parts of trends, and those trends as symptoms of underlying system structure, you wil be able to consider new ways to manage and new ways to live in a world of complex systems.
  • “Now once again, what made the Slinky bounce up and down?”

    The answer lies within the slinky itself. The hands that manipulate it, supress or release some behavior that is latent within the structure of the spring.

  • So, what is a system? A system is a set of things &mdash people, cells, molecules, or whatever &madash; interconnected in such a way that they produce their own pattern of behavior over time. The system may be buffeted, constricted, triggered, or driven by outside forces. But the system's response is seldom simple in the real world.
  • Psychologically and politically, we would much rather assume that the cause of the problem is 'out there', rather than 'in here.' It's almost irresistible to blame something or someone else, to shift responsibility away from ourselves, and to look for the control knob, the product, the fill, the technical fix that will make a problem go away.
  • … the basic operating unit of a system: the feedback loop.
  • Systems thinkers call these common structures that produce characteristic behaviors 'archetypes'.
  • The behavior of a system cannot be known just by knowing the elements of which the system is made.
  • A system is more than the sum of its parts. It may exhibit adaptive, dynamic, goal seeking, self preserving, and sometimes evolutionary behavior.
  • How to know whether you are looking at a system or just a bunch of stuff?
    1. Can you identify the parts? … and
    2. Do the parts affect each other? … and
    3. Do the parts together produce an effect that is different from the effect of each part on its own? … and perhaps
    4. Does the effect, the behavior over time persis in a variety of circumstances?
  • It's easier to learn about a system's elements than about its interconnections.
  • Many of the interconnections in systems operate through the flow of information. Information holds systems together and plays a great role in determining how they operate.
  • The best way to deduce the system's purpose is to watch for a while to see how the system behaves.
  • A stock is the memory of the history of changing flows within a system.
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  • If you understand the dynamics of stocks and flows — their behavior over time — you understand a good deal about the behavior of complex systems.
  • A stock can be increased by decreasing its outflow rate as well as by increasing its inflow rate
  • Stocks generally charge slowly, even when the flows into or out of them change suddenly. Therefore, stocks act as delays on buffers or shock absorbers in systems.
  • The timee lags that come from slowly changing stocks can cause problems in systems, but they can also be sources of stability
  • Stocks allow inflows and outflows to be decoupled and to be independent and temporarily out of balance with each other.
  • Systems thinkers see the world as a collection of stocks along with the mechanisms for regulating the levels in the stocks by manipulating flows.
  • In other words, if you see a behavior that persists over time, there is likely a mechanism creating that consistent behavior. That mechanism operates through a feedback loop.
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  • A feedback loop is a closed chain of causal connections from a stock, through a set of decisions or rules or physical laws or actions that are dependent on the level of the stock, and back again through a flow to change the stock
  • Energy level of a coffee drinker
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  • Remember — all system diagrams are simplifications of the real world.
  • Balancing feedback loops are goal-seeking or stability-seeking.
  • Balancing feedback loops are equilibrating or goal-seeking structures in systems and are both sources of stability and sources of resistance to change
  • The second kind of feedback loop is amplifying, reinforcing, self-multiplying, snowballing - a vicious circle that can cause healthy growth or runaway destruction. It is called a reinforcing feedback loop.
  • Reinforcing feedback loops are self-enchancing, leading to exponential growth or runaway collapses over time. They are found whenever a stock has the capacity to reinforce or reproduce itself.
  • Sometimes I challenge my students to try to think of any human decision that occurs without a feedback loop- that is, a decision that is made without regard to any information about the level of the stock it influences'
  • Instead of seeing only how A causes B, you'll begin to wonder how B may also influence A — and how A might reinforce or reverse itself.
  • You'll be thinking not in terms of a static world, but a dynamic one. You'll stop looking for who's to blame; instead you'll start asking, 'What's the system?' The concept of feedback opens up the idea that a system can cause its own behavior
  • One-stock systems
    A lock with two competing Balancing loops - a thermostat
  • The information delivered by a feedback loop — even nonphysical feedback — can only affect future behavior; it can't deliver a signal fast enough to correct behaivor that drove the current feedback. Even nonphysical information takes time to feed back into the system
  • Because it means there will always be delays in responding. It says that a flow can't react instantly to a flow. It can react only to a charge in a stock, and only after a slight delay to register the incoming information.
  • A stock with One Reinforcing Loop and One Balancing Loop- Population and Industrial Economy
  • Complex behaviors of systems often arise as the relative strengths of feedback loops shift, causing first one loop and then another to dominate behavior.
  • Questions for testing the value of a Model.
    1. Are the driving factors likely to unfold this way?
    2. If they did, would the system react this way?
    3. What is driving the driving factors?
  • Model utility depends not on whether its driving scenarios are realistic (since no one can know that for sure), but on whether it responds with a realistic pattern of behavior.
  • Systems with similar feedback structures produce similar dynamic behaviors.
  • A delay in a balancing feedback loop makes a system likely to oscillate.
  • Delays are persvasive in systems, and they are strong determinants of behavior. Changing the length of a delay may (or may not, depending on the type of delay of and the relative lengths of other delays) make a large change in the behavior of a system.
  • We can't begin to understand the dynamic behavior of systems unless we know where and how long the delays are.
  • Economies are extremely complex systems; they are full of balancing feedback loops with delays, and they are inherently oscillatory
  • Two stockc systems
    A renewable stock constrained by a non-renewable stock - on oil economy
  • In phycical exponentially growing systems, there must be at least one reinforcing loop driving the growth and at least one balancing loop constraining the growth, because no physical system can grow forever in a finite environment.
  • Renewable stock constrained by a renewable stock - a fishing economy.
  • Non renewable resources are stock-limited. The entire stock is available at once, and can be extracted at any rate ( limited mainly by extraction capital.) But since the stock is not renewed, the faster the extraction rate, the shorter the lifetime of the resource.
  • Renewable sources are flow-limited. They can support extraction or harvest indefinitely, but only at a finite flow rate equal to their regeneration rate. If they are extracted faster than they regenerate, they may be eventually bedriven below a critical threshold and become, for all practical purposes, nonrenewable.
  • I've shown three sets of possible behaviors of this renewable resource system here:
    • overshoot and adjustment to a sustainable equilibrium
    • overshoot beyond that equilibrium followed by oscillation around it, and
    • overshoot followed by collapse of the resource and the industry dependent on the resource.
    Which outcome actually occurs depends on two things. The first is the critical threshold beyond which the resource population's ability to regenerate itself is damaged. The second is the rapidity and effectiveness of the balancing feedback loop that slows capital growth as the resource becomes depleted
  • Chances are good that you may have observed one of three characteristics: resilience, self-organization, or hierarchy.
    Note: properties of highly functional systems
  • There are always limits to resilience.
  • Short term oscillations, or periodic outbreaks, or long cycles of succession, climax, and collapse may in fact be the normal condition, which resilience acts to restore!
    Note: seasons, boom-bust cycles, rhythms of work, tilting
  • Because resilience may not be obvious without a whole-system view, people often sacrifice resilience for stability, or for productivity, or for some other more immediately recognizable system property
  • Systems need to be managed not only for productivity or stability, they also need to be managed for resilience. the ability to recover from perturbation, the ability to restore or repair themselves.
  • Systems often have the property of self-organization — the ability to structure themselves, to create new structure, to learn, to diversify, and complexify. Even complete forms of self-organization may arise from relatively simple organizing rules - or may not.
  • Hierarchies are brilliant systems inventions, not only because they give a system stability and resilience, but also because they reduce the amount of information that any part of thesystem has to keep track of
  • Hierarchical systems evolve from the bottom up. The purpose of the upper layers is to serve the purposes of the lower layers
  • Everything we think we know about the world is a model. Our models do have a strong congruence with the world. Our models fall far short of representing the real world fully.
  • You cant navigate well in an interconnected, feedback-dominated world unless you take your eyes off short-term events and look for long-term behavior and structure; unless you are aware of false boundaries and bounded rationality; unless you take into account limiting factors, non linearities and delays. You are likely to mistreat, misdesign, or misread systems if you don't respect their properties of resilience, self-organization, and hierarchy.
  • The behavior of a system is its performance over time — its growth, stagnation, decline, oscillation, randomness, or evolution.
  • The structure of a system is its interlocking stocks, flows, and feedback loops.
  • System structure is the source of system behavior. System behavior reveals itself as a series of events over time.
    Note: can relationships be drawn using the system structure model?
  • Nonlinear systems generally cannot be solved and cannot be added together … Nonlinearity means that the act of playing the game has a way of changing the rules … That twisted changeability makes non linearity hard to calculate, but it also creates rich kinds of behaviors that never occur in linear systems.

    - Janis Gleick, author of Chaos: Making a New science
    Note: to-read, #eq
  • Many relationships in systems are non-linear. Their relative strengths shift in disproportionate amounts as the stocks in the system shift. Nonlinearities in feedback systems produce shifting dominance of loops and many complexities in system behavior
    Note: i.e. they change the relative strengths of feedback loops.
  • the greatest complicities arise exactly at boundaries… Disorderly, mixed-up borders are sources of diversity and creativity
  • Ideally we would have the mental flexibility to find the appropriate boundary for thinking about each new problem. We are rarely that flexible. We get attached to the boundaries our minds happen to be accustomed to.
  • It's a great art to remember that boundaries are of our own making, and that they can and should be reconsidered for each new discussion, problem, on purpose.
  • At any given time, the input that is most important to a system is the one that is most limiting
  • Insight comes not only from recognizing which factor is limiting, but from seeing that growth itself depletes or enhances limits and therefore changes what is limiting
  • Any physical entity with multiple inputs and outputs is surrounded by layers of limits
  • For any physical entity in a finite environment, perpetual growth is impossible. Ultimately the choice is not to grow forever but to decide what limits to live within.
  • There always will be limits to growth. They can be self-imposed. If they arent, they will be system-imposed
  • Delays determine how fast systems can react, how accurately they hit their targets, and how timely is the information passed around a system. Overshoots, oscillations, and collapses are always caused by delays.
  • when there are long delays in feedback loops, some sort of foresight is essential. To act only when a proplem becomes obvious is to miss an important opportunity to solve the problem.
  • Bounded rationality means that people make quite reasonable decisions based on the information they have. But they dont have perfect information, especially about more distant parts of the system
  • We are not omniscient, rational optimizers, says Simon: Rather we are blundering 'satisficers': attempting to meet (satisfy) our needs well enough (sufficiently) before moving on to our next decision.
    Note: Siimon Herbert - Nobel prize winning economist
  • To paraphrase a common prayer: God grant us the serenity to exerrcise our bounded rationality freely in the systems that are structured appropriately, the courage to restructure the systems that aren't, and the wisdom to know the difference!
  • It bounded rationality of each actor in a system may not lead to decisions that furthur the welfare of the system as a whole.
  • The Trap: Policy Resistance

    When various actors try to pull a system stock toward various goals, the result can be policy resistance. Any new policy, especially if it's effective, just pulls the stock furthur from the goals of the other actors and produces additional resistance, with a result that no one likes, but that everyone expends considerable effort in maintaining.

    The Way Out

    Let go. Bring in all the actors and use the energy formerly expended on resistance to seek out mutually satisfactory ways for all goals to be realized — or redefinitions of larger and more important goals that everyone can pull toward together.

  • The tragedy of the commons

    In any commons system there is, first of all, a resource that is commonly shared (the pasture). For the system to be subject to tragegy, the resource must not only be limited, but erodable when overused. That is, beyond some threshold, the less resource there is, the less it is able to regenerate itself, or the more likely it is to be destroyed.

  • A commons system also needs users of the resource (the cows and their owners), which have good reason to increase, and which increase at a rate that is not informed by the condition of the resource.
  • The tragedy of the commons arises from missing (or too long delayed) feedback from the resource to the growth of the users of that resource.
  • The Way Out

    Educate and exhort the users so they understand the consequences of abusing the resource. And also restore or strengthen the missing feedback link, either by privatizing the resource so each user feels the direct consequences of its abuse or (since many resources cannot be privatized) by regulating the access of all users to the resource.

  • The reinforcing loop going downward, which said 'the worse things get, the worse I'm going to let them get,' becomes a reinforcing loop going upward: 'The better things get, the harder I'm going to work to make them even better.'
  • The Trap: Drift to Low Performance

    Allowing performance standards to be influenced by past performance, especially if there is a negative bias in percieving past performance, sets up a reinforcing feedback loop of eroding goals that sets a system drifting toward low performance.

    The Way Out

    Keep performance standards absolute. Even better, let standards be enhanced by the best actual performances instead of being discouraged by the worst. Use the same structure to set up a drift toward high performance

  • The Trap: Escalation

    When the state of one stock is determined by trying to surpass the state of another stock - and vice versa - then there is a reinforcing feedback-loop carrying the system into an arms race, a wealth race, a smear campaign, escalating loudness, escalating violence. The escalation is exponential and can lead to extremes surprisingly quickly. If nothing is done, the spiral will be stopped by someone's collapse — because exponential growth cannot go on forever


    The Way Out

    The best way out of this trap is to avoid getting in it. If caught in an escalating system, one can refuse to compete (unilaterally disarm), thereby interrupting the reinforcing loop. Or one can negotiate a new system with balancing loops to control the escalation.

  • &hellip but this particular analysis of his [Karl Marx] — that market competition systematically eliminates market competition - is demonstrated wherever there is, or used to be, a competitive market
  • The Trap: Success to the Successful

    If the winners of a competition are systematically rewarded with the means to win again, a reinforcing feedback loop is created by which, if it is allowed to proceed uninhibited, the winners eventually take all, while the losers are elimitated.

    The Way Out:

    Diversification, which allows those who are losing the competition to get out of that game and start another one; strict limitations on the fraction of the pie any one winner may win (antitrust laws); policies that level the playing field, removing some of the advantage of the strongest players or increasing the advantage of the weakest; policies that devise rewards for success that do not bias the next round of competition.

  • The problem can be avoided up front by intervening in such a way as to strengthen the ability of the system to shoulder its own burdens.
    Note: note: problem = addictions
    • Why are the natural correcting mechanisms failing?
    • How can obstacles to their success be removed?
    • How can mechanisms for their successbe made more effective?
    Note: Questions to ask before intervening to help with an addiction
  • The Trap: Shifting the burden to the Intervener

    Shifting the burdern, dependence and addiction arise when a solution to a systemic problem reduces (or disguises) the symptoms but does nothing to solve the underlying problem. Whether it is a substance that dull's ones perception or a policy that hides the underlying trouble, the drug of choice interferes with the actions that could solve the real problem.

    If the intervention designed to correct the problems causes the self maintaining capacity of the original system to atrophy or erode, then a destructive reinforcing feedback loop is set in motion. The system deteriorates; more and more of the solution is then required. The system will become more and more dependent on the intervention and less and less able to maintain its own desired states.

    The Way Out

    Again the best way out of this trap is to avoid getting in. Beware of symptom-relieving or signal-denying policies or practices that don't really address the problem. Take-the focus off short-term relief and put it on long-term restructuring

  • The Trap: Rule Beating

    Rules to govern a system can lead to rule beating - perverse behavior that gives the appearance of obeying the rules or achieving the goals, but that actually distorts the system.

    The Way Out

    Design, or redesign, rules to release creativity not in the direction of beating the rules, but in the direction of achieving the purpose of the rules.
  • The Trap: Seeking The Wrong Goal

    System behavior is particularly sensitive to the goals of feedback loops. If the goals — the indicators of satisfaction of the rules — are defined inaccurately or incompletely, the system may obediently work to produce a result that is not really intended or wanted.

    The Way Out

    Specify indicators and goals that reflect the real welfare of the system. Be especially careful not to confuse effort with result or you will end up with a system that is producing effort, not result.

  • … leverage points — placeis in the system where a small change could lead to a large shift in behavior.
  • Counterintuitive — that is Forrester's word to describe complex systems. Leverage points, frequently are not intuitive. And if they are, we too often use them backward, systematically worsening wnatever problems we are trying to solve.
  • 12. Numbers - Constants and parameters such as subsidies, taxes, standards
  • 11. Buffers- The sizes of stabilizing stocks relative to their flows.
  • but buffers are usually physical entities, not easy to change
  • 10. Stock-and-Flow Structures - Physical systems and their nodes of intersections
  • 9. Delays - The lengths of time relative to the rates of system changes.
  • A delay in a feedback process is critical relatvite to rates of change in the stocks that the feedback loop is trying to control. Delays that are too short causes overreaction, 'chasing your tail,' oscillations amplified by the jumpiness of the response. Delays that are too long cause damped, sustained or exploding oscillations, depending on how much too long. Overlong delays in a system with a threshed, a danger point, a range past which irreversible damage can occur, cause overshoot and collapse.

    … delays are not often easily changeable. Things take as long as they take.

    Note: Stock of Me. What delays? For what impetus? What reaction times, response times?
  • 8. Balancing Feedback Loops - The strength of the feedbacks relative to the impacts they are trying to correct.
  • 7. Reinforcing Feedback Loops - The strength of the gain of driving loops
  • 6. Information Flows -The structure of who does and does not have access to information
  • 5. Rules - Incentives, punishments and constraints
  • 4. Self-Organization - The power to add, change, or evolve system structure.
  • Self-organization means changing any aspect of a system lower on this list- adding completely new physical structures, such as brains or wings or computers - adding new balancing or reinforcing loops, or new rules. The ability to self- organize is the strongest form of system resilience. A system that can evolve can survive almost any change, by changing itself.
  • Self-organization is basically a matter of an evolutionary raw material - a highly variable stock of information from which to select possible patterns - and a means for experimentation, for selecting and testing new patterns.
  • 3.Goals -The purpose or function of the system
  • John Kenneth Galbraith recognized that corporate goal — to engulf everything — long ago. It's the goal of cancer too. Actually, its the goal of every living population - and only a bad one when it isn't balanced by higher-level balancing feedback loops that never let an upstart power-loop-driven entity control the world.
  • 2. Paradigms - The mind-set out of which the system - its goals, structures, rules, delays, parameters - arises.
  • The shared idea in the minds of society, the great big unstated assumptions, constitute that society's paradigm, or deepest set of beliefs about how the world works.

    Money measures something real and has real meaning; therefore, people who are paid less are literally worth less. Growth is good. Nature is a stock of resources to be converted to human purposes. Evolution stopped with the emergence of Homo sapiens. One can 'own' land. Those are just a few of the paradigmatic assumptions of our current culture, all of which have utterly dumbfounded other cultures, who thought them not the least bit obvious.

  • … people who have managed to intervene in systems at the level of paradigm have hit a leverage point that totally transforms systems.
  • In a single individual it can happen in a millisecond. All it takes is a click in the mind, a falling of scales from the eyes, a new way of seeing. Whole societies are another matter - they resist challenges to their paradigms harder than they resist anything else.

    So how do you change paradigms? Thomas Kuhn, who wrote the seminal book about the great paradigm shifts of science, has a lot to say about that. You keep pointing at the anomalies and failures in the old paradigm. You keep speaking and acting, loudly and with assurance, from the new one. You insert people with the new paradigm in places of public visibility and power. You don't waste time with reactionaries; rather, you work with active change agents and with the vast middle ground of people who are open-minded.

    Systems modelers say that we change paradigms by building a model of the system, which takes us outside the system and forces us to see it whole.

  • 1. Transcending Paradigms
  • It is to 'get' at a gut level the paradigm that there are paradigms, and to see that that itself is a paradigm, and to regard that whole realization as devastatingly funny. It is to let go into not-knowiig, into what the Buddhists call enlightenment.
  • Surely, there is no power no control, no understanding; not even a reason for being, much less acting, embodied in the notion that there is no certainty in any worldview. But, in fact, everyone who has managed to entertain that idea, for a moment, for a lifeline lifetime, has found it to be the basis of for radical empowerment. If no paradigm is right, you can choose whatever one will help to achieve your purpose. If you have no idea where to get a purpose, you can listen to the universe.
  • You have to work hard at it, whether that means rigorously analyzing a system or rigorously casting off your own paradigms and throwing yourself into the humility of not-knowing. In the end, it seems that mastery has less to do with pushing leverage points than it does with strategically, profoundly, madly, letting go and dancing with the system.
  • Before you disturb the system in any way, watch how it behaves.

    Learn its history. Ask people who've been around a long time to tell you what has happened. If possible, find or make a time graph of actual data from the system - people's memories are not always reliable when it comes to timing.

  • Mental flexibility - the willingness to redraw boundaries, to notice that a system has shifted into a new mode, to see how to redesign structure, — is a necessity when you live in a world of flexible systems.
  • Thou shall not distort, delay or withhold information. You can drive a system crazy by muddying its information streams. You can make a system work better with surprising ease if you can give it more timely, more accurate, more complete information.
  • Information is power. Anyone interested in power grasps that idea very quickly. The media, the public relations people, the politicians, and advertisers who regulate much of the public flow of information have far more power than not people relize. They filter ard channel information
  • Our information streams are composed primarily of language. Our mental models are mostly verbal. Honoring information means above all avoiding language pollution - making the clearest possible use we can of language. Second, it means expanding our language so we can talk about complexity.
  • A society that talks incessantly about 'productivity' but that hardly understands, much less uses the word 'resilience' is going to become productive and not resilient.
    Note: talk more about what you believe in - your values
  • The first step in respecting language is keeping it as concrete, meaningful, and truthful as possible - part of the job of keeping information streams clear. The second step is to enlarge language and make it consistent with our enlarged understanding of systems.
  • Pay Attention to What is Important, Not Just what is Quantifiable

    Our culture obsessed with numbers, has given use the idea that what we can measure is more important than what we can't measure.

  • Pretend ng that something deesnt exist-if it's hard to quantify leads to faulty models. You've already seen the system trap that comes from setting goals around what is easily measured, rather than around what is important. So don't fallinto that trap. Human beings have been endowed with not only with the aibitity to count, but also with the ability to assess quality. Be a quality detector. Be a walking, noisy Geiger counter that registers the presence or absence of quality.

    If something is ugly, say so. If it is tacky, inappropriate, out of proportion unsustainable, morally degrading, ecologically impoverishing, or humanly demeaning, don't let it pass. Don't be stopped by the 'if you can't define it and measure it, I don't have to pay attention to it' ploy.

  • Go for the Good of the Whole

    Remember that hierarchies exist to serve the bottom layers, not the top. Don't maximize parts of the systems or subsystems while ignoring the whole.

  • Locate Responsibility in the system

    That's a guideline both for analysis and design. In analysis, it means looking for the ways the system creates its own behavioror. Do pay attention to the triggering events, the outside influences that bring forth one kid of behavior from the system rather than another.

    'Intrinsic responsibility' means that the system is designed to send feedback about the consequences of decision making directly and quickly and compellingly to the decision makers.

  • Stay Humble, - stay a Learner

    The thing to do, when you don't know, is not to bluff and not to freeze but to learn. The way you learn is by experiment — or, as Buckminister Fuller put it, by trial and error, error, error. In a world of complex systems, it is not appropriate to charge forward with rigid undeviating directives. 'Stay the course' is only a good idea if you're sure you're on course. Pretending you're in control even when you aren't is a recipe not only for mistakes, but for not learning from mistakes. What's appropriate when you're learning is small steps, constant monitoring, and a willingness to change course as you find out more about where it's leading.

  • Expand Time Horizons


    The longer the operant time horizon, the better the chances for survival.

  • Defy the Disciplines.

    In spite of what you majored in, or what the textbooks say, or what you think you're an expert at, follow a system wherever it leads. It will be sure to lead across traditional disciplinary lines. To understand that system, you will have to be able to learn from - while not being limited by - economists and chemists and psychologists and theologians. You will have to penetrate their jargons, integrate what they tell you, recognize what they can honestly see through their particular lenses, and discard the distortions that come from the narrowness and incompleteness of their lenses. They won't make it easy for you.

  • Expand the Boundary of caring
  • Don't Erode the Goal of Goodness

    The most damaging example of the systems archetype called 'drift to low performance' is the process by which modern industrial culture has eroded the goal of morality.

  • Book References from Thinking in Systems: A Primer