Excerpts from Thinking in Systems, A Primer by Donella Meadows
“People who are raised in the industrial world and who get enthused about systems thinking are likely to make a terrible mistake. They are likely to assume that here, in systems analysis, in interconnection and complication, in the power of the computer, here at last, is the key to prediction and control. This mistake is likely because the mindset of the industrial world assumes that there is a key to prediction and control.”
“Social systems are the external manifestations of cultural thinking patterns and of profound human needs, emotions, strengths, and weaknesses. Changing them is not as simple as saying “now all change,” or of trusting that he who knows the good shall do the good.”
“We ran into another problem. Our systems insights helped us understand many things we hadn’t understood before, but they didn’t help us understand everything. In fact, they raised at least as many questions as they answered. Like all the other lenses humanity has developed with which to peer into macrocosms and microcosms, this one too revealed wondrous new things, many of which were wondrous new mysteries.”
“Self-organizing, nonlinear, feedback systems are inherently unpredictable. They are not controllable. They are understandable only in the most general way.”
“The idea of making a complex system do just what you want it to do can be achieved only temporarily, at best. We can never fully understand our world, not in the way our reductionist science
has led us to expect.”
“Systems thinking leads to another conclusion, however, waiting, shining, obvious, as soon as we stop being blinded by the illusion of control. It says that there is plenty to do, of a different sort of “doing.” The future can’t be predicted, but it can be envisioned and brought lovingly into being. Systems can’t be controlled, but they can be designed and redesigned. We can’t surge forward with certainty into a world of no surprises, but we can expect surprises and learn from them and even profit from them. We can’t impose our will on a system. We can listen to what the system tells us, and discover how its properties and our values can work together to bring forth something much better than could ever be produced by our will alone.”
“We can’t control systems or figure them out. But we can dance with them! …. Living successfully in a world of systems requires more of us than our ability to calculate. It requires our full humanity—our rationality, our ability to sort out truth from falsehood, our intuition, our compassion, our vision, and our morality.”
” Living successfully in a world of systems requires more of us than our ability to calculate. It requires our full humanity—our rationality, our ability to sort out truth from falsehood, our intuition, our compassion, our vision, and our morality:
Get the Beat of the System – Before you disturb the system in any way, watch how it behaves.
Expose Your Mental Models to the Light of Day – We have to put every one of our assumptions about the system out where others (and we ourselves) can see them.
Honor, Respect, and Distribute Information – You’ve seen how information holds systems together and how delayed, biased, scattered, or missing information can make feedback loops malfunction. Decision makers can’t respond to information they don’t have, can’t respond accurately to information that is inaccurate, and can’t respond in a timely way to information that is late. I would guess that most of what goes wrong in systems goes wrong because of biased, late, or missing information.
Use Language with Care and Enrich It with Systems Concepts – Our information streams are composed primarily of language. Our mental models are mostly verbal. Honoring information means above all avoiding language pollution—making the cleanest possible use we can of language. Second, it means expanding our language so we can talk about complexity.
Pay Attention to What Is Important, Not Just What Is Quantifiable – Our culture, obsessed with numbers, has given us the idea that what we can measure is more important than what we can’t measure. Think about that for a minute. It means that we make quantity more important than quality. If quantity forms the goals of our feedback loops, if quantity is the center of our attention and language and institutions, if we motivate ourselves, rate ourselves, and reward ourselves on our ability to produce quantity, then quantity will be the result. You can look around and make up your own mind about whether quantity or quality is the outstanding characteristic of the world in which you live.
Make Feedback Policies for Feedback Systems – A dynamic, self-adjusting feedback system cannot be governed by a static, unbending policy. It’s easier, more effective, and usually much cheaper to design policies that change depending on the state of the system. Especially where there are great uncertainties, the best policies not only contain feedback loops, but meta-feedback loops—loops that alter, correct, and expand loops. These are policies that design learning into the management process.
Go for the Good of the Whole – Remember that hierarchies exist to serve the bottom layers, not the top. Don’t maximize parts of systems or subsystems while ignoring the whole. Don’t, as Kenneth Boulding once said, go to great trouble to optimize something that never should be done at all. Aim to enhance total systems properties, such as growth, stability, diversity, resilience, and sustainability
—whether they are easily measured or not.
Listen to the Wisdom of the System – Aid and encourage the forces and structures that help the system run itself. Notice how many of those forces and structures are at the bottom of the hierarchy. Don’t be an unthinking intervenor and destroy the system’s own self-maintenance capacities. Before you charge in to make things better, pay attention to the value of what’s already there.
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 behavior. Do pay attention to the triggering events, the outside influences that bring forth one kind of behavior from the system rather than another. Sometimes those outside events can be controlled (as in reducing the pathogens in drinking water to keep down incidences of infectious disease). But sometimes they can’t. And sometimes blaming or trying to control the outside influence blinds one to the easier task of increasing responsibility within the system.
Stay Humble—Stay a Learner – Systems thinking has taught me to trust my intuition more and my figuring-out rationality less, to lean on both as much as I can, but still to be prepared for surprises. Working with systems, on the computer, in nature, among people, in organizations, constantly reminds me of how incomplete my mental models are, how complex the world is, and how much I don’t know. 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 Buckminster 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.
Celebrate Complexity – Let’s face it, the universe is messy. It is nonlinear, turbulent, and dynamic. It spends its time in transient behavior on its way to somewhere else, not in mathematically neat equilibria. It self-organizes and evolves. It creates diversity and uniformity. That’s what makes the world interesting, that’s what makes it beautiful, and that’s what makes it work. There’s something within the human mind that is attracted to straight lines and not curves, to whole numbers and not fractions, to uniformity and not diversity, and to certainties and not mystery. But there is something else within us that has the opposite set of tendencies, since we ourselves evolved out of and are shaped by and structured as complex feedback systems.
Expand Time Horizons – The official time horizon of industrial society doesn’t extend beyond what will happen after the next election or beyond the payback period of current investments.
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. Seeing systems whole requires more than being “interdisciplinary,” if that word means, as it usually does, putting together people from different disciplines and letting them talk past each other.
Expand the Boundary of Caring – Living successfully in a world of complex systems means expanding not only time horizons and thought horizons; above all, it means expanding the horizons 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. The workings of the trap have been classic, and awful to behold.