More on this book
Community
Kindle Notes & Highlights
Today, it is widely accepted that systems thinking is a critical tool in addressing the many environmental, political, social, and economic challenges we face around the world.
If so, I think that this book can help. Although one can find dozens of titles on “systems modeling” and “systems thinking,” there remains a clear need for an approachable and inspiring book about systems and us—why we find them at times so baffling and how we can better learn to manage and redesign them.
While traveling to meetings and conferences during this time, Dana read the International Herald Tribune and during a single week found many examples of systems in need of better management or complete redesign.
Once you start to see the events of the day as parts of trends, and those trends as symptoms of underlying system structure, you will be able to consider new ways to manage and new ways to live in a world of complex systems.
If a factory is torn down but the rationality which produced it is left standing, then that rationality will simply produce another factory. If a revolution destroys a government, but the systematic patterns of thought that produced that government are left intact, then those patterns will repeat themselves.… There’s so much talk about the system. And so little understanding. —ROBERT PIRSIG, Zen and the Art of Motorcycle Maintenance
Managers are not confronted with problems that are independent of each other, but with dynamic situations that consist of complex systems of changing problems that interact with each other. I call such situations messes.… Managers do not solve problems, they manage messes. —RUSSELL ACKOFF,1 operations theorist
Once we see the relationship between structure and behavior, we can begin to understand how systems work, what makes them produce poor results, and how to shift them into better behavior patterns. As our world continues to change rapidly and become more complex, systems thinking will help us manage, adapt, and see the wide range of choices we have before us. It is a way of thinking that gives us the freedom to identify root causes of problems and see new opportunities.
Hunger, poverty, environmental degradation, economic instability, unemployment, chronic disease, drug addiction, and war, for example, persist in spite of the analytical ability and technical brilliance that have been directed toward eradicating them. No one deliberately creates those problems, no one wants them to persist, but they persist nonetheless. That is because they are intrinsically systems problems—undesirable behaviors characteristic of the system structures that produce them.
They will yield only as we reclaim our intuition, stop casting blame, see the system as the source of its own problems, and find the courage and wisdom to restructure it.
Pictures work for this language better than words, because you can see all the parts of a picture at once.
the Appendix provides ways to dig deeper into the subject with a glossary, a bibliography of systems thinking resources, a summary list of systems principles, and equations for the models described in Part One.
You can see some things through the lens of the human eye, other things through the lens of a microscope, others through the lens of a telescope, and still others through the lens of systems theory. Everything seen through each kind of lens is actually there. Each way of seeing allows our knowledge of the wondrous world in which we live to become a little more complete.
The behavior of a system cannot be known just by knowing the elements of which the system is made.
I have yet to see any problem, however complicated, which, when looked at in the right way, did not become still more complicated. —POUL ANDERSON
A system* is an interconnected set of elements that is coherently organized in a way that achieves something. If you look at that definition closely for a minute, you can see that a system must consist of three kinds of things: elements, interconnections, and a function or purpose.
Is there anything that is not a system? Yes—a conglomeration without any particular interconnections or function. Sand scattered on a road by happenstance is not, itself, a system. You can add sand or take away sand and you still have just sand on the road. Arbitrarily add or take away football players, or pieces of your digestive system, and you quickly no longer have the same system.
A system is more than the sum of its parts. It may exhibit adaptive, dynamic, goal-seeking, self-preserving, and sometimes evolutionary behavior.
Once you start listing the elements of a system, there is almost no end to the process. You can divide elements into sub-elements and then sub-sub-elements. Pretty soon you lose sight of the system. As the saying goes, you can’t see the forest for the trees.
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.
Purposes are deduced from behavior, not from rhetoric or stated goals.
An important function of almost every system is to ensure its own perpetuation.
Keeping sub-purposes and overall system purposes in harmony is an essential function of successful systems. I’ll get back to this point later when we come to hierarchies.
A change in purpose changes a system profoundly, even if every element and interconnection remains the same.
To ask whether elements, interconnections, or purposes are most important in a system is to ask an unsystemic question. All are essential. All interact. All have their roles.
Puntos a investigar
Information contained in nature … allows us a partial reconstruction of the past.… The development of the meanders in a river, the increasing complexity of the earth’s crust … are information-storing devices in the same manner that genetic systems are.… Storing information means increasing the complexity of the mechanism. —Ramon Margalef2
A stock is the foundation of any system. Stocks are the elements of the system that you can see, feel, count, or measure at any given time.
Stocks change over time through the actions of a flow. Flows are filling and draining, births and deaths, purchases and sales, growth and decay, deposits and withdrawals, successes and failures. A stock, then, is the present memory of the history of changing flows within the system.
You can adjust the drain or faucet of a bathtub—the flows—abruptly, but it is much more difficult to change the level of water—the stock—quickly. Water can’t run out the drain instantly, even if you open the drain all the way. The tub can’t fill up immediately, even with the inflow faucet on full blast. A stock takes time to change, because flows take time to flow. That’s a vital point, a key to understanding why systems behave as they do. Stocks usually change slowly.
The time lags imposed by stocks allow room to maneuver, to experiment, and to revise policies that aren’t working.
The presence of stocks allows inflows and outflows to be independent of each other 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.
That means system thinkers see the world as a collection of “feedback processes.”
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. It is the consistent behavior pattern over a long period of time that is the first hint of the existence of a feedback loop.
The world is full of goal-seeking feedback loops. Balancing feedback loops are equilibrating or goal-seeking structures in systems and are both sources of stability and sources of resistance to change.
When one loop dominates another, it has a stronger impact on behavior. Because systems often have several competing feedback loops operating simultaneously, those loops that dominate the system will determine the behavior.
Usar como argumento
A systems analysis can test a number of scenarios to see what happens if the driving factors do different things. That’s usually one purpose of a systems analysis. But you have to be the judge of which scenario, if any, should be taken seriously as a future that might really be possible.
QUESTIONS FOR TESTING THE VALUE OF A MODEL Are the driving factors likely to unfold this way? If they did, would the system react this way? What is driving the driving factors?
Is there anything about the size of the population, for instance, that might feed back to influence fertility or mortality? Do other factors—economics, the environment, social trends—influence fertility and mortality? Does the size of the population affect those economic and environmental and social factors?
One of the central insights of systems theory, as central as the observation that systems largely cause their own behavior, is that systems with similar feedback structures produce similar dynamic behaviors, even if the outward appearance of these systems is completely dissimilar.
And then the well-intentioned fixer pulls the lever in the wrong direction! This is just one example of how we can be surprised by the counterintuitive behavior of systems when we start trying to change them.
Economies are extremely complex systems; they are full of balancing feedback loops with delays, and they are inherently oscillatory.
But any real physical entity is always surrounded by and exchanging things with its environment. A corporation needs a constant supply of energy and materials and workers and managers and customers. A growing corn crop needs water and nutrients and protection from pests. A population needs food and water and living space, and if it’s a human population, it needs jobs and education and health care and a multitude of other things. Any entity that is using energy and processing materials needs a place to put its wastes, or a process to carry its wastes away.
Therefore, any physical, growing system is going to run into some kind of constraint, sooner or later.
The real choice in the management of a nonrenewable resource is whether to get rich very fast or to get less rich but stay that way longer.
If the land mechanism as a whole is good, then every part is good, whether we understand it or not. If the biota, in the course of aeons, has built something we like but do not understand, then who but a fool would discard seemingly useless parts? To keep every cog and wheel is the first precaution of intelligent tinkering. —Aldo Leopold,1 forester
Why do systems work so well? Consider the properties of highly functional systems—machines or human communities or ecosystems—which are familiar to you. Chances are good that you may have observed one of three characteristics: resilience, self-organization, or hierarchy.
Resilience arises from a rich structure of many feedback loops that can work in different ways to restore a system even after a large perturbation.
Hundreds of years of intensive management of the forests of Europe gradually have replaced native ecosystems with single-age, single-species plantations, often of nonnative trees. These forests are designed to yield wood and pulp at a high rate indefinitely. However, without multiple species interacting with each other and drawing and returning varying combinations of nutrients from the soil, these forests have lost their resilience. They seem to be especially vulnerable to a new form of insult: industrial air pollution.
I think of resilience as a plateau upon which the system can play, performing its normal functions in safety. A resilient system has a big plateau, a lot of space over which it can wander, with gentle, elastic walls that will bounce it back, if it comes near a dangerous edge. As a system loses its resilience, its plateau shrinks, and its protective walls become lower and more rigid, until the system is operating on a knife-edge, likely to fall off in one direction or another whenever it makes a move.
Computers were used to model mechanistic, “deterministic” systems, not evolutionary ones, because it was suspected, without much thought, that evolutionary systems were simply not understandable. New discoveries, however, suggest that just a few simple organizing principles can lead to wildly diverse self-organizing structures.
