Most natural systems recover well when buffeted by winds of change, even when they come fast and from many directions. But then when we try to control the results in the short term or define a too narrow range of performance, we can defeat the very mechanisms that allow them to behave so well.
Resilience brings the system back to center.
Oscillations, or conditions swinging back and forth around a central point, are often normal, both in the short-term and the long term. A healthy system has a collection of balancing loops that operate in different ways across these different lengths of time that bring the behavior back to that central point.
If we look at the system in too short a time frame or if the swings in behavior are too extreme for our expectations, then it sure doesn’t feel like it is behaving well! Then we might try to keep the recoveries from occurring, but without resilience the system would really take off in a direction we had not protected.
Self-organization allows a system to become more complex on its own.
Snowflakes grow and communities come together by following a few simple rules and relationships. But these simple rules make possible a larger, more complex system that can meet a challenge or just a slightly changed situation.
However, this can be disconcerting to us, because there’s no way to tell from the initial state and the rules (which we don’t always know) exactly what the end result is going to be. This is how we come up with snowflakes that all look different. If we try to say that only certain snowflakes are an acceptable shape then we keep the system from being able to reach its full potential.
A hierarchy of subsystems keeps effort from being repeated.
Most systems are layers of systems within systems, like cells in organs in our bodies. Because different functions can be assigned to different systems, like the lungs or the liver, then the overall system functions more effectively. In addition, two subsystems in different areas often don’t affect each other directly.
Hierarchy is also why the more usual practice of studying things by breaking them down into their parts works. We just can’t forget that the parts interact when they are in together.
This post is the fifth in a series that discusses the concepts in Thinking in Systems by Donella Meadows. It summarized chapter 3 which is titled rather more optimistically “Why Systems Work So Well.” I found the comments about short-sightedness that she embedded into her stories to be as important as the three characteristics themselves and tried to include a sense of them here. Also read my other posts: