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So, what is a system? A system is a set of things—people, cells, molecules, or whatever—interconnected in such a way that they produce their own pattern of behavior over time.
Because of feedback delays within complex systems, by the time a problem becomes apparent it may be unnecessarily difficult to solve.
A diverse system with multiple pathways and redundancies is more stable and less vulnerable to external shock than a uniform system with little diversity.
The behavior of a system cannot be known just by knowing the elements of which the system is made.
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.
system is more than the sum of its parts. It may exhibit adaptive, dynamic, goal-seeking, self-preserving, and sometimes evolutionary behavior.
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.
The least obvious part of the system, its function or purpose, is often the most crucial determinant of the system’s behavior.
A change in purpose changes a system profoundly, even if every element and interconnection remains the same.
unless changing an element also results in changing relationships or purpose.
stock is the memory of the history of changing flows within the system.
dynamic equilibrium—its level does not change, although water is continuously flowing through it.
A stock can be increased by decreasing its outflow rate as well as by increasing its inflow rate. There’s more than one way to fill a bathtub!
Stocks generally change slowly, even when the flows into or out of them change suddenly. Therefore, stocks act as delays or buffers or shock absorbers in systems.
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.
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.
Balancing feedback loops are equilibrating or goal-seeking structures in systems and are both sources of stability and sources of resistance to change.
Reinforcing feedback loops are self-enhancing, leading to exponential growth or to runaway collapses over time. They are found whenever a stock has the capacity to reinforce or reproduce itself.
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 behavior that drove the current feedback. Even nonphysical information takes time to feedback into the system.
A stock-maintaining balancing feedback loop must have its goal set appropriately to compensate for draining or inflowing processes that affect that stock. Otherwise, the feedback process will fall short of or exceed the target for the stock.
Complex behaviors of systems often arise as the relative strengths of feedback loops shift, causing first one loop and then another to dominate behavior.
Dynamic systems studies usually are not designed to predict what will happen. Rather, they’re designed to explore what would happen,
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?
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 pervasive 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 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. And we are aware that some delays can be powerful policy levers.
In physical, 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.
Nonrenewable 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 resources 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 eventually be driven below a critical threshold and become, for all practical purposes, nonrenewable.
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.
There are always limits to resilience.
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, diversify, and complexify. Even complex forms of self-organization may arise from relatively simple organizing rules—or may not.
When a subsystem’s goals dominate at the expense of the total system’s goals, the resulting behavior is called suboptimization
Hierarchical systems evolve from the bottom up. The purpose of the upper layers of the hierarchy is to serve the purposes of the lower layers.
Resilience, self-organization, and hierarchy are three of the reasons dynamic systems can work so well.
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.
long-term behavior provides clues to the underlying system structure. And structure is the key to understanding not just what is happening, but why.
System structure is the source of system behavior. System behavior reveals itself as a series of events over time.
We are too fascinated by the events they generate. We pay too little attention to their history. And we are insufficiently skilled at seeing in their history clues to the structures from which behavior and events flow.
Many relationships in systems are nonlinear. Their relative strengths shift in disproportionate amounts as the stocks in the system shift.
There are no separate systems. The world is a continuum. Where to draw a boundary around a system depends on the purpose of the discussion—the questions we want to ask.
At any given time, the input that is most important to a system is the one that is most limiting.
growth itself depletes or enhances limits and therefore changes what is limiting.
