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Managers do not solve problems, they manage messes.
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.
the system’s response to these forces is characteristic of itself, and that response is seldom simple in the real world.
Because of feedback delays within complex systems, by the time a problem becomes apparent it may be unnecessarily difficult to solve.
According to the competitive exclusion principle, if a reinforcing feedback loop rewards the winner of a competition with the means to win further competitions, the result will be the elimination of all but a few competitors.
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.
A 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.
If information-based relationships are hard to see, functions or purposes are even harder.
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.
Changing interconnections in a system can change it dramatically.
Changes in function or purpose also can be drastic.
A change in purpose changes a system profoundly, even if every element and interconnection remains the same.
And conversely, because land, factories, and people are long-lived, slowly changing, physical elements of the system, there is a limit to the rate at which any leader can turn the direction of a nation.
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.
A stock is the memory of the history of changing flows within the system.
Systems thinkers use graphs of system behavior to understand trends over time, rather than focusing attention on individual events. We also use behavior-over-time graphs to learn whether the system is approaching a goal or a limit, and if so, how quickly.
The pattern—the shape of the variable line—is important, as are the points at which that line changes shape or direction.
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!
A stock takes time to change, because flows take time to flow.
The time lags that come from slowly changing stocks can cause problems in systems, but they also can be sources of stability.
The presence of stocks allows inflows and outflows to be independent of each other and temporarily out of balance with each other.
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.
That means system thinkers see the world as a collection of “feedback processes.”
… Everything we do as individuals, as an industry, or as a society is done in the context of an information-feedback system.
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.
The stock level feeds back through a chain of signals and actions to control itself.
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 goal-seeking or stability-seeking.
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.
The second kind of feedback loop is amplifying, reinforcing, self-multiplying, snowballing—a vicious or virtuous circle that can cause healthy growth or runaway destruction. It is called a reinforcing feedback loop, and will be noted with an R in the diagrams.
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.
A Stock with Two Competing Balancing Loops—a Thermostat
There’s an important general principle here, and also one specific to the thermostat structure. First the general one: The information delivered by a feedback loop can only affect future behavior; it can’t deliver the information, and so can’t have an impact fast enough to correct behavior that drove the current feedback.
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.
your mental model of the system needs to include all the important flows, or you will be surprised by the system’s behavior.
A stock-maintaining balancing feedback loop must have its goal set appropriately to compensate for draining or inflowing processes that affect that stock.
A Stock with One Reinforcing Loop and One Balancing Loop—Population and Industrial Economy
This behavior is an example of shifting dominance of feedback loops. Dominance is an important concept in systems thinking. When one loop dominates another, it has a stronger impact on behavior.
Complex behaviors of systems often arise as the relative strengths of feedback loops shift, causing first one loop and then another to dominate behavior.
Are the driving factors likely to unfold this way? (What are birth rate and death rate likely to do?) If they did, would the system react this way? (Do birth and death rates really cause the population stock to behave as we think it will?) What is driving the driving factors? (What affects birth rate? What affects death rate?)
System dynamics models explore possible futures and ask “what if” questions.
Systems with similar feedback structures produce similar dynamic behaviors.
