Why Systems Surprise Us: Misleading Events and Linear Thinking

• There are at least six reasons why systems are so surprising to us. These reasons can also be thought of as ways in which our mental models fail to take into account the complications of the real world. In other words, this is a warning list that shows where hidden snags lie.

Misleading Events

• We fool ourselves by seeing the world as a series of events.
• For instance, the daily news tells of elections, battles, political agreements, disasters, stock market booms and busts. But events are merely moment by moment outputs from the system.
• Taking in the world as a series of events can be constantly surprising because this way of seeing the world has almost no predictive or explanatory value. Like the tip of an iceberg rising above the water, events are the most visible aspect of a larger complex. However, they’re not always the most important.
• We’re less likely to be surprised if we see how events accumulate into dynamic patterns of behavior. For instance, the basketball team is on a winning streak. Or the Dow Jones Industrial Average has been trending up for two years.
• The behavior of a system is its performance over time. This performance could be growth, stagnation, decline, oscillation, randomness, or evolution.
• If we did a better job of putting events into historical context, we’d have better behavior-level understanding, which is deeper than event-level understanding.
• When systems thinkers encounter a problem, the first thing they do is look for data or time graphs that show the history of the system. That’s because long-term behavior provides clues to the underlying system structure. And structure is the key to understanding not only what is happening, but why.

Determining a System’s Behavior

• The structure of a system is its interconnecting stocks, flows, and feedback loops. This structure determines the behaviors that are possible in a system. In other words, system structure is the source of system behavior. And system behavior reveals itself as a series of events over time.
• For instance, a goal-seeking feedback loop approaches or holds a dynamic equilibrium. An example of this is a cup of hot tea cooling down until it reaches room temperature.
• A reinforcing feedback loop generates exponential growth. An example of this is a savings account in which the more money you have in the account, the more interest you earn. And this interest is added to the money that’s already in the account, where it earns even more interest.
• A goal-seeking feedback loop and reinforcing feedback loop linked together are capable of growth, decay, or equilibrium. An example of this is an economy that grows by reinvesting its output to make new physical capital, and declines as physical capital is drained by depreciation.
• If the feedback loops also contain delays, this may produce oscillations. An example of this is a car dealer who tries to keep a constant level of inventory while purchases from customers are unpredictable, and deliveries from suppliers are sometimes delayed.
• Systems thinking goes back and forth constantly between structure, or the stocks, flows, and feedback loops, and the behavior, or the time graphs.

Key Connections For Systems Thinkers

• Systems thinkers strive to understand the connections between three things:
  1. Events, such as the hand releasing the Slinky,
  2. Behaviors, such as the resulting oscillations, and
  3. Structure, such as the mechanical characteristics of the Slinky’s helical coil.
• Much analysis in the world goes no deeper than events. However, these events give you no ability to predict what will happen tomorrow. On top of this, they give you no ability to change the behavior of the system.
• Economic analysis may go one level deeper, to behavior over time. For instance, econometric models strive to find the statistical links among trends in variables such as income, savings, and interest rates.
• But even though these behavior-based models are more useful than event-based ones, they still have two basic problems.
• First, they usually overemphasize system flows and underemphasize stocks. Economists follow the behavior of flows because that’s usually where the interesting variations and rapid changes show up. However, without seeing how stocks affect their related flows through feedback processes, you can’t understand the dynamics of economic systems or the reasons for their behavior.
• Second, in trying to find links that relate other flows to each other, these analysts are searching for something that doesn’t exist. There’s no reason to expect any flow to bear a stable relationship to any other flow. Flows go up and down in all sorts of combinations, not in response to other flows, but to stocks.
• Again, one reason why systems surprise us is that we’re too fascinated by the events they generate. On the other hand, we pay too little attention to their history. And, we’re not skilled enough to see in their history clues to the structures from which the behavior and events flow.

Linear Thinking in a Nonlinear World

• Many times, we’re not very skilled in understanding the nature of relationships.
• A linear relationship between two elements in a system can be drawn with a straight line. It’s a relationship with constant proportions.
• For instance, if you put 10 pounds of fertilizer on your field, your yield will go up by 2 bushels. If you put 20 pounds, your yield will increase by 4 bushels. And if you put 30 pounds, you’ll get an increase of 6 bushels.
• On the flip side, a nonlinear relationship is one in which the cause doesn’t produce a proportional effect. In other words, the relationship between cause and effect can only be drawn with curves or wiggles, not a straight line.
• Here, if you put 100 pounds of fertilizer on, your yield will increase by 10 bushels. But if you put on 200, your yield won’t go up at all. And if you put 300, your yield will actually go down. Why? Because you’ve damaged your soil with too much of a good thing.
• The world’s full of nonlinearities. And that’s why it often surprises our linear-thinking minds.
• If we’ve found that a small push produces a small response, we think that twice as big a push will produce twice as big a response. But in a nonlinear system, twice the push could produce one-sixth the response, or the response squared, or no response at all.
• Here are two other examples of nonlinearity:
  1. As the flow of traffic on a highway increases, car speed decreases only slightly over a large range of car density. But eventually, small further increases in density produce a rapid drop in speed. And when the number of cars builds up to a certain point, it can result in a traffic jam, and car speed drops to zero.
  2. A little tasteful advertising can spark interest in a product. But a lot of blatant advertising can cause disgust for the exact same product.

Why Nonlinearities Surprise Us

• So, nonlinearities produce surprises because they counter the reasonable expectation that if a little bit of a cure did a little good, then a lot of it would do a lot of good. Or alternatively, if a little destructive action caused only a tolerable amount of harm, then more of that same destruction will cause only a bit more harm. Reasonable expectations like these in a nonlinear world produce classic mistakes.
• But nonlinearities are important not only because they confuse our expectations about the link between action and response. They’re even more important because they change the relative strengths of feedback loops. In other words, they can flip a system from one mode of behavior to another.
• Nonlinearities are the main cause of the shifting dominance that characterizes several types of systems. Take, for instance, the swing between the exponential growth caused by a dominant reinforcing loop and the decline caused by a suddenly dominating balancing loop. A renewable stock that is ultimately constrained by a nonrenewable stock is an example of this.

This is part nine of the summary of Thinking in Systems by Donella Meadows. If you’d like to review, here are parts one, two, three, four, five, six, seven, and eight of the summary.

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