Thinking in Systems - Johannes Holmberg

I like the way the book provided me with a framework for how to think about systems. I didn’t really have a good mental map about the individual components that makes up a system, and the parts that affects the status of the system. This book provided me that. Enjoyable and informative throughout.

#Stocks and flows in systems

A system have something called a stock, and it’s the foundation for any system. A stock is an accumulation of material or information that has built up over time. Think of the water in a bathtub, or the books in a bookstore, or the money in a bank.

A stock is the memory of the history of changing flows within the system.

Stocks change over time through the actions of a flow. Flows are filling and draining, purchases and sales, growth and decay. A stock is then the present memory of the history of changing flows within the system. Remember that a stock takes time to change, because flows take time to flow. It takes a long time for populations to grow or stop growing. People often underestimate the inherent momentum of a stock.

Stocks generally change slowly, even when the flows into or out of a stock change suddenly. Stocks act as delays or buffers, or shock absorbers in systems.

The presence of stocks in systems allows inflows and outflows to be independent of each other and temporarily out of balance with each other.

The world is a collection of stocks along with the mechanisms for regulating the levels in the stocks by manipulating flows.

#Feedback loops in systems

Stocks are controlled by feedback loops. A feedback loop is a mechanism that can create consistent behavior pattern over a long period of time. It’s a bit like “course correcting” your system.

A feedback loop offers a closed chain of causal connections from a stock, through a set of decisions or rules or physical laws or actions that changes the stock dependent on its level.

There are only a few ways a population system could behave, and these depend on what happens to the “driving” variables, fertility and mortality. These are the only ones possible for a simple system of one reinforcing and one balancing loop.

A stock governed by linked reinforcing reinforcing loops and balancing loops will grow exponentially if the reinforcing loop dominates the balancing one. It will die off if the balancing loop dominates the reinforcing one.

#Balancing loops

A stabilizing, goal-seeking, regulating feedback loop, also know as a “negative feedback loop” because it opposes, or reverses, whatever direction of change is imposed on the system.

A balancing loop has the goal to stabilize the system.
A balancing feedback loop is goal-seeking or stability-seeking. It tries to keep a stock at a given value or within a range of values.
It’s an adjustment mechanism for the system.

Remember this: Every balancing feedback loop has its breakdown point, where other loops pull the stock away from its goal more strongly than it can pull back.

#Reinforcing loops

An amplifying or enhancing feedback loop, also known as a “positive feedback loop” because it reinforces the direction of change. These are vicious cycles and virtuous circles. A reinforcing feedback loop enhances whatever direction of change is imposed on it.
The more prices go up, the more wages have to go up if people are to maintain their standards of living. The more wages go up, the more prices have to go up to maintain profits. This means that wages have to go up again, so prices go up again.
The more I practice piano, the more pleasure I get from the sound, and so the more I play the piano, which gives me more practice.
Reinforcing loops are found wherever a system element has the ability to reproduce itself or to grow as a constant fraction of itself. Think about populations or economies.

#Influence

Instead of seeing only how A causes B, you’ll begin to wonder how B may also influence A — and how A might reinforce or reverse itself. When you hear in the nightly news that the Federal Reserve Bank has done something to control the economy, you’ll also see that the economy must have done something to affect the Federal Reserve Bank.

#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?

The central question of economic development is how to keep the reinforcing loop of capital accumulation from growing more slowly than the reinforcing loop of population growth — so that people are getting richer instead of poorer.

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.

#Delays

Changing the delays in a system can make it much easier or much harder to manage. Always be alert to see where delays occur in systems, how long they are, whether they are delays in information streams or in physical processes.

We can’t begin to understand the dynamic behavior of systems unless we know where and how long the delays are.

Economies are extremely complex systems; they are full of balancing feedback loops with delays, and they are inherently oscillatory.
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.

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.

#How do systems work

A system is a set of things—people, cells, molecules, or any other thing—interconnected in such a way that they produce their own pattern of behavior over time. Common structures that produce characteristic behaviors are called archetypes in systems thinking. A system could be described as an interconnected set of elements that’s coherently organized in a way that achieves something: a purpose.

What can we do to restructure the systems we live within?

#Essential parts of a system

A system consists of three things:

Elements
Interconnections
A function or purpose

Remember that elements doesn’t have to be physical things. It could also be intangibles, like pride, academic prowess, etc. Changing the purpose of the system changes the whole system profoundly, even if every element and interconnections remains the same.

#Systems and us

Consider the properties of highly functional systems, machines or human communities or ecosystems. Chances are good that you may have observed one of three characteristics: resilience, self-organization, or hierarchy. These are three of the reasons dynamic systems work so well.

#Resilience in systems

Resilience is a measure of a system’s ability to survive and persist within a variable environment. The opposite of resilience is brittleness or rigidity.

Resilience is the ability of a system to recover from perturbation—the ability to restore or repair or bounce back after a change due to an outside force.

Remember that there are always limits to resilience.

Example: 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.

#Self-organization in systems

The capacity of a system to make its own structure more complex is called self-organization. You see self-organization in a small, mechanistic way whenever you see a snowflake, or ice feathers on a poorly insulated window, or a supersaturated solution suddenly forming a garden of crystals.

Here are some other examples of simple organizing rules that have led to self-organizing systems of great complexity:

All of life, from viruses to redwood trees, from amoebas to elephants, is based on the basic organizing rules encapsulated in the chemistry of DNA, RNA, and protein molecules.
The agricultural revolution and all that followed started with the simple, shocking ideas that people could stay settled in one place, own land, select and cultivate crops.
“God created the universe with the earth at its center, the land with the castle at its center, and humanity with the Church at its center”—the organizing principle for the elaborate social and physical structures of Europe in the Middle Ages.
“God and morality are outmoded ideas; people should be objective and scientific, should own and multiply the means of production, and should treat people and nature as instrumental inputs to production”—the organizing principles of the Industrial Revolution.

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.

#System hierarchy

In the process of creating new structures and increasing complexity, one thing that a self-organizing system often generates is hierarchy.
A cell in your liver is a subsystem of an organ, which is a subsystem of you as an organism, and you are a subsystem of a family, an athletic team, a musical group, and so forth.
If subsystems can largely take care of themselves, regulate themselves, maintain themselves, and yet serve the needs of the larger system, while the larger system coordinates and enhances the functioning of the subsystems, a stable, resilient, and efficient structure results.
Complex systems can evolve from simple systems only if there are stable intermediate forms. The resulting complex forms will naturally be hierarchic.
Hierarchies are brilliant systems inventions, not only because they give a system stability and resilience, but also because they reduce the amount of information that any part of the system has to keep track of. In hierarchical systems relationships within each subsystem are denser and stronger than relationships between subsystems. Everything is still connected to everything else, but not equally strongly.
The original purpose of a hierarchy is always to help its originating subsystems do their jobs better.
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.

#Why systems surprise us

#Beguiling events

The daily news tells of elections, battles, political agreements, disasters, stock market booms or busts. Much of our ordinary conversation is about specific happenings at specific times and places. Remember that there is a difference between event-level analysis and behavior-level analysis.

The behavior of a system is its performance over time—its growth, stagnation, decline, oscillation, randomness, or evolution. If the news did a better job of putting events into historical context, we would have better behavior-level understanding, which is deeper than event-level understanding.

We are too fascinated by the events that systems 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.

#The limiting factor

A patch of growing grain needs:

sunlight
air
water
nitrogen
phosphorus
potassium
dozens of minor nutrients
a friable soil and the services of a microbial soil community
some system to control weeds and pests
protection from the wastes of the industrial manufacturer

It was with regard to grain that Justus von Liebig came up with his famous “law of the minimum.” It doesn’t matter how much nitrogen is available to the grain, he said, if what’s short is phosphorus. It does no good to pour on more phosphorus, if the problem is low potassium.

At any given time, the input that is most important to a system is the one that is most limiting.

For any physical entity in a finite environment, perpetual growth is impossible. Ultimately, the choice is not to grow forever but to decide what limits to live within.

#Bounded rationality

Bounded rationality means that people make quite reasonable decisions based on the information they have. But they don’t have perfect information, especially about more distant parts of the system.
Fishermen don’t know how many fish there are, much less how many fish will be caught by other fishermen that same day.
We live in an exaggerated present—we pay too much attention to recent experience and too little attention to the past, focusing on current events rather than long-term behavior.

#System traps

Some systems are perverse. These are the systems that are structured in ways that produce truly problematic behavior. Many of these systems are common.

#Policy Resistance—fixes that fail

Say you’re trying to change the stock of something, but there are other actors all with their own inherent goals, then a step toward changing it may in fact be counterproductive. And things will remain at status quo.
An alternative to overpowering policy resistance is: let go. Give up on your ineffective policies. If you calm down, those who are pulling against you will calm down too.
Calming down may provide the opportunity to look more closely at the feedbacks within the system, to understand the bounded rationality behind them, and to find a way to meet the goals of the participants in the system while moving the state of the system in a better direction.
For example, a nation wanting to increase its birth rate might ask why families are having few children and discover that it isn’t because they don’t like children. Perhaps they haven’t the resources, the living space, the time, or the security to have more.

#The trap

When various actors try to pull a system stock toward various goals, the result can be policy resistance. Any new policy, especially if it’s effective, just pulls the stock farther from the goals of other actors and produces additional resistance, with a result that no one likes, but that everyone expends considerable effort in maintaining.

#The way out

Let go. Bring in all the actors and use the energy formerly expended on resistance to seek out mutually satisfactory ways for all goals to be realized—or redefinitions of larger and more important goals that everyone can pull toward together.

#The tragedy of the commons

The tragedy of the commons arises from missing (or too long delayed) feedback from the resource to the growth of the users of that resource. The more users there are, the more resource is used.

The structure of a commons system makes selfish behavior much more convenient, and profitable, than behavior that is responsible to the whole community and to the future.

There are three ways to avoid the tragedy of the commons:

Educate and exhort. Help people to see the consequences of unrestrained use of the commons. Appeal to their morality. Persuade them to be temperate. Threaten transgressors with social disapproval or eternal hellfire.
Privatize the commons. Divide it up, so that each person reaps the consequences of his or her own actions. If some people lack the self-control to stay below the carrying capacity of their own private resource, those people will harm only themselves and not others.
Regulate the commons. “Mutual coercion, mutually agreed upon.” Regulation can take many forms, from outright bans on certain behaviors to quotas, permits, taxes, incentives. To be effective, regulation must be enforced by policing and penalties.

#The trap

When there is a commonly shared resource, every user benefits directly from its use, but shares the costs of its abuse with everyone else. Therefore, there is very weak feedback from the condition of the resource to the decisions of the resource users. The consequence is overuse of the resource, eroding it until it becomes unavailable to anyone.

#The way out

Educate and exhort the users, so they understand the consequences of abusing the resource. And also restore or strengthen the missing feedback link, either by privatizing the resource so each user feels the direct consequences of its abuse or (since many resources cannot be privatized) by regulating the access of all users to the resource.

#Drift to low performance

Some systems not only resist policy and stay in a normal bad state, they keep getting worse. One name for this archetype is “drift to low performance.”

The actor tends to believe bad news more than good news. As actual performance varies, the best results are dismissed as aberrations, the worst results stay in the memory. The actor thinks things are worse than they really are.

The lower the desired state, the less discrepancy, and the less corrective action is taken. The less corrective action, the lower the system state. If this loop is allowed to run unchecked, it can lead to a continuous degradation in the system’s performance.

This behavior is called eroding goals, or “the boiling frog syndrome”.

Drift to low performance is a gradual process. If the system state plunged quickly, there would be an agitated corrective process. But if it drifts down slowly enough to erase the memory of (or belief in) how much better things used to be, everyone is lulled into lower and lower expectations, lower effort, lower performance.

The way out. Keep performance standards absolute. Even better, let standards be enhanced by the best actual performances instead of being discouraged by the worst. Set up a drift toward high performance!

#The escalation trap

“I’ll raise you one” is the decision rule that leads to escalation. Escalation comes from a reinforcing loop set up by competing actors trying to get ahead of each other.

#The trap

When the state of one stock is determined by trying to surpass the state of another stock—and vice versa—then there is a reinforcing feedback loop carrying the system into an arms race, a wealth race, a smear campaign, escalating loudness, escalating violence. The escalation is exponential and can lead to extremes surprisingly quickly. If nothing is done, the spiral will be stopped by someone’s collapse — because exponential growth cannot go on forever.

#The way out

The best way out of this trap is to avoid getting in it. If caught in an escalating system, one can refuse to compete (unilaterally disarm), thereby interrupting the reinforcing loop. Or one can negotiate a new system with balancing loops to control the escalation.

#Success to the successful — Competitive exclusion

Using accumulated wealth, privilege, special access, or inside information to create more wealth, privilege, access or information are examples of the archetype called “success to the successful.”

The trap. If the winners of a competition are systematically rewarded with the means to win again, a reinforcing feedback loop is created by which, if it is allowed to proceed uninhibited, the winners eventually take all, while the losers are eliminated.

The way out. Diversification, which allows those who are losing the competition to get out of that game and start another one; strict limitation on the fraction of the pie any one winner may win (antitrust laws); policies that level the playing field, removing some of the advantage of the strongest players or increasing the advantage of the weakest; policies that devise rewards for success that do not bias the next round of competition.

#The addiction trap

This trap is known by many names: addiction, dependence, shifting the burden to the intervenor. The structure includes a stock with in-flows and out-flows. The stock can be physical (a crop of corn) or meta-physical (a sense of well-being or self-worth).

The stock is maintained by an actor adjusting a balancing feedback loop—either altering the in-flows or out-flows. The actor has a goal and compares it with a perception of the actual state of the stock to determine what action to take.

#The trap: Shifting the burden to the intervenor

Shifting the burden, dependence, and addiction arise when a solution to a systemic problem reduces (or disguises) the symptoms, but does nothing to solve the underlying problem. Whether it is a substance that dulls one’s perception or a policy that hides the underlying trouble, the drug of choice interferes with the actions that could solve the real problem. If the intervention designed to correct the problem causes the self-maintaining capacity of the original system to atrophy or erode, then a destructive reinforcing feedback loop is set in motion. The system deteriorates; more and more of the solution is then required. The system will become more and more dependent on the intervention and less and less able to maintain its own desired state.

#The way out

Again, the best way out of this trap is to avoid getting in. Beware of symptom-relieving or signal-denying policies or practices that don’t really address the problem. Take the focus off short-term relief and put it on long-term restructuring.

#Rule beating

Wherever there are rules, there is likely to be rule beating. Rule beating means evasive action to get around the intent of a system’s rules—abiding by the letter, but not the spirit, of the law.

#The trap

Rules to govern a system can lead to rule beating—perverse behavior that gives the appearance of obeying the rules or achieving the goals, but that actually distorts the system.

#The way out

Design, or redesign, rules to release creativity not in the direction of beating the rules, but in the direction of achieving the purpose of the rules.

#Seeking the wrong goal

If the desired system state is national security, and that is defined as the amount of money spent on the military, the system will produce military spending. It may or may not produce national security. Remember to measure what matters, not just what’s convenient.

#The trap

System behavior is particularly sensitive to the goals of feedback loops. If the goals—the indicators of satisfaction of the rules—are defined inaccurately or incompletely, the system may obediently work to produce a result that is not really intended or wanted.

#The way out

Specify indicators and goals that reflect the real welfare of the system. Be especially careful not to confuse effort with result or you will end up with a system that is producing effort, not result.

#Summary of systems principles

#Systems

A system is more than the sum of its parts.
Many of the interconnections in systems operate through the flow of information.
The least obvious part of the system, its function or purpose, is often the most crucial determinant of the system’s behavior.
System structure is the source of system behavior.
System behavior reveals itself as a series of events over time.

#Stocks, flows, and dynamic equilibrium

A stock is the memory of the history of changing flows within the system.
If the sum of inflows exceeds the sum of outflows, the stock level will rise.
If the sum of outflows exceeds the sum of inflows, the stock level will fall.
If the sum of outflows equals the sum of inflows, the stock level will not change — it will be held in dynamic equilibrium.
A stock can be increased by decreasing its outflow rate as well as by increasing its inflow rate.
Stocks act as delays or buffers or shock absorbers in systems.
Stocks allow inflows and outflows to be de-coupled and independent.

#Feedback loops

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.
The information delivered by a feedback loop—even nonphysical feedback—can affect only future behavior; it can’t deliver a signal fast enough to correct behavior that drove the current feedback.
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.
Systems with similar feedback structures produce similar dynamic behaviors.

#Constraints on systems

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 system can grow forever in a finite environment.
Nonrenewable resources are stock-limited.
Renewable resources are flow-limited.

#Resilience, self-organization, and hierarchy

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.
Systems often have the property of self-organization—the ability to structure themselves, to create new structure, to learn, diversify, and complexify.
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.

#Mindsets and models

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.

#Places to intervene in a system

12. Numbers. Constants and parameters such as subsidies, taxes, and standards. 11. Buffers. The sizes of stabilizing stocks relative to their flows. A big, stabilizing stock is known as a buffer. It works as a shock absorber in any system. 10. Stock-and-Flow Structures. Physical systems and their nodes of intersection. 9. Delays. The lengths of time relative to the rates of system changes. 8. Balancing Feedback Loops. The strength of the feedbacks relative to the impacts they are trying to correct. 7. Reinforcing Feedback Loops. The strength of the gain of driving loops. 6. Information Flows. The structure of who does and does not have access to information. 5. Rules. Incentives, punishments, constraints. Find out who decides the rules. 4. Self-Organization. The power to add, change, or evolve system structure. 3. Goals. The purpose of the system. 2. Paradigms. The mind-set out of which the system—its goals, structure, rules, delays, parameters—arises. 1. Transcending Paradigms.

#Guidelines for living in a world of systems

Get the beat of the system.
Expose your mental models to the light of day.
Honor, respect, and distribute information.
Use language with care and enrich it with systems concepts.
Pay attention to what is important, not just what is quantifiable.
Make feedback policies for feedback systems.
Go for the good of the whole.
Listen to the wisdom of the system.
Locate responsibility within the system.
Stay humble—stay a learner.
Celebrate complexity.
Expand time horizons.
Defy the disciplines.
Expand the boundary of caring.
Don’t erode the goal of goodness.