- 12. Numbers: Constants and parameters such as subsidies, taxes, and standards
- 11. Buffers:The sizes of stabilizing stocks relative to their flows
- 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
- 4. Self-Organization: The power to add, change, or evolve system structure
- 3. Goals:The purpose or function of the system
- 2. Paradigms: The mindset out of which the system—its goals, structure, rules, delays, parameters—arises.
- 1. Transcending Paradigms
How do we change the structure of systems to produce more of what we want and less of that which is undesirable? After years of working with corporations on their systems problems, MIT’s Jay Forrester likes to say that the average manager can define the current problem very cogently, identify the system structure that leads to
the problem, and guess with great accuracy where to look for leverage points—places in the system where a small change could lead to a large shift in behavior.
This idea of leverage points is not unique to systems analysis—it’s embedded in legend: the silver bullet, the miracle cure, the secret passage, the magic password, the nearly effortless way to cut through or leap over huge obstacles. We not only want to believe that there are leverage points, we want to know where they are and how to get our hands on them. Leverage points are points of power.
But Forrester goes on to point out that although people deeply involved in a system often know intuitively where to find leverage points, more often than not they push the change in the wrong direction.
The classic example of that backward intuition was my own introduction to systems analysis, the World model. Asked by the Club of Rome—an international group of businessmen, statesmen, and scientists—to show how major global problems of poverty and hunger, environmental destruction, resource depletion, urban deterioration, and unemployment are related and how they might be solved, Forrester made a computer model and came out with a clear leverage point: growth.1 Not only population growth, but economic growth. Growth has costs as well as benefits, and we typically don’t count the costs—among which are poverty and hunger, environmental destruction, and so on—the whole list of problems we are trying to solve with growth! What is needed is much slower growth, different kinds of growth, and in some cases no growth or negative growth.
The world’s leaders are correctly fixated on economic growth as the answer to virtually all problems, but they’re pushing with all their might in the wrong direction.
Another of Forrester’s classics was his study of urban dynamics, published in 1969, which demonstrated that subsidized low-income housing is a leverage point.2 The less of it there is, the better off the city is—even the low-income folks in the city. This model came out at a time when national policy dictated massive low-income housing projects, and Forrester was derided. Since then, many of those projects have been torn down in city after city.
Counterintuitive—that’s Forrester’s word to describe complex systems. Leverage points frequently are not intuitive. Or if they are, we too often use them backward, systematically worsening whatever problems we are trying to solve.
I have come up with no quick or easy formulas for finding leverage points in complex and dynamic systems. Give me a few months or years, and I’ll figure it out. And I know from bitter experience that, because they are so counterintuitive, when I do discover a system’s leverage points, hardly anybody will believe me. Very frustrating—especially for those of us who yearn not just to understand complex systems, but to make the world work better.
It was in just such a moment of frustration that I proposed a list of places to intervene in a system during a meeting on the implications of global-trade regimes. I offer this list to you with much humility and wanting to leave room for its evolution. What bubbled up in me that day was distilled from decades of rigorous analysis of many different kinds of systems done by many smart people. But complex systems are, well, complex. It’s dangerous to generalize about them. What you read here is still a work in progress; it’s not a recipe for finding leverage points. Rather, it’s an invitation to think more broadly about system change.
The “state of the system” is whatever standing stock is of importance: amount of water behind the dam, amount of harvestable wood in the forest, number of people in the population, whatever. System states are usually physical stocks, but they could be nonmaterial ones as well: self-confidence, degree of trust in public officials, perceived safety of a neighborhood.
There are usually inflows that increase the stock and outflows that decrease it. River inflow and rain raise the water behind a dam; evaporation and discharge through the spillway lower it. Political corruption decreases trust in public officials; experience of a well-functioning government increases it.
Insofar as this part of the system consists of physical stocks and flows—and they are the bedrock of any system—it obeys laws of conservation and accumulation. You can understand its dynamics readily if you can understand a bathtub with some water in it (the stock, the state of the system) and an inflowing faucet and outflowing drain. If the inflow rate is higher than the outflow rate, the water gradually rises. If the outflow rate is higher than the inflow, the water gradually goes down. The sluggish response of the water level to what could be sudden twists in the input and output valves is typical; it takes time for flows to accumulate in stocks, just as it takes time for water to fill up or drain out of the tub. Policy changes take time to accumulate their effects.
As systems become complex, their behavior can become surprising. Think about your checking account. You write checks and make deposits. A little interest keeps flowing in (if you have a large enough balance) and bank fees flow out even if you have no money in the account, thereby creating an accumulation of debt. Now attach your account to a thousand others and let the bank create loans as a function of your combined and fluctuating deposits, link a thousand of those banks into a federal reserve system—and you begin to see how simple stocks and flows, plumbed together, create systems way too complicated and dynamically complex to figure out easily.
That’s why leverage points are often not intuitive. And that’s enough systems theory to proceed to the list.
Places to Intervene in a System
(in increasing order of effectiveness)
12. Numbers: Constants and parameters such as subsidies, taxes, and standards
Think about the basic stock-and-flow bathtub. The size of the flows is a matter of numbers and how quickly those numbers can be changed. Maybe the faucet turns hard, so it takes a while to get the water flowing or to turn it off. Maybe the drain is blocked and can allow only a small flow. Maybe the faucet can deliver with the force of a fire hose. Some of these kinds of parameters are physically locked in and unchangeable, but many can be varied, making them popular intervention points.
Consider the national debt. It may seem like a strange stock; it is a money hole. The rate at which the hole deepens is called the annual deficit. Income from taxes shrinks the hole, government expenditures expand it. Congress and the president spend most of their time arguing about the many, many parameters that increase (spending) and decrease (taxing) the size or depth of the hole. Since those flows are connected to us, the voters, these are politically charged parameters. Despite all the fireworks, and no matter which party is in charge, the money hole has been deepening for years now, just at different rates.
The amount of land we set aside for conservation each year. The minimum wage. How much we spend on AIDS research or Stealth bombers. The service charge the bank extracts from your account. All of these are parameters, adjustments to faucets. So, by the way, is firing people and getting new ones, including politicians. Putting different hands on the faucets may change the rate at which the faucets turn, but if they’re the same old faucets, plumbed into the same old system, turned according to the same old information and goals and rules, the system behavior isn’t going to change much.
Numbers, the sizes of flows, are dead last on my list of powerful interventions. It’s not that parameters aren’t important—they can be, especially in the short term and to the individual who’s standing directly in the flow. People care deeply about such variables as taxes and the minimum wage, and so fight fierce battles over them. But changing these variables rarely changes the behavior of the national economy system. Whatever cap we put on campaign contributions, it doesn’t clean up politics. The Fed’s fiddling with the interest rate hasn’t made business cycles go away. After decades of the strictest air pollution standards in the world, Los Angeles' air is less dirty, but it isn’t clean. Spending more on police doesn’t make crime go away.
Since I’m about to get into some examples where parameters are leverage points, let me stick in a big caveat here: Parameters become leverage points when they go into ranges that kick off one of the items higher on this list. Interest rates, for example, or birth rates, control the gains around reinforcing feedback loops. System goals are parameters that can make big differences.
These kinds of critical numbers are not nearly as common as people seem to think they are. Most systems have evolved or are designed to stay far out of range of critical parameters. Mostly, the numbers are not worth the sweat put into them.
11. Buffers: The sizes of stabilizing stocks relative to their flows
Consider a huge bathtub with slow in- and outflows. Now think about a small one with very fast flows. That’s the difference between a lake and a river. You hear about catastrophic river floods much more often than catastrophic lake floods because stocks that are big, relative to their flows, are more stable than small ones. In chemistry and other fields, a big, stabilizing stock is known as a buffer.
The stabilizing power of buffers is why you keep money in the bank rather than living from the flow of change through your pocket. It’s why stores hold inventory instead of calling for new stock just as customers carry the old stock out the door. It’s why we need to maintain more than the minimum breeding population of an endangered species.
You can often stabilize a system by increasing the capacity of a buffer.3 But if a buffer is too big, the system gets inflexible. It reacts too slowly. And big buffers of some sorts, such as water reservoirs or inventories, cost a lot to build or maintain. Businesses invented just-in-time inventories because occasional vulnerability to fluctuations or screw-ups is cheaper than certain, constant inventory costs—and because small to vanishing inventories allow for a more flexible response to shifting demand.
There’s leverage, sometimes magical, in changing the size of buffers. Buffers are usually physical entities, not easy to change. The storage capacity of a dam is literally cast in concrete. So I haven’t put buffers very high on the list of leverage points.
10. Stock-and-Flow Structures: Physical systems and their nodes of intersection
The plumbing structure, the stocks and flows, and their physical arrangement, can all have an enormous effect on how the system operates. When the Hungarian road system was laid out so that all traffic from one side of the nation to the other had to pass through central Budapest, that determined a lot about air pollution and commuting delays that is not easily fixed by pollution control devices, traffic lights, or speed limits.
The only way to fix a system that is laid out poorly is to rebuild it, if you can. Amory Lovins and his team at Rocky Mountain Institute have done wonders on energy conservation by simply straightening out bent pipes and enlarging ones that are too small. If we did similar energy retrofits on all the buildings in the United States, we could shut down many of our electric power plants.
But often, physical rebuilding is the slowest and most expensive kind of change to make in a system. Some stock-and-flow structures are just plain unchangeable. The baby-boom swell in the U.S. population first caused pressure on the elementary school system, then high schools, then colleges, then jobs and housing, and now we’re supporting its retirement. There’s not much we can do about it because five-year-olds become six-year-olds, and sixty-four-year-olds become sixty-five-year-olds, predictably and unstoppably.
Physical structure is crucial in a system, but it is rarely a leverage point because changing it is rarely quick or simple. The leverage point is in proper design in the first place. After the structure is built, the leverage is in understanding its limitations and bottlenecks, using it with maximum efficiency, and refraining from fluctuations or expansions that strain its capacity.
9. Delays: The lengths of time relative to the rates of system changes
Delays in feedback loops are critical determinants of system behavior. They are common causes of oscillations. If you’re trying to adjust a stock, but you receive only delayed information about what the state of the stock is, you will overshoot or undershoot your goal. The same is true if your information is timely, but your response isn’t. It takes several years to build an electric power plant that will likely last thirty years. Those delays make it impossible to build exactly the right number of power plants to supply changing demand for electricity. Even with immense effort at forecasting, almost every electricity industry in the world experiences long oscillations between overcapacity and undercapacity. A system just can’t respond to short-term changes when it has long-term delays.
Because we know they’re important, we see delays wherever we look. For example, the delay between the time when a pollutant is dumped on the land and when it trickles down to the groundwater, or the delay between the birth of a child and the time when that child is ready to have a child, or the time it takes for a price to adjust to a supply-demand imbalance.
A delay in a feedback process is critical relative to rates of change in the stocks that the feedback loop is trying to control. Delays that are too short cause overreaction, oscillations amplified by the jumpiness of the response. Delays that are too long cause dampened, sustained, or exploding oscillations. Overlong delays in a system with a threshold, a range past which irreversible damage can occur, cause overshoot and collapse.
I would list delay length as a high leverage point, except for the fact that delays are not often easily changeable. Things take as long as they take. You can’t do a lot about the construction time of a major piece of capital, or the maturation time of a child, or the growth rate of a forest. It’s usually easier to slow down the change rate, so that inevitable feedback delays won’t cause so much trouble. That’s why growth rates are higher up on the leverage point list than delay times.
And that’s why slowing economic growth is a greater leverage point in Forrester’s World model than faster technological development or freer market prices. Those are attempts to speed up the rate of adjustment. But the world’s physical capital stock, its factories and boilers, can change only so fast, even in the face of new prices or new ideas—and prices and ideas don’t change instantly either, not through a whole global culture. There’s more leverage in slowing the system down so technologies and prices can keep up with it, than there is in wishing the delays would go away.
But if there is a delay in your system that can be changed, changing it can have big effects. Watch out! Be sure you change it in the right direction!
8. Balancing Feedback Loops: The strength of the feedbacks relative to the impacts they are trying to correct
Now we’re beginning to move from the physical part of the system to the information and control parts, where more leverage can be found.
Balancing feedback loops are ubiquitous. Nature evolves them and humans invent them as controls to keep important stocks within safe bounds. A thermostat loop is the classic example. Its purpose is to keep the system stock fairly constant near a desired level. Any balancing feedback loop needs a goal (the thermostat setting), a monitoring and signaling device to detect deviation from the goal (the thermostat), and a response mechanism (the furnace or air conditioner, fans, pumps, pipes, and fuel).
A complex system usually has numerous balancing feedback loops, so it can self-correct under different conditions and impacts. Some of those loops may be inactive much of the time—like the emergency cooling system in a nuclear power plant, or your ability to sweat or shiver to maintain your body temperature—but their presence is critical to the long-term welfare of the system.
One of the big mistakes we make is to strip away these “emergency” response mechanisms because they aren’t often used and they appear to be costly. In the short term, we see no effect from doing this. In the long term, we drastically narrow the range of conditions over which the system can survive. One of the most heartbreaking ways we do this is in encroaching on the habitats of endangered species. Another is in encroaching on our own time for rest, recreation, socialization, and meditation.
The strength of a balancing loop—its ability to keep its appointed stock at or near its goal—depends on the combination of all its parameters and links—the accuracy and rapidity of monitoring, the quickness and power of response, the directness and size of corrective flows. Sometimes there are leverage points here.
Take markets, for example, the balancing feedback systems that are all but worshipped by many economists. They can indeed be marvels of self-correction, as prices vary to moderate supply and demand and keep them in balance. Price is the central piece of information signaling both producers and consumers. The more the price is kept clear, unambiguous, timely, and truthful, the more smoothly markets will operate. Prices that reflect full costs will tell consumers how much they can actually afford and will reward efficient producers. Companies and governments are fatally attracted to the price leverage point, but too often determinedly push it in the wrong direction with subsidies, taxes, and other forms of confusion.
These modifications weaken the feedback power of market signals by twisting information in their favor. The real leverage here is to keep them from doing it. Hence, the necessity of antitrust laws, truth-in-advertising laws, attempts to internalize costs (such as pollution fees), the removal of perverse subsidies, and other ways of leveling market playing fields.
The strength of a balancing feedback loop is important relative to the impact it is designed to correct. If the impact increases in strength, the feedbacks have to be strengthened too. A thermostat system may work fine on a cold winter day—but open all the windows and its corrective power is no match for the temperature change imposed on the system. Democracy works better without the brainwashing power of centralized mass communications. Traditional controls on fishing were sufficient until sonar spotting and drift nets and other technologies made it possible for a few actors to catch the last fish.
Examples of strengthening balancing feedback controls to improve a system’s self-correcting abilities include:
- preventive medicine, exercise, and good nutrition to bolster the body’s ability to fight disease,
- integrated pest management to encourage natural predators of crop pests,
- the Freedom of Information Act to reduce government secrecy,
- protection for whistleblowers, and
- impact fees, pollution taxes, and performance bonds to recapture the externalized public costs of private benefits.
7. Reinforcing Feedback Loops: The strength of the gain of driving loops
A balancing feedback loop is self-correcting; a reinforcing feedback loop is self-reinforcing. The more it works, the more it gains power, driving system behavior in one direction. The more people catch the flu, the more they infect other people. The more babies are born, the more people grow up to have babies. The more money you have in the bank, the more interest you earn, the more money you have in the bank. The more the soil erodes, the less vegetation it can support, the fewer roots and leaves soften rain and runoff, the more soil erodes.
Reinforcing feedback loops are sources of growth, explosion, erosion, and collapse in systems. A system with an unchecked reinforcing loop ultimately will destroy itself. That’s why there are so few of them. Usually a balancing loop will kick in sooner or later. The epidemic will run out of infectible people—or people will take increasingly stronger steps to avoid being infected. The death rate will rise to equal the birth rate—or people will see the consequences of unchecked population growth and have fewer babies. The soil will erode away to bedrock, and after a million years the bedrock will crumble into new soil—or people will put up check dams, plant trees, and stop overgrazing to stop the erosion.
In all those examples, the first outcome is what will happen if the reinforcing loop runs its course; the second is what will happen if there’s an intervention to reduce its self-multiplying power. Reducing the gain around a reinforcing loop—slowing the growth—is usually a more powerful leverage point in systems than strengthening balancing loops, and far more preferable than letting the reinforcing loop run.
Population and economic growth rates in the World model are leverage points because slowing them gives the many balancing loops, through technology and markets and other forms of adaptation, time to function.
There are many reinforcing feedback loops in society that reward the winners of a competition with the resources to win even bigger next time—the “success to the successful” trap. Rich people collect interest; poor people pay it. Rich people pay accountants and lean on politicians to reduce their taxes; poor people can’t. Rich people give their kids inheritances and good educations. Antipoverty programs are weak balancing loops that try to counter these strong reinforcing ones. It would be much more effective to weaken the reinforcing loops. That’s what progressive income tax, inheritance tax, and universal high-quality public education programs are meant to do. If the wealthy can influence government to weaken, rather than strengthen, those measures, then the government itself shifts from a balancing structure to one that reinforces success to the successful!
Look for leverage points around birth rates, erosion rates, “success to the successful” loops, any place where the more you have of something, the more you have the possibility of having more.
6. Information Flows: The structure of who does and does not have access to information
In some of the houses of a Dutch housing development, electric meters were installed in the basement; in others, they were installed in the front hall. With no other differences in the houses, electricity consumption was 30 percent lower in the houses where the meter was in the highly visible location in the front hall.
I love that story because it’s an example of a high leverage point in the information structure of the system. It’s not a parameter adjustment, not a strengthening or weakening of an existing feedback loop. It’s a new loop, delivering feedback to a place where it wasn’t going before.
Missing information flows are among the most common causes of system malfunction. Adding or restoring information can be a powerful intervention, usually much easier and cheaper than rebuilding physical infrastructure. The tragedy of the commons that is crashing the world’s commercial fisheries occurs because there is little feedback from the state of the fish population to the decision to invest in fishing vessels. Contrary to economic opinion, the price of fish doesn’t provide that feedback. As the fish get scarcer, they become more expensive, and it becomes all the more profitable to go out and catch the last few. That’s a perverse feedback, a reinforcing loop that leads to collapse. It is not price information but population information that is needed.
It’s important that the missing feedback be restored to the right place and in compelling form. To take another tragedy of the commons example, it’s not enough to inform all the users of an aquifer that the groundwater level is dropping. That could initiate a race to the bottom. It would be more effective to set the cost of water to rise steeply as the pumping rate begins to exceed the recharge rate.
Other examples of compelling feedbacks are not hard to find. Suppose taxpayers got to specify on their return forms what government services their tax payments must be spent on. (Radical democracy!) Suppose any town or company that puts a water-intake pipe in a river had to put it immediately downstream from its own wastewater outflow pipe. Suppose any public or private official who made the decision to invest in a nuclear power plant got the waste from that facility stored on his or her lawn.
There is a systematic tendency on the part of human beings to avoid accountability for their own decisions. That’s why there are so many missing feedback loops—and why this kind of leverage point is so often popular with the masses, unpopular with the powers that be, and effective, if you can get the powers that be to permit it to happen (or go around them and make it happen anyway).
5. Rules: Incentives, punishments, constraints
The rules of the system define its scope, its boundaries, and its degrees of freedom. Thou shalt not kill. Everyone has the right of free speech. Contracts are to be honored. The president serves four-year terms and cannot serve more than two of them. Nine people on a team, you have to touch every base, three strikes and you’re out. If you get caught robbing a bank, you go to jail.
Constitutions are the strongest examples of social rules. Physical laws, such as the second law of thermodynamics, are absolute rules, whether we understand them or not or like them or not. Laws, punishments, incentives, and informal social agreements are progressively weaker rules.
To demonstrate the power of rules, I like to ask my students to imagine different ones for a college. Suppose the students graded the teachers, or each other. Suppose there were no degrees: You come to college when you want to learn something, and you leave when you’ve learned it. Suppose tenure were awarded to professors according to their ability to solve real-world problems, rather than to publish academic papers. Suppose a class got graded as a group, instead of as individuals.
As we try to imagine restructured rules and what our behavior would be under them, we come to understand their power. They are high leverage points. Power over the rules is real power. That’s why lobbyists congregate when Congress writes laws and why the Supreme Court, which interprets and delineates the Constitution—the rules for writing the rules—has even more power than Congress. If you want to understand the deepest malfunctions of systems, pay attention to the rules and to those who have power over them.
4. Self-Organization: The power to add, change, or evolve system structure
The most stunning thing living systems and some social systems can do is to change themselves utterly by creating whole new structures and behaviors. In biological systems, that power is called evolution. In human economies it’s called technical advance or social revolution. In systems lingo it’s called self-organization.
Self-organization means changing any aspect of a system lower on this list—adding completely new physical structures, new balancing or reinforcing loops, or new rules. The ability to self-organize is the strongest form of system resilience. A system that can evolve can survive almost any change by changing itself.
The power of self-organization seems so wondrous that we tend to regard it as mysterious, miraculous, heaven sent. Economists often model technology as magic—coming from nowhere, costing nothing, increasing the productivity of an economy by some steady percentage each year. For centuries people have regarded the spectacular variety of nature with the same awe. Only a divine creator could bring forth such a creation.
Further investigation of self-organizing systems reveals that the divine creator, if there is one, does not have to produce evolutionary miracles. He, she, or it just has to write marvelously clever rules for self-organization. These rules basically govern how, where, and what the system can add onto or subtract from itself and under what conditions. As hundreds of self-organizing computer models have demonstrated, complex and delightful patterns can evolve from quite simple sets of rules. The genetic code, and the rules for replicating and rearranging it, has been constant for something like three billion years, during which it has spewed out an unimaginable variety of failed and successful self-evolved creatures.
When you understand the power of system self-organization, you begin to understand why biologists worship biodiversity even more than economists worship technology. The wildly varied stock of DNA, evolved and accumulated over billions of years, is the source of evolutionary potential, just as science libraries and labs and universities where scientists train are the source of technological potential. Allowing species to go extinct is a systems crime, just as randomly eliminating all copies of particular science journals or particular kinds of scientists would be.
The same could be said of human cultures, of course, which are the store of behavioral repertoires accumulated over hundreds of thousands of years. They are a stock out of which social evolution can arise. Unfortunately, people appreciate the precious evolutionary potential of cultures even less than they understand the preciousness of every genetic variation in the world’s ground squirrels. Insistence on a single culture shuts down learning and cuts back resilience. Any system, biological, economic, or social, that gets so encrusted that it cannot self-evolve, a system that systematically scorns experimentation and wipes out the raw material of innovation, is doomed over the long term on this highly variable planet.
3. Goals: The purpose or function of the system
The diversity-destroying consequences of the push for control demonstrates why the goal of a system is a leverage point superior to the self-organizing ability of a system. If the goal is to bring more and more of the world under the control of one particular central planning system (the empire of Genghis Khan, the Church, the People’s Republic of China, Wal-Mart, Disney), then everything further down the list, physical stocks and flows, feedback loops, information flows, even self-organizing behavior, will be twisted to conform to that goal.
That’s why I can’t get into arguments about whether genetic engineering is a “good” or a “bad” thing. Like all technologies, it depends on who is wielding it, with what goal. The only thing one can say is that if corporations wield it for the purpose of generating marketable products, that is a very different goal, a very different selection mechanism, a very different direction for evolution than anything the planet has seen so far.
As my little single-loop examples have shown, most balancing feedback loops within systems have their own goals—to keep the bathwater at the right level, to keep the room temperature comfortable, to keep inventories stocked at sufficient levels, to keep enough water behind the dam. Those goals are important leverage points for pieces of systems, and most people realize that. If you want the room warmer, you know the thermostat setting is the place to intervene. But there are larger, less obvious, higher-leverage goals: those of the entire system.
Even people within systems don’t often recognize what whole-system goal they are serving. “To make profits,” most corporations would say, but that’s just a rule, a necessary condition to stay in the game. What is the point of the game? To grow, to increase market share, to bring the world (customers, suppliers, regulators) more and more under the control of the corporation, so that its operations become ever more shielded from uncertainty. John Kenneth Galbraith recognized that corporate goal—to engulf everything—long ago.4 It’s the goal of a cancer, too. Actually it’s the goal of every living population—and only a bad one when it isn’t balanced by higher-level, balancing feedback loops that never let an upstart, power-loop-driven entity control the world. The goal of keeping the market competitive has to trump the goal of each individual corporation to eliminate its competitors, just as in ecosystems, the goal of keeping populations in balance and evolving has to trump the goal of each population to reproduce without limit.
I said a while back that changing the players in the system is a low-level intervention, as long as the players fit into the same old system. The exception to that rule is at the top, where a single player can have the power to change the system’s goal.
That’s what Ronald Reagan did, and we watched it happen. Not long before he came to office, a president could say, “Ask not what government can do for you, ask what you can do for the government,” and no one even laughed. Reagan said, over and over, the goal is not to get the people to help the government and not to get government to help the people, but to get government off our backs. One can argue, and I would, that larger system changes and the rise of corporate power over government let him get away with that. But the thoroughness with which the public discourse in the United States and even the world has been changed since Reagan is testimony to the high leverage of articulating, meaning, repeating, standing up for, and insisting upon new system goals.
2. Paradigms: The mindset out of which the system—its goals, structure, rules, delays, parameters—arises
Another of Jay Forrester’s famous systems sayings goes: It doesn’t matter how the tax law of a country is written. There is a shared idea in the minds of the society about what a “fair” distribution of the tax load is. Whatever the laws say, by fair means or foul, by complications, cheating, exemptions or deductions, actual tax payments will push right up against the accepted idea of “fairness.”
The shared ideas in the minds of society, the great big unstated assumptions, constitute that society’s paradigm, or deepest set of beliefs about how the world works. These beliefs are unstated because it is unnecessary to state them—everyone already knows them. Money measures something real and has real meaning; therefore, people who are paid less are literally worth less. Growth is good. One can “own” land. Those are just a few of the paradigmatic assumptions of our current culture, all of which have utterly dumbfounded other cultures, who thought them not the least bit obvious.
Paradigms are the sources of systems. From them, from shared social agreements about the nature of reality, come system goals and information flows, feedbacks, stocks, and everything else about systems. The ancient Egyptians built pyramids because they believed in an afterlife. We build skyscrapers because we believe that space in downtown cities is enormously valuable. Whether it was Copernicus and Kepler showing that the earth is not the center of the universe, or Adam Smith postulating that the selfish actions of individual players in markets wonderfully accumulate to the common good, people who have managed to intervene in systems at the level of paradigm have hit a leverage point that totally transformed systems.
You could say paradigms are harder to change than anything else about a system, and therefore this item should be lowest on the list, not second. But there’s nothing physical or expensive or even slow in the process of paradigm change. In a single individual, it can happen in a millisecond. All it takes is a click in the mind, a falling of scales from the eyes, a new way of seeing. Whole societies are another matter—they resist challenges to their paradigms harder than they resist anything else.
So how do you change paradigms? Thomas Kuhn, who wrote the seminal book about the great paradigm shifts of science, has a lot to say about that.5 You keep pointing at the anomalies and failures in the old paradigm. You keep speaking and acting, loudly and with assurance, from the new one. You insert people with the new paradigm in places of public visibility and power. You don’t waste time with reactionaries; rather, you work with active change agents and with the vast middle ground of people who are open-minded.
Systems modelers say that we change paradigms by building a model of the system, which takes us outside the system and forces us to see it whole. I say that because my own paradigms have been changed that way.
1. Transcending Paradigms
There is yet one leverage point that is even higher than changing a paradigm. That is to keep oneself unattached in the arena of paradigms, to stay flexible, to realize that no paradigm is “true,” that every one, including the one that sweetly shapes your own worldview, is a tremendously limited understanding of an immense and amazing universe that is far beyond human comprehension. It is to “get,” at a gut level, the paradigm that there are paradigms, and to see that that itself is a paradigm, and to regard that whole realization as devastatingly funny. It is to let go into not-knowing, into what the Buddhists call enlightenment.
People who cling to paradigms (which means just about all of us) take one look at the spacious possibility that everything they think is guaranteed to be nonsense and pedal rapidly in the opposite direction. Surely there is no power, no control, no understanding, not even a reason for being, much less acting, embodied in the notion that there is no certainty in any worldview. But, in fact, everyone who has managed to entertain that idea, for a moment or for a lifetime, has found it to be the basis for radical empowerment. If no paradigm is right, you can choose whatever one will help to achieve your purpose. If you have no idea where to get a purpose, you can listen to the universe.
It is in this space of mastery over paradigms that people throw off addictions, live in constant joy, bring down empires, get locked up or burned at the stake or crucified or shot, and make impacts that last for millennia.
There is so much that could be said to qualify this list of places to intervene in a system. It is a tentative list and its order is slithery. There are exceptions to every item that can move it up or down the order of leverage. Having had the list percolating in my subconscious for years has not transformed me into Superwoman. The higher the leverage point, the more the system will resist changing it—that’s why societies often rub out truly enlightened beings.
Magical leverage points are not easily accessible, even if we know where they are and which direction to push them. There are no cheap tickets to mastery. You have to work hard at it, whether that means rigorously analyzing a system or rigorously casting off your own paradigms and throwing yourself into the humility of not-knowing. In the end, it seems that mastery has less to do with pushing leverage points than it does with strategically, profoundly, madly, letting go.
- Forrester, JW. World Dynamics. (Wright-Allen Press, Cambridge, 1971).
- Forrester, JW. Urban Dynamics. (The MIT Press, Cambridge, 1969).
- Meadows, D. Dynamics of Commodity Production Cycles. (Wright-Allen Press, Cambridge, 1970).
- Galbraith, JK. The New Industrial State. (Houghton Mifflin, Boston, 1967).
- Kuhn, T. The Structure of Scientific Revolution. (University of Chicago Press, Chicago, 1962).