permaculture

[Wesley Roe and Santa Barbara Permaculture Network <lakinroe@silcom.com>]

Leverage Points: Places to Intervene in a System

http://donellameadows.org/archives/leverage-points-places-to-intervene-in-a-system/
 
<http://donellameadows.org/archives/leverage-points-places-to-intervene-in-a-system/>

 <https://www.facebook.com/DonellaMeadowsInstitute>  
<http://twitter.com/DanaMeadowsInst>
By Donella Meadows~

Folks who do systems analysis have a great belief in “leverage points.” These 
are places within a complex system (a corporation, an economy, a living body, 
a city, an ecosystem) where a small shift in one thing can produce big 
changes in everything.

This idea is not unique to systems analysis — it’s embedded in legend. The 
silver bullet, the trimtab, the miracle cure, the secret passage, the magic 
password, the single hero who turns the tide of history. 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.

The systems analysis community has a lot of lore about leverage points. Those 
of us who were trained by the great Jay Forrester at MIT have all absorbed 
one of his favorite stories. “People know intuitively where leverage points 
are,” he says. “Time after time I’ve done an analysis of a company, and I’ve 
figured out a leverage point — in inventory policy, maybe, or in the 
relationship between sales force and productive force, or in personnel 
policy. Then I’ve gone to the company and discovered that there’s already a 
lot of attention to that point. Everyone is trying very hard to push it 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 to show how 
major global problems — poverty and hunger, environmental destruction, 
resource depletion, urban deterioration, unemployment — are related and how 
they might be solved, Forrester made a computer model and came out with a 
clear leverage point1 
<http://donellameadows.org/archives/leverage-points-places-to-intervene-in-a-system/#one>:
 Growth. 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, etc. — the whole list of 
problems we are trying to solve with growth! What is needed is much slower 
growth, much 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 urban dynamics study, published in 
1969, which demonstrated that subsidized low-income housing is a leverage 
point.2 
<http://donellameadows.org/archives/leverage-points-places-to-intervene-in-a-system/#two>
 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. Now 
those projects are being torn down in city after city.

Counterintuitive. That’s Forrester’s word to describe complex systems. 
Leverage points are not intuitive. Or if they are, we intuitively use them 
backward, systematically worsening whatever problems we are trying to solve.

The systems analysts I know have come up with no quick or easy formulas for 
finding leverage points. When we study a system, we usually learn where 
leverage points are. But a new system we’ve never encountered? Well, our 
counterintuitions aren’t that well developed. Give us a few months or years 
and we’ll figure it out. And we know from bitter experience that, because of 
counterintuitiveness, when we do discover the system’s leverage points, 
hardly anybody will believe us.

Very frustrating, especially for those of us who yearn not just to understand 
complex systems, but to make the world work better.

So one day I was sitting in a meeting about how to make the world work better 
— actually it was a meeting about how the new global trade regime, NAFTA and 
GATT and the World Trade Organization, is likely to make the world work 
worse. The more I listened, the more I began to simmer inside. “This is a 
HUGE NEW SYSTEM people are inventing!” I said to myself. “They haven’t the 
SLIGHTEST IDEA how this complex structure will behave,” myself said back to 
me. “It’s almost certainly an example of cranking the system in the wrong 
direction — it’s aimed at growth, growth at any price!! And the control 
measures these nice, liberal folks are talking about to combat it — small 
parameter adjustments, weak negative feedback loops — are PUNY!!!”

Suddenly, without quite knowing what was happening, I got up, marched to the 
flip chart, tossed over to a clean page, and wrote:

PLACES TO INTERVENE IN A SYSTEM

(in increasing order of effectiveness)

9. Constants, parameters, numbers (subsidies, taxes, standards).
8. Regulating negative feedback loops.
7. Driving positive feedback loops.
6. Material flows and nodes of material intersection.
5. Information flows.
4. The rules of the system (incentives, punishments, constraints).
3. The distribution of power over the rules of the system.
2. The goals of the system.
1. The mindset or paradigm out of which the system — its goals, power 
structure, rules, its culture — arises.

Everyone in the meeting blinked in surprise, including me. “That’s 
brilliant!” someone breathed. “Huh?” said someone else.

I realized that I had a lot of explaining to do.

I also had a lot of thinking to do. As with most of the stuff that come to me 
in boil-over mode, this list was not exactly tightly reasoned. As I began to 
share it with others, especially systems analysts who had their own lists and 
activists who wanted to put the list to immediate use, questions and comments 
came back that caused me to rethink, add and delete items, change the order, 
add caveats.

In a minute I’ll go through the list I ended up with, explain the jargon, 
give examples and exceptions. The reason for this introduction is to place 
the list in a context of humility and to leave room for 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 
are about to read is 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.

Here, in the light of a cooler dawn, is a revised list:

PLACES TO INTERVENE IN A SYSTEM

(in increasing order of effectiveness)

12. Constants, parameters, numbers (such as subsidies, taxes, standards).
11. The sizes of buffers and other stabilizing stocks, relative to their 
flows.
10. The structure of material stocks and flows (such as transport networks, 
population age structures).
9. The lengths of delays, relative to the rate of system change.
8. The strength of negative feedback loops, relative to the impacts they are 
trying to correct against.
7. The gain around driving positive feedback loops.
6. The structure of information flows (who does and does not have access to 
information).
5. The rules of the system (such as incentives, punishments, constraints).
4. The power to add, change, evolve, or self-organize system structure.
3. The goals of the system.
2. The mindset or paradigm out of which the system — its goals, structure, 
rules, delays, parameters — arises.
1. The power to transcend paradigms.

To explain parameters, stocks, delays, flows, feedback, and so forth, I need 
to start with a basic diagram.



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, amount of money in the bank, 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. Deposits increase the money in the bank; withdrawals decrease it. River 
inflow and rain raise the water behind the dam; evaporation and discharge 
through the spillway lower it. Births and immigrations increase the 
population, deaths and emigrations reduce 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 state of the system) and an inflowing 
faucet and outflowing drain. If the inflow rate is higher than the outflow 
rate, the stock gradually rises. If the outflow rate is higher than the 
inflow, the stock 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, just as it takes time for 
water to fill up or drain out of the tub.

The rest of the diagram is the information that causes the flows to change, 
which then cause the stock to change. If you’re about to take a bath, you 
have a desired water level in mind. You plug the drain, turn on the faucet 
and watch until the water rises to your chosen level (until the discrepancy 
between the desired and the actual state of the system is zero). Then you 
turn the water off.

If you start to get in the bath and discover that you’ve underestimated your 
volume and are about to produce an overflow, you can open the drain for 
awhile, until the water goes down to your desired level.

Those are two negative feedback loops, or correcting loops, one controlling 
the inflow, one controlling the outflow, either or both of which you can use 
to bring the water level to your goal. Notice that the goal and the feedback 
connections are not visible in the system. If you were an extraterrestrial 
trying to figure out why the tub fills and empties, it would take awhile to 
figure out that there’s an invisible goal and a discrepancy-measuring process 
going on in the head of the creature manipulating the faucets. But if you 
watched long enough, you could figure that out.

Very simple so far. Now let’s take into account that you have two taps, a hot 
and a cold, and that you’re also adjusting for another system state — 
temperature. Suppose the hot inflow is connected to a boiler way down in the 
basement, four floors below, so it doesn’t respond quickly. And you’re making 
faces at yourself in the mirror and not paying close attention to the water 
level. And, of course, the inflow pipe is connected to a reservoir somewhere, 
which is connected to the whole planetary hydrological cycle. The system 
begins to get complex, and realistic, and interesting.

Mentally change the bathtub into your checking account. Write checks, make 
deposits, add a faucet that keeps dribbling in a little interest and a 
special drain that sucks your balance even drier if it ever goes dry. 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, make up systems way too complex to figure out.

That’s why leverage points are not intuitive. And that’s enough systems 
theory to proceed to the list.

12. Constants, parameters, numbers (subsidies, taxes, standards).

“Parameters” in systems jargon means the numbers that determine how much of a 
discrepancy turns which faucet how fast. Maybe the faucet turns hard, so it 
takes awhile to get the water flowing or to turn it off. Maybe the drain is 
blocked and can allow only a small flow, no matter how open it is. Maybe the 
faucet can deliver with the force of a fire hose. These considerations are a 
matter of numbers, some of which are physically locked in and unchangeable, 
but most of which are popular intervention points.

Consider the national debt. It’s a negative bathtub, a money hole. The rate 
at which it sinks is called the annual deficit. Tax income makes it rise, 
government expenditures make it fall. Congress and the president spend most 
of their time arguing about the many, many parameters that open and close tax 
faucets and spending drains. Since those faucets and drains are connected to 
us, the voters, these are politically charged parameters. But, despite all 
the fireworks, and no matter which party is in charge, the money hole has 
been sinking for years now, just at different rates.

To adjust the dirtiness of the air we breathe, the government sets parameters 
called ambient air quality standards. To assure some standing stock of forest 
(or some flow of money to logging companies) it sets allowed annual cuts. 
Corporations adjust parameters such as wage rates and product prices, with an 
eye on the level in their profit bathtub — the bottom line.

The amount of land we set aside for conservation. The minimum wage. How much 
we spend on AIDS research or Stealth bombers. The service charge the bank 
extracts from your account. All 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 isn’t going to change much. Electing Bill Clinton was definitely 
different from electing George Bush, but not all that different, given that 
every president is plugged into the same political system. (Changing the way 
money flows in that system would make much more of a difference — but I’m 
getting ahead of myself on this list.)

Parameters are dead last on my list of powerful interventions. Diddling with 
the details, arranging the deck chairs on the Titanic. Probably 90, no 95, no 
99 percent of our attention goes to parameters, but there’s not a lot of 
leverage in them.

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 parameters and fight fierce battles over them. But they RARELY 
CHANGE BEHAVIOR. If the system is chronically stagnant, parameter changes 
rarely kick-start it. If it’s wildly variable, they don’t usually stabilize 
it. If it’s growing out of control, they don’t brake it.

Whatever cap we put on campaign contributions, it doesn’t clean up politics. 
The Feds fiddling with the interest rate haven’t made business cycles go 
away. (We always forget that during upturns, and are shocked, shocked by the 
downturns.) 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 
positive feedback loops. System goals are parameters that can make big 
differences. Sometimes a system gets onto a chaotic edge, where the tiniest 
change in a number can drive it from order to what appears to be wild 
disorder.

These 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 critical 
parameter ranges. Mostly, the numbers are not worth the sweat put into them.

Here’s a story a friend sent me over the Internet to makes that point:3 
<http://donellameadows.org/archives/leverage-points-places-to-intervene-in-a-system/#three>
When I became a landlord, I spent a lot of time and energy trying to figure 
out what would be a “fair” rent to charge.

I tried to consider all the variables, including the relative incomes of my 
tenants, my own income and cash flow needs, which expenses were for upkeep 
and which were capital expenses, the equity versus the interest portion of 
the mortgage payments, how much my labor on the house was worth, etc. 

I got absolutely nowhere. Finally I went to someone who specializes in giving 
money advice. She said: “You’re acting as though there is a fine line at 
which the rent is fair, and at any point above that point the tenant is being 
screwed and at any point below that you are being screwed. In fact there is a 
large grey area in which both you and the tenant are getting a good, or at 
least a fair, deal. Stop worrying and get on with your life.”

11. The sizes of buffers and other 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. Soils in the eastern U.S. are 
more sensitive to acid rain than soils in the west, because they haven’t got 
big buffers of calcium to neutralize acid.

You can often stabilize a system by increasing the capacity of a buffer.4 
<http://donellameadows.org/archives/leverage-points-places-to-intervene-in-a-system/#four>
 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 (for them, anyway) than certain, constant inventory 
costs — and because small-to-vanishing inventories allow more flexible 
response to shifting demand.

There’s leverage, sometimes magical, in changing the size of buffers. But 
buffers are usually physical entities, not easy to change. The acid 
absorption capacity of eastern soils is not a leverage point for alleviating 
acid rain damage. 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. The structure of material stocks and flows and nodes of intersection 
(such as transport networks, population age structures, flow of nitrogen 
through soil).

The plumbing structure, the stocks and flows and their physical arrangement, 
can have an enormous effect on how the system operates. When the Hungarian 
road system was laid out so all traffic from one side of the nation to the 
other has to pass through central Budapest, that determined a lot about air 
pollution and commuting delays that are not easily fixed by pollution control 
devices, traffic lights, or speed limits.

The only way to fix a system that is laid out wrong is to rebuild it, if you 
can. Amory Lovins does wonders of energy conservation by straightening out 
bent pipes and enlarging too-small ones. If we let him do energy retrofits on 
all the buildings of the nation,we could shut down at least half 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 looking forward to supporting its 
retirement. 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. The same can be said for the lifetime of 
destructive CFC molecules in the ozone layer, for the rate at which 
contaminants get washed out of aquifers, for the fact that an inefficient car 
fleet takes 10-20 years to turn over.

Physical structure is crucial in a system, but 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. The lengths of delays, relative to the rate of system changes.

Remember that bathtub on the fourth floor I mentioned, with the water heater 
in the basement? I actually experienced one of those once, in an old hotel in 
London. It wasn’t even a bathtub, it was a shower — no buffering capacity. 
The water temperature took at least a minute to respond to my faucet twists. 
Guess what my shower was like.

Right, oscillations from hot to cold and back to hot, punctuated with 
expletives.

Delays in feedback loops are critical determinants of system behavior. They 
are common causes of oscillations. If you’re trying to adjust a system state 
to your goal, but you only receive delayed information about what the system 
state is, you will overshoot and undershoot. Same if your information is 
timely, but your response isn’t. For example, it takes several years to build 
an electric power plant, and then that plant lasts, say, thirty years. Those 
delays make it impossible to build exactly the right number of plants to 
supply a rapidly changing demand. 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. That’s why a massive 
central-planning system, such as the Soviet Union or General Motors, 
necessarily functions poorly.

Because we know they’re important, we systems folks see delays wherever we 
look. The delay between the time when a pollutant is dumped on the land and 
when it trickles down to the groundwater. The delay between the birth of a 
child and the time when that child is ready to have a child. The delay 
between the first successful test of a new technology and the time when that 
technology is installed throughout the economy. 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 
(growth, fluctuation, decay) IN THE STOCKS THAT THE FEEDBACK LOOP IS TRYING 
TO CONTROL. Delays that are too short cause overreaction, “chasing your 
tail,” oscillations amplified by the jumpiness of the response. Delays that 
are too long cause damped, sustained, or exploding oscillations, depending on 
how much too long. At the extreme they cause chaos. Overlong delays in a 
system with a threshold, a danger point, 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 plant, its factories and boilers, the concrete 
manifestations of its working technologies, can only change 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 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! 
(For example, the great push to reduce information and money transfer delays 
in financial markets is just asking for wild gyrations)

8. The strength of negative feedback loops, relative to the impacts they are 
trying to correct against.

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.

Negative feedback loops are ubiquitous in systems. Nature evolves them and 
humans invent them as controls to keep important system states within safe 
bounds. A thermostat loop is the classic example. Its purpose is to keep the 
system state called “room temperature” fairly constant at a desired level. 
Any negative feedback loop needs a goal (the thermostat setting), a 
monitoring and signaling device to detect excursions from the goal (the 
thermostat), and a response mechanism (the furnace and/or air conditioner, 
fans, heat pipes, fuel, etc.).

A complex system usually has numerous negative feedback loops it can bring 
into play, 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 negative 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 negative feedback systems that are all but 
worshipped by economists — and they can indeed be marvels of self-correction, 
as prices vary to moderate supply and demand and keep them in balance. The 
more the price — the central piece of information signaling both producers 
and consumers — 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, of course, all of them determinedly pushing it in the wrong 
direction with subsidies, fixes, externalities, taxes, and other forms of 
confusion.

These folks are trying to 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 anti-trust laws, truth-in-advertising 
laws, attempts to internalize costs (such as pollution taxes), the removal of 
perverse subsidies, and other ways of leveling market playing fields.

None of which get far these days, because of the weakening of another set of 
negative feedback loops — those of democracy. This great system was invented 
to put self-correcting feedback between the people and their government. The 
people, informed about what their elected representatives do, respond by 
voting those representatives in or out of office. The process depends upon 
the free, full, unbiased flow of information back and forth between 
electorate and leaders. Billions of dollars are spent to limit and bias and 
dominate that flow. Give the people who want to distort market price signals 
the power to pay off government leaders, get the channels of communication to 
be self-interested corporate partners themselves, and none of the necessary 
negative feedbacks work well. Both market and democracy erode.

The strength of a negative 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 will fail. 
Democracy worked better before the advent of the brainwashing power of 
centralized mass communications. Traditional controls on fishing were 
sufficient until radar spotting and drift nets and other technologies made it 
possible for a few actors to wipe out the fish. The power of big industry 
calls for the power of big government to hold it in check; a global economy 
makes necessary a global government and global regulations.

Here are some examples of strengthening negative feedback controls to improve 
a system’s self-correcting abilities:

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,
monitoring systems to report on environmental damage,
protection for whistleblowers,
impact fees, pollution taxes, and performance bonds to recapture the 
externalized public costs of private benefits.
7. The gain around driving positive feedback loops.

A negative feedback loop is self-correcting; a positive feedback loop is 
self-reinforcing. The more it works, the more it gains power to work some 
more. 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 to soften rain and runoff, the more soil erodes. The 
more high-energy neutrons in the critical mass, the more they knock into 
nuclei and generate more.

Positive feedback loops are sources of growth, explosion, erosion, and 
collapse in systems. A system with an unchecked positive loop ultimately will 
destroy itself. That’s why there are so few of them. Usually a negative loop 
will kick in sooner or later. The epidemic will run out of infectable people 
— or people will take increasingly strong 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 stop overgrazing, put up checkdams, 
plant trees, and stop the erosion.

In all those examples, the first outcome is what will happen if the positive 
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 
positive loop — slowing the growth — is usually a more powerful leverage 
point in systems than strengthening negative loops, and much preferable to 
letting the positive loop run.

Population and economic growth rates in the world model are leverage points, 
because slowing them gives the many negative loops, through technology and 
markets and other forms of adaptation, all of which have limits and delays, 
time to function. It’s the same as slowing the car when you’re driving too 
fast, rather than calling for more responsive brakes or technical advances in 
steering.

Another example: there are many positive feedback loops in society that 
reward the winners of a competition with the resources to win even bigger 
next time. Systems folks call them “success to the successful” loops. 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; poor kids lose out. 
Anti-poverty programs are weak negative loops that try to counter these 
strong positive ones. It would be much more effective to weaken the positive 
loops. That’s what progressive income tax, inheritance tax, and universal 
high-quality public education programs are meant to do. (If rich people can 
buy government and weaken, rather than strengthen those of measures, the 
government, instead of balancing “success to the successful” loops, becomes 
just another instrument to reinforce them!)

The most interesting behavior that rapidly turning positive loops can trigger 
is chaos. This wild, unpredictable, unreplicable, and yet bounded behavior 
happens when a system starts changing much, much faster than its negative 
loops can react to it. For example, if you keep raising the capital growth 
rate in the world model, eventually you get to a point where one tiny 
increase more will shift the economy from exponential growth to oscillation. 
Another nudge upward gives the oscillation a double beat. And just the 
tiniest further nudge sends it into chaos.

I don’t expect the world economy to turn chaotic any time soon (not for that 
reason, anyway). That behavior occurs only in unrealistic parameter ranges, 
equivalent to doubling the size of the economy within a year. Real-world 
systems can turn chaotic, however, if something in them can grow or decline 
very fast. Fast-replicating bacteria or insect populations, very infectious 
epidemics, wild speculative bubbles in money systems, neutron fluxes in the 
guts of nuclear power plants. These systems are hard to control, and control 
must involve slowing down the positive feedbacks.

In more ordinary systems, look for leverage points around birth rates, 
interest 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. The structure of information flows (who does and does not have access to 
information).

There was this subdivision of identical houses, the story goes, except that 
for some reason the electric meter in some of the houses was installed in the 
basement and in others it was installed in the front hall, where the 
residents could see it constantly, going round faster or slower as they used 
more or less electricity. With no other change, with identical prices, 
electricity consumption was 30 percent lower in the houses where the meter 
was in the front hall.

We systems-heads 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 loop. It’s a NEW 
LOOP, delivering feedback to a place where it wasn’t going before.

A more recent example is the Toxic Release Inventory — the U.S. government’s 
requirement, instituted in 1986, that every factory releasing hazardous air 
pollutants report those emissions publicly every year. Suddenly every 
community could find out precisely what was coming out of the smokestacks in 
town. There was no law against those emissions, no fines, no determination of 
“safe” levels, just information. But by 1990 emissions dropped 40 percent. 
They’ve continued to go down since, not so much because of citizen outrage as 
because of corporate shame. One chemical company that found itself on the Top 
Ten Polluters list reduced its emissions by 90 percent, just to “get off that 
list.”

Missing feedback is one of 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 no 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 more scarce and hence more 
expensive, it becomes all the more profitable to go out and catch them. 
That’s a perverse feedback, a positive loop that leads to collapse.)

It’s important that the missing feedback be restored to the right place and 
in compelling form. To take another tragedy of the commons, 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 a 
water price that rises steeply as the pumping rate begins to exceed the 
recharge rate.

Compelling feedback. 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 outflow pipe. Suppose 
any public or private official who made the decision to invest in a nuclear 
power plant got the waste from that plant stored on his/her lawn. Suppose 
(this is an old one) the politicians who declare war were required to spend 
that war in the front lines.

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. The rules of the system (incentives, punishments, constraints).

The rules of the system define its scope, its boundaries, 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.

Mikhail Gorbachev came to power in the USSR and opened information flows 
(glasnost) and changed the economic rules (perestroika), and look what 
happened.

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 like that and what our behavior would 
be under them, we come to understand the power of rules. 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 who has power 
over them.

That’s why my systems intuition was sending off alarm bells as the new world 
trade system was explained to me. It is a system with rules designed by 
corporations, run by corporations, for the benefit of corporations. Its rules 
exclude almost any feedback from any other sector of society. Most of its 
meetings are closed even to the press (no information flow, no feedback). It 
forces nations into positive loops “racing to the bottom,” competing with 
each other to weaken environmental and social safeguards in order to attract 
corporate investment. It’s a recipe for unleashing “success to the 
successful” loops, until they generate enormous accumulations of power and 
huge centralized planning systems that will destroy themselves, just as the 
Soviet Union destroyed itself, and for similar systemic reasons.

4. The power to add, change, evolve, or self-organize 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, such as brains or wings or 
computers — adding new negative or positive 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 human 
immune system has the power to develop new responses to (some kinds of ) 
insults it has never before encountered. The human brain can take in new 
information and pop out completely new thoughts.

The power of self-organization seems so wondrous that we tend to regard it as 
mysterious, miraculous, manna from heaven. Economists often model technology 
as literal manna — coming from nowhere, costing nothing, increasing the 
productivity of an economy by some steady percent 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 under what conditions. As hundreds of self-organizing 
computer models have demonstrated, complex and delightful patterns can evolve 
from quite simple evolutionary algorithms. (That need not mean that 
real-world algorithms are simple, only that they can be.) The genetic code 
within the DNA that is the basis of all biological evolution contains just 
four different letters, combined into words of three letters each. That 
pattern, 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.

Self-organization is basically a matter of an evolutionary raw material — a 
highly variable stock of information from which to select possible patterns — 
and a means for experimentation, for selecting and testing new patterns. For 
biological evolution the raw material is DNA, one source of variety is 
spontaneous mutation, and the testing mechanism is something like punctuated 
Darwinian selection. For technology the raw material is the body of 
understanding science has accumulated and stored in libraries and in the 
brains of its practitioners. The source of variety is human creativity 
(whatever THAT is) and the selection mechanism can be whatever the market 
will reward, or whatever governments and foundations will fund, or whatever 
meets human needs.

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 are trained 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 not billions, but 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. I guess that’s because one aspect 
of almost every culture is the belief in the utter superiority of that 
culture.

Insistence on a single culture shuts down learning. 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.

The intervention point here is obvious, but unpopular. Encouraging 
variability and experimentation and diversity means “losing control.” Let a 
thousand flowers bloom and ANYTHING could happen! Who wants that? Let’s play 
it safe and push this leverage point in the wrong direction by wiping out 
biological, cultural, social, and market diversity!

3. The goals of the system.

Right there, the diversity-destroying consequence of the push for control, 
that 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 world of Islam, the People’s Republic of 
China, Wal-Mart, Disney, whatever), 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 upon 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 different selection mechanism, a different 
direction for evolution than anything the planet has seen so far.

As my little single-loop examples have shown, most negative 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 becomes ever more shielded from uncertainty. John Kenneth 
Galbraith recognized that corporate goal — to engulf everything — long ago.5 
<http://donellameadows.org/archives/leverage-points-places-to-intervene-in-a-system/#five>
 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 
negative 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 corporation to eliminate its competitors (and brainwash its 
customers and swallow its suppliers), 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 awhile 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. I have watched in wonder as — only very 
occasionally — a new leader in an organization, from Dartmouth College to 
Nazi Germany, comes in, enunciates a new goal, and swings hundreds or 
thousands or millions of perfectly intelligent, rational people off in a new 
direction.

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 U.S. and even the world 
has been changed since Reagan is testimony to the high leverage of 
articulating, meaning, repeating, standing up for, insisting upon new system 
goals.

2. The mindset or paradigm 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 
rules say, by fair means or foul, by complications, cheating, exemptions or 
deductions, by constant sniping at the rules, actual tax payments will push 
right up against the accepted idea of “fairness.”

The shared idea in the minds of society, the great big unstated assumptions — 
unstated because unnecessary to state; everyone already knows them — 
constitute that society’s paradigm, or deepest set of beliefs about how the 
world works. There is a difference between nouns and verbs. Money measures 
something real and has real meaning (therefore people who are paid less are 
literally worth less). Growth is good. Nature is a stock of resources to be 
converted to human purposes. Evolution stopped with the emergence of Homo 
sapiens. One can “own” land. Those are just a few of the paradigmatic 
assumptions of our current culture, all of which have utterly dumfounded 
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, flows and everything else about systems. No one has 
ever said that better than Ralph Waldo Emerson:

Every nation and every man instantly surround themselves with a material 
apparatus which exactly corresponds to … their state of thought. Observe how 
every truth and every error, each a thought of some man’s mind, clothes 
itself with societies, houses, cities, language, ceremonies, newspapers. 
Observe the ideas of the present day … see how timber, brick, lime, and stone 
have flown into convenient shape, obedient to the master idea reigning in the 
minds of many persons…. It follows, of course, that the least enlargement of 
ideas … would cause the most striking changes of external things.6 
<http://donellameadows.org/archives/leverage-points-places-to-intervene-in-a-system/#six>
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. (Except for blighted spaces, often near the skyscrapers, 
which we believe are worthless.) Whether it was Copernicus and Kepler showing 
that the earth is not the center of the universe, or Einstein hypothesizing 
that matter and energy are interchangeable, 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 transforms 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-to-highest. 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 
eyes, a new way of seeing. Whole societies are another matter — they resist 
challenges to their paradigm 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,7 
<http://donellameadows.org/archives/leverage-points-places-to-intervene-in-a-system/#seven>
 has a lot to say about that. In a nutshell, you keep pointing at the 
anomalies and failures in the old paradigm, you keep coming yourself, and 
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 folks would say you change paradigms by modeling a system, which 
takes you outside the system and forces you to see it whole. We say that 
because our own paradigms have been changed that way.

1. The power to transcend 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, in the notion or experience 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 (or put in the name of your favorite deity here) and 
do his, her, its will, which is probably a lot better informed than your will.

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 have impacts that last for millennia.

A Final Caution

Back from the sublime to the ridiculous, from enlightenment to caveats. There 
is so much that has to be said to qualify this list. It is tentative 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 a Superwoman. The higher 
the leverage point, the more the system will resist changing it — that’s why 
societies have to rub out truly enlightened beings.

Magical leverage points are not easily accessible, even if we know where they 
are and which direction to push on 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.

 

J.W. Forrester, World Dynamics, Portland OR, Productivity Press, 1971
J.W. Forrester, Urban Dynamics, Portland OR, Productivity Press, 1969.
Thanks to David Holmstrom of Santiago, Chile.
For an example, see Dennis Meadows’s model of commodity price fluctuations: 
D.L. Meadows, Dynamics of Commodity Production Cycles, Portland OR, 1970.
John Kenneth Galbraith, The New Industrial State, 1967.
Ralph Waldo Emerson, “War,” (lecture delivered in Boston, March, 1838). 
Reprinted in Emerson’s Complete Works, vol. XI, Boston, Houghton, Mifflin & 
Co., 1887, p. 177.
Thomas Kuhn, The Structure of Scientific Revolutions, Chicago, University of 
Chicago Press, 1962.