Leverage point

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Leverage points are part of system analysis and system dynamics (more at page System Dynamics).

Definition of 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." [1]


In the case of system analysis the definition for system is: "System is a set of elements whose interconnections determine their behaviour and the behaviour of the entire system." [2]
Important notion is that the systems modelled can be complex. Leverage points are even in such grand models such as the model of the world. The limits of scope and detail can be set by what problem we are trying to solve.
In complex systems it is almost necessary to focus effort of change (in solving problems) into those points, where least effort brings biggest change.
The idea of leverage points is not unique to system analysis. The cure-all, the magic password, have been known for ages. Leverage points are points of power.

Key Principles

Here are some key principles that one has to bear in mind when finding/dealing with leverage points: [2]
• While fixating on parts, we miss understanding the whole
• Actions can have cascading effect over time
• There can be unintended consequences
• Find most important places for intervention, to change the long-term behaviour of a system

Understanding leverage points

In an already established system, leverage points are usually already known to exist.
People find them intuitively and focus attention to them, however they can do so in the wrong direction, yielding results contrary to expectation.
To further grasp the concept of leverage points and how people intuitively find the wrong conclusions, here are some examples:[1]

Example: World Model

When looking at problems like poverty, hunger, resource depletion or environmental destruction, their leverage point is growth.
Not only that of population, but also economical. Growth has both positive and negative feedback.
The nations and corporations focus on positive growth thinking it solves the problems, but in some things the growth needs to be slowed down or even negative.

Example: Low-income Housing

The problem is how to house low-income citizens. Many cities have implemented programs to build such houses, but it turned out,
that the less of such houses in a city the better for the city (even for low-income citizens). Nowadays cities are tearing down such structures.


Leverage points are counter intuitive. Or if intuitive we use them backwards, worsening the problems they were meant to solve.
Finding leverage points in an already established system (by studying it) isn’t all that hard, however in a new system it is quite so.
Another problem is that when leverage points are discovered, it is hard to convince others of the correct approach because of the counter intuitiveness.

Places to intervene in a system

Donella Meadows [1] wrote an amazing scientific paper which is easy to understand, useful in real-life and cuts to the core of the problem.
Since most internet articles heavily link to her paper, I consider this the fundamental basis of understanding leverage points.
Below are 12 principles / places where to intervene in a system, ordered from least to most effective.
The points are taken from the paper and the description of each point is my understanding of how D. Meadows described them.

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

Numbers and their influence on the system, they can change, but they would only speed up / slow the rate of flow, hence the least effect.
Example: how much is invested into medical research vs military stealth bombers.
A lot of attention goes to setting parameters, but the effect is far from efficient. Not that they aren’t important, they are – especially in short term.
The focus here is however to change behaviour – long lasting efficiency.

11. The sizes of buffers and other stabilizing stocks, relative to their flows

A sort of “inventory” to keep, so that the stock is large enough for the amount of flow. Big buffer provides stability, but can become inflexible, it also comes at an expense.
But even a small stock can be good in certain circumstances (just-in-time, lean). Some buffers are physical and hard to change (water dam), this is why they are low in the list.

10. The structure of material stocks and flows (such as transport networks, population age structures)

The only way to fix a system that is laid out wrong is to rebuild it. This is however slowest and most expensive, sometimes unchangeable.
This puts them down the list, even though they have great effect, changing them ex post is just too expensive.

9. The lengths of delays, relative to the rate of system change

Delays cause oscillations. Delay in feedback is relative to rates of change in the stocks that the feedback loop is trying to control.
It is usually easier to slow down the change rate so that delays don’t cause so much trouble, and that’s why slowing economic growth in the world model is better,
so if there is a delay that can be changed it is great to do so, however it has to be in the right direction.

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

A complex system usually has numerous negative feedback loops so it can self-correct under different conditions.
They might not be used on a regular basis and serve as a form of emergency mechanisms, the fault here would be to get rid of them, which compromises the long-term welfare of the system.
Example: Price in supply demand chart, the real leverage in this case would be laws to keep the suppliers in check. Another example would be exercising to keep body in good health.
The strength of a negative feedback loop is important relative to the impact it is designed to correct.

7. The gain around driving positive feedback loops

Positive feedback loop is self-reinforcing. They are source of growth and collapse (unchecked loop).
(More people with flu -> more infected people; more money in bank -> more interest -> more money.)
Reducing gain from positive loops is usually more powerful than strengthening negative loops.
Example: Rich get richer, poor get poorer. Introducing anti-poverty laws has less effect than progressive income tax.

6. The structure of information flows (who does and does not have access to information)

Having information which previously wasn’t available creates a whole new loop of feedback. Missing feedback causes system malfunctions.
Adding information can be a powerful intervention – easy and cheap in comparison to other leverage points.
Important is that the information gets to the right place and in the right form (where someone can use it and understands it).

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

Rules are very powerful tools. To get a scope of how much one can imagine how a system would work if there would be change in rules,
for example if teachers would get paid by solving real-world problems instead of writing academical papers, if there would be no degrees and the sole purpose of going to university would be to learn something and leave when you’ve learnt it.
Power over the rules is real power – high leverage points.

4. The power to add, change, evolve, or self-organize system structure

The ability to self-organize is the strongest form of system resilience. Adaptive system can survive almost any change, by changing itself.
In economical systems it is usually caused by technology. To find which way to ‘evolve’ the system has to experiment and invite diversity.
However, this is perceived as losing control and hard to push through. This works in living organisms (which are systems), much harder to control in an organization or economy – the problem is that you can’t really control it.

3. The goals of the system

The goal is high on the list because every point below it must work ‘for it’. Sometimes even people within system don’t recognize the whole-system goal (laying bricks vs building a cathedral).

2. The mindset or paradigm out of which the system — its goals, structure, rules, delays, parameters — arises

Shared idea, unstated, something everyone already knows – this creates a paradigm. They are source of systems, a base for system goals, flows, feedbacks etc.
Changing a paradigm completely transforms systems. Paradigms are extremely hard to change, yet such process has no cost nor material change required.
One way of changing a paradigm is to model the system, which creates a view outside the system and makes us see it whole.

1. The power to transcend paradigms.

To look at things without paradigms; to reach enlightenment and see things purely objectively. Nearly impossible to reach yet stated as the final, most effective leverage point.