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Twelve Leverage Points [Business Models
Posted on May 30, 2014 @ 10:06:00 AM by Paul Meagher

Lately I've been studying systems thinking and have blogged recently about some of what I've learned (i.e., Systems Thinking and Sustainability, Aspirational Networks of Collaboration, Diagramming Systems, Limits To Growth). My recent interest in this area has been inspired by my discovery of, and appreciation for, the work of the late Donella Meadows. I'm nearing the end of her book Thinking in Systems: A Primer (2008) Chelsea Green Publishing. Her second last chapter is "Leverage Points - Places to Intervene in a System" and in today's blog I want to share some of her thinking on finding leverage points in a system.

It is an interesting exercise to develop systems models so that you can better understand a particular system such as a business in a particular industry and the factors leading to its growth or decline. The business could be represented as a capital stock that is subject to positive feedback loops leading to growth and negative or balancing feedback loops constraining or leading to the decline of capital stock. This is all fine and good, but how do we influence the system so as to increase the growth of the business or change it in some other manner (e.g., towards a goal of efficiency, sustainability, democracy, etc...). The answer is that we have to find the leverage points in the system that enable us to make the desired changes.

Finding a leverage point in a system is easier said than done. Even when you find the leverage point, there is the disturbing tendency in complex systems to react in the exact opposite way you want the system to when you start to apply leverage. We all know this system tendency when trying to raise children to be polite, hardworking, and rule abiding. Sometimes our interventions produce the exact opposite result. So finding the appropriate leverage point or points and applying leverage in the appropriate way are both difficult and subtle undertakings.

An important benefit of systems thinking is that it allows us to appreciate the large number of possible leverage points that any system has and that some of these leverage points have a greater or lesser effect on the system than others. Donella compiled a list of 12 leverage points in her thinking about systems which I want to share with you today. You can read Donella's book to find more discussion on the nature of these leverage points. They are extremely useful to be aware of and to think about if you want to change a system in some way. The 12 leverage points are listed below with the least powerful interventions first followed by the most powerful interventions at the bottom. Keep in mind that sometimes you don't want or need to use the most powerful interventions and oftentimes we end up using weak interventions when we try to change a system when more powerful ones are required. So without further ado, here are the 12 leverage points with some discussion (this was reproduced from Wikipedia's page Twelve leverage points which uses a Lake as the system under consideration):

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

    Parameters are points of lowest leverage effects. Though they are the most clearly perceived among all leverages, they rarely change behaviors and therefore have little long-term effect.

    For example, climate parameters may not be changed easily (the amount of rain, the evapotranspiration rate, the temperature of the water), but they are the ones people think of first (they remember that in their youth, it was certainly raining more). These parameters are indeed very important. But even if changed (improvement of upper river stream to canalize incoming water), they will not change behavior much (the debit will probably not dramatically decrease).

  2. The size of buffers and other stabilizing stocks, relative to their flows

    A buffer's ability to stabilize a system is important when the stock amount is much higher than the potential amount of inflows or outflows. In the lake, the water is the buffer: if there's a lot more of it than inflow/outflow, the system stays stable.

    For example, the inhabitants are worried the lake fish might die as a consequence of hot water release directly in the lake without any previous cooling off.

    However, the water in the lake has a large heat capacity, so it's a strong thermic buffer. Provided the release is done at low enough depth, under the thermocline, and the lake volume is big enough, the buffering capacity of the water might prevent any extinction from excess temperature.

    Buffers can improve a system, but they are often physical entities whose size is critical and can't be changed easily.

  3. Structure of material stocks and flows (such as transport network, population age structures)

    A system's structure may have enormous effect on operations, but may be difficult or prohibitively expensive to change. Fluctuations, limitations, and bottlenecks may be easier to address.

    For example, the inhabitants are worried about their lake getting polluted, as the industry releases chemical pollutants directly in the water without any previous treatment. The system might need the used water to be diverted to a wastewater treatment plant, but this requires rebuilding the underground used water system (which could be quite expensive).

  4. Length of delays, relative to the rate of system changes

    Information received too quickly or too late can cause over- or underreaction, even oscillations.

    For example, the city council is considering building the wastewater treatment plant. However, the plant will take 5 years to be built, and will last about 30 years. The first delay will prevent the water being cleaned up within the first 5 years, while the second delay will make it impossible to build a plant with exactly the right capacity.

  5. Strength of negative feedback loops, relative to the effect they are trying to correct against

    A negative feedback loop slows down a process, tending to promote stability. The loop will keep the stock near the goal, thanks to parameters, accuracy and speed of information feedback, and size of correcting flows.

    For example, one way to avoid the lake getting more and more polluted might be through setting up an additional levy on the industrial plant based on measured concentrations of its effluent. Say the plant management has to pay into a water management fund, on a weekly or monthly basis, depending on the actual amount of waste found in the lake; they will, in this case, receive a direct benefit not just from reducing their waste output, but actually reducing it enough to achieve the desired effect of reducing concentrations in the lake. They cannot benefit from "doing damage more slowly" -- only from actually helping. If cutting emissions, even to zero, is insufficient to allow the lake to naturally purge the waste, then they will still be on the hook for cleanup. This is similar to the US "Superfund" system, and follows the widely accepted "polluter pays" principle.

  6. Gain around driving positive feedback loops

    A positive feedback loop speeds up a process. Meadows indicates that in most cases, it is preferable to slow down a positive loop, rather than speeding up a negative one.

    The eutrophication of a lake is a typical feedback loop that goes wild. In a eutrophic lake (which means well-nourished), lots of life can be supported (fish included).

    An increase of nutrients will lead to an increase of productivity, growth of phytoplankton first, using up as much nutrients as possible, followed by growth of zooplankton, feeding up on the first ones, and increase of fish populations. The more available nutrients there are, the more productivity is increased. As plankton organisms die, they fall to the bottom of the lake, where their matter is degraded by decomposers.

    However, this degradation uses up available oxygen, and in the presence of huge amounts of organic matter to degrade, the medium progressively becomes anoxic (there is no more oxygen available). In time, all oxygen-dependent life dies, and the lake becomes a smelly anoxic place where no life can be supported (in particular no fish).

  7. Structure of information flow (who does and does not have access to what kinds of information)

    Information flow is neither a parameter, nor a reinforcing or slowing loop, but a loop that delivers new information. It is cheaper and easier to change information flows than it is to change structure.

    For example, a monthly public report of water pollution level, especially nearby the industrial release, could have a lot of effect on people's opinions regarding the industry, and lead to changes in the waste water level of pollution.

  8. Rules of the system (such as incentives, punishment, constraints)

    Pay attention to rules, and to who makes them.

    For example, a strengthening of the law related to chemicals release limits, or an increase of the tax amount for any water containing a given pollutant, will have a very strong effect on the lake water quality.

  9. Power to add, change, evolve, or self-organize system structure

    Self-organization describes a system's ability to change itself by creating new structures, adding new negative and positive feedback loops, promoting new information flows, or making new rules.

    For example, microorganisms have the ability to not only change to fit their new polluted environment, but also to undergo an evolution that makes them able to biodegrade or bioaccumulate chemical pollutants. This capacity of part of the system to participate in its own eco-evolution is a major leverage for change.

  10. Goal of the system

    Changing goals changes every item listed above: parameters, feedback loops, information and self-organization.

    A city council decision might be to change the goal of the lake from making it a free facility for public and private use, to a more tourist oriented facility or a conservation area. That goal change will effect several of the above leverage points: information on water quality will become mandatory and legal punishment will be set for any illegal effluent.

  11. Mindset or paradigm that the system — its goals, structure, rules, delays, parameters — arises from

    A societal paradigm is an idea, a shared unstated assumption, or a system of thought that is the foundation of complex social structures. Paradigms are very hard to change, but there are no limits to paradigm change. Meadows indicates paradigms might be changed by repeatedly and consistently pointing out anomalies and failures in the current paradigm to those with open minds.

    A current paradigm is "Nature is a stock of resources to be converted to human purpose". What might happen to the lake were this collective idea changed ?

  12. Power to transcend paradigms

    Transcending paradigms may go beyond challenging fundamental assumptions, into the realm of changing the values and priorities that lead to the assumptions, and being able to choose among value sets at will.

    Many today see Nature as a stock of resources to be converted to human purpose. Many Native Americans see Nature as a living god, to be loved, worshipped, and lived with. These views are incompatible, but perhaps another viewpoint could incorporate them both, along with others.

So the next time you decide that you want to intervene in a system, for example, to promote your business in your local newspaper, you might reflect on what type of intervention this is based on this list, how powerful that intervention is as a means to achieving your goal, and what other interventions might be possible. Donella's list of leverage points provides a useful resource for thinking about how to intervene in a system to make changes. To learn more, you can google "Twelve Leverage Points" and you'll find more discussion on these different types of leverage points applied to other example systems (as a result of such googling I came across Donella's chapter Leverage Points: Places to Intervene in a System which, in book form, inspired this blog). I'll end this blog with a nice visual representation of leverage points from Kallokain's blog post on Re-Imagining Agile. The Kallokain blog has some good blogs on systems thinking so check it out as well.


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