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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):
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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).
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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.
- 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).
- 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.
- 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.
- 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).
- 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.
- 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.
- 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.
- 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.
- 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 ?
- 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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Investment Pitching Patterns |
[Selling] |
Posted on May 22, 2014 @ 11:40:00 AM by Paul Meagher
Many entrepreneurs already know the best way to pitch their deal based on experience, however, some stuggle
to figure out a format to use. Today I want to discuss a couple of pitching patterns that might help you
come up with ideas about what to include in your pitch.
Oren Klaff is the author of a book "Pitch Anything" which I partially reviewed in my last blog
on Prizing Your Deal. In his section on Pitching Your Big Idea, Oren endorses the
Idea Introduction Pattern as a useful element to add to a pitch. The Idea Introduction Pattern was originally developed by venture capitalist, and popular business writer, Geoffrey Moore. Here is
Oren's version of the pattern (p.105):
For [target customers]
Who are dissatisfied with [the current offerings in the market].
My idea/product is a [new idea or product category]
That provides [key problem/solution features].
Unlike [the competing product].
My idea/product is [describe key features].
Below is an example of using the pattern, also from Oren's book. This particular pattern may have been the one Oren used when he was trying to get investors involved in financing a new Airport in California, a 1 billion dollar deal that the company he represented won the rights to obtain financing for:
For investors needing a 10 percent cash yield or better
Who are dissatisfied with risky investments such as stocks.
My airport deal is a project with low risk and lots of protection
That provides a current cash flow.
And unlike most development projects
You can cash out any time you want.
The Idea Introduction Pattern takes less than a minute to deliver in person so is not the whole of the pitch. When you are writing a pitch, however, an Idea Introduction Pattern as brief as this can form the
core, and possibly, the complete body of your pitch if done right. The objective of your pitch in the context of this site is to generate enough interest in your idea that an investor wants to connect with you to further
discuss you idea. The Idea Introduction Pattern is a good tool to have in your pitching toolkit to help make that happen.
In a twenty minute in-person pitch, Oren would also discuss out how large market forces are coming together to make this the right time for the idea and the deal. Oren's favorite forces are economic forces, technological forces, and social forces. Oren calls the combination of these three forces the "Three-Market-Forces Pattern". The basic idea is to frame your product or idea against the background of these evolving market forces. This is how Oren characterizes these forces (pp. 99-101):
- Economic forces. Briefly describe what has changed financially in the market for your big idea. For example, are customers wealthier, is credit more available, is financial optimism higher Increases or decreases in interest rates, inflation, and the value of the dollar are considered as prime examples of forces that have significant impact on business opportunities... Another example is The cost of making this product has just gone below the $10 mark. This means that the retail price can be $69. We've been waiting two years to hit this price point.
- Social forces. Highlight what emerging changes in people's behavior patterns exist for your big idea. An obvious example in the market for automobiles, concern over the environment - a social force - is driving demand for electric vehicles. Another example is One of the changes in our society is that people don't get enough sleep or even the right kind of sleep. While this problem is growing only 1.8 percent a year, awareness of it is skyrocketing. People know that they need better sleep; it is a hot topic at all levels of society.
- Technology forces. Technological change can flatten existing business models and even entire industries because demand shifts from one product to another. In electronics, for example, change is rapid and constant, but in furniture manufacturing, change is more gradual. An example of a technological force is This device requires a controlling chip and solenoid that now can be manufactured small enough and a a controllable price, allowing us mass-market capabilities.
When writing a pitch for this site, you probably can't spend too much time discussing all of these forces, but you probably can focus on at least one major force that might be relevant so as to position your idea as part of an evolutionary process leading to the current gap in the market for your product or service.
So if you are having trouble figuring out how to pitch your big idea, you now have two pitch patterns that you can use to help guide you to what to include in your pitch to investors. You can find out more about investment pitching patterns by googling "investment pitch patterns", "investment pitching templates", "investment pitchdecks", and so on. You might find some inspiration in the patterns that other entrepreneurs have used to successfully pitch their big idea.
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Prizing Your Deal |
[Selling] |
Posted on May 21, 2014 @ 08:47:00 AM by Paul Meagher
I just finished reading Oren Klaff's book Pitch Anything (2011) McGraw Hill.
I would rate it as a very entertaining read, filled with lots of humor, anecdotes and examples of his pitching
techniques in action, and a window into the world of pitching big deals worth many millions of dollars and, in
one case, a billion dollar deal (to be the company in charge of raising 1 billion for a new Airport complex
in California).
I thought the book would focus on the narrative elements of a good pitch but instead the book focuses more
on the psychology of the 20 minute pitch in front of 2 to 3 investors. It provides a useful inventory of
terminology and concepts to characterize all of the psychological elements that come into play during an
in-person pitch and how to mobilize them towards a successful deal.
The 20 minute time limit is what Oren feels is the appropriate amount of time to give yourself to pitch a deal
in person to an investor. Anymore and you start to lose the attention of the investor which is the main thing
you are wanting to manage during the pitch. Investors can start to lose their attention after the first 3 minutes
if they are not getting any novelty from the pitch, and even with novelty and a barrage of tricks and maneuverings
to maintain attention on the deal, investor's interest will likely start to wane after 20 minutes. That is a good
time to end the pitch and deal with potential questions.
In several places in the book, Oren stesses that a major deal killer is neediness, or "validation-seeking
behavior". Oren went through a bad stretch where he was unable to make a deal with several VC's he presented to
and his company was running out of money. He had successfully pitched large deals in the past, but now something
was different. He talked with a mentor about he last few presentations and eventually his mentor pointed out
the flaw. In his last presentation, after he gave what he thought was a great pitch, he said things like "Do
you still think it's a good deal?", "So, what do you think?", and "We can sign a deal right away if you want
us to?". These comments turned investor excitement over the deal into fear and anxiety. The proper frame of
mind to pitch in, according to Oren, is to "want nothing" so that you do not come off as needy. The other
adjustments are to focus on "prizing" - presenting the deal as a prize that the investor might not get in
on if they don't act. Prizing a deal is not simple to pull off and involves many psychological elements,
some of which Oren discusses in this YouTube video:
Oren argues that prizing works because of three fundamental behaviors of human beings (p. 64):
- We chase that which moves away from us.
- We want what we cannot have.
- We only place value on things what are difficult to obtain.
So if you are too eager to make a deal, or it is too easy to get what you have, then investors may not value
what you have. Behaving in this way, means that you are failing to prize your deal.
Prizing is only one of the psychological techniques Oren discusses in his book, but this should give you
a flavor of some of the unique psychology that potentially goes into successful pitching and deal making.
In my next blog, I want to focus more on Oren's discussion of the narrative elements to include in a good pitch.
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Limits to Growth |
[Growth] |
Posted on May 16, 2014 @ 02:27:00 AM by Paul Meagher
Today's blog title, "Limits to Growth", is inspired by the work of Donella Meadows whose work I've been reading lately. See my last few blogs.
"Limits To Growth" was a pioneering and best-selling book from 1972 whose main author was Donella Meadows. This book has been updated 3 times since then,the most recent version was published in 2005 (4 yrs after her death). It is a foundational book on sustainability.
For me, "Limits to Growth" also refers to a specific section in Donella's posthumously published book "Thinking in Systems" (2008, 7 years after her death) in which she provides some very insightful advice to startups. The specific passage occurs between pages 100-103 in a section
called "Layers of Limits". The basic idea is that startups grow by overcoming limits. They stop growing if they can
not overcome such limits. Simple ideas, but operating in reverse to the way we might normally think about growth (i.e, focus on positive growth factors only if you want a recipe for growth).
You can focus on trying to "grow" your company by listening to advice about how to grow your business.
Donella would argue you should focus on identifying and overcoming the "limits" of your company to grow your business.
There are four key paragraphs in "Thinking In Systems" in which Donella lays out her argument for the importance of
overcoming limits as the key to startup growth:
It was with regard to grain that Justus von Liebig came up with his famous "law of the minimum." It doesn't matter how much
nitrogen is available to the grain, he said, if what's short is phosphorus. It does no good to pour on more phosphorus, if
the problem is low potassium.
...
This concept of a Limiting Factor is simple and widely misunderstood. Agronomists assume, for example, that they know
what to put in an artificial fertilizer, because they have identified many of the major and minor ingredients in good soil. Are
there any essential nutrients they have not identified? How do artifical fertilizers affect soil microbe communities? Do they
interfere with, and therefore limit, any other functions of good soil? And what limits the production of artifical fertilizers?
...
There are layers of limits around every growing plant, child, epidemic, new product, techological advance, company, city, economy,
and population. Insight comes not only from recognizing which factor is limiting, but from seeing that growth itself
depletes or enhances limits and therefore changes what is limiting. The interplay between plant growth and the soil, a growing
company and its market, a growing economy and its resouce base, is dynamic. Whenever one factor ceases to be limiting, growth occurs,
and the growth itself changes the relative scarcity of factors until another potential limiting factor is to gain real understanding
of, and control over, the growth process.
...
The company may hire salespeople, for example, who are so good that they generate orders faster than the factory can produce.
Delivery delays increase and customers are lost, because production capacity is the most limiting factor. So the managers expand
the capital stock of production plants. New people are hired in a hurry and trained too little. Quality suffers and customers
are lost because labor skill is the most limiting factor. So manage the order-fulfillment and record-keeping system clogs.
And so forth.
So, in one book, Donella argues that there are ecological limits to growth in general. In another book, she argues that startup growth
is also subject to "layers of limits". The concepts of growth and limits appear to be inseparable in many ways and at many layers of a company.
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Diagramming Systems |
[Business Models] |
Posted on May 9, 2014 @ 08:21:00 AM by Paul Meagher
To attain better mastery of systems theory, I thought that a good exercise would be to diagram a system in the way that Donella Meadows suggested they be diagrammed by using a "stock and flow" diagram. Donella's book, Thinking in Systems: A Primer, provides many examples of system diagrams for many different types of systems. This is one reason it is such a useful book - it provides many templates to get you started with. The system that I chose to develop my own diagram for is Donella's version of the "Ecomomic System" (she calls it the "heart of the economic system"). I chose to diagram this system for two reasons: 1) It is an simple diagram of a complex system that nevertheless provides useful insight, 2) it includes most of the basic devices used in stock and flow systems diagramming. Here is my diagram of the "Economic System" which just tries to copy Donella's version (i.e., learn by copying):
The exercise of copying Donella's systems diagram helped me to recognize some of the finer details of her diagrams. One thing to note is the labels "R" and "B" in the middle of the two loops. The label "R" stands for Reinforcing. In other words, it is a factor that makes the capital stock increase. The label "B" stands for "Balancing". It is a factor that diminishes capital stock. In any system, there is at least one reinforcing component and at least one balancing component. One lesson we might take from this is that when we think about business growth we often focus on the reinforcing component that produces the growth but we should keep in mind that there are also balancing forces preventing that growth from happening. The idea of viral growth suggests only reinforcing growth is at play, but at some point even viral growth gets balanced out. Yin and yang.
Another aspect of the diagram to note is the arrows that point to the two taps that are not part of a loop. These are "control variables" that have an influence on the level of your capital stock. In this case, one control variable on the input tap is the "investment fraction" (fraction of output that is reinvested into the economy) and the other control variable on the output tap is the "capital lifetime" (how quickly infrastructure starts to fail). It is important to note that control variables are not always under the control of someone. Nature can be the controller in some cases. If climate becomes more extreme, the capital lifetime of infrastructure can be reduced significantly. In the case of home heating, the flow of heat out of your building is controlled by the balancing loop of the temperature outside and is moderated by the level of insulation in your house. The control variable, temperature outside, is set by nature.
What distinguishes systems diagrams from other forms of modelling is the use of reinforcing, balancing, and control variables to depict how the entity being modelled works. Other forms of modelling that have arrows pointing from one part to another part might bear a resemblance to systems models, but if they don't conceptualize the arrows as control, reinforcing, or balancing, then they are probably not systems models per se.
According to Peter Senge, "systems thinking is not about fighting complexity with more complexity. It simply means stepping back and seeing patterns that are, when seen clearly, intuitive and easy to grasp". So a stylistic note for systems diagramming is not to get carried away with drawing loops, arrows, and boxes. In many cases, you are looking for the simplist diagram that provides useful insight into the system.
To design my systems diagram I used the http://www.draw.io website. It is a very powerful free online tool for drawing diagrams that I would recommend you try out. It took awhile to find the shape library that I wanted to use to represent the tap symbol. It also took awhile to get used to creating and editing the parts of the diagram but towards the end I found diagramming was happening at a good clip. You can save your diagram in various output formats from svg to png. Join the fun and use draw.io to create your own systems diagrams!
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Aspirational Networks of Collaboration |
[Business Models] |
Posted on May 7, 2014 @ 10:21:00 AM by Paul Meagher
In my last blog, Systems Thinking and Sustainability, I focused on the work of one leading Systems Thinker, Donella Meadows. Today I want to focus on the work of another leading Systems Thinker, Peter Senge, whose writings have been influential among business managers and organizational theorists.
Peter Senge promoted Systems Thinking in business, particularly management, with his best-selling business book The Fifth Discipline. More recently (2008), he wrote a book on sustainability called The Necessary Revolution. I haven't read the latter book because my wife discovered my recent purchase (second hand for $1.50) and she is reading it. She read his first book and says she is liking this one quite a bit. She is a manager in the Public Service.
I haven't watched a video of Peter Senge presenting in person so I searched on YouTube for any recent presentations he might have done to see what he is currently up to. I found a recent Youbube video (Oct. 2013) by Peter Senge doing a keynote presentation (1 hr 41 min) in which he discusses the importance of aspirational goals and networks of collaboration. Lots of interesting and useful ideas of relevance to the management of startups and innovative businesses. It provoked in me the idea that successful startups and innovative businesses might be conceptualized as Aspirational Networks of Collaboration, hence the title of this blog. The video below consists of Peter Senge delivering a presentation via teleconference for around 35 minutes. After that he takes questions. I'd recommend you to watch the first 22 minutes to get the aspirational networks of collaboration stuff, then flip to around the 35 minute mark to see him handle a few questions.
I have experience working in a poorly managed startup as an employee. I would rate as fairly important the idea that your employees have to be aspiring to a common goal if the organization is going to work. We had too many projects with no one project having most of the thunder. There was not enough rallying around a common cause, just a bunch of people working in different silos. We did manage to secure a good amount of funding because we had the networks of collaboration part running well through connections one of our founders had with a major investor and his network of associates. That network can fade away, however, if you are not producing economic results. The aspirational part is what helps you to do that. Without it, you are probably toast.
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