System Thinker Notebook

by James Shelley

This is a rough draft manuscript in development

Last updated on July 11, 2018, at 11:27 AM

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Copyright © 2018 by James Shelley (contact@jamesshelley.com)

System Thinker Notebook is released under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License


Acknowledgments

I would like to extend a heartfelt ‘thank you’ to Michael Ayres, Helene Berman, Eugenia Canas, Michael Clarke, Adam Fearnall, Janet Frood, Marc Langlois, Chris Moss, Abe Oudshoorn, Heenal Rajani, Matt Ross, and Andre Vashist for the many interesting conversations, shared resources, wisdom, coffees, and ideas along the way.

Introduction

In his 1964 book, Conduct of Inquiry, American philosopher Abraham Kaplan (1918–1993) recounts a popular allegory1 which he described as “the drunkard’s search.”

There is a story of a drunkard searching under a street lamp for his house key, which he had dropped some distance away. Asked why he didn’t look where he had dropped it, he replied, “It’s lighter here!” 2

It is easy to laugh at the poor illogical, inebriated fellow, but Kaplan’s point was quite serious: he cautioned that scientists are sometimes like the keyless drunkard – they are limited by searching with the light they already have. The process of scientific inquiry can only uncover the kind of truth that can be intuited, hypothesized, tested, and observed by experiment. The discipline of science is limited to the street lamp of science.

More recently, this phenomenon has been described as the “streetlight effect.”3We love to look for answers where the light is good… but just because visibility is high does not necessarily mean that the truth is in the vicinity. Groping blindly down dark alleyways offers little hope of insight. Better, we think, to camp out near the glimmer of knowledge we already have. But fixed street lamps limit the scope and proximity of your search, no matter how illuminating and promising they might appear to be.

The resource you are holding right now is simply intended to give you some new tools to find new places to look. For the past fifteen years, I have discovered time and time again that seeing the world through a ‘complex systems’ lens opens new avenues for exploring old questions. Whether working in strategic development, research, project design, or program evaluation, here are some flashlights and new lampposts to help broaden your search.

The only true voyage of discovery, the only fountain of Eternal Youth, would be not to visit strange lands but to possess other eyes, to behold the universe through the eyes of another, of a hundred others, to behold the hundred universes that each of them beholds, that each of them is…4

Please do not think of this document as a proper book. This is a rough manuscript. It is perpetually incomplete and in a state of constant revision. Every time I present, lecture, and coach complexity and systems theory, I walk away having gained far more insight from my ‘students’ than I impart. These pages represent the notes I am compiling along the way.

Opening the door to complexity means, in no uncertain terms, accepting the simple reality that all knowledge is fragmentary, incomplete, and provisional. To explore systems is to acknowledge one’s ignorance. This text is the growing and morphing over time, through pedagogy, research, and conversation. The premise of presenting a ‘final word’ on systems is categorical nonsense, and so this is a document in continual evolution and iteration. The version you are holding might have a glossy cover, but don’t be deceived. This text is a draft. I very intentionally describe it as a notebook – a notebook that I can share with others along the way.

It feels like no matter how long a workshop, session, or coaching term is scheduled, the time allotted is never long enough. My hope is that this collection of perspectives, questions, and approaches will provide you with some tools to continue the journey, long after our session. I consider this compilation effort a ‘success’ to the extent that it fosters ongoing conversation with your colleagues and contributes to the system-level analysis capacity of your organization.

Most everything that follows is derived from many, many other brilliant people. Their insights astound and humble me. I encourage you to drop this notebook and consult the citations whenever inclined to do so. I have not so much tried to duplicate or fully encapsulate the work of others, as much to describe only sufficiently enough to show how they might fit together. This ‘notebook’ is just a glorified directory of ideas, most of which I have either adopted or adapted from the work others.


Chapter I – Systems

Bathtub

Think of the bathtub at your house. It is pretty simple, right? You turn the taps the put the water in. You unplug the drain to take the water out.5

Seems straightforward, yes. But let’s draw a map to see where your bathtub works in the system. When you open the drain, where does the water go? If you live in an urban environment, the water enters an elaborate network of pipes in the municipal infrastructure. The water is treated. It is then discharged back into the ecological system, reentering the hydrological cycle of the planet once again.

Water, in turn, is harvested, chlorinated, pumped back through the municipal supply lines, and fills up your bathtub again. It is entirely possible that some molecules of water disappearing down the drain might come back into your bathtub through the faucets. In other words: your bathtub is not an island. Your so-called ‘simple’ bathtub is not so simple after all. It is directly connected to an immense network of water harvesting, supply, treatment, and discharge. And this process, in turn, is connected to the planet’s hydrological cycle.6

You have a desired temperature range in mind for your bath, which means that you have variable inflows — hot and cold. Hot water presumably has to travel from a heater or boiler somewhere, which requires another system of energy inflows and outflows to heat the water. The energy itself, in turn, was generated by a system of inflows and outflows

What makes your bathtub especially complex is that it is part of a network of bathtubs. Sure, on its own it may not seem very interesting, but attach the drain of your bathtub to a maze of pipes that empties into a reservoir along with a few million other bathtubs and you begin to appreciate the seismic influence that bathtubs have on your municipal infrastructure. The next time you are soaking in a hot bath, you might ask yourself, Where did the energy come to heat this water? A lump of coal? A barrel of oil? A split nucleus?

The inflows and outflows of your bathing are systemically interconnected with the inflows and outflows of a vast system of systems. There is nothing ‘simple’ about taking a bath. (For rural readers: even if your water comes from a well or spring, is heated by firewood in a kettle, and tossed behind a hedge or into a septic system, the interplay of systems is no less complex: consider the natural filtration of the well, the photosynthesis of the tree, and the water tables under your yard.)

However, we are still only scratching the surface of grasping the systemic nature of your bathtub. For example, consider the pipe that connects to the drain: where did the raw materials come from to make that pipe? How was the manufacturing of that pipe related to the economy? What laws or legislation that regulate the mining industry or local building codes influenced the creation of that pipe?

In a sense, but not in exaggeration, you could explain in one way or another how everything in the world is eventually ‘connected’ to your bathtub.

Air

Take a deep breath. Now, think about everything that has influenced the air you just inhaled: the HVAC in the building, the particulate matter from nearby vehicle exhaust, and even regional weather systems and atmospheric jet streams. And don’t forget about all the phytoplankton and plants that produced the oxygen diffusing into your blood at this very moment. Each breath is interconnected to a vast array of other systems: from the hydrological cycle of the planet, to policies regulating the automotive industry; from forests and oceans, to the mining for the raw materials to construct the duct work.

What is the most important thing to you right now? Not many of probably answer saying, “The atmosphere,” or “Phytoplankton.” This is interesting, because the very next breath you take utterly depends on them.

Pencil

Who knows how to make a pencil?

In 1958, an economist named Leonard Read pointed out that, in fact, no one knows how to make a pencil.7 The pencil, as simple as it might seem, is really the sum product of a vast range of specialities that are, collectively, more complex than any one person could accomplish:

Think of all the persons and the numberless skills that went into their fabrication: the mining of ore, the making of steel and its refinement into saws, axes, motors; the growing of hemp and bringing it through all the stages to heavy and strong rope; the logging camps with their beds and mess halls, the cookery and the raising of all the foods. Why, untold thousands of persons had a hand in every cup of coffee the loggers drink!

Thus the humble pencil, like virtually every human invention, is a testimony to the power of creative collaboration working through the synthesis of diverse disciplines.

There isn’t a single person in all these millions, including the president of the pencil company, who contributes more than a tiny, infinitesimal bit of know-how. From the standpoint of know-how the only difference between the miner of graphite in Ceylon and the logger in Oregon is in the type of know-how.

There is another contemporary edition of this thought experiment. As a design challenge in 2008, Thomas Thwaites set out to make a simple electric toaster from scratch with raw materials. After figuring out what he needed (copper, nickel, iron, oil for plastic, and so on) he was faced with sourcing questions: where could he get these materials himself, without industrial machinery and assistance? How could he even get to those places without accounting for the travel technologies and his footwear? Thwaites chronicles his journey in The Toaster Project8, which, like Read’s essay on the pencil, highlights the depth of interdependency we have on networks and one another for even the simplest of actions. Who actually knows how to make a slice of toast?


Chapter II – Complexity

Air, Guppies, and Carbon

First, what is complexity, anyway? It is a tricky concept to pin down. Here is an illustration. Consider the molecular makeup of these three objects: an empty room, a lump of carbon, and a guppy.9

The empty room may not look very interesting, but it is actually highly unstable: air molecules are colliding and interacting with each other in all sorts of unpredictable ways. An empty room is chaotic.

Think about a lump of carbon. Its molecular movement can be brought almost to a complete stop as its temperature decreases. Chilled carbon is static and unchanging.

Now, think about a guppy. Its molecular structure is much less chaotic than the empty room, but also more active than the lump of carbon. Unlike the room full of air, it is highly ordered and structured—but unlike the lump of carbon, it is neither inanimate nor fully stable. The simple guppy is a complex organism.

Recipes, Rockets, and Raising Children

In a popular report on health care system reform, Sholom Glouberman and Brenda Zimmerman describe the difference between simple, complicated, and complex systems by highlighting the following distinctions:

In simple problems like cooking by following a recipe, the recipe is essential. It is often tested to assure easy replication without the need for any particular expertise. Recipes produce standardized products and the best recipes give good results every time. Complicated problems, like sending a rocket to the moon, are different. Formulae or recipes are critical and necessary to resolve them but are often not sufficient. High levels of expertise in a variety of fields are necessary for success. Sending one rocket increases assurance that the next mission will be a success. In some critical ways, rockets are similar to each other and because of this there can be a relatively high degree of certainty of outcome. Raising a child, on the other hand, is a complex problem. Here, formulae have a much more limited application. Raising one child provides experience but no assurance of success with the next. Although expertise can contribute to the process in valuable ways, it provides neither necessary nor sufficient conditions to assure success. To some extent this is because every child is unique and must be understood as an individual. As a result there is always some uncertainty of the outcome. The complexity of the process and the lack of certainty do not lead us to the conclusion that it is impossible to raise a child.10

On one end of the continuum, following a recipe is a completely linear process: add the right ingredients, in the right amounts, cooked in precise conditions, and you can be pretty confident that the baked goods will turn out as intended. On the other end of the continuum, raising a child is an entirely nonlinear process: there is no parenting ‘style’ or practice that guarantees any results, and there is no way to predict for the events, opportunities, and tragedies that will come along. Formulae have limited applicability and expertise alone is not a sufficient ingredient for success. Children are complex because every relationship is unique, which means the dynamic of every relationship defies stringent rules and specification.

Glouberman and Zimmerman go on to argue that health care systems are complex. They are composed of human beings and they interact with human beings. Providing effective health care is therefore more like raising a child it is like baking cookies or sending a rocket into orbit.

The problem is that we want to intervene in health care systems as they are complicated systems, like rockets, not complex things, like parenting. If only we could align the right budgets, hire the right executives, develop the perfect strategy, then we would have the most ‘successful’ healthcare, or so we think.

Life = Disequilibrium

Comparing a guppy to a lump of coal and a room full of air illustrates one of the key characteristics of life itself. You could say disequilibrium is our raison d’être, at least in terms of biochemistry.

Suppose you are the guppy. If you came into perfect equilibrium with your environment, you would altogether cease to exist. The systems that are madly at work right now to keep you breathing and metabolizing are vigorously staving off the relentless forces of equilibrium for as long as they can. Life, the energy that holds your entire molecular structure together, is your stand against equilibrium. All the little bits of matter that make you a living organism are constantly being pulled towards disordered chaos, but so far you’ve managed to hold it all together.

If the tables were turned — if equilibrium were on our side — our biological existence would simply last forever. Instead, like a seed finding traction and nutrients in a crack of concrete, our existence is one of challenging the insurmountable problem of equilibrium for as long as possible.

What makes life special is not that we will one day ‘conquer’ equilibrium once and for all, but that we replicate ourselves in spite of the odds. If you pull up that little plant growing in the crack of concrete, another one will replace it. All around us, life is looking to take root, ready to pounce on any opportunity to exist, and ready to thwart equilibrium for just a little longer.

Eventually, equilibrium is guaranteed. It cannot be held at bay forever. Like every pendulum, you and I will eventually come to a state of complete rest. But if you are reading this today, it is because you are living and breathing for the cause of disequilibrium.

What makes you different than a rock?

If you, a guppy, and a rock were picked apart, piece by piece, you would both be little piles of atomic dust. Yet even though you are made of the same base materials when picked apart, you appear remarkably different in your present compositions as ‘rock’ and ‘guppy’ respectively.

So what makes something ‘alive?’ On first examination, the most obvious difference is that you and guppies can do things. While the rock just sits there – motionless unless kicked, rolled, or throw – you can move yourself and transport things. But to pinpoint the essential difference between you and rock, we must explore your greatest dissimilarity: you have a metabolism, the rock does not. The word metabolism comes from the Greek metabole, meaning ‘change’. To be alive requires an on-going exchange of resources between you and your environment. Life is give and take. The fundamental difference between you and the rock lies in your respective interaction and relationship with energy.

Metabolism

Every cell in your body does 5 things:

converts energy
digests nutrients
excretes waste
reproduces
takes in oxygen

Metabolism is made of two distinct processes:

catabolic — breaking compounds down (in order to release energy)
anabolic — building of compounds (which uses energy)

You are not only made up cells, but you only count as ‘living’ for as long as your body effectively mirrors the activities of your cells. In other words, you and your cells need to do exactly the same things, because you are ultimately the cells that compose you.

The Great Rebellion Against Entropy

The Italian doctor Santorio Sanctorius (1561–1636) devised a set of experiments to precisely measure fluctuations in his weight. He would regularly weigh himself before each meal, weigh the food and drink he was about to consume, and then weigh himself again after the meal. Then he would sit on a scale and watch his weight decrease over time. He would also weigh his urine and excrement, and calculated how much more goes into the body than ever seems to come out. He proved, beyond a shadow of a doubt, that most of what we consume just seems to disappear, through some kind of mysterious ‘insensible perspiration.’11

Of course, what we consume does not really disappear: it is metabolized, converted to the animating energy that we describe as ‘life’. Rocks only ‘do’ one thing: they erode. If your heart stopped beating (thus ceasing to circulate oxygen throughout your body) you would erode too. In fact, you’d disintegrate even faster than the rock. But while you are alive, your body valiantly battles erosion. Your body’s first and most important mission is to keep putting itself back together, at a molecular level. You do this by metabolizing enough energy to remain in a more-or-less consistent state of self-repair and regeneration.

Another notable dissimilarity is that the temperature of the rock is always moving towards equilibrium with its environment: put the rock in either a hot or cold place, and it will eventually become exactly the same temperature as the place you leave it. On the other hand, as long as you are alive, your system will do everything possible to keep your core internal body temperature steady, at about thirty-seven degrees celsius. What powers this remarkable thermal regulation? Enter: Sanctorius' ‘insensible perspiration’.

What is the point of this reflection? If we strip everything else away, perhaps the best way to describe life is that it is a planetary uprising against entropy. Life is a rebellion against the forces of dispersion and fragmentation. Our enemy is decay itself. Like the erosion of the rock, time always moves in the direction of order to disorder. Like the grains of sand on the beach, everything disintegrates and divides, ever smaller, and ever more scattered. Like an office desk or backyard shed, everything moves consistently towards disorganization. But then life shows up. One molecule at a time, life harvests whatever energy it can metabolize and organizes itself into a tiny erosion-battling machine – bacteria, plants, and animals alike. A general characteristic of all life seems to be “entropy reduction.”12

To be alive is to seek order. Literally, it’s in your genes, and it is an operation manifested by the activity every cell in your body.

Rodents, Whales, and You

Question: What does a rodent, a whale, and you have in common with each other?

Answer. This equation: q0 ~ M¾

q0 equals metabolic rate, M equals mass. The basal metabolism of warm-blooded animals is proportional to the three-quarter power of the body weight.13 This little formula is known as Kleiber’s Law. “From mice to cattle,” wrote Max Kleiber, “metabolic rate and body size are correlated.”14

Think of it this way: mammals have about a billion heartbeats to use in a lifetime. The mouse burns through their allotment in about three years (at about 500 heart beats per minute) while the whale stretches them out for up to 150 years (at around 9 beats per minute). The bigger the animal mass, the slower the metabolic rate, the longer the life — but the ratio of metabolic rate to mass remains amazingly the same.

The average heart rate for an adult human is 72 beats per minute, in keeping with the ratio. What makes humans somewhat of an outlier, however, is that we seem to get more heart beats: about 2.21 billion over a lifetime. (But this doesn’t make us particularly special: chickens are the other outlier, who have about 2.17 billion heartbeats. So don’t get cocky.)

A Coffee Mug in the Universe

My morning coffee reminds me of my predicament. It sits there, on my desk, freshly percolated, and still steaming. But an hour goes by, and its temperature returns to thermodynamic equilibrium with the rest of the room.

The last few sips, at this unsavoury temperature, retell the story of my own situation in an entropic universe. My coffee, like everything, moves only in one direction: from hot to cold.

What made my coffee hot in the first place? The energy that excited the molecular state of my mug – whether extracted from a coal mine or harvested from the solar radiation with photovoltaic cells – was a unique occurrence. Never again will that lump of coal be burned. Never again will that wave of radiation strike the Earth. Never again will that gust of wind push a turbine. Just as the coal mine cannot be replenished, the sun cannot be refuelled. From the vantage point of thermodynamics, the notion of truly renewable energy is an odd bit of make-believe. Entropy says that nothing can possibly be renewable forever. Even the gases that give rise to new stars must, eventually, run out. Therefore, the particular sequence of chemical interactions used to raise the temperature of my coffee will never be repeated: this instance of energy is a singularity.

Thus, the law of entropy states that everything moves towards disorder. The energy that was harnessed to heat my coffee has been distributed out into the world, now lost in chaotic non-usefulness. It was transferred to my hand, the air, and the desk upon which it was sitting. It irreversibly rushed towards uniformity with everything around it. Like the combustion that released it, it too is now gone. Irrecoverable.

Like the heat it once possessed, the structural integrity of my mug itself is no less susceptible to entropy. Just as rocks, mountains, and continents erode, it too will disintegrate. Like energy, matter is destined to scatter. Everything falls apart eventually, but systems — like our incredibly evolved metabolisms, for instance — give us a shot at life.

Fractals

Consider this pattern in nature:

The trunk of a tree divides into branches, which divide into sub-branches, which divide into twigs.

Water trickles from a puddle into a stream, which merges into a river, which merges into the ocean.

Blood from the heart travels through the aorta, which divides into arteries, which divide into capillaries.

The same branching ‘fan out’ pattern exists in the bronchioles of your lungs and dendrites of your nervous system.

If you ‘zoom in’ on a tree, you discover that a single, tiny twig shares the same basic structure and form of the whole tree, just smaller. You could think of the twig as a ‘fractal’ of the tree, a term coined in 1975 by Benoit Mandelbrot (1924–2010) to describe the geometry of nature. The natural world, he proposed, is not random at all, but it follows “strict order” self-similar, geometric properties.15 Thus, fractals provide a mathematical framework to measure the ratios and scales of ecological life.

Nature, honed for efficiency, works in scaling, self-replicating patterns. Life is created by repeating the form of itself at numerous scales of detail. In the domain of human invention and systems, our designs tend to follow similar fractal patterns:

Traffic from an expressway merges on to avenues, which divide into streets, which divide into driveways.

Decisions are made in boardrooms, disseminated through departments, assigned to teams, executed by individuals.

The data of an email message travels between routers, to a server, to a local network, to an email client.

Biological life is created as cells replicate themselves. The social and cultural lives we create for ourselves are, likewise, inherently self-replicating. A country is like a bigger version of a city, which is like a bigger version of a neighbourhood, which is like a bigger version of a family. A family, in turn, is like a bigger version of an individual – who is composed of mutually dependent cells giving rise to life. And yet, at the microscopic level, a single eukaryote cell looks like a bustling, complex metropolis, full of labour divisions and communication protocols. Here, in the world of fractals, we discover that everything is like a copy of something else.

Systems as Organisms

Seeing complexity, disequilibrium, and entropy help us understand how and why systems act like organisms. Remember the bathtub illustration? That system of mining, construction, repair, treatment, harvesting, and discharge has striking similarities to the complexity of your physical, metabolic biology. After all, water systems are built by living organisms for the purpose of providing dependable access to clean water.

This means we need to think about life systems – such as human societies and the organizations that humans make – differently than we think about other kinds of complicated problem.

Ant Colonies vs Combustion Engines

The capacity for self-organization is an important distinction between complex systems and complicated systems.

Like a rocket, a car engine is complicated: It has many interacting parts that are finely tuned and synchronized. It mechanistically converts energy into force. It is designed. It behaves predictably and controllably.

A colony of ants is complex: A single foraging ant randomly discovers a source of food, and then leaves a pheromone trail on its way back home. Another ant comes across the pheromone trail and follows it. If the second ant finds food at the end of the trail, it strengthens the pheromone signal of the path on its way back to the colony. If there are multiple routes to the same food source, the signal for the shortest path will become stronger since it requires less travel time – a feedback loop that eventually turns the most efficient path into the most popular path.

Complexity creates new forms and structures, but complicated systems remain static. On its own, the engine in your car cannot create new routes to the grocery store, no matter hoccw complicated the engine itself might be. On the other hand, a colony of ants will significantly alter the landscape of their environment.

The Belgian physical chemist Ilya Prigogine (1917–2003) pioneered the theory of “order through fluctuation.” He demonstrated that complexity creates order, even though the variables and processes might appear, at first glance, to be chaotic and random.16

It was the laws of thermodynamics unlocked discovery. Your car engine is an isolated (or closed) energy system. If you put the world’s most super-advanced car engine in your backyard and leave it there, it will do absolutely nothing (except cause an eyesore for your neighbours). No matter how complicated the engine may be, it will always rush to thermodynamic equilibrium with its environment (whether it is just sitting in the backyard or revved to its full combustion capacity on the highway).

While we are contemplating the thermodynamic state of the rusting engine, ants are busily going about the construction and expansion of their metropolises. Like us, ants do not live in equilibrium. Their existence depends on constantly exchanging matter and energy with their environment. (As we’ve discussed, the only time living creatures reach full equilibrium is when they die.) Prigogine described this as a “dissipative structure.” Out of the constant exchange/consumption of energy comes order: witness an army of ants cooperatively marching along a self-made path in order to sustain their community. Open energy systems are self-organizing. They must be self-organizing in order to exist at all.

Complexity provides an interesting vantage point on the world. We can see it everywhere: flocking birds, schooling fish, highway traffic, epidemic outbreaks, stock exchanges, viral memes, weather events, coral reefs, revolutions, and large crowds. Self-organization is all around us.

Like ants, it is impossible for us to go about our lives without participating in this massive, endless, collective project of self-organization. No matter how autonomous and unique we like to think of ourselves, our actions, interactions, ideas, and purchases are not unlike the pheromone trails of ants – signals and signs we leave for one another. Every time we move along a route, we create the conditions of the route for others. There is no such thing as non-participation in the colony we create: getting off the beaten path influences the conditions of the path just as much as being an advocate for it.

Beyond Newton

Many of the methodologies we use in science are grounded on a Newtonian view of the world. We assume that if we can measure and quantify cause and effect, gather enough data, and analyze our observations in a rational and systematic way, we’ll get at this ‘thing’ we call the truth. In many pursuits for knowledge, this strategy works beautifully.

However, there are some other latent assumptions in the Newtonian worldview. First, it assumes that everything can be taken apart and dissected. It sees everything as made of discreet parts. If the world was a giant piece of machinery, like a combustion engine or a clock, this would be a valid assumption, but you can’t necessarily explain the architecture or floor plan of an anthill by dissecting a bunch of ants and taking each molecule apart under a microscope. What ants – and humans – do together cannot be described by sheer reductionism. Brenda Zimmerman describes this distinction as the difference ‘clockware’ and complexity.17

Traditional methods of seeing the world compare its workings to a machine. We say “things are working like clockwork” or “like a well-oiled machine,” and people are seen as “human resources” who use management “tools.” By using a machine metaphor, of unconsciously, we ignore the living aspects of our world and our work.18

The psychologist Kurt Koffka said:

our reality is not a mere collocation of elemental facts, but consists of units in which no part exists by itself, where each part points beyond itself and implies a larger whole. Facts and significance cease to be two concepts belonging to different realms, since a fact is always a fact in an intrinsically coherent whole. We could solve no problem of organization by solving it for each point separately, one after the other; the solution had to come for the whole. Thus we see how the problem of significance is closely bound up with the problem of the relation between the whole and its parts. It has been said: The whole is more than the sum of its parts. It is more correct to say that the whole is something else than the sum of its parts, because summing is a meaningless procedure, whereas the whole-part relationship is meaningful.19

Segregation

Another interesting, and sobering, example of emergence can be seen a game theory model developed by Thomas Schelling. This mathematical model demonstrates how even highly tolerant individuals will divide into separate, racially identifiable communities based on a few very tendencies of behaviour.20

Consilience

William Whewell (1794–1866) was an accomplished polymath; his research included oceanology, mechanics, economics, and physics. He was also a poet and served as an Anglican priest. And he had a knack for coining new words.

Sometimes, he explained, disparate pieces of evidence “jump together” from across branches of science. If your physics discovery blatantly contradicts strong evidence from chemistry and biology, you have a serious dilemma on your hands – but when your physics harmoniously align with chemistry and biology, a beautiful validation occurs. “I will take the liberty of describing it by a particular phrase,” wrote Whewell, calling it the “Consilience of Inductions.”21

The Consilience of Inductions takes place when an Induction, obtained from one class of facts, coincides with an Induction, obtained from another different class. This Consilience is a test of the truth of the Theory in which it occurs.

Different kinds of inquiries into the natural world ought to provide results that are more or less unified. Whether you measure the distance between your home and office by an odometer in your car, a pedometer on your hip, GPS coordinates, or even lengths of tape, all the results should be fairly consistent with one another. If there is a lack of consilience between the measurements, you will rightly question the variance.

When the “facts” do not corroborate with each other, we have good reason to be suspicious of factuality.

Edward Wilson (b. 1929) argues that we need to look for consilience not only in the natural sciences, but across all disciplines of knowledge. Consider these four fields of research: environmental policy, ethics, social science, and biology. When you look at that list, intuition demonstrates how all four domains are interconnected. However, in the world of academics, these four pursuits are unique, highly specialized domains, each with “its own practitioners, language, modes of analysis, and standards of validation.” Consilience is what happens when the quadrants meet to inform and learn from one another.22

Physics emerges into chemistry
Chemistry emerges into biology
Biology emerges into psychology
Psychology emerges into sociology
Sociology emerges into economics, politics, history, and technology

Consilience hints at the presence of a unified theory, perhaps an equation upon which everything ultimately rests. It seems everything is made of other things: nucleon → atoms→ molecules → cells → tissue → organs → organisms → psychologies → social systems → societies → global system.

So an interesting question to ponder the next time you are awake at 3am: when do molecules become political?

Coopetition

Consider two rival airlines companies. In the United States, Delta Airlines and United Airways are fierce competitors. They go head-to-head for prime time slots, routes, airport boarding gates, and, most importantly of all, customers. They are corporate giants squared off against one another in a cutthroat, high-stakes market.

However, underneath the battle we see on the surface, these two competitors are in fact cooperating with each other in many ways. When Delta and United both contract Boeing to develop a more efficient airliner, the two companies benefit by sharing in the investment, thus lowering the cost of next-generation jets for both companies.23 Simply put, they are better at competing with each other when they cooperate with each other.

Look past the marketing and advertising: the airline industry, like every industry, is a massive interconnected web of suppliers, competitors, and partners. Airlines in direct competition with each other realize if they do not cooperate with other carriers to share airports and transit hubs, their ability to compete will essentially vanish. Of course, air carriers are just one example — wherever business transactions take place you can see some degree of cooperative coordination.

The word ‘coopetition’ has been used for a long time to describe this phenomenon in business. In 1911, an oyster packager named Kirk S. Pickett described his sales agent strategy as “co-operating with one another to develop more business for each of you. You are in co-opetition, not in competition.”24 More recently, in 1993, Ray Noorda wrote an article arguing that businesses need to think more strategically about how they mutually cooperate while they are competing against one another. Co-opetition is a globally occurring phenomenon in business: cooperation and competition happen at the same time.25

I recently went to the hardware store to buy a furnace filter. As with most purchases, many options were presented. Not only could I purchase multiple filter sizes, but there were also multiple brands of each filter size to choose from. True, all the brands were in competition to sell me their product, but yet they were also cooperating: distributing their product to a central retailer, largely co-investing in the same supply chain, and, of course, manufacturing standardized filter dimensions to fit my furnace. Past the first glance, competition can look and function a lot like cooperation.

Rather than deifying one and demonizing the other, a system lens should invite you to examine your world beyond the strict, divisive categories of competition and cooperation. A city that can cooperate enough to provide enough bread for all its citizens is a city that likely has strong competition between its bakeries. Competing helps us cooperate; cooperating helps us compete. Today, as both a competitor and cooperator, take a moment and appreciate the symmetry.

Life as Cooperation?

Let’s imagine that you are in charge of creating a new animal species.

Ground rules: you must play by the basic laws of life, remembering that about four-fifths of your own genetic makeup is the same as mice.26 In other words, you can be imaginative, but not too imaginative! Your experimental creature must be a plausible inhabitant on Earth, so it needs to follow the same processes that apply to all living things we know. Three-part DNA nucleotide codes must signify the same amino acid proteins – just as they do in you, me, guppies, bacteria, and trees.

In order to survive, your creature must internally cooperate with itself: the genes in their genomes, the cells in their tissues — and all the innumerable subprocesses must work in conjunction with one another.

Here is another question: how will your new animal interact socially? How will it treat members of its own species? Will your species have a hierarchical society or exist in virtual isolation? Will it live in herds and packs, or solitarily, only interacting for the purpose of procreation? You must exercise a rigorous cost/benefit analysis here: in a collective herd, the ability of your species to notice (and thus escape) predators increases significantly, but living in a herd will also increase the competition for food within your species. Also, a highly cooperative clan of animals might have a lower breeding rate in order to reciprocally help nurture their young infants — but this comes at the expense of not otherwise producing more offspring.27

As in the human species, the consequence of cooperating at the collective level is often greater competition at the individual level. Whether in the microscopic, cellular domain or at the scale of behavioural interaction, cooperation and coopetition are usually causations of each other. Barely can one exist without necessitating and precipitating the other. When two animals fight over the right to mate, their vicious competition results in improving the strength of the herd. Conversely, when the employees of a business firm effectively cooperate with one another, they tend to out-perform their competition. A highly competitive sports team is marked by high levels of teamwork and cooperation. Cooperation and competition are inseparable: they make each other happen.

Whether it was the formation of your own genetic identity at conception, or the capacity of one business to rise above another company, or even the survival rate of your imaginative species, one remarkable observation bears noting: the better we tend to be at cooperating, the better we tend to be at competing, and vice versa.

As individuals, we seem disposed to emphasize (and moralize) one above the other. On the left, in praise of interdependency, we deem that cooperation is superior to competition. On the right, in praise of fairness, we deem that competition is superior to cooperation. From a systems perspective, the two tend to merge in praxis.

For the Want of a Nail

For want of a nail the shoe was lost.
For want of a shoe the horse was lost.
For want of a horse the rider was lost.
For want of a rider the message was lost.
For want of a message the battle was lost.
For want of a battle the kingdom was lost.
And all for the want of a horseshoe nail.28

In complexity theory, we might describe the absence of the horseshoe nail as an initial condition. Even the slightest change in an initial condition can have system-wide consequences. This is memorably illustrated by mathematician and meteorologist Edward Lorenz’s (1917–2008) famous question, “Does the flap of a butterfly’s wings in Brazil set off a tornado in Texas?”29

What prompted Lorenz’s question? Using computer simulation models to predict weather patterns, Lorenz realized that even seemingly insignificant differences at the start of an algorithm lead to far-reaching and wildly different results. Initial conditions, it turns out, directly impact end results.

The key idea here is that complexity is not randomness. At first glance, unpredictable, non-linear, non-repeating patterns appear to us as utterly baffling and incomprehensible. There is no rhyme or reason to it; sheer haphazardness defies explanation. But Lorenz developed a mathematical framework to show that the disintegration of order and stability – whether a tropical cyclone or a social uprising – is actually not random at all. Instead, the cyclone and uprising were destined to occur precisely because of initial conditions. This, he explains, is deterministic chaos.

However, no matter how determined chaos might be, it is still entirely unpredictable. The lack of a horseshoe defined the fate of the kingdom, but it was absolutely impossible to anticipate the importance of a single horseshoe at the outset. Why? The horseshoe is only one of innumerable variables, any one of which, when examined on its own, is too insignificant to measure. Just like the flapping wings of a butterfly.

This can be a tricky notion to wrap our human brains around: just because something is unpredictable does not mean that it is random. Today, right now, the weather outside of your window is not random at all. It is the incalculable result of innumerable causations. And, like the present meteorological conditions, the events of your day will also unfold in this chaotically destined world.

Consider this: Since you started reading this chapter, the variables of your day have already shifted. Every millisecond you spend reading this paragraph repositions the course of your future. Sit and contemplate this paragraph for an extra minute and you may, or may not, ‘just happen’ to have a conversation with the person in the line ahead of you at the cafe. Who knows the ramifications of this potential interaction? Whatever the case, you can only unravel the chains of causality in reverse. Or, as another saying goes: hindsight is 20/20.

Blackout

On Thursday, August 14, 2003, just after 4:10 p.m., an estimated 10 million people in Ontario and 45 million people in eight U.S. states were affected by a power outage.

The cause of this massive power grid failure? A tree in Ohio. As millions of people turned on their air conditioners on a hot summer day, some electrical lines heated and expanded near Akron, Ohio. The transmission lines came in contact with foliage. A software ‘bug’ in the energy management control software failed send an automated alert to neighbouring power stations to redistribute the load adequately. This created a vicious cycle of subsequent power stations passing on the overload down the chain. What would have otherwise been a localized blackout cascaded into massive grid failure.

A hot day. A tree. And a software bug…all that is need to disrupt electrical power to 55 million people.

When the power went I out, I was sitting in a coffee shop in a meeting with my boss. Due to franchise rules, the staff informed us that customers are required vacate the premises in the event of a power failure. We were duly ushered outside.

At what point did the tree in Ohio and the software bug ‘connect’ to my life? Was the tree wholly ‘separate’ from my life until the moment it touched the wire? What about the software bug that overloaded the system?

The fact that one tree and a program error in Ohio can suddenly affect the lives of millions of people demonstrates an important principle of complexity: increasing interconnectedness increases the rapidity of change. The more interconnected we are, the higher the chance that a very small event in one part of the system can have significant consequences across the entire system. Interconnectedness increases the speed of change. As the world grows increasingly connected, examples of this proliferate:

Pandemics that would have once been regionally isolated can now spread around the world in mere hours via transoceanic flights.

A natural disaster in one part of the world disrupt commodity and service delivery elsewhere – and therefore economies – in other parts of the world.

Increased social connectedness via social media can facilitate social upheaval, such as the Arab Spring, and the stories and messages of social upheaval in one region can trigger further upheaval elsewhere.

A general observation in complexity: greater connectivity tends to equate to faster change.


Chapter III – Actions

Leadership

If we live and work in systems, how do we create systemic change? Is change possible? Systems thinking, most simply, is a way of describing how interconnected, complex relationships operate, and then hypothesizing and postulating how we can change and adapt these environments.

This simple definition raises important personal questions:

If you adopt and internalize the proposition that everything is connected, how will this assumption change the way you make decisions?

How do you intentionally nurture your capacity and curiosity to see more of the big picture?

Stock and Flow

Remember our bathtub? The amount of water in the bathtub is the stock. Water can accumulate in the bathtub by entering (inflow) through the faucet or leave by going down the drain (outflow). If the inflow is greater than the outflow, the stock (in this case, the water) rises.

Whereas stock is the level (or amount) of water in the bathtub, flow is the rate (or speed) at which the bathtub can be filled or emptied. Think of the stock of Lake Erie relative to the flow of Niagara Falls. Here are some other examples:

Suppose you own a mountain or a forest full of trees. Stock is the number and volume of trees that you own. Outflow is the time it takes to harvest the lumber and turn it into toothpicks or paper. Inflow is the time it takes for your next generation of trees to be planted and mature.

Think about your recent bank statement. Stock is the balance you have sitting in your account. Flow is the rate at which your earnings are deposited and your expenses are debited.

In a large urban centre, there is number (stock) of people who do not have adequate housing. There is an outflow rate at which people find or receive adequate housing and an inflow rate at which people enter the vulnerable position of homelessness.

What is in the bathtub?

This is the first and most important question to ask in a system analysis: what does the bathtub represent to your, or to your organization, or even to a particular program? Think of the change you want to see in the world as represented by a bathtub.

What do you wan to see more of or less of in the world? Are you trying to increase the volume of something in the bathtub (such as increasing the number of trees in the forest) or diminish the volume of the bathtub (such as decreasing the number of people in a city who are living on the streets)?

How does is this bathtub influenced by all the variables around it? For instance, let’s suppose you want to address poverty in your city. Your bathtub represents the number of people in your city who are living on the street. Before you can think about increasing or decreasing the ‘stock’ in this bathtub, you need to think about the flow. How do people find themselves in this situation? If you start brainstorming the intersecting stories and potentials, it probably will not take long before the ‘map’ starts looking very complex indeed.

In fact, the diagram will eventually start to look inscrutable and incomprehensible. As complexity theory suggests, it is virtually impossible for us to define a singular reason why any given person finds themselves in poverty. Indeed, the ‘cause’ of poverty for any given person is as unique as the individual themselves. Therefore, you could potentially draw an infinite number of causal relationships in this map…and still not be able to pretend to understand poverty in any whole or comprehensive way.

And if you think about how people might ‘exit’ the waiting list for affordable housing — and what other aspects of the system are involved — the mental model for this map could grow to be infinitely complex, with an infinite number of factors, actors, or ‘nodes’ in the system. You could probably spend days speculating and drawing causative relationships between different parts of the whole system.

What is the lesson the analogy so far? The ‘bathtub’ you want to affect in the world is probably just as systemically complex as the bathtub in your house. In fact, it is likely even more complex and interconnected. Furthermore: the bathtub ‘out there’ does not have handy faucets and a drain plug you can easily turn to tweak water level, either.

The contents of your bathtub must be quantifiable. It needs to be something has a number or metric that can be counted — such as the number of trees per square kilometre in your forest or the number of people on a waiting list for affordable housing. Can’t come up with something countable? What would be a viable ‘proxy’ measure — something observable in the world — that would indicate you are achieving your objective? Put the proxy in the bathtub.

Beware of putting ‘immeasurables’ in your bathtub. Resist the temptation to use words that are technically subjective or otherwise empirically undefinable — such as ‘poverty,’ ‘wealth,’ ‘value,’ ‘engagement,’ or ‘capacity.’ Instead, ask: if we had more/less of this in the bathtub, what measurable difference would we see in the world?

PowerPoint Fail?

A famous example of such an analysis is illustrated by a consulting group working with United States military in 2009. The team produced a diagram that attempted to map the key factors and players involved in Afghanistan, from the military’s perspective. The PowerPoint slide was acquired by the media, and the military was subsequently lampooned in public discourse for the apparent nonsensical nature of the image. However, the exercise does highlight the point: as soon as you try to determine all of the variables influencing any given situation, you are opening the door to a situation that might soon appear intractable.30

Living in a World of Bathtubs

The problem with our bathtub analogy so far is that it is too simple. We need to think about every part of the system ‘map’ as something like a bathtub of its own.

This illustration serves as a good example of complexity. How does raising or lowering the level in bathtub affect the rest of the system? Sure, you could analyze this diagram and create a mathematical equation to provide an ‘answer,’ but in the real world you can never be quite sure that you have account for all the possible ‘bathtubs’ out there. In the real world, different parts of the system have a tendency to interact with one another in ways no one can predict for forecast.

Leverage Points

Your capacity for affecting the amount and temperature of water in your personal bathtub at home is very straightforward. In order to enjoy a bath, you plug the drain and open the faucets. That’s easy enough with a real bathtub.

But what about adjusting the contents of our metaphorical bathtub — the one that represents the state of something that we want to change in the world? What actions can you take to reconcile the discrepancy between the current ‘perceived state’ of the bathtub and its ‘desired state?’ In systems theory, the tools for influencing the stock and flow of the bathtub are often described as ‘leverage points.’ The following order and description of leverage points is derived from the work of Donella Meadows.

Dials and knobs

When most of us want to change something, the first thing we instinctively reach for are things like the budgets, policies, subcommittees, and org charts. Think: what are the easiest to reach ‘faucets’ and ‘drains’ around you? What are the ‘dials’ can you turn by striking a working group?

When governments want to change things, they often do it by adjusting tax rates or tariffs for this or that. The minimum wage is a popular number to change, too. We love adjusting numbers and budget allocations in the name of changing the system. But to what extent does changing numbers change behaviour?

“Let’s adjust the budget!” is often the first thing that comes to mind when we want to incite change of some kind. But in the grand scheme of things, it doesn’t often tend to yield a very significant impact. “Diddling with the details, arranging the deck chairs on the Titanic,” according to Donella Meadows.

It is a little bit like adjusting the faucets on your personal bathtub and expecting it to affect the temperature in your neighbour’s shower. Fiddling with the particularities of your organization’s plumbing does not tend to make much of a difference to the contents of much bigger ‘bathtubs’ of things like affordable housing waitlists, crime rates, literacy scores, air quality, etc.

Buffers and stabilizers

Buffers are the things we build or acquire to give us some breathing room. They give us a sense of stability. And building buffers usually means building physical structures. Your bathtub at home is connected to some buffers — perhaps a water tower or reservoir on the outside of town acts to stabilize the water supply in dry seasons.

Like rushing to committee meetings to tweak numbers, building bigger buffers is an instinctive, but not particularly efficient strategy. For example, if the waiting list for affordable housing is long, building more low-cost dwellings might seem like a really good, viable solution. But increasing the buffer of your low-rent housing is extremely expensive, especially if it comes as the alternative to intervening in other ways that could diminish the demand for cheap housing without jumping to the knee-jerk reaction of increasingly the supply of cheap housing. In other words: if there was another way to assist people getting off the waiting list for affordable houses without building more affordable houses, wouldn’t that be more desirable everyone?

Building bigger buffers is tempting. And sometimes they are necessary. But buffering capacity is not always the most creative solution or intervention. A city that finds itself facing summer droughts will likely try to think of various ways to manage or conserve water use before running ahead to build more infrastructure that will, in turn, consume further maintenance, repair, and operating costs. The problem with the buffer-building strategy is that it usually involves building more infrastructure…

Infrastructure

If you want to change the way your home bathtub behaves, you have some options. You could, for instance, dig up your supply lines and install bigger supply pipes. This would give you more water pressure in the shower. On the other hand, you could install a more water efficient shower head to decrease the flow. Home renovation adventures might impact the operation of your bathtub, but at scale, infrastructure is often a last resort.

Consider a city with bad traffic congestion. In an effort to keep tax increases to a minimum, many cities will try to incentivize carpooling or transit use before expanding highway infrastructure. It is much easier to relegate a lane to ‘carpool only’ than it is to rip up the whole highway to add another lane. If you have ever lived in a city that has retrofitted its streets for rapid transit, you know just how costly and burdensome it is to solve a problem like vehicular bottleneck by adding even more transportation infrastructure.

The point is not that infrastructure work is ineffective or unimportant. On the contrary, there is little else that has more seriously damning consequences than poorly designed infrastructure. It is for this reason that building more infrastructure as a ‘bandaid’ solution to previously bad design often compounds and exacerbates existing problems. From a systems perspective, messing around with infrastructure is often considered a last resort.

Delays

The time in between turning the hot water knob and hot water actually coming out of the faucet depends on the technology you use to heat your water and how far away that contraption is from your bathtub. You could, move your water right beside your bathtub for the fastest response time. This is not necessarily advisable, but it serves as an example of how delays work in interconnected systems.

In fact, understanding delays is a necessarily mental tool for thinking systemically. There is a delay between the birth of the baby-boomer generation and the seismic impact that they will have on the health care system in their later years of life. There is a delay between the moment that ‘patient zero’ contracts a devastating contagion and first symptoms of outbreak in a population. There is a delay between the invention and release of an innovative app and economic disruption for established business models. There is a delay between an economic downturn and employees receiving severance packages.

The point is this: nothing that happens in a system happens to the whole system at exactly the same moment. All systemic change occurs in ‘ripples’ that take time to germinate. Revolutionary mobs are not incited overnight, but emerge as the culmination of numerous preceding factors and triggers.

Intervening in delays is virtually impossible. Unless you do all the hard infrastructure work to change buffers, you cannot really do much to leverage a delay. But that said, you must be aware of delays in order to leverage much of anything else.

Negative Feedback Loops

Think of negative feedback loops as ‘balancing’ or ‘self-correcting’ loops.

Consider the ecological relationship between foxes and rabbits. Foxes eat rabbits. So a lot of foxes will make a sizeable dent in the rabbit population. But as the rabbit population declines, so too does the nutrition source for the fox population. This, in turn, causes the fox population to decline, which, of course, allows the rabbit population to grow again.31

Some more examples…

There’s a shortage of bananas (supply drops). Decreased availability means the price of bananas goes up. Increased price of bananas increases the profit incentive for suppliers, so more bananas are brought to market.

Your furnace thermostat is based on negative feedback. When the temperature in the room drops below its set level, the system fires up to close the gap between the actual temperature and the desired temperature.

Your body is full of negative feedback loops: when you are hot you sweat, when you are cold you shiver.

A negative feedback loop is like a ball in a valley. If you roll the ball up the side, it ‘wants’ to roll back down to the basin. In other words, it wants to self-correct. Think about how things like taxation and whistleblower protection work to keep balls like monopolization and fraud from rolling completely out of control.

Most of the time negative feedback loops do not exist in a vacuum. If we go back to the rabbit and fox example, we could ‘zoom out’ a bit further to consider the ways that the 'self-correcting balance in the two populations is tied to a potentially limitless number of other factors in the ecosystem.

One of the beautiful things about self-correcting loops is they tend to be widely distributed. This is why they work so well for maintaining a stead state of dynamic disequilibrium in the system. The more diversified and distributed they are, the more robust they usually become.

Positive Feedback Loops

Positive feedback loops are not inherently ‘positive’ in the sense of moral or value goodness. Perhaps we should call them ‘self-reinforcing’ loops instead. Here’s an easy definition for positive feedback loops: the more of something you have, the more of something you get. Positive feedback loops do not self-correct.

Heat makes the ice caps melt, which means more ocean water traps heat, which means more ice caps melt.

Wealthy people have money to invest, so they earn interest and get even richer. Poor people are often paying interest on debt, so they lose a portion of their income instead of saving it, which keeps them poor.

Person A hears a rumour and passes it on to Person B.
Person B tells Person C.
Person C tells Person A.
“Ah hah!” explains Person A, “I can’t believe you heard that, too! It must be true!” Having received positive feedback from the system, Person A is reenergized to communicate the rumour more widely, thus influencing an even greater scope of the network. (In social systems like ours, multiple, conflicting rumours circulate simultaneously. Each rumour reinforces its believers and infuriates its skeptics. When rumours clash, they force people to respond by accepting, rejecting, adapting, synthesizing, or amalgamating rumours. This, in turn, gives rise to even more rumours.)

A positive feedback loop is like a ball rolling down a hill. A simple little nudge is all it takes for the process to gain momentum, and with enough momentum the ball becomes unstoppable. Eventually, a positive feedback loop will lead to collapse: an uncheck or unregulated positive feedback loop is like an epidemic that will sooner or later run out of victims to infect. If everything has not already collapsed, it is because a negative (self-correcting) feedback loop has emerged.

Information Flows

Changing the way information is shared can have significant implications in the way a system self-organizes. Consider the affect that electronic highway information signs have on congestion: by warning drivers of blocked lanes or slow traffic ahead, some motorists will choose different routes, helping the highway system to partially ‘self-correct’ around the bottleneck. Aside from constructing signs and designing a data network for accurate updates, this intervention does not require significant infrastructure development. No new roads are built. Simply by changing the way information flows within the system, motorists are incentivized to use existing infrastructure more efficiently.

Information flows are often valuable leverage points for conservation efforts. For example, imagine what would happen if you moved your hydro meter into your front hallway, instead of leaving it hidden outside of your house or in your basement. Simply by presenting yourself with a constant reading of the cost of your energy use you would probably begin to consume less power. Nothing fundamentally changed about your house. The only thing we tweaked was the way information about energy is distributed. (Or consider the potential of having energy usage notifications piped directly to your smartphone.) Greater transparency in corporations or governments can yield similar outcomes. For example, when a particular industry is required to report on pollution outputs, companies scramble to clean up their acts in a desperate attempt to not feature as prominent members on the ‘Top Ten Biggest Polluters’ list. Once again, the only ‘change’ made here is broadening the reach of information, but sharing information differently can produce new incentivizes.

Dynamic highway traffic update signs, hydro consumption monitoring, and transparency legislation all have something in common: they effectively add new loops to the system. Behaviour and information are inextricably related. You, your customers, your users, or your clients are constantly responding to variables. When you change the way information moves, you change the decision-making environment for everyone.

Rules

Rules are real. And rules matter. Constitutions, bylaws, and the little league rulebook – they all determine daily experiences and expectations. Rules are hard to change because they have a lot of inertia: think of it as ‘social momentum’. Changing the rules of baseball to include 4 strikes instead of 3 would change the story of every subsequent baseball game. But rules are not just social conventions.

We believe rules only count if they can be enforced, and uninforced rules can be ignored. The threat of a penalty only counts if there are referees with red cards in their pockets – who have been appointed by the league. In other words: rules are the endpoints of power. Who has the power the rewrite a constitution when a president or prime minister who refuses to step down after their term? What if the laws surrounding your municipal water infrastructure could be rewritten by lobbyists from the Coca-Cola Company or some multinational beverage corporation? What if your municipal government enact bylaws that directly contradict the legislation of your provincial or federal government?

Changing a rule tends to take an immense effort. The higher the impact that changing the rule will have on the system, the more work it will likely take to change the rule. The world is exemplary of the systemic ripples and reactions that can occur when the rules change. Just consider:

Closing or opening borders

Legalizing cannabis

Physician or medical assistance in dying

The ‘clawback’ on income earnings for people receiving social assistance

Understanding the sheer power of rules to affect change (both positive and negative), most democracies make the alteration of rules intentionally difficult by organizing institutional checks and balances.

Self-Organization

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.32

Does life have a rulebook? In a sense, it absolutely does. It’s call Laws of Genetics. This rulebook describes how hydrogen, oxygen, nitrogen, carbon, and phosphorus can be organized into four coded sequences called nucleic acids, which we label G, A, C, and T respectively. Combining three of these letters at a time into different combinations gives us an incredible biomolecule ‘programming language’ called deoxyribonucleic acid, or DNA.

What makes the Laws of Genetics a fascinating rulebook is the fact that it is not a recipe for any specific kinds of lifeforms. The rules only describe how molecules can use basic elements like a programming language to self-organize and replicate themselves. What comes of the rules is a result of adapting to selective pressures, environmental conditions, and about three billion years of experimentation.

While the Laws of Genetics might be considered as a rulebook or sorts, it is equally the opposite of a rulebook. DNA represents the power of self-organization. Molecules organize themselves into lifeforms, or they don’t – and life figures out a way to survive, or it doesn’t. As Darwin famously discovered: the only ‘law’ of life is surviving long enough to self-replicate.

Despite first appearances, complex systems are self-organizing. Think about your local hospital. There is doubtlessly a pile of policies and meeting minutes stashed away in cabinets. There are boardroom tables surrounded by executives, managers, administrators, and consultants talking about strategies and pointing lasers at PowerPoint slides. Further, all of this is happening under the auspice of healthcare legislation from the government. But how do you describe your experience as a patient? How are you treated by the doctors and nurses? Who is involved in the decision-making process that affects your health outcome – and are they having a good day?

It is easy to think of the hospital as a bureaucratic hierarchy. Indeed, an obvious chain-of-command is established. But if you think of the hospital as an organism, a wholly different picture emerges: what is happening at any given moment in the institution is the result of hundreds of individual decisions that, collectively, give rise to the totality of your experience as a patient.

Suppose you are the CEO of the hospital and you want to make hospital visits more pleasant for your patients. You could take a ‘command and control’ approach and write a memo to all of your employees: ‘Dear staff, you must be nicer to the patients. Or I will fire you.’ How much impact will this have? Or you might take a more structural approach and review policies related to workload, working conditions, and vacation time, on the understanding that the attitudes of your staff are highly related to their employment environment. At the same time, however, you realize that you cannot control the domestic, psychological, or personal complexities of your staff’s lives, all of which must contribute to the way they treat patients and co-workers when they are on the clock.

As the executive of the hospital, one of the most powerful questions you can ask explore is how the hospital ‘organism’ can reorganize itself. Ultimately, the thing you want to change – interpersonal dynamics between staff and patients – is categorically outside of your direct control. It is not in your power to dictate people’s patience and emotions. Interestingly, it is the frontline staff themselves who are in the best position in the system to change the way patients are treated. They hold the power. Regardless of how many memos you write, the hospital only changes to the extent that the hospital changes itself.

“When you understand the power of system self-organization, you begin to understand why biologists worship biodiversity even more than economists worship technology,” write Donella Meadows. Self-organizing systems are a testament to the vitality of diversity for sustainability. We often run towards to homogeneity because we feel it is predictable and safe, but dynamism and longevity is found in adaptive decentralization that can experiment with many different iterations and ideas along the way.

Goals

Why does your municipal water infrastructure exist? Who set it up? What were they striving to achieve?

What is the purpose of your hospital? Whose agenda does it serve?

Over the years, the principle goal of many institutions and corporations has been to centralize control. In their own ways, Catholicism, Genghis Khan, and Comcast, have all sought to dictate their own monochrome ideals to the rest of the world. Such blatantly totalitizing agendas have a lot to teach us about the power of goals.

When a corporation or ideology sets out to bring more and more of the world under its control – whether to make profits or to convert heathens – everything else it does will follow suit. Consider how a corporation is beholden to cause of generating return on the investment for its shareholders. You can tweak, arrange, and strategize all you want to change company culture, but ultimately the goal of profit will seep into every nook and cranny. It is inevitable. It seems impossible to disentangle the goal of a corporation from its day-to-day operations: the parts of the corporation that do not serve the goal will eventually be shuttered. Or, in religious terms, excommunicated.

This is why goals are so powerful. It is mostly impossible to change a system without changing its goal, and vice versa. To change one is to change the other. However, sometime such a shift occurs swiftly, at an enormous scale: like when a demagogue or revolutionary figurehead taps into the hopes and fears of the disenfranchised masses. Revolts and rebellions are ultimately demands for the goals of the system to change.

Institutions survive by evolving their goals. The big railroad companies that held monopolies in transport and travel are no more. What happened? Railroads suffered from a chronic case of ‘Marketing Myopia’, according to economist Theodore Levitt:

The railroads did not stop growing because the need for passenger and freight transportation declined. That grew. The railroads are in trouble today not because that need was filled by others (cars, trucks, airplanes, and even telephones) but because it was not filled by the railroads themselves. They let others take customers away from them because they assumed themselves to be in the railroad business rather than in the transportation business. The reason they defined their industry incorrectly was that they were railroad oriented instead of transportation oriented; they were product oriented instead of customer oriented…33

For another example, consider the photography industry. Kodak was revolutionary in its radically innovative goal of making photography accessible for everyone, but eventually got so wrapped up in the goal selling film that it grew uncompetitive in overall picture-making market.

Paradigms

The goals of a system are crucial, but there is yet another bedrock layer beneath them. Let’s call this substratum the ‘paradigms’ of the system. Paradigms are the largely unconscious assumptions and cultural beliefs that underlay everything that happens in a society:

Land can be owned by humans.

Nouns are different than verbs.

Money has value.

Humans eat animals.

Time is linear.

Think of it this way: the ancient Egyptians built pyramids because they had certain beliefs about the afterlife, and we build skyscrapers because we have certain beliefs about the value of downtown real estate.

Consider the ways that the ideas of people like Plato, Thomas Hobbes, Martin Luther, Nicolaus Copernicus, Johannes Kepler, Adam Smith, Albert Einstein, Simone de Beauvoir, and Kimberlé Crenshaw have influenced and shaped societies. Ideas – especially the beliefs we share in common about ‘the way world is’ – are the systemic bedrock of the social worlds we then create. Paradigms are like the elementary particles of human culture, and therefore the fundamental building blocks of human systems.

Paradigms present a paradox. On one hand, changing the paradigm of a society seems like one of the hardest undertakings imaginable. Historically, these kinds of seismic shifts appear rarely, as if the markers of bygone epochs. But on the other hand, a single individual can have their paradigm shifted in an instant – it can happen as quickly as reading a sentence.

Transcendence

Donella Meadows argues that the only thing more powerful than changing a paradigm is staying unattached to paradigms altogether. This might seem like the height of abstraction, but let’s follow her reasoning. Consider any specific paradigm from the previous section, such as the idea that Land can be owned by humans. First, we recognize that this is a paradigm, which means accepting that our own latent assumptions about geography are subjective, a priori, and deeply rooted in culture and tradition. Next we now recognize that dividing up different ideas about land ownership into paradigms is a paradigm, too.

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.34

Everything that has preceded this paragraph presents a particular mental model. This text is a paradigm – a perspective, an interpretation, a set of assumptions – about the nature of systems. But another book might present systems thinking from an entirely different paradigm. You should be rightly suspicious that you are reading the final and absolute truth on the matter. Far from it. This is just another paradigm. Everything is a paradigm, including the postulate that everything is a paradigm. The paradigm that paradigms are paradigms is a paradigm, too. It is an infinite regression.

[Insert the sound of one hand clapping here.]

Is there a practical application to this point? (Other than assuming the lotus position to meditate on your assumed paradigm that ‘practical application’ serves as a justifiable measure for value?) Our ability to critique the paradigm of a system is largely dependent on our ability to transcend our own paradigms. Because paradigms are so invisible and embedded in our mental constructs of the world, it is only in rare moments that we mortals can see them for what they are – let alone see above or beyond them. This is why it is important to recognize that concept of a paradigm is a paradigm: it is the hard mental labour of training to see beyond own blinders.

Some of the most penetrating (and difficult) dynamics you can explore and analyze in any human system are its paradigms about its paradigms. How far down the rabbit hole can you go? Try explaining your company or organization from this perspective.

Meadow’s Hierarchy

The order of the above ‘leverage points’ is not arbitrary. The sequence is based on the work of systems theorist Donella Meadows. Meadows suggested that there is a hierarchy to these points. The leverage points on the top are relatively easier to implement, but tend to have less impact in the system. Conversely, the farther down the list you go, both the difficulty of intervention and the systemic ‘payoff’ increase in turn.

Let’s look at the list again:

Dials and knobs
Buffers and stabilizers
Infrastructure
Delays
Negative Feedback Loops
Positive Feedback Loops
Information Flows
Rules
Self-Organization
Goals
Paradigms
Transcendence

Meadow’s hypothesis is that changing dials and knobs – budget lines, the heading font on office memos, and so – are fairly easy to do, but they have little consequence. On the other hand, if you can influence the paradigms or goals of the system, the impact can be seismic.

Where will you prioritize your efforts?


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  2. Kaplan, Abraham. (1964). The Conduct of Inquiry: methodology for behavioral science. San Francisco: Chandler Pub. Co. p. 11  ↩

  3. Freedman, David H. (2010a). Wrong: Why experts keep failing us–and how to know when not to trust them. New York: Little, Brown and Company. p. 40. & Freedman, David H. (2010b). Why Scientific Studies Are So Often Wrong: The Streetlight Effect. Discover Magazine. July-August 2010. http://discovermagazine.com/2010/jul-aug/29-why-scientific-studies-often-wrong-streetlight-effect  ↩

  4. Proust, Marcel. (2006[1927]). Remembrance of Things Past, Volume 2. (Trans. Charles Kenneth Scott-Moncrieff). Wordsworth Edition. p. 657  ↩

  5. Meadows H., Donella. (1997). Leverage points: places to intervene in a system. http://www.donellameadows.org/archives/leverage-points-places-to-intervene-in-a-system/  ↩

  6. The Water Cycle diagram is in the public domain, provided by U.S. Geological Survey, available at https://water.usgs.gov/edu/watercycle.html  ↩

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  17. Zimmerman, Brenda. Lindberg, Curt. Plsek, Paul. (1998). Edgeware: Lessons From Complexity Science for Health Care Leaders. Dallas, TX: VHA Inc. See https://uwaterloo.ca/waterloo-institute-for-social-innovation-and-resilience/sites/ca.waterloo-institute-for-social-innovation-and-resilience/files/uploads/files/4._primer_on_complexity-from_edgeware-adapted_for_website.pdf  ↩

  18. Westley, Frances. Zimmerman, Brenda. & Patton, Michael. (2006). Getting to Maybe: How the World Is Changed. Random House Canada. p. 7  ↩

  19. Koffka, Kurt. (1935). Principles of Gestalt Psychology. New York: Harcourt, Brace and Company. p. 176  ↩

  20. Schelling, Thomas. (1971). Dynamic Models of Segregation. Journal of Mathematical Sociology. 1971, Vol. 1, pp. 143–186 www.stat.berkeley.edu/aldous/157/Papers/Schelling_Seg_Models.pdf Play a simulation of the theory produced by Nicky Case called Parable of the Polygons at ncase.me/polygons/  ↩

  21. Whewell, William. (1847[1840]) Philosophy of the Inductive Sciences. Founded Upon Their History. London: John W. Parker. p. 65  ↩

  22. Wilson, Edward O. (1999[1998]). Consilience: the unity of knowledge. New York: Vintage Books. p. 9  ↩

  23. Brandenburger, Adam & Nalebuff, Barry. (1996). Co-Opetition. New York: Currency Doubleday. p. 20, 28  ↩

  24. Cherington, Paul Terry. (1913). Advertising as a Business Force: A Compilation of experiences, 1976 reissue edition. Manchester, NH: Ayer Co Pub. p. 144  ↩

  25. Noorda, Ray. (1993). Co-opetition. Electronic Business Buyer. December Vol., pp. 8–12. and Stein, Harald D. (2010). Business: Theory and practice. 2010 11(3): pp. 256–265  ↩

  26. Church, Deanna., Goodstadt, Leo., Hillier, LaDeana., Zody, Michael., Goldstein, Steve., et al. (2009) Lineage-Specific Biology Revealed by a Finished Genome Assembly of the Mouse. PLoS Biol 7(5)  ↩

  27. Rubenstein, Dustin. & Kealey, James. (2012) Cooperation, Conflict, and the Evolution of Complex Animal Societies. Nature Education Knowledge 3(10):78  ↩

  28. There are numerous versions of this proverb, referenced as far back as the 13th century. Wikipedia has a good list of them here: https://en.wikipedia.org/wiki/For_Want_of_a_Nail#Historical_references  ↩

  29. Lorenz, Edward N. (1972). Predictability; Does the Flap of a Butterfly’s wins in Brazil Set Off a Tornado in Texas? American Association for the Advancement of Science, 139th Meeting. December 29, 1972.  ↩

  30. Liu, David. (2013). Hey New York Times: a causal loop diagram is not a PowerPoint fail (SD Wise blog) http://sdwise.com/2013/07/hey-new-york-times-a-causal-loop-diagram-is-not-a-powerpoint-fail/  ↩

  31. Loopy, design by Nicky Case, is a great tool for visualizing and experimenting with self-correcting feedback loops. See http://ncase.me/loopy/  ↩

  32. Meadows, Donella H. (1997). Leverage points: places to intervene in a system. http://www.donellameadows.org/archives/leverage-points-places-to-intervene-in-a-system/  ↩

  33. Levitt, Theodore. (1960). Marketing Myopia. The Harvard Business Review. July–August 1960. p. 138  ↩

  34. Meadows, Donella H. (1997). Leverage points: places to intervene in a system. http://www.donellameadows.org/archives/leverage-points-places-to-intervene-in-a-system/  ↩