I am working with a client on a book about system thinking for business, an particularly in the service industry. You will find a description of the book here. Which meant I had to read up about system thinking. It is like watching paint dry. Very dull and boring. I was recommended to read “Thinking in Systems: A Primer”
A system is a set of things—people, cells, molecules, or whatever—interconnected in such a way that they produce their own pattern of behaviour over time. A system is an interconnected set of elements that is coherently organised in a way that achieves something. A system is more than the sum of its parts. It may exhibit adaptive, dynamic, goal-seeking, self-preserving, and sometimes evolutionary behaviour.
One of the central insights of systems theory, as central as the observation that systems largely cause their own behaviour, is that systems with similar feedback structures produce similar dynamic behaviours, even if the outward appearance of these systems is completely dissimilar. The structure of a system is its interlocking stocks, flows, and feedback loops. The behaviour of a system is its performance over time—its growth, stagnation, decline, oscillation, randomness, or evolution. Systems fool us by presenting themselves—or we fool ourselves by seeing the world—as a series of events. The idea of making a complex system do just what you want it to do can be achieved only temporarily, at best. Systems can’t be controlled, but they can be designed and redesigned. We can’t control systems or figure them out. But we can dance with them!
There are no separate systems. The world is a continuum. Everything we think we know about the world is a model. Every word and every language is a model. All maps and statistics, books and databases, equations and computer programs are models. So are the ways you picture the world in your head—your mental models. None of these is or ever will be the real world.
Once we see the relationship between structure and behaviour, we can begin to understand how systems work, what makes them produce poor results, and how to shift them into better behaviour patterns. These behaviour-based models are more useful than event-based ones, but they have fundamental problems. They typically overemphasise system flows and underemphasize stocks. On the one hand, we have been taught to analyse, to use our rational ability, to trace direct paths from cause to effect, to look at things in small and understandable pieces, to solve problems by acting on or controlling the world around us. On the other hand, long before we were educated in rational analysis, we all dealt with complex systems. We are complex systems ourselves. Our own bodies are magnificent examples of integrated, interconnected, self-maintaining complexity.
What did I learn
The lessons I picked up:
- Because of feedback delays within complex systems, by the time a problem becomes apparent, it may be unnecessarily difficult to solve. A stitch in time saves nine.
- Don’t put all your eggs in one basket.
- Systems happen all at once.
- The behaviour of a system cannot be known just by knowing the elements of which the system is made.
- When a living creature dies, it loses its “system-ness.”
- Elements do not have to be physical things. Intangibles are also elements of a system.
- Once you start listing the elements of a system, there is almost no end to the process.
- Many of the interconnections in systems operate through the flow of information. Information holds systems together and plays a great role in determining how they operate.
- Purposes are deduced from behaviour, not from rhetoric or stated goals.
- Keeping sub-purposes and overall system purposes in harmony is an essential function of successful systems.
- A system generally goes on being itself, changing only slowly if at all, even with complete substitutions of its elements—as long as its interconnections and purposes remain intact.
- The least obvious part of the system, its function or purpose, is often the most crucial determinant of the system’s behaviour.
- A change in purpose changes a system profoundly, even if every element and interconnection remains the same.
- Interconnections are also critically important. Changing relationships usually change system behaviour.
- Stock is the foundation of any system. Stocks are the elements of the system that you can see, feel, count, or measure at any given time.
- A stock is the memory of the history of changing flows within the system.
- Stocks generally change slowly, even when the flows into or out of them change suddenly. Therefore, stocks act as delays or buffers or shock absorbers in systems.
- Changes in stocks set the pace of the dynamics of systems.
- The time lags that come from slowly changing stocks can cause problems in systems, but they also can be sources of stability.
- The presence of stocks allows inflows and outflows to be independent of each other and temporarily out of balance with each other.
- Human beings have invented hundreds of stock-maintaining mechanisms to make inflows and outflows independent and stable.
- Most individual and institutional decisions are designed to regulate the levels in stocks.
- Systems thinkers see the world as a collection of stocks along with the mechanisms for regulating the levels in the stocks by manipulating flows.
- The information delivered by a feedback loop can only affect future behaviour; it can’t deliver the information, and so can’t have an impact fast enough to correct the behaviour that drove the current feedback.
- Complex behaviours of systems often arise as the relative strengths of feedback loops shift, causing first one loop and then another to dominate behaviour.
- Delays are pervasive in systems, and they are strong determinants of behaviour. Changing the length of a delay may (or may not, depending on the type of delay and the relative lengths of other delays) make a large change in the behaviour of a system.
- Whenever we see a growing entity, whether it be a population, a corporation, a bank account, a rumour, an epidemic, or sales of a new product, we look for the reinforcing loops that are driving it and for the balancing loops that ultimately will constrain it.
- A quantity growing exponentially toward a constraint or limit reaches that limit in a surprisingly short time.
- When a subsystem’s goals dominate at the expense of the total system’s goals, the resulting behaviour is called suboptimisation.
- When a systems thinker encounters a problem, the first thing he or she does is look for data, time graphs, the history of the system.
- Systems rarely have real boundaries.
- The greatest complexities arise exactly at boundaries.
- You can often stabilise a system by increasing the capacity of a buffer.
- We are too fascinated by events. We pay too little attention to their history.
- Rebuilding is the slowest and most expensive kind of change to make in a system.
- Things take as long as they take.
- Missing information flows is one of the most common causes of system malfunction.
- Paradigms are the sources of systems.
- The physical structure is crucial in a system, but is rarely a leverage point, because changing it is rarely quick or simple.
- Disorderly, mixed-up borders are sources of diversity and creativity.
- Changing the length of a delay may utterly change behaviour.
- Change comes first from stepping outside the limited information that can be seen from any single place in the system and getting an overview.
- We don’t give all incoming signals their appropriate weights
- Remember that hierarchies exist to serve the bottom layers, not the top.
- Thou shalt not distort, delay, or withhold information.
- Power over the rules is real power.
The terms I learned:
- Perception delay
- Response delay.
- Delivery delay
- Physical delay
- System traps
Perspective on resilience
Systems need to be managed not only for productivity or stability, but they also need to be managed for resilience. Resilience is “the ability to bounce or spring back into shape, position, etc., after being pressed or stretched. The ability to recover strength, spirits, good humour, or any other aspect quickly.” is a measure of a system’s ability to survive and persist within a variable environment. The opposite of resilience is or rigidity. There are always limits to resilience.
The human body
The human body is an astonishing example of a resilient system. It can fend off thousands of different kinds of invaders, it can tolerate wide ranges of temperature and wide variations in food supply, it can reallocate blood supply, repair rips, gear up or slow down metabolism, and compensate to some extent for missing or defective parts.
Ecosystems are also remarkably resilient, with multiple species holding each other in check, moving around in space, multiplying or declining over time in response to weather and the availability of nutrients and the impacts of human activities. Read “Cascade“.
- Injections of genetically engineered bovine growth hormone increase the milk production of a cow. The cost of increased production is lowered resilience. The cow is less healthy, less long-lived, more dependent on human management.
- Just-in-time deliveries of products to retailers or parts to manufacturers have reduced inventory instabilities and brought down costs in many industries. Making them vulnerable, however, to perturbations in fuel supply, traffic flow, computer breakdown, labour availability, and other possible glitches.
- Hundreds of years of intensive management of the forests of Europe gradually have replaced native ecosystems with single age, single-species plantations, often of nonnative trees. These forests have lost their resilience.
A perspective on self-organisation
Like resilience, self-organisation is often sacrificed for purposes of short-term productivity and stability. Self-organisation produces heterogeneity and unpredictability. It is likely to come up with whole new structures, whole new ways of doing things. When you understand the power of system self-organisation, you begin to understand why biologists worship biodiversity even more than economists worship technology. The same could be said of human cultures, of course, which are the store of behavioural repertoires, accumulated over not billions, but hundreds of thousands of years. They are a stock out of which social evolution can arise. Any system, biological, economic, or social that gets so encrusted that it cannot self-evolve, a system that systematically scorns experimentation and wipes out the raw material of innovation, is doomed over the long term.
Perspective on hierarchies
Corporate systems, military systems, ecological systems, economic systems, living organisms, are arranged in hierarchies. The world, or at least the parts of it humans think they understand, is organised in subsystems aggregated into larger subsystems, aggregated into still larger subsystems. Hierarchies are brilliant systems inventions, not only because they give a system stability and resilience, but also because they reduce the amount of information that any part of the system has to keep track of. Hierarchical systems evolve from the bottom up. The purpose of the upper layers of the hierarchy is to serve the purposes of the lower layers.
Perspective on language
Our information streams are composed primarily of language. Our mental models are mostly verbal. Honouring information means above all avoiding language pollution—making the cleanest possible use we can of language. Second, it means expanding our language so we can talk about complexity.
Our perspectives on the world depend on the interaction of our nervous system and our language. The first step in respecting language is keeping it as concrete, meaningful, and truthful as possible—part of the job of keeping information streams clear. The second step is to enlarge language to make it consistent with our enlarged understanding of systems. If the Eskimos have so many words for snow, it’s because they have studied and learned how to use snow.
Perspective on measurement
Our culture, obsessed with numbers, has given us the idea that what we can measure is more important than what we can’t measure. Don’t be stopped by the “if you can’t define it and measure it, I don’t have to pay attention to it” ploy. No one can define or measure justice, democracy, security, freedom, truth, or love. No one can define or measure any value. Read “Buddhist economics“.
Analysing a system
- You need to be watching both the short and the long term—the whole system.
- You need to watch for what really happens, instead of listening to peoples’ theories of what happens, can explode many careless causal hypotheses.
- You need to pay attention to history. We pay too much attention to recent experience and too little attention to the past, focusing on current events rather than long term behaviour.
- You need to look for the ways the system creates its own behaviour. Do pay attention to the triggering events, the outside influences that bring forth one kind of behaviour from the system rather than another.
- You need to draw structural diagrams and then write equations, to make our assumptions visible and to express them with rigour.
- You need to get the beat of the system before you disturb the system in any way, watch how it behaves.
Let’s face it, the universe is messy. It is nonlinear, turbulent, and dynamic. It spends its time in transient behaviour on its way to somewhere else, not in mathematically neat equilibria. It self-organises and evolves. It creates diversity and uniformity. That’s what makes the world interesting, that’s what makes it beautiful, and that’s what makes it work. Remember, always, that everything you know, and everything everyone knows, is only a model. We are too fascinated by the events they generate. In the end, it seems that mastery has less to do with pushing leverage points than it does with strategically, profoundly, madly, letting go and dancing with the system. And remember that power over the rules is real power.
Going over the notes, system thinking seems to be highly philosophical and has a lot of overlap with being mindful and aware. Maybe it is not watching paint dry after all.