An intro to complex systems and systems thinking
Everyone can (and should) think in systems
Welcome to Think in Systems. I’m glad you’re here. This first post is all about:
Complex systems,
What differentiates them from simple and complicated systems, and
How systems thinking can help us navigate them.
Our world is full of complex systems, and they’re getting more complex by the day.
Complexity can be beautiful and inspiring—it’s a reflection of natural evolution and human progress. Things as diverse as modern societies, human thought, and bee colonies wouldn’t be possible without complexity.
Unfortunately, complexity can also lead to some serious problems. Climate change, geopolitical instability, and recessions are complex, systemic issues. Linear thinking and outdated problem-solving techniques don’t work very well on these problems.
That’s where systems thinking comes in. Systems thinking is an approach to dealing with complexity and, you guessed it, complex systems. It’s also a mindset that can help us change how we think about growth, progress, and the challenges facing our world.
But before we get started with systems thinking, we first need to understand systems.
What is a system, really?
Systems are, quite literally, everywhere. Some systems have names that tell you they’re systems, like cardiovascular, transportation, and healthcare systems. Other systems hide in plain sight: government, team, economy, forest.
Intuitively, we know these are systems, but what does that really mean? I’ll borrow a definition from Donella Meadows’s Thinking in Systems, one of the best systems thinking books out there (emphasis added):
A system is an interconnected set of elements that is coherently organized in a way that achieves something.
That seems simple enough, right? All systems share three fundamental components:
Elements: The things that make up a system.
Interconnections: The relationships between the elements.
A function or purpose:1 The reason(s) the elements are interconnected.
Knowing the definition of a system only gets us so far in practice because systems range in complexity—from simple to complicated to complex—across what I’ll call the complexity continuum.
Simple systems have few components. Their behavior is predictable and easy to analyze using equation-based methods. A basic wheel and axle is a good example of a simple system. It contains two connected elements and its purpose, like that of all simple machines, is to make moving things easier. A wheel and axle can be part of a complicated or complex system, but it is simple on its own.
Complicated systems generally have more interconnected elements and more dynamic behavior than simple systems, but they are also fairly easy to understand with the proper technical knowledge. For example, a car battery is technologically complicated to many people, but not an engineer. Designing a car battery and projecting its degradation over time might be a technically challenging problem, but it’s just math, science, and know-how at the end of the day.
Complex systems are another beast entirely. Their individual elements and the relationships between them are challenging to identify and even more challenging to understand. Cars are complicated systems, but when you throw a bunch of them together on the road you get a complex traffic system. The elements are constantly changing and the behavior of the system becomes impossible to predict as you add more cars, a couple of distracted drivers, some cyclists, nasty weather, and whatever else you might experience on your daily commute.
Complex systems are intriguing and frustrating because they adapt over time and their behavior defies expectations. Many are systems of systems. Others are part of more extensive systems.
From here on out we’ll focus on complex systems because experts have simple and complicated systems pretty well figured out by now.
A complex system is more than the sum of its parts
There’s no love in a carbon atom, no hurricane in a water molecule, no financial collapse in a dollar bill. - Peter Dodds
Complex systems are tricky because they can’t be understood simply by analyzing the individual components. To demonstrate what this means, let’s continue digging into our earlier example of a complex system, a city’s traffic or transportation system.
A transportation system comprises many interconnected things like roads, vehicles, drivers, traffic laws, public transportation options, and many more (its elements). Together, they ostensibly allow people to go from Point A to Point B safely and efficiently (its purpose).
This sounds good, but we all know that transportation systems generally don’t work that well in the real world. Traffic is inevitable, crashes are common, and travel times are downright unpredictable. These problems are unsurprising because we experience them often, but the people who designed our cities certainly didn’t intend for these problems to be so prevalent, right? Probably not, but they probably didn’t understand complex systems all that well, either.
Game theory might be able to tell us that two drivers alone on the road will seek to 1) avoid a crash and 2) find the fastest route to wherever they’re going, but it doesn’t get us very far when there are thousands of drivers on the road with competing priorities, varying driving abilities, and jaywalking pedestrians to worry about.
The problem isn’t that the urban planners were bad at their jobs. Instead, the trouble lies in how complex systems work. The unpredictable behavior of a complex system results from the interactions between the system’s elements, not the individual components themselves. This phenomenon is known as emergence.2
Emergence makes complex systems dynamic and unpredictable. Traffic jams are common despite the fact that urban planners want safe and efficient traffic flow and commuters want to get to their destinations as quickly as possible without crashing.
The closer we look at complex systems, the clearer it becomes that we can’t predict their behavior simply by analyzing and understanding their parts individually. This begs the question, how can we understand and fix lousy system behaviors (like traffic jams) if we can’t easily predict how a complex system will behave in the first place?
This is why systems thinking is so important. It helps us adopt a nonlinear approach to understanding systems and their problems. It allows us to zoom out to see the forest instead of focusing only on the trees (yes, overused corporate jargon can actually be a helpful tool to understand systems thinking).
The problem with traditional reductionist thinking regarding complex systems is that there’s usually no single element we can remove, add, or change to improve the system.3 There’s no “one cause” or trigger that we can point to or blame for bad system behavior and results. There’s no silver bullet equation we can use to explain the emergent behavior of complex systems and no technique to choose the “right” solution from a list based on the explanation.
Systems thinking works because it helps us uncover complex and hidden elements and interactions that contribute to systemic issues and design holistic solutions that break destructive behavior patterns. We can also use this approach to build new systems designed to produce better behavior from the start.
Anyone can think in systems
One of the most beautiful things about systems thinking is that it doesn’t belong to a single domain or field; it applies to every system and every system problem. Thinking in systems isn’t reserved for scientists, programmers, and systems designers. Anyone can think in systems, and many do (or try to) without even knowing it.
A manager building a new team might want to consider how the team’s structure, members, policies, and incentives might lead to good team behavior and results (productivity, healthy work environment, worker retention, better company performance, etc.). An investor thinks about the potential impact of a single investment on the entire portfolio. A real estate developer might consider how new developments will affect local traffic patterns, cost of living, and the environment.
There’s a long way to go before systems thinking is mainstream, but it’s getting there. A growing number of people and organizations are using systems thinking approaches to make a dent in some of the most pressing challenges facing our world.
I encourage you to try a little exercise to start your systems thinking journey. Pick a system you interact with frequently at work or in your personal life and ask yourself a few questions:
What are the elements of this system, and how are they interconnected?
What is the purpose of this system?
Is it working well or producing bad results?
How might we make it work better?
When you start engaging more with the systems in your life, you’ll realize just how broken some of them are. And you’ll appreciate that there’s hope to fix them.
I’ll dig into more features and examples of complex systems and related topics like crypto networks, nature, and Russia’s invasion of Ukraine in future posts. I hope you’ll join me on this journey by subscribing below.
Housekeeping
This is my first ever post on Substack; thanks for reading! Feel free to reach out with comments, suggestions, or questions.
Further Reading (and More)
I really cannot recommend Thinking in Systems enough. It is a phenomenal introduction to systems thinking and goes deeper than I did here. Meadows was a brilliant writer, and she makes systems, even complex ones, easier to understand. Meadows tragically passed away in the early 2000s, but her legacy continues. She continues to influence and inspire people in the field.
Some other interesting resources (there’s a lot more where this came from):
Videos (part 1 of 4 linked) of some of Meadows’s lectures on sustainable systems at the University of Michigan’s Ross School of Business (from 1999, still highly relevant)
A series of three short videos from lectures given by former Wharton professor Dr. Russell Ackoff in the early 2000s: Part 1, Part 2, and Part 3
A couple of short IDEO blog posts on systems design:
A long and very strangely produced (but good/interesting) Radiolab podcast on emergence from 2007
“Function” is usually used for nonhuman systems, while “purpose” is typically reserved for human ones. This distinction can be helpful, but it isn’t cut and dry because many systems have human and nonhuman elements. You can use whichever gets your point across.
Many people “quote” Aristotle when they talk about emergence, saying, “the whole is greater than the sum of its parts.” As this blog post from the Chesapeake Chapter of INCOSE points out, this is a misquote of a passage from Aristotle’s Metaphysics (from the 1908 translation by W. D. Ross):
In the case of all things which have several parts and in which the totality is not, as it were, a mere heap, but the whole is something besides the parts, there is a cause; for even in bodies contact is the cause of unity in some cases, and in others viscosity or some other such quality.
The misquote isn’t egregious, as it gets the point across. People might be better off quoting Euclid’s Elements, Book I, Common Notion 5:
The whole is greater than the part.
There’s a lot of debate about reductionistic vs. holistic thinking and methodologies in philosophy and science (these debates have been going on for centuries, far longer than “systems thinking” has formally been around). Someone who believes in/practices methodological reductionism might tell you that you can understand complex things by reducing them into simpler, more easily understandable component parts and analyzing those parts. Such a person would probably disagree with a systems thinker’s approach to complex systems, but systems thinkers know that complex systems problems can’t have simple solutions.