Complexity isn't Complicated
Or 'How we're smashing our heads into a brick wall without realising'
Imagine you’re the conductor for a symphony orchestra - you’ve spent years honing your craft, you’re revered for your understanding and control of the symphony with which you’re charged. People marvel at the consistency at which your orchestra performs; not a single note is ever out of place.
You’re performing tonight - it’s the biggest performance of the year. But as you enter the hall, you notice something out of place; you smell a cigarette burning somewhere. You turn the corner - and your orchestra isn’t there! In their place, there are five strangers wearing black turtlenecks. You’re about to conduct a jazz ensemble with no experience in jazz.
This is the scene I imagine when I imagine us mistaking complex systems for complicated ones - fruitlessly trying to control something that by it’s very nature defies control. Trying to conduct jazz as if it were classical music.
I have been that conductor many times - assuming ‘complicated’ and ‘complex’ were the same thing; or two sides of the same coin. I still find myself doing it today sometimes - but I catch myself, because it turns out they’re completely different. And this misconception is gumming up the works of our most critical complex ecosystems; companies, communities, economies - even nature itself.
What’s complicated
Complicated problems are challenging and tricky - but they can be understood, predicted, and known. There’s a cause and effect at work that we can have a high degree of confidence in. Computers are some of the most complicated things we’ve ever created - but they’re not complex. I find the rules of basketball often defy my understanding - but if I really put in effort, I can know them; the sport is complicated, but the rules are known.
Mozart’s Symphony no. 40 is beautifully complicated; but for the most part, you know what you’re going to get.
What’s complex
Complex problems have a dynamic element to them; they defy prediction - either because there are too many variables to be known, or the interrelation between those variables creates unknowable feedback loops. Complex systems are often adaptive - they evolve to suit the environment they’re met with. Complex problems can never be permanently solved. Economies are complex. Any given game of basketball is complex. Teams are complex.
Jazz is complex; if you go to your local bar and hear a jazz quartet, you don’t know what you’re going to get. It might be following the rough pattern of Moanin’ (take your pick between Mingus or Blakey), but it could veer off in any direction at any given moment.
The dangers of mixing them up
Complex and complicated systems respond to interventions totally differently - approaching a complex challenge as if it were complicated will lead to a lot of sisyphusian analogies being thrown about - right before people start rage quitting.
Trying to predict, control, and tame complex systems is an exercise in futility - but we do it all the time.
Aaron Dignan put it really well in his book Brave New Work -
“every five-year plan, every annual budget and every fixed target is a public confession that we don’t understand the nature of our organisations. Our desire for control blinds us to the truth”.
When we mistakingly believe we’re working in a complicated system - or don’t understand the distinction between complication and complexity - we’re prone to chase impossible-to-reach metrics, treat sieves like they’re buckets, try to apply ‘one size fits all’ solutions, and generally run ourselves into the ground while tearing our hair out.
Our attempts to control these systems create situations that guarantee something will break - and the people involved tend to hit their breaking point before the system they’re working with does.
Simple rules inform complex behaviours
At this point I think it’s easy to throw your hands up, broadly refuse to work with these systems that apparently defy prediction and control, and call it a day. But complex systems can often be easier to understand than complicated ones; we just need the right lens.
There’s the classic example of Murmurations; these hypnotically beautiful movements and shapes that flocking birds make in flight.
Looking at a murmuration in action, you immediately get a sense of complex behaviour; there’s no predicting where the flock will go next, nor what shape they’ll take - but it turns out there are 3 simple rules that determine this behaviour. These aren’t necessarily rules in the sense that we can now predict how a murmuration will behave; think of them more like guidelines to help us better understand how the game works.
avoid obstacles
align with neighbours
steer towards the centre
Avoid crowding the birds around you, steer towards the average heading, and try to stay equidistant from your neighbours. These three guidelines inform the behaviour that looks impossibly complex.
In the real world
As Donella Meadows put it - the best we can hope to do is dance with complex systems. They can’t be solved, snuffed out, or tamed; we need to accept a lack of control in these interactions, and instead focus our energy into ensuring we can respond to the most likely outcomes.
Complex systems are also less about the things in the system, and more about how they interact; thinking about that in a team context for example, it could be worth loosening the formality of roles (the things) and moving that energy into creating more effective team structures (the interactions between the things). This is something I’m looking into with Supermesh - and I’d love to hear about your experiences in this space if you’re interested in chatting!
Here are a few more ways complex adaptation can manifest…
Following general guidelines instead of detailed rules
Creating autonomy in your teams so they can respond to emerging insights in their environment
Letting roles evolve naturally as people gravitate towards problems they identify
Equipping your team with tools and skills for continuous development and experimentation; give them a home for their curiosity
Ensuring transparency across the board so information is actionable
Investing in trust and psychological safety
Strengthening the collective intelligence of your team by embracing diversity and inclusion
Allowing more resource for reactive / responsive work
Following the old ‘plans are useless; planning is invaluable’ maxim
Distributing decision-making authority across the organisation, creating an ecosystem of influence
Being willing to re-write any rule in the playbook
No binaries
It’s worth highlighting now that complex and complicated systems aren’t mutually exclusive; they’re not a binary where something is one or the other. It’s not even a spectrum, where a gain in one represents a diminishment of the other. We need to think of it like a matrix; where we can have highly complicated AND complex systems, or very simple systems on both axes.
It’s also worth noting some complex systems are complex because we lack the compute power or insights to truly understand them - maybe one day we’ll be able to predict and plot how a murmuration will behave, for example.