I never set out to become someone who advises governments on how to rewire their economies or helps ministers rethink entire education systems. It happened gradually, through a relentless curiosity about “why things are the way they are” – and an almost obsessive need to follow every thread until I could see the whole picture of the world – I just loved information and understanding “what is happending and why”.
What I didn’t realise until much later was that I had been developing a skill. One that has a name: systems thinking. And one that, I now firmly believe, is the most important mental skill any human being can cultivate for the century we’re living in.
Let me tell you how I actually think about it – not the polished, conference-talk version, but the real honest version.
It Started With Asking Annoying Questions
When I was younger, I drove people crazy – especially my parents and teachers. Not only because I was difficult (“just a little”), but because I couldn’t stop asking why. Why does that exist? Why do people keep doing it this way? Who benefits from this? What would would be done differently?
I genuinely wanted to understand the machinery underneath the surface – and it gave me a piece of mind to understand it.
Over time – through building companies, consulting across industries, travelling obsessively, spending hours in museums and at events talking to people I had no business talking to – I began to see that almost everything is connected to almost everything else. A decision made in a finance ripples into labour markets, which ripple into family structures, which ripple into political sentiment, which eventually loops back to reshape the original policy. Nothing sits still. Nothing exists in isolation.
This is systems thinking in its rawest form: the stubborn refusal to accept that anything has a single cause or a simple solution.
The Moment It Clicked
There was no single eureka moment, but I remember the first time I was asked to help the Swiss government think through a technological transformation of 30.000 SMEs and realised that “technology policy” was just like a big puzzle that needs to be solved.
And it is till today – you need to see a big picture, see so many interests, so many intertwinings and dependencies – not just economically, but psychologically, in terms of identity and purpose. You cannot talk about technology without talking about how education systems were designed for a world that no longer exists or how companies are optimizing nowadays. You cannot talk about that without confronting the cultural stories we tell ourselves about what makes a human being valuable – value systems and more. And you cannot talk about any of that without examining who holds power, who stands to gain from the status quo, and what incentives are keeping a clearly broken system in place.
And as always it was like that: the problem is never the problem. The problem is always a symptom of a system.
What I Actually Do When I Think About Complex Problems
People often ask me for my “method” or “how can I also do that?” – and I find it always hard to answer because it’s less a method and more a set of reflexes I’ve trained over years and which came naturally to me. But if I had to break it down, here’s what happens in my head when I encounter a big, messy problem:
- I ask who is involved and why. Not who is supposed to be involved – who actually is, and what they’re getting out of the current situation. Follow the incentives and you’ll find the stickiness or also the sickness.
- I look for feedback loops. Thats always a fun game and everyone who knows me knows I love this game? What is reinforcing this pattern? What would have to change for things to change? Often the most powerful intervention point isn’t obvious – it’s not the thing everyone is talking about, but the hidden dependency that nobody wants to name.
- I ask what the mental models are. This is the one most people skip, and it’s the most important. Every system is held in place by stories – stories people tell themselves about what’s natural, what’s possible, what they deserve, what they fear. You can change a law, restructure an institution, pour money into a programme – and if the underlying mental model doesn’t shift, everything reverts. Always.
- I look for historical patterns. Almost nothing happening today is genuinely new. The technologies are new, the scale is new, but the dynamics — the power struggles, the resistance to change, the unexpected consequences — these have shapes we’ve seen before. History is one of the most underrated tools for systems thinking.
- I ask what will resist change. Before I think about solutions, I spend a lot of time thinking about the forces that will push back. Not because I’m pessimistic, but because understanding resistance is how you design interventions that actually work rather than interventions that feel good.
The Hardest Thing to Accept
Here’s what nobody tells you about systems thinking: it doesn’t make you feel smarter. It makes you feel more uncomfortable because its a constant chasing of things where you dont have answers to.
Once you start seeing systems, you also start seeing how rarely they change in the way people intend – making you quite frustrated sometimes. You see well-funded programmes fail because they addressed symptoms rather than causes. You see brilliant policies get quietly dismantled because they threatened the wrong people’s interests. You see innovations that were supposed to liberate people end up concentrating power instead – Crypto I am looking at you.
The hardest lesson I’ve had to learn – and re-learn, constantly – is that complex systems cannot be solved. They can only be influenced. And even then, the influence rarely looks like what you planned. And its making me anxious.
Change is non-linear. It builds invisibly for years and then suddenly tips. Or it looks like progress and then snaps back. Or it works in one context and catastrophically fails when transplanted somewhere else. Our brains are wired for linear cause-and-effect thinking, and systems operate on entirely different logic. Accepting this is genuinely difficult. I still find it difficult.
Technology Is Not a Solution — It’s an Amplifier
I want to spend a moment on this because I think it’s deeply misunderstood, especially right now with the noise around AI and every new hype every few years.
Technology does not fix systems. It accelerates them – both their best and their worst. Digital platforms didn’t create polarisation; they amplified the polarisation that was already latent in our social fabric. AI won’t create inequality; it will intensify the inequality already embedded in our economic structures. It will also potentially accelerate our ability to solve problems we’ve never been able to solve before – but only if the surrounding systems are designed to actually do that.
This is why conversations about AI that focus purely on the technology — its capabilities, its risks in isolation, its ethical principles in the abstract — frustrate me. The technology is not the interesting question. The interesting question is: what system will it be embedded in? Who controls it? Who benefits? Who is excluded? What stories will we tell ourselves to justify the outcomes?
Those are systems questions. And they require systems thinking to even begin to approach.
How Megatrends Actually Work
As a futurist, I think about a lot of variations of the reality and especially three timeframes simultaneously – always (and its tiring at times). The historical patterns that shaped where we are – or “why did it evolve like this”. The current state, with all its tangled complexity to understand “status quo and the system supporting it”. And the megatrends – the large, slow-moving forces that are reshaping everything of “possible futures evolving and intertwining”.
The megatrends of our moment — AI and automation, the climate crisis, demographic ageing, the fragmentation of societies, the transformation of work — are not separate phenomena. They are interconnected, and they interact with each other in ways that multiply both opportunities and risks.
Take something as apparently simple as the ageing of populations in wealthy countries. On the surface: labour shortages, healthcare costs, pension systems under pressure. But follow the threads: pressure to automate (which intersects with AI), changing political coalitions (older voters dominate democracies), shifting cultural values around care and family structure, increasing demand for immigration (which intersects with polarisation), redesigning cities (which intersects with climate infrastructure)…
And yet the fascinating thing is that every megatrend itself is just a node in a network of megatrends. When you try to address one without understanding how it connects to the others, you create unintended consequences (which policies often do – they are singular measures in a complicated web of interconnected actions). Often the consequences are worse than the original problem and we have seen it often enough – well intended actions lead to unforseen consequences – because it is not so easy to understand complex systems easily.
Why Simple Answers Are So Dangerous Right Now
This is a topic where I want to be direct about something that concerns me deeply: the market for simple answers has never been larger, and the cost of simple answers has never been higher. Simplicity is often stupidity in disguise.
I sit in rooms with very smart, very powerful people who are under enormous pressure to do something. The pressure pushes toward oversimplification. It produces policies and programmes that address the most visible symptom rather than the underlying dynamic. It produces technology solutions deployed without thinking through second-order effects. It produces political narratives that reduce genuinely complex problems to single villains or single solutions.
None of this is malicious. Most of it comes from good intentions. But good intentions running on oversimplified mental models of the world tend to produce bad outcomes.
Systems thinking is, at its heart, an act of intellectual humility. It’s the practice of saying: this is more complicated than I thought, and I need to sit with that complication rather than flee from it. But in the world of populism there isnt much space anymore for complexity and uncertainty as its only about fast, simple and especially “loud” answers.
How to Actually Develop This Skill
So lets speak about more positive things, I tried hard to explain my world of thoughts and why its important but also that I have been fortunate to have large-scale, high-stakes problems as my training ground. Most people don’t. But the skill is genuinely learnable, and you don’t need to advise governments to build it.
- Seek complexity. When you encounter a problem – in your team, your organisation, your community – resist the urge to reach for the first explanation. Map the actors. Trace the incentives. Ask what beliefs are keeping the current pattern in place.
- Study failures obsessively. I’ve learned more from interventions that failed spectacularly than from ones that succeeded. Failure reveals the hidden wiring of a system. Why did that initiative collapse? Why did that well-funded programme make things worse? Why do people keep behaving in ways that are against their apparent interests? The answers to these questions are where systems thinking lives.
- Read across domains. The structure of an education system and the structure of a healthcare system have more in common than people think. Economic history and ecology share deep patterns. Anthropology illuminates political dynamics. The more you read outside your domain, the more pattern recognition you develop.
- Travel and talk to strangers. Seriously. Nothing breaks a mental model faster than encountering how differently people in different contexts understand the same problem. I’ve had my assumptions demolished in places I never expected. That’s the point.
- Embrace tension instead of resolving it. Systems often present genuine dilemmas: efficiency versus resilience, standardisation versus adaptability, speed versus thoughtfulness. The instinct is to pick a side. The systems thinker’s job is to understand the deeper structure creating the tradeoff — and to design for both rather than choosing between them.
- Build feedback into everything. When you intervene in a system — even a small one — pay close attention to what actually happens, especially the surprises. The surprises are data. They are the system telling you what you didn’t understand.
Why This Matters Now More Than Ever
I’ll end this article with something I genuinely believe: we are living in an era where the complexity of our challenges is increasing faster than the complexity of our thinking. The systems we’ve built – financial, ecological, political, technological – are now so deeply intertwined that linear, single-domain and simplified thinking is not just insufficient – It’s actively dangerous.
Climate change is a systems problem – a big one. Inequality is a systems problem. The crisis of democracy in the digital age is a systems problem. The disruption of work by automation is a systems problem. None of these can be addressed with a single policy, a single technology, a single intervention. All of them require the capacity to see whole pictures, trace connections, anticipate consequences, and design with the grain of system dynamics rather than against them.
Systems thinking is not an academic skill. I would even argue, it could be the most important fundamental literacy of the 21st century.
The good news – and this genuinely excites me – is that it can be learned or better said “trained”. And from what I see its not something you do quickly, and not easily, but it can be trained. It requires curiosity above all else. It requires the humility to sit with uncertainty and dedicate time to thought experiments and curisosity. It requires the patience to trace threads even when they seem to lead nowhere. And it requires a deep, enduring fascination with why things are the way they are – and what it would actually take for them to be different.
If you’re reading this and you feel that itch – the discomfort with surface explanations, the sense that there’s always more going on underneath – that’s not a liability. That’s the beginning of systems thinking. Follow it.
I promise the world starts to look a lot more interesting when you do – and if you start with it drop me a line and tell me how its going 🙂
You can read also my original publication on MoreThanDigital: Systems Thinking in Practice – Understanding Complexity, Causality, and Transformational Change
