The Impossibility of Systems Thinking and Leadership: A Critique and Alternative

I come to bury systems thinking; not to praise it.

Systems thinking and systems leadership have long been held up as the pinnacle of strategic intelligence—the means by which we can master complexity, predict outcomes, and guide organisations and societies toward better futures.

From boardrooms to the cabinet office, the belief that we can design and steer large-scale systems dominates decision-making. Yet, this assumption is deeply flawed. The world does not behave like a machine with predictable inputs and outputs; it is an evolving, interdependent web of relationships, feedback loops, and emergent properties that defy our control.

I will argue for the impossibility of systems thinking and leadership ever succeeding, arguing that their failures stem from an overconfidence in human rationality, an underestimation of uncertainty, a misplaced faith in managerialism and a severe case of epistemic over reach. I will use case studies to illustrate these failures and propose an alternative way of being and becoming in the world—one that embraces humility, adaptability, and relational ethics over control and optimisation.

The Philosophical Problem: Why Systems Thinking Fails

At its core, systems thinking rests on the assumption that we can fully understand and model complex systems. This belief emerges from a legacy of rationalist, Enlightenment-era thinking, which assumes that with enough data, analysis, and expertise, we can map the world and intervene effectively. We may have to deal with a few ‘unintended consequences’ but, in essence, systems thinking provides the answers. However, complexity theorists like Edgar Morin, Gregory Bateson, and F.A. Hayek have highlighted the fundamental limits of knowledge in complex systems.

1. Emergence and Unpredictability: Complex systems behave in ways that we can’t predict. Economic markets, ecosystems, and societies evolve through non-linear interactions, producing outcomes that evade even the best predictive models. Seemingly stable systems transform themselves in ways that we can’t predict.

2. Observer Dependence: We are part of the systems we seek to analyse, so our perspectives are always partial and influenced by our own biases, desires, sensory limitations and blind spots.

3. The Hubris of Control: The assumption that we can design better systems ignores the self-organising capacities of decentralised, adaptive networks. Attempts at control lead to unintended consequences that often exacerbate the very problems they aim to solve.

Case Studies: The Failure of Systems Thinking in Action

1. The 2008 Financial Crisis

Economists and financial leaders believed they had tamed risk through complex financial instruments and predictive models. Yet, the crisis revealed how interconnected financial systems were, with hidden dependencies and feedback loops that turned small shocks into cascading failures. The over-reliance on models that assumed rational actors and predictable outcomes blinded experts to the systemic risks they were creating.

2. Climate Policy Missteps

Large-scale climate interventions—such as carbon offset markets, geo-engineering schemes, and megadams—always produce unintended consequences. Carbon markets have led to land grabs in the Global South, harming local communities while failing to reduce emissions meaningfully. These failures arise from the assumption that climate and socio-political systems can be managed like machines rather than lived-in, evolving ecologies.

3. COVID-19 Response Failures

While decisive action was necessary, the pandemic exposed the limits of centralised, top-down crisis management. Policies imposed without local adaptability—such as rigid lockdowns or mass-scale digital tracking—often failed to account for social complexity, leading to unintended harms like mental health crises, economic devastation, and increased inequalities. The assumption that a global crisis could be ‘managed’ through uniform strategies neglected the need for localised, emergent responses.

An Alternative Way of Being and Becoming

If systems thinking and leadership fail due to their epistemic overreach, what is the alternative? Instead of striving for mastery over complex systems, we should cultivate a way of being that embraces humility, adaptability, and relational ethics:

1. Epistemic Humility: Recognising that we do not and cannot fully know or control the systems we are part of. This means designing policies and interventions that are flexible and open to revision rather than rigidly committed to theoretical models 10 year plans, blueprints or roadmaps.

2. Decentralised Adaptation: Instead of imposing solutions from above, we should cultivate local, context-sensitive responses. Grassroots initiatives, community-led governance, and indigenous knowledge systems offer models of resilience that emerge from within rather than being imposed from without.

3. Ethics of Care Over Managerialism: A relational, ethics-based approach recognises that real change happens not through control but through stewardship, reciprocity, and attentiveness to lived experiences. Instead of optimising systems, we should focus on fostering conditions that allow for diverse forms of flourishing.

4. Learning from Nature: Many of the most resilient systems—forests, wetlands, traditional agricultural communities—do not operate through centralised planning but through distributed, self-regulating processes. We should take inspiration from ecological intelligence rather than corporate managerialism.

Conclusion

The idea that we can understand, control, and optimise complex systems is an illusion born of hubris. The world is not a problem to be solved but a reality to be engaged with. Instead of systems thinking and leadership, we need a way of being that prioritises humility, adaptability, and relationality. By acknowledging our limits and embracing uncertainty, we may not perfect the world—but we might just learn how to live in it more wisely.

Think am being a bit hard on systems thinking?

Have a different point of view?

Let me know in the comments.