Systems Change: Beyond Seeing to Shifting Systems

Satellite image of a winding river flowing through an arid landscape, showing a green river system cutting through desert terrain.

Source: USGS @usgs via Unsplash

summary || Systems Change: Beyond Seeing to Shifting Systems

Most change efforts don’t fail because leaders misunderstand the system. They fail because understanding alone doesn’t change the conditions that shape behaviour.

Systems thinking has helped many organisations see patterns, feedback loops, and unintended consequences more clearly. But seeing the system is not the same as shifting it. This piece explores why systems resist change, why insight is so often mistaken for intervention, and what it actually takes to alter outcomes in complex human systems.

  • noun

    plural noun: systems

    1. a set of things working together as parts of a mechanism or an interconnecting network; a complex whole.

      "the state railway system"

    2. a set of principles or procedures according to which something is done; an organized scheme or method.

      "the public school system"

  • verb

    1. make (someone or something) different; alter or modify.

      "both parties voted against proposals to change the law"

      "she decided to change her name"

    noun

    1. an act or process through which something becomes different.

      "the change from a nomadic to an agricultural society”

      "a handful of loose change"

8min read

The Map Is Not the Territory

You've drawn the diagram. Mapped the stakeholders. Identified the feedback loops. Everyone in the room nods - yes, this is why the system behaves the way it does. The insight feels powerful, even liberating.

Then you try to change something.

Six months later, the same patterns have reasserted themselves. The workarounds you designed have been worked around. The new process has been absorbed into the old culture. And the most frustrating part? Everyone still agrees with the analysis. They can see the system. They just can't seem to shift it.

If you've led change in a complex organisation, you've likely lived some version of this story. The gap between understanding a system and actually changing it can feel vast and vaguely humiliating. Not because the analysis was wrong, but because analysis alone was never going to be enough.

Why Seeing Doesn't Mean Shifting

Systems thinking teaches us to look for patterns, connections, and unintended consequences. It's a powerful lens. But here's what it doesn't do: it doesn't automatically alter the conditions that keep the system behaving the way it does.

Knowing that your organisation has a "hero culture" that burns people out doesn't stop managers from rewarding heroics. Understanding that your funding model creates perverse incentives doesn't change the funding model. Seeing that informal networks hold more power than formal structures doesn't redistribute that power.

The system you've mapped exists in the real world, held in place by budgets, job descriptions, performance metrics, unwritten rules, historical grudges, and people's mortgages. These aren't abstractions. They're the material and social infrastructure of how things get done. And they don't shift just because you've drawn them on a whiteboard.

This is the gap that trips up so many change efforts. We treat insight as if it were an intervention. We think that once people see the system differently, they'll naturally act differently. But people act within constraints, and those constraints rarely change just because our mental models do. Research on implementation consistently shows that insight fails when it's not embedded in the routines, incentives, and governance structures that shape everyday behaviour.

Why Systems Push Back

Human systems are not neutral containers waiting to be redesigned. They're alive with competing interests, established routines, and self-reinforcing dynamics. When you try to change them, they push back. Not out of malice, but because that's what systems do.

Feedback Loops Don't Care About Your Intentions

The same mechanisms that stabilise a system also resist change. Negative feedback loops, the ones that keep things in equilibrium, will work just as hard to correct your intervention as they do to correct any other disturbance.

You introduce a new approval process to improve quality. Middle managers, already stretched, find ways to shortcut it. You mandate collaboration between siloed teams. They comply by holding meetings where nothing of substance is shared. The system adapts, and your change becomes theatre.

Informal Norms Trump Formal Rules

Every organisation has two operating systems: the one in the policy manual and the one people actually use to get things done. The informal system: who really makes decisions, which rules can be bent, what behaviours are secretly rewarded, is often far more powerful than the formal one.

You can rewrite the org chart, but if the CFO still has the CEO's ear and everyone knows it, the real structure hasn't changed. You can announce new values, but if people still get promoted for the old behaviours, the culture hasn't shifted. Decades of transformation research, across industries and continents, show that 60 to 70 per cent of large-scale change efforts fail or underdeliver for precisely this reason: the underlying systems that shape day-to-day behaviour quietly reassert themselves.

Adaptation Absorbs Your Moves

Complex systems are adaptive. They learn. When you intervene, the system adjusts around you, sometimes in ways that undermine the very change you intended.

Policy resistance is the classic example: you push in one direction, and the system pushes back harder in the opposite direction, often leaving you worse off than when you started. You mandate reporting to increase accountability, so people game the reports. You centralise decision-making to improve coordination, so local innovation dies. You create incentives to shift behaviour, and people find clever ways to collect the incentive without actually changing.

This isn't sabotage. It's intelligent people responding rationally to the conditions you've created, conditions that may not align as neatly with your intent as you imagined.

What Systems Change Actually Requires

If systems resist being changed from the outside, what does work? Not magic, and not heroics, but a different way of working with complexity.

Find the Leverage Points (and Accept That They're Rarely Where You Think)

Some interventions matter more than others. The trick is figuring out which ones.

Leverage points are places in a system where a small shift can produce significant change. But they're often counterintuitive. Pouring resources into a struggling programme might do less than changing the goal the programme is trying to achieve. Hiring more staff might be less powerful than changing the information flows that determine how staff spend their time.

The highest-leverage interventions are often the least obvious: the paradigms that shape how people think, the goals the system is organised around, the power to change the system's structure.

These are harder to see and harder to touch than, say, a new IT system or a restructure, but they're where lasting change actually happens.

Shift the Conditions, Not Just the Behaviour

If you want people to act differently, change the environment they're acting in. Exhorting them to behave differently within the same constraints is exhausting for everyone and rarely sticks.

This means working on incentives, information flows, decision rights, resource allocation, and accountability structures - the conditions that shape what's easy, what's hard, what's visible, and what gets rewarded.

It means asking not "How do I get people to do this?" but "What would make this the natural thing to do?"

Sometimes this is as simple as making the right thing easier than the wrong thing. Sometimes it requires dismantling structures that are actively working against you - and acknowledging the loss that creates for those who've built their work around them. Either way, it's not about willpower. It's about design.

Experiment and Learn in Public

You don't have all the answers. Neither does anyone else. Complex systems are too complex for that.

So run experiments. Small ones. Real ones. Not pilots that are secretly fully formed solutions in disguise, but genuine tests of assumptions where failure teaches you something useful.

And do it in a way that builds collective learning. Make your hypotheses explicit. Track what happens. Adjust based on what you learn, not what you hoped would happen. Invite others into the inquiry.

This approach doesn't feel as decisive as a big change programme with a glossy deck and a three-year roadmap. But it's far more likely to produce change that lasts, because it's responsive to the system as it actually is - not as you wish it were.

In complex adaptive systems, outcomes emerge from interactions and feedback, not from central control.

Work with the Grain (Even When You're Trying to Change It)

Resistance isn't always something to overcome. Sometimes it's information.

When people push back against a change, they might be protecting something valuable. Or they might see a consequence you missed. Or they might be pointing to a constraint you don't have the power to shift.

This doesn't mean you abandon the change. But it does mean you get curious. What is the system trying to preserve? What needs are being met by the current state, even if it's dysfunctional? Where is the energy for change actually coming from, and where is it absent?

Systems change isn't about imposing a vision from above. It's about working with the living reality of the system - its people, its history, its contradictions - and finding the pathways that open up when you stop fighting quite so hard.

A Question to Sit With

So here's the invitation: think about a change you're leading or supporting right now. You've probably done the analysis. You might even have broad agreement on what needs to shift.

Now ask yourself: are you trying to change the system, or are you trying to change people's behaviour within an unchanged system?

Because if it's the latter, if you're asking people to act differently without shifting the conditions that shape their choices, you're not leading systems change. You're leading an exercise in willpower. And willpower runs out.

Real systems change is harder and slower and less dramatic than most change programmes promise. It requires humility about what you can control, curiosity about what's really going on, and patience to work with complexity rather than against it.

But it's also the only kind of change that lasts.


Researched and written by Rebecca Agent, with credit to the following AI tools for assistance in producing this content:

. . .
 

Sources & Further reading

This article draws on contemporary research in systems change, organisational transformation, and adaptive leadership. A few key threads inform the thinking here:

  • On why insight doesn't automatically produce change: Research on implementation science consistently shows that systems thinking, while valuable as a diagnostic lens, rarely shifts behaviour unless embedded in the routines, incentives, and governance structures that shape day-to-day work (Nilsen, 2015; Academy of Management Annals, 2025). The OECD Observatory of Public Sector Innovation's work on systems approaches makes a useful distinction: systems thinking helps us see complexity; systems change is the work of intervening in it (OECD, 2019).

  • On transformation failure rates: The figure that 60–70% of large-scale transformations fail or underdeliver comes from longitudinal research across McKinsey & Company, BCG, and Harvard Business Review case studies spanning more than a decade (2015–2025). The pattern is consistent: organisations redesign strategy and structure, but the underlying systems - incentives, decision rights, operating models - quietly reassert themselves.

  • On complex adaptive systems: The framing of change as emergent rather than programmable is informed by recent systematic reviews on complex adaptive systems in healthcare and public policy (Cairney & Toomey, 2025; Health Foundation, 2024; Emerald Publishing, 2025). These studies emphasise that outcomes emerge from interactions, feedback loops, and adaptation - not from central control.

  • On leverage points: Donella Meadows' Thinking in Systems (2008) remains the foundational text on leverage points. The core insight holds: the highest-leverage interventions are often the least obvious - paradigms, goals, and system structure matter more than parameters and flows.

  • On adaptive leadership: The shift away from heroic leadership models toward leaders as stewards and enablers of emergence is well documented in recent reviews (Sott & Bender, 2025; Cairney & Toomey, 2025). Heifetz, Grashow, and Linsky's The Practice of Adaptive Leadership (2009) remains essential reading on navigating loss, power, and informal authority in systems change.

  • On experimentation and learning: The argument for small, genuine experiments - and against "pilots" that are really disguised rollouts - comes from evaluation research on systems change initiatives (Evaluation Journal, 2025) and from Westley, Zimmerman, and Patton's Getting to Maybe (2006), which frames systems change as an ongoing learning process rather than a fixed intervention.

  • On systems thinking as cognitive framework: Recent research demonstrates that systems thinking functions as a cognitive capability at the organisational level, not merely an individual skill or analytical method (Burato et al., 2023).

. . .

Reference List

. . .

See related pieces (on the blog) :


If this content was helpful to you and your work please comment, share, and like !

Strategic Innovation, Embedded ChangeRebecca AgentComment