A larger reality: how governments can escape the local maximum

Back in September, James Plunkett and I launched the Centre for the Edge, a new collaboration between JRF and Kinship Works. We are interested in how public institutions can renew themselves in a moment when the systems that once felt stable are faltering, and increasingly disconnected from the vibrant alternatives emerging at the edges. We want to explore how to help public institutions bridge to these new practices and possibilities — not to drag them into existing domains, but rather to adapt and learn from them.

This week, we’re publishing two essays that explore questions of data, measurement and control mechanisms. James kicked off the story with a question: is government stuck in a “local maximum”? In his piece, which you can read here, he uses the image of a robot vacuum cleaner trapped under a table to explain this concept: imagine the machine, busy, diligent, and fairly efficient within a tiny patch of carpet, but fundamentally unable to see the wider room and what cleaning might be needed there.

This essay is my response to James’s piece. Let me know what you think.

I think James poses a crucial question in his piece: what if government is not simply performing poorly against some important indicators, but is actually structurally stuck in the “local maximum” that his piece describes? The question I take from James’s provocation is this: what if the problem is not so much a lack of effort or good intent, but rather the narrowness of the lens through which public institutions perceive knowledge and value, risk and possibility? What if the institutions that have been designed to stabilise and predict are now at risk of leaving themselves blind to complexity and opportunity?

This rings true to me, as someone who is trying to steward a programme of work to resource the energy at the edges, from inside a large philanthropic organisation. From this vantage point, I see a kind of epistemic and imaginative narrowness, as well as the methodological narrowness that James points to. Public institutions — and I include philanthropic foundations and think tanks alongside government departments here — don’t just overuse certain tools; they tend to underuse entire ways of knowing, especially relational, experiential, community-rooted and future-facing ones.

In James’s terms, they cling tightly to the “A-space” — the domain where problems are legible and causality is predictable — while largely overlooking the “B-space”, where complexity lives, and where the future often arrives, unevenly and from the margins.

I am not advocating that we abandon one space in favour of the other. Rather, I am interested in the tensions that come from the need for public institutions to live in two worlds at once. One is the world they were built for — predictable, legible, stable. This is their comfort zone, and it is what their architecture is designed around. The other is the world as it actually is — turbulent, complex, characterised today by a series of interconnected and cascading crises, as well as glimmers of possibility that defy existing categories.

The tension between these worlds is the heart of the “local maximum” that James identifies. I think that escaping it and finding better ways to move between these worlds requires three critical capabilities:

• A deep learning orientation, allowing institutions to move away from the false comfort of predictability, to practise sensing, adapting and acting in real time.

• Epistemic justice, widening the knowledge we value, and in doing so expanding the aperture of reality and possibility.

• The cultivation of imagination as a critical and legitimate form of anticipatory evidence.

These capabilities are not abstract ideas. They manifest in the capabilities we build in the state: the institutional designs, the methods and disciplines we give weight to, the people we hire and the skills we cultivate. Together they stretch the cognitive and cultural bandwidth of public institutions. They hold the potential of enabling public institutions to live productively between the worlds that James maps so well. Each of the capabilities I explore here in more depth can help institutions to dance between these modes without collapsing everything into one, or denying the importance of the other.

It’s hard to write a piece like this to describe these capabilities, as what I notice is that they only really come alive in practice. And each of these themes is already being modelled by many organisations who are currently working “at the edge” — even as they struggle to convey the value and power of their work when considered against the narrow field of view that the provocation diagnoses. As I explore further down, there are also some examples of where governments are beginning to put them into practice too.

So, if public institutions want to learn how to do this, they would do well to get out to the edges — not to fold them into the centre, but rather to learn from them about how to inhabit complexity, how to work with wider forms of evidence and ways of knowing, and how to rehearse the better futures we dream of. But for now, I hope this piece is a helpful stimulus for discussion.

Learning as a capacity to be cultivated

Government’s local maximum is sustained by a mental model of linearity — in a world that is inescapably non-linear. Moving past the local maximum requires institutions that can learn in motion, not merely review in hindsight.

Back in 2002, when I was working at Demos, we commissioned energy professor Jake Chapman to write a pamphlet about the application of systems thinking to public policy questions. System Failure went on to become one of our most widely read publications. In it, Jake invited public policy officials to step away from machine metaphors and linear cause-and-effect models of change — the dominant mindsets of the early New Public Management era — and instead see public policy challenges through ecological eyes.

James picks up these themes in his piece when he highlights the dominance of narrow evaluation methods. These tools work well for predictable systems. But I completely agree with James that we can no longer ignore the complex, non-linear reality around us. I would argue it was always a fantasy anyway. Yet many government evaluations still assume the very qualities that contemporary challenges don’t always possess: predictability, stable causality, and responsiveness to control mechanisms, to name a few.

This is not just a methodological or tools-based problem. Beneath that lies a more fundamental question too: how do public institutions understand change itself? To answer that, we need to look at the metaphors that shape the way governments imagine change. This matters because the lens through which we view change shapes how we understand impact, and in turn, how we evaluate it.

Returning to Jake’s pamphlet, he wrote about ecological models of change — models that centre evolution, adaptation, emergence, and the relationships between things, as well as the things themselves. These metaphors echo many living-systems traditions: the Berkana Institute’s two-loop model, which we use at JRF; the Māori Haumanu framework; Theory U; and wider fields like integral theory and spiral dynamics. They all share a lineage that understands systems as alive, relational and dynamic.

It continues to intrigue me how public institutions — and others, here’s looking at you, economics curriculums — can so easily sideline this long and respectable history of holism in favour of the relatively recent mental models of rationalism and duality. But that’s an essay for another time.

My observation for now is this: governments struggle because their dominant paradigm treats learning as a downstream activity “done to” the system, rather than a living operating principle that needs to be cultivated as part of nurturing change in adaptive complex systems.

I’m going to simplify things to illustrate my point. There are, of course, brilliant civil servants who understand these challenges deeply. But at an organisational level, public institutions tend to treat learning as:

• An audit function: “prove this worked”.

• A performance regime: “show me the KPIs”.

• A compliance task: “complete the reporting template”.

The learning traditions rooted in ecological worldviews offer an alternative. Think of Chris Argyris’s double- and triple-loop learning, Donella Meadows’s work on mental models, or Human Learning Systems’ emphasis on relationships, context and adaptation. These frameworks share a core insight: in complex, emergent systems, learning is not an after-the-fact evaluation activity. It is the work.

Take the Three Loops of Learning model. This positions learning as operating across different layers:

• Single-loop learning: Are we doing things right?

• Double-loop learning: Are we doing the right things?

• Triple-loop learning: How do we decide what’s right?

Too often, public institutions remain trapped in the first loop — optimising delivery, designing for predictability and refining processes accordingly. It is this that keeps them stuck in a local maximum. Meanwhile, complex challenges require learning systems: organisations that engage in the double and triple loops too, by cultivating inquiry, sensing, reflection and adaptation as everyday habits.

So what might it look like to treat learning as the operating system itself?

UNDP’s portfolio sense-making approach offers one example. It starts with the premise that no single actor sees the whole picture in complex environments. Sense-making therefore becomes a collective, relational practice — bringing together multiple perspectives to interpret emerging signals and consider what they might mean. UNDP treats these spaces as the “engine room” of their strategy work: sites where the organisation learns in real time, bridging quantitative data with lived experience and narrative insight, and creating a shared interpretation of system shifts rather than a narrow tally of outputs.

This shift — from mechanistic metaphors to a living-systems perspective — is, I believe, foundational to our ability to navigate the polycrisis. In living systems, change happens through learning, adaptation and emergence, not simply through delivery and evaluation. In this view, systems can change in certain directions because actors develop a shared “pattern literacy”, and then have the capacity to adapt together in real time.

This speaks directly to James’s critique. The state keeps iterating on the logics it already knows — more reporting, more controls, more precision — when what is needed are learning ecosystems and real-time sense-making infrastructures. The tools are not the blockage; the paradigm is.

Putting this into practice — some ideas

• Create “dual operating modes” in government: units that deliver predictable services alongside teams that explore, prototype and experiment.

• Encourage adaptive governance: develop evaluation systems that value learning over compliance, and track relational, systemic and long-term change.

• Embed structured reflection and sense-making into team routines.

• Shift MEL — monitoring, evaluation and learning — from compliance to inquiry.

• Invest in capabilities for working with complexity, such as systems thinking.

• Adopt developmental and complexity-aware evaluation approaches.

• Fund learning partners, not just evaluators.

• Use measurement to understand patterns, relationships and emerging dynamics.

Epistemic justice: who gets to speak?

Whose experiences are afforded the dignity of being treated as evidence or valuable insight in the first place? Escaping the local maximum requires a widening of perspectives on where knowledge lives, and who is permitted to hold it.

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James argues that our public institutions only recognise a sliver of what is knowable; I agree. Miranda Fricker’s notion of epistemic justice really helps to illuminate the stakes here. She describes epistemic injustice as a “wrong done to someone in their capacity as a knower”. It’s a particularly silent form of injustice, where certain people’s words are discounted before they’ve even left their mouths, where their wisdom is dismissed and rendered invisible. It often happens when certain voices do not match the tone and timbre that institutions have become attuned to. This costs those institutions in two ways: valuable knowledge is not used, and the person from whom that knowledge originates is diminished.

This isn’t just about individuals. Epistemic injustice is also in action when whole groups are kept outside the powerful circles where policies are made, because their concepts and ways of making meaning don’t fit the official lexicon. Their stories don’t travel well through the authorised channels, and so their experience becomes somehow illegible to those sitting within the logics of our public institutions.

This is a strange kind of invisibility: it is a form of injustice that isn’t about the absence of certain people, but rather the absence of particular concepts or ways of seeing the world. In the global north, this manifests most obviously as colonial thinking, white supremacy, ableism and poverty stigma. As many marginalised communities know, if you cannot say your experience in a form the system recognises, it is as though your experience does not exist.

From the work I do, I observe that this injustice is not limited to identity-based marginalisation alone. It also extends to those whose worldviews stretch beyond the narrow tramlines of our current economic models: the visionaries, the community weavers, the healers, the practitioners building new models of living together rooted in values like solidarity, regeneration and interdependence.

The knowledge of these people at the edges is not discounted because it lacks depth or rigour, but because it lives beyond the assumptions of institutions built to exist in an economic operating model whose foundations are extraction, efficiency and control. When someone speaks from a worldview centring reciprocity or relational balance, their insights often sound unintelligible within policy frameworks that assume individualism. When someone speaks from an ontology of regeneration and more-than-human perspectives, they are dismissed as fantasists against the political imperative of growth. They become marginal because their principles do not fit.

I think this stuff is going to matter more, not less, in a world shaped by AI, where the robots get to decide more and more of what we notice. AI is designed to amplify the patterns it already sees, meaning that there are huge risks that epistemic injustices become silently baked in and automated into both knowledge-generating processes and decision-making processes.

So epistemic justice asks us to do something that’s likely to become ever more important in an AI-driven world: to build institutions that can hear without shrinking the world to fit their existing or inherited categories. It is a call to treat a rich diversity of lived experience — whether that is forged through oppression or radical imagination — as credible on its own terms, and as a crucial counterweight to AI-generated models where errors and biases can grow rapidly.

There are governments who are tentatively beginning to explore this, from whom we can learn. Wales’s Well-being of Future Generations Act, with its long horizon and its insistence on cultural and ecological knowledge, hints at the potential of a broader epistemic base. New Zealand’s work on Māori data sovereignty challenges colonial assumptions about who gets to interpret community knowledge. Canada’s distinctions-based approach makes room for Indigenous worldviews to shape, rather than simply comment on, policy architecture.

bell hooks shows us how systems reproduce domination when they anoint some experiences as authoritative, and reduce others to mere anecdotes. So as I read James’s piece, I wanted him to draw the full conclusion of what he hints at: that many of the system’s failures today come from its refusal to recognise the full spectrum of human knowing.

It’s time for the centre to become more edge-literate, rather than demanding that the edge must fit into the centre’s dominant logics.

Putting this into practice — some ideas

• Expand what counts as “value”: not just economic or output metrics, but also intangible things like care, solidarity, wellbeing and ecological resilience.

• Measure more than efficiency: include relational outcomes, such as trust and community capacity, as well as equity and systemic resilience.

• Bring in community-led and distributed governance models, such as participatory budgeting, community assemblies and co-design frameworks.

• Involve communities with lived experience in framing and interpreting evidence: build participatory and co-created evaluation processes.

• Build policies and institutions that emphasise trust, reciprocity and relationships, not just transactions.

• Create spaces to question underlying narratives and institutional logics: encourage inquiry into purpose, equity and long-term outcomes.

• Train leaders in reflective and relational practice.

Imagination as a practice of possibility

Imagination reveals unrealised possibilities, emergent patterns and future conditions — all crucial to the art of good government, which is about building better futures as well as managing current challenges.

If learning helps institutions understand the world more fully, and epistemic justice helps them hear it more clearly, then imagination is what helps institutions see beyond the world as it is now. It’s the capacity that a system has — or lacks — to perceive that which does not yet exist, to detect the glimmers of something that hasn’t yet fully come into view.

Building on the arguments of James’s piece, I would suggest that the challenge for public institutions in their use of data and evidence is less of a technical one, and more of a topographical one: current practice is designed to build a sharper picture of the geography of where we are. But we need imagination too, to glimpse the landscape beyond our current maps.

This matters, because public institutions exist not just to manage systems, but also to shape future possibilities.

For three years now, JRF has supported a network of 700+ imagination practitioners. Their work on the ground alongside communities up and down the country has brought people together to imagine how they might rearrange their relationships to food, energy, land and one another. These imaginative acts often start with a simple “What if?” question, a conversation between a few people in a community hall or around a kitchen table. But over time they can morph into new social enterprises, new collaborations, and new-found purpose for derelict buildings and abandoned parks. The imagined becomes the material. What begins as possibility becomes proof.

Imagination, then, can be understood as a form of anticipatory evidence that bridges into the future. It allows public institutions to think beyond the immediate cycles of performance indicators and difficult budgets. By rehearsing futures that are grounded in the values and practices we want to grow, we are better able to detect patterns and opportunities today that will bear fruit over the longer term.

This kind of anticipatory work often yields insights into resilience, adaptability and latent capacity that are all but invisible to traditional evaluation methods. Like triple-loop learning, imagination practice not only asks “what should we do?” but also “what should we value, and who should decide what becomes possible?” It expands the space of the thinkable.

To imagine is also to refuse inevitability. It is to hold on to the hope that other worlds are possible beyond this one that is riven by economic injustice and ecological collapse. In this sense, I think it has important connections to epistemic justice: imagination is a site of power, for whoever imagines the future gets to shape it. When imagination is monopolised by the already powerful, we end up with futures designed in the image of the present. When imagination is returned to communities — especially those who have experienced marginalisation, or those whose work operates at the edges — we grow futures that do not simply re-pattern the way things are now.

It’s fifty years since Alvin Toffler wrote Future Shock, which warned of the dangers of societies losing their bearings because they lacked the imaginative range to navigate rapid change. Back in 2023, James wrote a wonderful piece about Toffler’s book, with lots of resonance with our two pieces here now.

Today, as AI systems increasingly shape our way of understanding the world, we need the strategic intelligence of human imagination more than ever. AI models can only articulate futures that are versions of what has already been, anchored in priors and patterns that we will need to move away from if we are to find a pathway through the polycrisis.

I want us to hold on to our capacity to imagine futures that the models can’t easily predict. In that sense, I see collective imagination as so much more than an act of creativity. I think it’s a vital form of civic infrastructure that we need to cultivate with great care.

By embedding imagination into the routines of governance through foresight exercises, scenario planning, community visioning and participatory prototyping, we could turn it into a continuous, actionable form of broad and wide knowledge. It could be a central instrument of public decision-making: helping institutions to detect early signals of change, to prototype emerging futures, and to recognise patterns that the present cannot fully explain.

Imaginative practices let systems “see” their own adjacent possibles — those neighbouring, reachable futures that remain invisible until someone somewhere is brave enough to name them.

Gloria Steinem once declared that “imagination is a form of planning”. I love this: it underlines this notion of imagination as crucial source material for public institutions. It invites public officials to see those who cultivate imagination as serious “practitioners of possibility” who play a vital role in the art of governing in a polycrisis.

Other governments are beginning to recognise this. Finland’s Committee for the Future, Singapore’s Centre for Strategic Futures, Ireland’s anticipatory governance unit and the UAE’s Ministry of Possibilities are all early expressions of an institutional imagination practice trying to be born.

Ultimately, I think we need to treat imagination as the anticipatory material of possibility. It reopens the future, offering governments a way out of the blind and frankly terrifying alley of the present. And it reminds us that the landscape beyond the local maximum is alive with experiments, prototypes, visions and relationships that only become legible when we learn to look together at the imaginative possibilities of less familiar territory.

To take imagination seriously is to take the future seriously, and to recognise that we are not only managing systems but shaping future possibilities. Both are critical to good government.

Putting this into practice — some ideas

• Treat imagination as a legitimate and serious source of strategic insight. Recognise imaginative tools as central to decision-making. You could start with this set of imagination practices we curated, as well as foresight exercises, scenario planning and participatory prototyping.

• Build institutional infrastructure for imagination, for example in strategy units. Create protected spaces for creative exploration, collective imagination and speculative thinking.

• Embed explicit futures mandates in government strategy, such as long-term horizon goals, futures offices and strategic reviews.

• Combine foresight with evaluation in strategy and policy cycles. Recognise imaginative work as legitimate strategic input: require staff to demonstrate how they are bridging today’s decisions with future trajectories.

• Reform budgeting and planning processes to account for long-term social and ecological outcomes.

• Build futures literacy across government. Train officials to interpret weak signals, explore adjacent possibilities and anticipate emergent trends.

• Support and recognise “creative bureaucrats” who blend policy work with experimentation, through reward structures, funding and capacity-building support.

• Support communities and civil servants to dream into and rehearse the future. Democratise foresight practice, involving diverse communities in imagining and co-designing future scenarios.

• Convene multi-stakeholder, cross-sector foresight forums regularly to interpret emerging signals and shape shared visions.

Dancing between predictability and emergence

If there is a single thread running through both James’s essay and this response, it is that public institutions are being asked to live in two worlds at once. One is the world they were built for, a landscape of predictability, legible problems and stabilising routines. The other is the world as it actually is: turbulent, interdependent, marked by cascading crises and glimmers of possibility that don’t fit neatly into existing categories.

Much of the systems field has been grappling with this tension for decades. Dave Snowden’s Cynefin framework reminds us that there are domains where order holds and where plans, metrics and targets still have enormous value. But he also describes the adjacent terrain that is relational, complex and constantly shifting. In this territory, cause and effect can only be known in retrospect: what matters is attentiveness rather than control. The work is about sensing and adaptation, rather than prediction and optimisation. The long lineage of complexity theorists all tell us the same story: systems must be capable of both stability and renewal if they are to remain alive.

What is new is the scale and urgency with which public institutions must now cultivate this dual capacity. The question for public institutions is not whether they should choose predictability or emergence. It is how they might hold both at once, moving fluidly between them without tearing themselves apart.

That is not the same as co-opting everything into one system or the other. In fact, what we really need are governance processes that can move fluidly between modes: processes that allow a department to deliver benefits payments predictably on a Tuesday morning and still create space on a Thursday afternoon to explore the future of economic security with communities whose knowledge is too often sidelined.

The capacity to do this dance depends on the quality of the institution’s imaginative practice and mindset. It depends on whether the institution sees itself as a learning system, rather than a performance machine. It relies on those institutions being willing and able to work with epistemically just systems of evidence rather than epistemically narrow ones.

James and I are interested in asking how government might escape its local maximum. I think the answer is that it must learn to see a larger reality: to stretch its conception of evidence and to widen its field of view. I recognise that these aren’t marginal adjustments or simple technical fixes. They’re the foundations of a different kind of public institution: one that regains the capacity to perceive possibilities more clearly, and thus steer towards more equitable and just futures, rather than remaining trapped in the local maximum of simply reacting to what is and what has been.

This essay is published as part of the Centre for the Edge, a partnership between JRF and Kinship Works to help public sector leaders support and spread promising alternatives. You can read more about the initiative here.