Our contemporary obsession with complexity frameworks is a symptom of a deeper malaise. In almost every sector, but especially in governance, business, education, technology, security and even defence – we feel a world slipping beyond the grasp of established logics. The response has been to apply “new” logics: matrices, continua, quadrant diagrams, taxonomies of order and disorder, each promising to tell us where we stand and how we should proceed. They give us the impression of sophistication. They comfort anxious leaders with the suggestion that, before we act, we can diagnose the nature of the situation and match it with the appropriate toolkit.
Thus they appear to promise diagnosis before action, order before engagement, and methodological confidence in the face of ambiguity. My contention in this essay is that these promises are mis-framed: in social systems, complexity is never encountered “raw”. It’s always already shaped by the narratives through which we make sense of the world.
Systems thinking has long sought ways to orientate action in uncertain environments. Some approaches – from Peter Checkland’s Soft Systems Methodology to Jay Forrester’s system dynamics, and from scenario planning matrices to participatory modelling – engage directly with pluralism, feedback, and emergence without attempting to classify situations in advance. Others rely on grids, matrices, and typologies: Ralph Stacey’s Matrix, David Snowden’s Cynefin model, and various complexity continua propose locating a situation along axes of certainty, agreement, predictability, or coherence and, from that positioning, infer an appropriate mode of response. The appeal of these classificatory frameworks is understandable. In a turbulent world they seem to offer a stable vantage point, a way of standing outside the mess in order to organise it. Yet this promise is largely illusory.
Even the better frameworks conceal as much as they reveal because they perpetuate the idea that we can occupy a neutral vantage point outside the systems we inhabit, inspect them as objects and classify them as simple, complicated, complex, or chaotic prior to intervening. They invite us to believe that the nature of a system is there to be discovered in advance of engagement, as though complexity were a fixed property of the world, independent of the ways we make sense of it and the stories that authorise us to act.
The most influential alternative to such ontological frameworks within systems thinking is the System of Systems Methodologies, first articulated by Michael Jackson and Robert Keys in 1984. Unlike complexity matrices that claim to describe properties of the world “as it is”, the SOSM operates at a second‑order level. Its intent is epistemological rather than ontological. It doesn’t ask what kind of system we’re confronting, but what kind of world a given methodology assumes it’s intervening in. That distinction is foundational.
The SOSM reveals that methodologies do not simply analyse reality from different angles; they presuppose different realities altogether. Hard operations research imagines a unitary, optimisable world in which problems can be clearly formulated and solutions computed. Soft Systems Methodology presumes a pluralist and socially constructed world in which “problems” are negotiated between actors with differing worldviews. Critical systems approaches foreground power, coercion, and marginalisation, and therefore assume a world in which emancipation and voice are central concerns. Complexity‑informed approaches assume non‑linearity, emergence, and irreducibility. In this sense, methodologies are not neutral tools. They are meaning‑making devices. Every method embodies a theory of reality, of agency, of what counts as improvement, and of who has the right to decide.
The value of the SOSM lies in its reflexivity. It forces practitioners to confront their own assumptions before acting, rather than projecting certainty onto the situation itself. It aligns implicitly with second‑order cybernetics: the observer cannot be separated from what is observed, and intervention alters the very conditions it seeks to address. Instead of pretending to see the world “as it is”, SOSM encourages us to see how we are seeing, and to choose our methodological stance accordingly.
That move is vital because the central flaw in ontological complexity matrices is their overconfident assumption of pre‑intervention diagnosis. They imply that one can determine whether a situation is simple, complicated, chaotic or complex before engaging with it. In lived social systems, this is rarely possible. Complexity is not a stable property waiting to be discovered. It’s a property that emerges through interaction. The moment we intervene, we reshape the system’s behaviour, its feedback loops, and its apparent level of complexity. A situation may appear merely complicated under a command‑and‑control intervention, yet rapidly reveal itself as complex or chaotic once participation, contestation, or learning are introduced. The difference doesn’t lie in the system alone, but in the epistemic stance brought to it. Complexity, in this sense, is relational.
This recognition is one of the strengths of David Snowden’s Cynefin framework. Snowden is correct when he argues that Cynefin is better positioned than many earlier models to deal with complexity. Unlike a static two‑by‑two grid, Cynefin treats context as dynamic and emphasises that we’re always, unavoidably, in the system we’re trying to make sense of. It refuses the comforting fiction that situations can be classified once and for all. It distinguishes between ordered and unordered domains, acknowledges non‑linearity, and insists that in complex situations the appropriate mode is to probe, sense, and respond. Small, parallel, safe‑to‑fail experiments, conducted by diverse groups, are favoured over grand designs and universal recipes. Cynefin recognises that systems can and do shift between domains, sometimes abruptly, depending on how they are engaged. On those terms, it is indeed a substantial advance on the Stacey Matrix and similar typologies. It is already a critique of naïve systems thinking, pushing participants away from mechanistic blueprints and towards contextual, iterative judgement.
However, even 2nd‑order approaches such as the SOSM, and even a sophisticated complexity framework such as Cynefin, reach their limit at a deeper threshold. Cynefin presents itself as a sense‑making framework, and that seems modest enough. In practice, though, it is already making prior commitments about reality: what counts as a “context”, who has the authority to name it, and what kinds of responses are legitimate. It assumes, for example, that the world can be meaningfully parsed into domains such as clear, complicated, complex, chaotic, or aporetic; that actors can agree, at least provisionally, on which domain they are in; and that it’s acceptable, and safe enough, to run probes, tolerate certain failures, and learn from them.
Those assumptions don’t arise from the science of complexity alone. They evolve from stories about expertise, responsibility, and progress. Cynefin works best in cultures where experimentation is valued over blame, and some degree of decentralised agency is permitted. It also assumes executives who are willing to admit not knowing and to share sense‑making. In many institutional settings, those preconditions are absent, not because people are ignorant of complexity, but because the governing narrative punishes uncertainty, pathologises dissent, and centralises control. In such settings, the same Cynefin practices manifest very differently: probes become sanitised pilots, “safe‑to‑fail” degenerates into “must‑succeed” under another name, and feedback that challenges officialdom of any kind is suppressed. What appears, from a Cynefin perspective, as complexity or incoherence is, from a narrative perspective, the collision between a failing story and an emerging reality.
Up to this point I have focused on how different frameworks position us in relation to complexity. But there’s a deeper layer that remains largely unexplored that even SOSM and Cynefin don’t fully address. Both of these help us choose between methodologies and adapt our responses to contextual conditions, but they don’t interrogate why certain forms of sense‑making are available, legitimate, or compelling in the first place. They remain focused on how we intervene, rather than on the stories that make particular interventions imaginable. They rarely ask why some cultures, sectors, or regimes refuse complexity‑appropriate action even when it’s clearly in their interest, or why in other settings everything is suddenly declared “complex” as a way of avoiding accountability. Those are not methodological puzzles so much as narrative phenomena. To address that deeper layer, we began to work explicitly with narrative itself.
This is precisely the gap Marvin Oka and I attempted to work with in developing the Transformational Narrative model. If 1st‑order change alters behaviours within an existing frame, and 2nd‑order change questions and adapts the frame itself, then 3rd‑order change concerns the stories and deep coding that make any frame intelligible or legitimate in the first place.
The Transformational Narrative methodology is an interaction of three models operating to instill 3rd-order change. It does not classify systems, nor does it only critique methodologies. It intervenes in the narrative architecture that holds a system together. It starts from the recognition that organisations, institutions, and societies do not primarily run on structures or strategies, but on stories: stories about purpose, contribution, risk, evolution, responsibility, authority, and even time itself. These narratives are not decorative. They are causal.
To intervene at this level of 3rd-order change requires morphological analysis within what I refer to as the “expanded now” – a reflective space in which past, present, and possible are held in suspension, freed temporarily from the relentless pressure of clock time. This is not a stance outside the system or outside time, but a way of becoming more consciously aware of how we are already immersed within it: how remembered histories, present commitments, and imagined futures co‑shape what we can see and do.
Within this field of inquiry, the narrative architecture of systems becomes visible, and we see how alternative stories actively modulate complexity as experienced. Within the “expanded now” we can apply “acupunctural” analysis to find the most benign points for intervention. Deep design then becomes possible. Not design as blueprint or plan, but as a repatterning of meaning that honours memory, engages presence, and opens toward potentiality. It is from this field that new stories can be articulated with enough integrity and coherence to shift the attractor landscape of a system.
This is not to suggest that narrative somehow replaces material conditions or biophysical constraints. Rather, narratives and material systems co‑evolve: stories shape structures, and structures in turn reinforce or erode stories.
Narratives determine what counts as a problem, who is allowed to act, which risks are tolerable, what time horizons matter, and which futures are even conceivable. Before there can be agreement or disagreement, certainty or uncertainty, there must be a shared narrative frame within which such distinctions make sense. Until that frame exists, attempts to classify complexity are premature. The choice between “sense-categorise-respond” and “probe-sense-respond”, or between hard operations research and Soft Systems Methodology, is always made inside a story about who we are, what we owe each other, and where we think we’re heading.
In this light, complexity does not precede narrative; it follows it. What we experience as complexity in social systems is already filtered through, and shaped by, our underlying stories. So, although Snowden is justified in claiming that Cynefin is better positioned than most models to engage with complexity, at least as it appears within prevailing institutional narratives, my argument goes further: those self-same narratives modulate what counts as complex, which probes are thinkable, and which signals can be heard.
In one city we worked with, a shift from “global competitiveness” to “intergenerational stewardship” as the guiding story led, within three years, to reallocating budget from road expansion to urban wetlands restoration and community land trusts. The technical tools used (scenario analysis, participatory design, systemic acupuncture, and complexity-informed policy prototyping) were not new; what changed was which tools were considered legitimate and what counted as “success”.
In practice, this kind of work means convening processes where people surface the stories they are inhabiting, test them against lived realities, and prototype alternative narratives through concrete experiments in policy, governance, and everyday life. The Transformational Narrative Model makes visible something that neither Stacey nor SOSM nor Cynefin can fully account for: narratives actively amplify or dampen complexity. Scarcity, fear, and control narratives increase volatility and brittleness. They narrow option space, suppress learning, and produce defensive behaviours that escalate systemic risk. In such stories, safe-to-fail experiments are domesticated into risk-free trials, and the slightest sign of failure is punished, which in turn distorts feedback and fuels fragility. Conversely, regenerative, evolutionary narratives expand adaptive capacity. They legitimise experimentation, distribute agency, and enable emergence without collapse. In those circumstances, the same technical conditions are met with curiosity rather than panic. Complexity becomes challenging but hardly ever paralysing.
Thus, true complexity is not merely revealed by engagement; it is modulated by meaning. A food system communicated as a global efficiency machine will be organised in one way; the same biophysical realities narrated as a living commons of interdependence will be organised very differently. The material intricacy of soils, climate, labour, and logistics is real in both cases, but the apparent complexity of governance, coordination, and crisis response will differ radically.
At scale, this insight is decisive. Many of the failures we attribute to complexity – in governance, education, economics, climate response, and now artificial intelligence – are in fact failures of narrative. This is the main point I am making in my book, Teaching Silicon How to Feel. Institutions persist in reciting stories that no longer explain their reality, justify authority, or command trust. As these narratives lose credibility, coordination falters, polarisation accelerates, and systems inevitably tip into instability. We then label the resulting turbulence “complexity” and reach for more elaborate frameworks in an attempt to stabilise what is, at root, a breakdown in meaning.
Consider four fault‑lines that are affecting people everywhere: escalating climate disruption, recurring financial crises, the rapid spread of algorithmic systems and AI, and the erosion of trust in public institutions. In each domain, experts talk fluently about non‑linearity, tipping points, feedback loops, emergent risks. Cynefin‑like thinking is often present: probing scenarios, mapping contexts, experimenting with interventions. Yet the overall trajectory barely shifts. Why is that? One hypothesis, which I would frame as a question inviting further inquiry, is that the limiting factor is not our capacity to recognise complexity, but our reluctance to question the meta‑stories that have guided modern civilisation for the past few centuries: stories of endless economic expansion, of human separation from the rest of life, of salvation through technology, of nation‑states locked in perpetual rivalry.
Take AI as one example. Dominant narratives here include geopolitical competition – “If we don’t race ahead, others will, and we will be dominated” – and techno‑solutionism – “Any serious problem can and should be handed to machine intelligence at scale.” Inside those stories, calls for caution, reversibility, or genuine safe-to‑fail experiments look like weakness, naivety, or blatant obstruction. The language of complex systems can be deployed, but the direction of travel is set: accelerate, scale, pre‑empt rivals, absorb collateral damage. So Cynefin can help practitioners navigate within that frame, but it does not, and probably cannot on its own, authorise the deeper question: what if the story itself is pathological?
A similar pattern arises in climate policy conducted within the story that perpetual GDP growth is non‑negotiable, or in healthcare organised under the story that market efficiency is the supreme value, or in education systems bound to the story that standardised testing defines merit. In such circumstances, Cynefin improves navigation inside the inherited game; a Transformational Narrative inquiry, however, asks whether this is the game we should still be playing at all, and, if not, what other game might confer dignity, viability, and coherence.
The Transformational Narrative model does not ask, “What kind of system is this?” It asks, “What story is this system trapped inside, and what story would make a different future possible?” It investigates how grand worldviews – shared civilisational belief systems – manifest as palpable world‑systems, and how those world‑systems are interpreted and reinterpreted through malleable (and multiple) cultural mindsets. It makes explicit the myths that underwrite progress, security, sacrifice, and belonging in different societies, and examines how those myths shape material arrangements: energy infrastructures, legal codes, digital platforms, trade routes, border regimes et al. It recognises that a young entrepreneur in Accra, an elder in a First Nations community in Australia, a gig worker in Manila, and a civil servant in Berlin are all, in different ways, caught up in overlapping world‑systems driven by stories that may or may not serve their aspirations or their environments.
Once identity, purpose, and legitimacy are reframed at that narrative level, questions of methodology and complexity reorganise naturally around the new narrative centre. If a city shifts from seeing itself as a competitive growth engine to seeing itself as a steward of ecological and cultural well‑being, the Cynefin domains will be experienced differently; what once felt chaotic now appears as necessary discontinuity, what once seemed merely complicated now opens into fruitful complexity. If a school moves from a narrative of ranking and exclusion to a narrative of capability and contribution, the same classroom dynamics present as a different kind of system.
In that regard, if the Stacey Matrix offers a map, and SOSM offers a map of maps, and Cynefin offers a dynamic way of moving between maps as contexts shift, then Transformational Narrative reshapes the terrain itself. It changes what actions make sense, what futures can be named, and what forms of innovation are possible. It doesn’t add yet another box or domain; it questions why these boxes and domains were drawn in this way in the first place, for whose benefit, and what other cartographies might be required now.
In an age defined less by technical difficulty than by narrative exhaustion, this is not merely better systems thinking. It is arguably the precondition for real systemic metamorphosis. Complexity frameworks, including Cynefin, are at their best when they help us navigate situations where the underlying story still holds enough coherence to allow investigation and adaptation. Where the story itself is decaying – where people no longer believe in the promises being marketed by their institutions, where the symbols of authority have lost their charge, where young generations sense that inherited futures are bankrupt – complexity language alone is insufficient. Without inquiry at a narrative level, we will continue to mistake symptoms for causes and turbulence for fate.
Transformational Narrative doesn’t remove difficulty. It relocates agency. Instead of waiting for experts, algorithms, or senior executives to tell us which quadrant or domain we currently inhabit, we begin to ask what stories we are living by and whether those stories are still worthy of our allegiance. That profound question applies across all cultures, religions, and circumstances. No worldview, East or West, North or South, has a monopoly on wisdom or folly. Every tradition holds stories that can be reinterpreted and renewed; every community hosts emergent narratives that challenge the prevailing scripts.
When we engage at that level – exposing the stories, testing them against lived reality, and crafting alternatives grounded in actual experiments of living differently – we begin to shift the attractor landscape of our systems. New forms of co‑operation and co‑creation become thinkable. Old reflexes of control and denial become harder to justify. Complexity remains, but now it’s encountered within narratives that enhance, rather than erode, our collective capacity to respond.
Again, Dave Snowden is correct to insist that complexity demands different habits of thought and action than those inherited from the industrial era. I would simply argue that, in the end, even Cynefin is downstream of story. Before we declare a situation complex, we’re already in a narrative that decides what the situation is, whose suffering counts, which futures matter, and who gets to draw the frameworks. Transforming those narratives is not a luxury or an afterthought. It’s the ground on which any meaningful response to complexity must stand.