Four registers: crisis, organising, culture, information
Crisis thinking, teal organisations, metamodernism and warm data each express complexity thinking in a different register. Read through complexity, each gains discipline. Each also supplies something complexity science lacks.
Why these four
Complexity science is good at mechanisms and weak at most other things. It can explain how a cascade spreads. It has less to say about why anyone should care, how to organise people to respond, how to commit to a direction you know is partial, or what kind of information would show you the pattern in the first place.
These four bodies of work each answer one of those gaps, in their own register. Crisis thinking works at the level of planetary and institutional dynamics, and supplies urgency. Teal organisations work at the level of organisational design, and supply an existence proof for distributed authority. Metamodernism works as a cultural stance, and supplies a way to commit sincerely under partiality. Warm data works at the level of information, and supplies a concept of relational information.
None of the four is a science, and the evidence for each is thinner than its advocates suggest. That is part of the point. Each is useful, and each needs complexity to keep it honest.
Why sensibilities matter
Complexity thinking is not only a set of concepts and methods. It also needs a sensibility: a characteristic way of attending, valuing and committing. You can know everything about feedback loops and still reach for the single cause the moment a meeting gets tense.
Two of the registers, metamodernism and warm data, are mainly about that sensibility. They describe how a person or a group holds a situation, as well as what they know about it. That is why they sit on a page about complexity at all.
Planetary and institutional dynamics
Crisis thinking
The vocabulary of creeping crisis, polycrisis, permacrisis, metacrisis and omnicrisis. Read for mechanisms, it is a set of complexity claims made at different depths. Used loosely, it is atmosphere.
In brief
The crisis vocabulary has its own page, which sets out each term, the question it forces, the mechanism behind it and how it fails when used loosely. The short version is that crisis has drifted from its original meaning, a moment that calls for judgement, to a permanent condition we are asked to feel.
Complexity reads crisis as a regime: a system operating near its thresholds. That is where small, well-timed actions have the largest effects, which turns crisis back into a moment of decision.
Organisational design
Teal organisations
Laloux’s account of organisations that distribute authority, invite whole people to work, and follow a purpose they sense rather than set. Vivid, influential and thinly evidenced. Its best idea survives once the colour scheme is taken away.
Three breakthroughs
Laloux (2014) describes teal organisations through three breakthroughs. Self-management distributes authority through peer processes instead of a hierarchy. Wholeness invites people to bring their whole selves to work, not a narrow professional mask. Evolutionary purpose treats the organisation as a living system whose purpose is sensed and followed, not set by its leaders.
The best-known example is Buurtzorg, the Dutch home-care organisation run by small self-managing nursing teams (Kreitzer et al., 2015).
Three correspondences
Each breakthrough matches a complexity principle. Self-management puts sensing and decision where the variety is met, at the bedside or in the classroom. That is Ashby’s (1956) law of requisite variety in organisational form: only a system with enough variety of response can handle the variety of situations it faces.
Wholeness widens what an organisation can perceive. In Bateson’s terms, it admits the warm data that role-bounded professional exchanges filter out. Evolutionary purpose treats direction as emergent, which puts it close to effectuation and to the Cynefin tradition’s management of dispositions.
Evidence and critique
The evidence is thin and mostly case-based. Lee and Edmondson (2017) define self-managing organisations as those that radically decentralise authority in a formal and systematic way. They find real benefits and real limits. These forms are hard to sustain, demand heavy investment in process and skill, and can create anxiety when roles are fluid.
Freeman’s (1972) essay on the tyranny of structurelessness makes the older warning. Remove formal hierarchy and an informal one often grows in its place, less visible and less accountable. The uneven adoption of holacracy (Robertson, 2015) underlines the point.
The colour problem
Laloux’s colours are adapted from Spiral Dynamics (Beck & Cowan, 1996), which ranks forms of organising on a developmental ladder. Teal sits at the top. That invites moralising: the flat organisation as the enlightened one, the hierarchy as the one that has not grown up yet.
It also hides the more useful point. Different forms of organising fit different conditions. A hospital needs a different shape in a routine week from the one it needs in a mass-casualty event.
Requisite distribution of authority
Complexity’s contribution is not that flat beats hierarchical. It is that authority should be distributed in proportion to the variety and tempo of the problems an organisation faces, and redistributed as those change. Call it requisite distribution of authority: fit, not flatness.
High-reliability organisations show this most clearly. They run on hierarchy for routine operations, and defer to expertise wherever it sits when things go wrong (Weick & Sutcliffe, 2007). Uhl-Bien and colleagues’ (2007) enabling leadership manages the tension between the administrative and the adaptive. Ostrom’s (2009) polycentric governance shows nested authorities organising themselves reliably. Heterarchy, first described by McCulloch (1945) and developed for organisations by Stark (2009), describes organisations with several overlapping orders of worth, whose friction produces new ideas.
So distributed authority is a design choice, matched to the situation’s profile, especially its coupling, tempo and legitimacy. It is not a developmental stage to aspire to.
Cultural stance
Metamodernism
A structure of feeling that moves between modern enthusiasm and postmodern irony. It answers a question complexity raises and cannot answer itself: how to act with conviction when every frame is partial.
Origins
Vermeulen and van den Akker (2010) described metamodernism as a structure of feeling that oscillates between modern enthusiasm and postmodern irony, between hope and melancholy, naivety and knowingness. Their phrases for it were an “informed naivety” and a “pragmatic idealism”.
The point is the oscillation. Neither the enthusiasm nor the irony is allowed to settle the matter, so belief survives knowing better.
Three strands
A cultural strand follows Vermeulen and van den Akker. A political and developmental strand (Freinacht, 2017; Andersen, 2019) links metamodernism to adult development, to Bildung and to the idea of a “listening society”.
A philosophical strand (Storm, 2021) proposes a metamodern theory that moves beyond both positivism and postmodern scepticism. Its social ontology is a process one: social kinds are dynamic clusters, not fixed essences. Its stance is “zetetic”, treating knowledge as provisional but real.
What it contributes
Complexity science tells you every model is partial. It does not tell you how to act anyway. Metamodernism does. It holds a sincere commitment to a direction and an ironic awareness of the frame’s limits at the same time, without letting either cancel the other.
That makes it the cultural form of provisional commitment: commit firmly, hold the frame lightly, set triggers for revisiting. Storm’s process ontology also lines up closely with complexity. Social kinds are stabilised patterns, which is what complexity would predict.
Limits
Metamodernism is diffuse. Its para-academic strands lean on contested developmental hierarchies and can become self-congratulatory, the claim that we are the ones who integrate everything. Its academic strand is philosophical rather than operational.
So it is best used as a stance and a vocabulary. It is not a theory of change, and it should not be sold as one.
Information
Warm data
Relational information about how the parts of a living system bear on each other across contexts. A precise critique of the decontextualised metric, and a practice for surfacing what departmental data cannot represent.
Origins
Warm data was developed by Nora Bateson and the International Bateson Institute, building on Gregory Bateson’s (1972) ecology of mind. The Institute defines it as “relational and transcontextual information” about the interrelationships that hold a complex system together.
Bateson (2023) adds two further terms. Symmathesy is mutual learning through interaction in living systems. Aphanipoiesis names the unseen processes by which living systems coalesce towards vitality.
Method
Warm Data Labs bring people into conversation about a shared issue across many contexts: economy, health, family, education, ecology, technology. They deliberately avoid problem-solving. The aim is to let interdependencies surface and new perceptions form, before anyone reaches for a fix.
What it contributes
Warm data offers a precise critique of cold data: metrics stripped of the relationships that gave them meaning. It sits alongside Campbell’s law, that the more a measure is used for decisions the more it distorts what it measures, and Strathern’s critique of audit. It also gives the relational contribution of complexity thinking an information concept of its own.
In practice it lets an institution perceive how things compound across contexts. Housing, health, employment and schooling can bear on a single household at once, and each department sees only its own slice.
Limits and bridges
The evidence is mostly practitioner reports, and the method resists scaling and measurement by design. That is a principled position and a practical problem.
The most promising bridges are to sensemaking at scale, such as self-signified micro-narratives (see Snowden & Rancati, 2021), and to thick description (Geertz, 1973). Warm and cold data are complements. Cold data monitors the variables you already know about. Warm data perceives the relationships cold data cannot represent.
Common ground
What the four share
The affective and perceptual layer
Metamodernism and warm data come from different places and share three habits. Both resist premature closure. Both put relationship first. Both treat the inquirer’s stance as part of the inquiry, so how you hold a question changes what you can find.
Together they form complexity thinking’s affective and perceptual layer. They are the reason complexity thinking cannot be reduced to modelling. A model can tell you a situation is entangled. It takes a sensibility to stay with the entanglement long enough to see it, and to act without pretending it has gone away.
At school
The registers in a school
Who decides, and at what scale
Requisite distribution of authority gives a school a better question than whether the assessment plan should be top-down or bottom-up. It asks which decisions need the variety of a classroom and which need the reach of the whole school. How a Secondary 2 science class gets feedback on its work is a classroom decision, because the teacher meets the variety: this cohort, these mistakes, this student who is strong in class and freezes in timed writing. Whole-class feedback worked because it started there, outside the policy. What a rating means to parents, or what to do once a teacher has quietly rated borderline students up, is a whole-school decision, taken soon and from the centre. The same school needs both shapes, and has to notice when a decision has moved from one to the other.
The teal cautions apply too. Practices that spread informally between a few teachers can be killed by being formalised. Write a habit into the marking policy, with a format and a book check, and the people who were doing it freely may step back.
Warm data next to the dashboard
A dashboard showing 96 per cent compliance that nobody believes is cold data doing what cold data does. It counts a known variable after the variable has learned to perform. The things that explained the semester arrived as warm data: a mother at a Saturday morning Meet-the-Parents session seeing her daughter’s quiz record for the first time, an allied educator for learning support noticing who is rated Emerging and why, students explaining which subjects are harsh. None of it fits a cell on a spreadsheet, and all of it crosses contexts the dashboard keeps apart. The discipline is to keep both, and to watch for warm data cooling. A quiz that is never recorded becomes a measure as soon as someone starts collecting the results.
Provisional sincerity
The metamodern stance is the one the school’s leaders end up needing. Commit to a direction sincerely, say aloud that the frame is partial, and set the conditions for revisiting it. A one-year contract extension taken at a higher price is that stance in budget form. A format check proposed for removal inside the school, while the compliance figure is still reported upwards, is what happens when sincerity and irony come apart: everyone knows the figure means little, and it goes on being sent. The stance does not resolve that. It makes it harder to stop noticing.
Reading
Where it comes from
Start with the first on the list.
Laloux, F. (2014). Reinventing organizations. Nelson Parker.
The source of teal, and the most widely read case for self-management, wholeness and evolutionary purpose.
Lee, M. Y., & Edmondson, A. C. (2017). Self-managing organizations: Exploring the limits of less-hierarchical organizing. Research in Organizational Behavior, 37, 35–58.
The careful academic account of what self-management delivers and where it struggles.
Freeman, J. (1972). The tyranny of structurelessness. Berkeley Journal of Sociology, 17, 151–164.
Why removing formal hierarchy tends to produce an informal one that is less accountable.
Weick, K. E., & Sutcliffe, K. M. (2007). Managing the unexpected: Resilient performance in an age of uncertainty (2nd ed.). Jossey-Bass.
High-reliability organisations, and authority that moves to expertise when things go wrong.
Uhl-Bien, M., Marion, R., & McKelvey, B. (2007). Complexity leadership theory: Shifting leadership from the industrial age to the knowledge era. The Leadership Quarterly, 18(4), 298–318.
Leadership as managing the tension between administrative and adaptive work.
Vermeulen, T., & van den Akker, R. (2010). Notes on metamodernism. Journal of Aesthetics & Culture, 2(1), 5677.
The essay that named metamodernism as an oscillation between sincerity and irony.
Storm, J. A. J. (2021). Metamodernism: The future of theory. University of Chicago Press.
The philosophical strand, with a process view of social kinds close to complexity’s own.
Bateson, G. (1972). Steps to an ecology of mind. Chandler.
The ecology of mind that warm data builds on.
International Bateson Institute. (n.d.). Warm Data. https://www.batesoninstitute.org/warm-data
The Institute’s own definition of warm data and account of Warm Data Labs.
Snowden, D., & Rancati, A. (2021). Managing complexity (and chaos) in times of crisis: A field guide for decision makers inspired by the Cynefin framework. Publications Office of the European Union.
Sensemaking at scale, including micro-narratives, as a bridge between warm and cold data.
Unsettled
What I would still argue about
The questions this page does not settle.
- How to decide, in practice, when a decision has moved from needing local variety to needing central speed. The principle is clear. The moment of switching is usually only obvious afterwards.
- Whether informal practice can be supported without being formalised to death. Every way I know of recognising good practice also changes it.
- How to keep warm data warm once an institution starts relying on it. Anything collected regularly and read by leaders tends to cool into a measure.
- Whether provisional sincerity can be taught to a leadership team, or whether it only shows up in people who already had it. I suspect the second, and hope I am wrong.