The fact that order exist in nature (a constrained system that prevents agent action independent of the system) does not entail the statement that therefore all things can be reduced to order.

If you look at this from the perspective of constraints, relaxation and imposition then a lot of the problems you state above go away and there is no need to see order as an abstraction it is a phase state.

Looks like I need to do a fair bit of study on the theory of constraints…

But in some ways that isn’t related to the points I was trying to make. I fear we may be talking at slight cross-purposes here: surely the idea of a ‘phase state’ is an abstraction? a way of trying to shoehorn complexity into the knowable space?

Perhaps I could try tackling this a slightly different way…

Two quotes come to mind. One is a phrase that I think comes from James Gleick’s Chaos: “it turns out that behind apparent order lies an eerie kind of chaos; and behind that chaos lies an even eerier kind of order”. The kind of ‘order’ in the known-domain is not so much simple as simplistic, and to try to make it work in the real world we rapidly find ourselves making things more and more complicated, to cover more and more ’special-cases’ – in other words, we find ourselves in the knowable-domain, but still clinging to a strict concept of cause-and-effect, a linear notion of ‘order’. Hence Dave’s descriptions of those two domains as the ‘ordered’ side of the framework. But at some point we realise that even that isn’t going to work – usually because we run out of time to deal with the inevitable ‘analysis paralysis’ – which is when we switch over to the ‘unordered domains’. But even here we still cling onto the idea of ‘order’, although now it takes the form of Gleick’s ‘even eerier kind of order’, as attractors and constraints and so on. So what I’m suggesting here is that ‘unordered’ in Cynefin is perhaps a misnomer: it’s still ‘ordered’ – a different kind of abstraction, but still an abstraction. With all of the problems that that entails.

As I said in the last post, it’s essentially a philosophical position: we can choose to believe that “order is real”, or we can choose otherwise. I’m with Feyerabend: I don’t believe ‘order’ has any inherent reality – it’s a tool that’s useful for sensemaking, but that’s it.

In essence, it comes down to a question of ‘truth’ versus ‘usefulness’ – otherwise known as science versus technology. (Technology is not ‘applied science’ – though that’s something to be argued in another post!)

Which brings me to the second quote, or editorial headline, rather, from the current issue of the BMJ: “Cardiovascular risk tables: estimating risk is not the problem, using it to tailor treatment is”. Risk-tables are classic examples of artefacts of complex-space: we can model the attractors, the constraints and the rest of the respective collective risk. Insurance people then move sideways into the knowable-domain to calculate required profit-margins and the rest, in terms of the collective risk. But the moment we think that these tables tell us much about individuals, we’re in deep trouble – straight into the Gambler’s Fallacy, in fact. The notion of ‘order’ fails us, because it assumes that an abstraction about a generalised collective (i.e. pattern, law, etc) will apply to any individual which might appear to belong to the set described by that abstraction. But in terms of set-theory, if the individual only intersects with the abstraction’s set – in other words, is not entirely enclosed as a subset – then other factors may come to play, which may take priority over the expectations of the abstraction.

(To give another medical example, there was an article many years ago in World Medicine with an allegorical tale of “Ulbricht the Badger’s Guide to Immunology”. The key point was that whilst we understand extremely well why people fall ill, we still understand very little about why they don’t fall ill – and even less about how they have the temerity to fall well when we don’t expect them to do so!)

Many people make the mistake of thinking that chaos-theory and attractors and the like make the unpredictable predictable. They don’t: they make the type of unpredictability, or degree of unpredictability, more predictable, but that’s it. The ‘order’ they describe is that, ultimately, there is no order. Kind of a paradox, really, but there ’tis.

Which comes back to the practice of business, and business-consultancy. It’s not an abstraction: we have to find a way to get real results, in the real world. Which happens to be made up of individual instances. Which damn well ought to tell us that, at best, we are always dealing with some of the ‘unorderedness’ of the Cynefin chaotic-domain, and probably some of the Cynefin ‘unknown’ as well. If we start to believe that ‘order is real’ – that the real world is somehow ‘wrong’ if it fails to match our expectations – then we’re on the slippery slope to the inane world of Victorian medicine, in which surgeons routinely reported “operation successful, but patient died”…

Science expects ‘fail-safe’ conformance to its ‘truth’; but technology aims for useful approximations – hence ’safe-fail’. (Therein lies another post I ought to write, about ‘Inverse Murphy’.) In technology, we take an occurrence which is probably rare in nature, and provide conditions under which it becomes more and more probable – but as any maintenance engineer would warn us, we don’t delude ourselves into thinking we have any real ‘control’ over what happens. However probable it may become, it is never more than probable: it never becomes certain. The delusion of ‘control’ is useful when we’re dealing with incidents en masse – as in risk-tables and the like – but it’s not useful once we come down to the infinite complexities of individuals.

Hence, in Cynefin terms, we start off in the ‘unknown’ space; we’re usually wisest to start sensemaking in the ‘unordered’ space, working orderwards (clockwise) from chaotic, to complex, to knowable, to known. Dave describes this as “from exploration to exploitation”, but I’d suggest it’s better described as “from exploration to planning for exploitation” – because to do the exploitation, we need to work back to unordered in order to deal with individuality, the ‘market of one’ and suchlike.

So I don’t see how descriptions of phase-states and the like actually help that much in this – true, they’re not the same kind of ‘order’ as in the known and knowable domains, but it’s still ‘order’, still an abstraction. Useful for planning, for sense-making – but sometimes dangerously misleading at ‘the coal-face’.

Sure, attractors and constraints and the like are a heck of a lot more useful than Taylorism when we’re dealing with the messy complexity of the real-world: but if we’re not careful, the notion of ‘order’ itself – in whatever form it may take – can lead us straight back to what is really nothing more than a subtler form of the Taylorist trap. Guess that’s all I’m saying, really.