(This series of posts explores a concept of ‘problem-space’ versus ‘solution-space’ which in part demonstrates alternative uses and interpretations of the Simple / Complicated / Complex / Chaotic categorisation originally described in the Cynefin diagram. It must be emphasised that this is not about the Cynefin Framework; for details on Cynefin, please contact Cognitive Edge.)
This post represents yet another attempt to describe certain fundamental differences in approach from twf (aka ‘That Welsh Framework‘ – so-called because we’re no longer allowed to use its official name at all) and to find an alternative term that might reduce the ongoing friction in that quarter.
To do this, we need to go right back to first-principles: the core concept of context-space, which eventually leads us to context-space mapping.
(Another long-ish post: more after the ‘Read more…’ link.)
Before any notion of order or unorder, or even of disorder, there is simply ‘the everything’: everything and nothing, all one, everything and nothing connected to everything and nothing else, a place-that-is-no-place that incorporates within itself every possibility. It’s not ‘chaos’ – it simply is.
There are all manner of names for this ‘active no-thing-ness’: Lao Tse called it ‘the Tao’, for example, whilst the ancient Greeks described it as ‘the Void’. For the more business-oriented purpose of enterprise-architects, though, we’ll need to constrain the scope of this ‘the everything’ somewhat, and we’ll also need a more ‘business-like’ label. So let’s call it context-space – the holographic, bounded-yet-unbounded space that contains every possibility within the chosen context.
In previous posts I’ve split this context-space into problem-space – the context in which things happen – and solution-space – the space in which we decide what to do in relation to what’s happening. But ultimately there’s just the context: “the only true model of a system is the system itself”.
Yet to make sense of anything, we need to impose some kind of structure. One place to start would be to filter ‘the everything’ in terms of its variability. Perceived-repeatability is one example of a variability that we might use (which we’ll come back to in a moment), but there are of course many others.
Initially this gives us a finely-graded spectrum of variability. Yet interestingly, most human sensory-perception is not very good with smooth gradations: it works much better with firmer boundaries. Hence most sensemaking will usually attempt to place some kind of ordered structure upon what may initially seem like unbounded chaos.
When we look at the physical world, of matter and material, we can see both of these processes in action, even within matter itself. There is a fairly smooth gradation of variability, primarily linked to temperature; yet there are also explicit ‘phase-boundaries’ where the internal relationship of matter undergo fundamental changes. Significant amounts of energy (‘latent heat’) can be absorbed or released in the ‘phase-transitions’ between these modes. In effect, these present as four distinct states of matter, traditionally described as Earth, Water, Air and Fire, for which the more scientific terms are respectively Solid, Liquid, Gas and Plasma.
Looking at the internal structures of matter within each of these states, we would typically describe the respective structural relationships as Simple, Complicated, Complex and Chaotic, as phases or domains within the context-space of matter. This categorisation along a single axis represents a simple first-order map of that context-space – hence context-space mapping.
Much the same applies to just about any other view into the overall context-space. If we take almost any type of gradation, we will be able to identify distinct phase-boundaries that can be used to partition the context-space into distinct regions along that axis: the nominal split of the visible-light spectrum into Red, Orange, Yellow, Green, Blue, Indigo and Violet is one such example. But perhaps the most useful split of all for enterprise-architecture and business-architecture is along an axis of repeatability, dividing the inherent uncertainty of context-space into regions that we could describe, in parallel with those states of matter, as Simple, Complicated, Complex and Chaotic.
Which brings us, unfortunately, into the same conceptual space as twf (That Welsh Framework) – though we’ve arrived there via what is, in very literal sense, a fundamentally-different route. And unlike twf, we can now see:
- how and why we’ve arrived at those particular categorisations
- how and why to use any specific axis for such categorisation
- what the boundaries between the ‘domains’ in the categorisation will look like
- how, why and when the nominally-Simple boundaries between categories may move (Complicated), blur (Complex) or fragment (Chaotic).
This provides a layered, recursive richness that is largely absent in twf. It also provides a means to link right across every possible view into context-space, rather than solely a specific set of interventions that focus primarily on a set of views into the Complex domain.
A first-order (single-axis) context-space map – such as the Simple-to-Chaotic ‘stack’ – is not all that much use in practice. To make it more useful, we’ll need to add other axes as filters for sensemaking, to enable relevant information to fall out of the respective comparison. And we make it more useful again by selecting a related set of axes to provide a multi-dimensional base-map upon which other filters can be placed. (Two-dimensional base-maps are the easiest to work with, for obvious reasons, but three or more dimensions are entirely feasible – the tetradian is one example of a four-dimension frame compressed into three-dimensions for use as a base-map.) To do this, we choose axes which force the domains of the original single-axis spectrum into relationships of opposition and similarity with each other. For example, if we use ‘levels of abstraction’ as the core axis, and overlay that with timescale in one direction and a ‘value-versus-truth’ spectrum in the other, we arrive at the following base-map and its ‘cross-map’ of interpretive text-overlays:
Here Chaotic and Simple are in opposition over their means of interpretation, but similar in terms of timescale; Chaotic and Complex are similar in their means of interpretation, but opposites in terms of timescale; Simple and Complex, and Complicated and Chaotic, oppose each other on both axes; yet all domains are related in terms of layers of abstraction. The central region (‘reality’) is essentially a reminder that the domains represent related yet arbitrary views into what is actually the total ‘hologram’ of context-space – everything else is actually an abstraction from the real.
We then layer this recursively to apply to the nominal boundaries between each of the domains, so that these too may be considered to be fixed, movable, porous or fragmented or transient. An axis based on a simple binary true/false categorisation (in other words, a Simple boundary) will split the the context-space into two domains along that axis; if both overlay-axes have relatively-Simple categorisations (or movable two-part categorisations, in Complicated style), the overall context-space is split into four regions – which aligns well with the ‘matter’-type categorisation of Simple, Complicated, Complex and Chaotic. Likewise a smooth gradation along both axes pushes the context-space into four regions with Complex or even Chaotic boundaries between them.
Because of this, a four-region base-map is likely to be the most common and most useful two-dimensional type – hence, we may note, the twf is often shown paired with two-axis overlays. But other layouts are possible and sometimes useful: for example, a pair of tri-value axes would typically be used to align an eight- or nine-domain primary axis, such as seven-colour plus infra-red and ultra-violet.
The result is a consistent structure for base-maps that are simultaneously bounded and not-bounded, and that describe the whole of a context-space by structured views into that context-space that also acknowledge that the context-space ultimately has no actual structure. Hence the importance and validity of the assertion that even though twf is often shown paired with two-axis overlays, it is not solely a two-axis matrix. The other point, though, is that this indicates that twf is merely one instantiation (or set of instantiations, rather) of a generic class of context-space mappings that has been around and in general use for a lot longer than twf itself.
Hence to avoid further clashes with twf, I suggest that in future we use the generic term context-space mappings to denote base-maps and derivatives that use this type of structure.
Once we’ve cleared that particular road-block, we should be free to concentrate more on practical applications of context-space mapping for whole-of-enterprise architecture, but I’ll leave it there for now. As usual, any constructive comments, ideas and suggestions would be most welcome 
– over to you, if you would?
Previous posts in this series:
- ‘Complexity, chaos and enterprise-architecture‘
- ‘More on chaos and Cynefin‘
- ‘Alternatives to the ‘Cynefin’ term, please?‘
- ‘Solution-space: beyond Cynefin?‘
- ‘On meta-methodology‘
- ‘Using ‘Cynefin-like’ cross-maps‘
- ‘More ‘Cynefin-like’ cross-maps‘
- ‘And more ‘Cynefin-like’ cross-maps‘
- ‘More on meta-methodology‘
- ‘‘tinc’ – a Temporary Inconvenience‘
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