Just Enough Detail.

To which people will, of course, immediately ask, “Okay, but how much detail is ‘Just Enough Detail’?”. And I’ll have to admit that there isn’t a simple. certain, predefined answer. You just have to kinda know when enough is enough, you know? – which is why it’s more art than science, I guess. And why experience – usually gained by not getting it right… – is so important here.

One thing I do know is that one of the most-quoted answers is usually just plain wrong for this. John Zachman has always said that we need to document everything in ‘excruciating detail’. In a sense, yes, he’s sort-of right, especially if you hold to his metaphor that enterprise-architecture is essentially the same as engineering an aircraft. (I happen to believe that that’s a seriously-misleading metaphor, but that’s another story.) Yet in the real world – even in aircraft-engineering, as I know from much first-hand experience – much of the detail won’t stay the same for long enough to make that ‘excruciating detail’ requirement achievable in practice. Tricky…

Reality is that everything changes, everything moves. And the more they change, the more the demand for ever-more-detail becomes a trap. And when the pace of change itself is accelerating fast – as is definitely the case in most enterprise-architecture contexts right now – the more dangerous that ‘too-much-detail’ trap becomes, and the more we risk falling into it.

Yet on the other side, not enough detail means we won’t have enough of an anchor for meaningful sensemaking or decision-making – so we risk making bad decisions on the basis of too many arbitrary assumptions. That’s not a good idea either.

Hence Just Enough Detail.

The point is that that ‘just enough’ of Just Enough Detail varies all the time, from context to context, depending on who we’re with, what we’re doing, what we’re aiming to do, the type and rate of change, and all manner of other factors. Take this example from one of my favourite ‘show this to clients’ books, Matthew Frederick’s 101 Things I Learned In Architecture School:

There’s actually not much detail in that image. There’s no detail at all of the wall – and yet that’s still enough detail to make out that it is a wall (and probably a white-plaster wall at that). Other than the outline, there’s almost no detail of the woman, or her clothing – and yet it’s enough to get a good sense of who she is, what she looks like. There’s a bit more detail of the church and its dome – enough to tell that it is Brunelleschi‘s masterpiece in Florence – and of the townscape around it. Not much detail, then – and yet that’s all the detail it needs to tell the story. Not too much; not too little; Just Enough Detail.

So, over to you: how much or how little is Just Enough Detail in each part of your enterprise-architecture? How do you show that Just Enough Detail to whoever needs to see the story?

How much does Just Enough Detail change between different layers of abstraction, between different audiences, between backbone versus edge?

How do you know when it’s too much detail, or too little? How do you know when it’s just right? – when it’s Just Enough Detail?

How do you learn this delicate, ever-changing balance of ‘just enough’? From where and in what ways do you learn that balance – without causing too much damage whilst learning it?

Just Enough Detail, always. An interesting challenge, yes?

Uh, no. Not a good idea. Not just because it’s a really bad deal from our perspective, but much more that Reality Department really doesn’t work that way: there’s no short-cut to experience.

Yes, it all looks simple enough – in fact that’s the whole point. A lot of simple visual summaries, and surprisingly simple-seeming methods, too. Yet it only looks simple because we’ve been through a heck of lot of hard work to make it that way. Hard-won experience, won the hard way through years and years of practice in many, many different contexts, getting it ‘wrong’ time and time again, in many, many different ways in order to get it right.

The real trap is that these simple-seeming ideas and methods aren’t simple rules, prepackaged sense-making and decision-making that will always work in every context. These are simple principles, simple guidelines, the kind of easy-to-memorise information that helps decision-making in real-time, in circumstances that are subtly different every time. (See my SCAN posts for more on these distinctions.) If you try to use them as ‘rules’ for inherently-uncertain contexts, without understanding why those principles apply, or how they need to be tweaked every time to match each different context, you’re going to be in real trouble – along with everyone else around you. Not a good idea…

The same often applies even to things that really are ’rules’. Take that example of perhaps the greatest simplification ever made: e=mc². All the core information you need to build a nuclear power-station is right there in that equation: but there’s a heck of a long way – a heck of a lot of engineering-experience – to go from that one equation to building a nuclear-power station that actually works.

Same with everything else, really: simplification is essential, but can also be deceptive – especially when people mistake ‘simple’ for ‘easy’…

Which is also why I get a bit hot-under-the-collar about the current proliferation of ‘certification-schemes’ in enterprise-architecture and elsewhere. Some of them are genuinely valuable, but others – to be blunt – are little better than money-spinning scams, in terms of the actual value that they (don’t) deliver. And the crucial distinction revolves around the role and recognition of experience.

For example, the TOGAF Foundation and Archimate Foundation certifications have real value. They verify that the respective person has a credible command of the terminology and language – a requirement that matters a lot for communication across a dispersed and disparate team.

Likewise the ATAC certifications should have real value, because each explicitly tests practical experience in the respective area.

But unless they’ve changed it in the past year or so, the full TOGAF certification is delivered through the absurdly-inappropriate mechanism of a multiple-choice test. And to my mind, that’s not merely useless, it’s actually worse than useless, because it’s exactly how not to test for the kind of experience that that type of competence requires. (When I did the TOGAF 8 exam some years back, I almost failed because I answered several key questions correctly in terms of real-world experience, rather than the theory-based wrong-assumptions that the test thought were ‘right’.) The result of that kind of pseudo-test is a bevy of people who can wave a certificate around, but have no idea how to do the work in any real-world context.

A good training-course can make all the difference, and the better training-providers do take up some of the slack here. (I’ll wave a flag at this point for John Polgreen at Architecting The Enterprise, who’s been doing sterling work for years on adapting TOGAF for the US-government context.) Yet none of that competence carries through anywhere into the actual test: so unless we know each of the training-providers, we have no way to tell whether a candidate does actually know what they’re doing, or merely that they have a piece of paper to prove that they know just enough to get into real trouble, but not enough to get out of it again.

In effect, right now, the full TOGAF certification is of less real-world value than the Foundation certification – which is both bizarre and sadly pointless. And I’ll hasten to add that I’m using TOGAF here merely as one example amongst many: it may well be that most of the so-called ‘certifications’ in this field are even more meaningless than that. And the results can be seen everywhere in the trade…

In short, it’s a mess.

What we need to be testing for is genuine understanding of a context, and the ability to adapt for uniqueness. And that calls for much, much more than can be covered in a crude multiple-choice test delivered through a mindless machine. Sure, that kind of test is cheap, and relatively easy to administer: but it’s also all but meaningless for anything than foundation-level rote-knowledge. It really does take years of painful practice to develop the experience needed to do this work well: and if this trade is to gain the credibility that it needs, we need to stop pretending that we don’t need to test for that experience.

Time to re-think how we do this, and how we respect this, too: there’s no short-cut to experience.

• transarchitect: The priority shift we make is from efficiency to effectiveness to co-creativity. #complexity

Of course. Yes. That’s obvious, the moment I look at it.

Except that I’d completely missed before now.

Oops…

I’ve long since drawn a distinction between efficiency and effectiveness. Or rather, that efficiency – ‘doing more with less’, ‘doing things right’ – is only one dimension of effectiveness – ‘doing the right things right’.

[The set of five dimensions that I've used to summarise effectiveness, if you're interested, is efficient, reliable, elegant, appropriate, integrated - see  the slidedeck 'What is effectiveness?' or my book SEMPER & SCORE: enhancing enterprise effectiveness.]

Yet that type of ‘effectiveness’ assumes that there’s some kind of pre-ordained plan – ‘effective in terms of the plan’. What if there isn’t a plan? What if we don’t know what the plan is? What if we’ll only know what the plan was – or sort-of ‘was’ – once we’ve completed it? (‘Retrospective causality’, as a certain person would put it.)

That’s where co-creativity comes into the picture. Co-creating a ‘plan that is no-plan‘, together.

And that’s what I’d missed.

[I can see why I'd missed it: to be blunt, I'm, uh, not good at anything that involves being social, and the whole point and focus of co-creativity is that it's social. But it still doesn't excuse the fact that I shouldn't have missed it. Sigh.]

Yet I’m not the only one who’s missed it: there’s a whole societal shift implied here – a completely different way of working. One that doesn’t assume that there’s ‘The Plan’. One that doesn’t assume that there’s The Person In Control, or The Person Who Knows What’s Going On. Or even that there’s anyone who knows what’s going on. Instead, there’s a trust that co-creation will take us where we want to go: an effectiveness that’s an emergent property of the collective, without any ‘plan’ or pre-certainty at all.

I don’t see this as an ‘either/or’ – either effectiveness-relative-to-a-plan, or co-creation-with-no-plan. It’s more a ‘both/and’ – it seems more an effectiveness that arises from a sort-of plan-that-is-no-plan, one that covers the entirety of the SCAN decision-making space:

The classic ‘efficiency’-based approach is mostly about the left-hand side: assertions about ‘the true metrics’ and so on leads to The Plan which leads to control of actions and decisions at real-time – the Belief ‘domain’. It’s very mechanical – often literally so.

Looking at it now, the approach I’d taken to effectiveness did incorporate a lot more of the right-hand side, with a strong acceptance of various aspects of uncertainty – particularly in the human space, the ‘elegant’-dimension of effectiveness. But it still presumes a plan, an Assertion – and hence that’s where it naturally tends to return.

Co-creativity would seem to focus more on the ‘Use’-domain – literally, “What’s the Use?”. I believe that to work well – to avoid a collapse into a dysfunctional-chaotic free-for-all, a ‘co-non-creation’ – it’d still need some kind of guiding-light or anchor or direction, a shared “What’s the purpose here?”. Yet even that would likely be co-created too – a nice recursion there.

Hmm… A lot to think about. Or, preferably, co-create? Thanks anyway, Bert!

Yes, I do know that those questions might seem to fit more in philosophy or psychology. But as per the previous post, they also have huge ramifications in user-experience and user-interface design, in product-design, in sensemaking and decision-making, and in enterprise-architecture, business-architecture, security-architecture and many other architectures in general.

Quick summary so far:

• there’s a decision-making ‘I’ – “I am that which chooses”, that which experiences the world as ‘I’ and responds accordingly, and which can be highly volatile, especially in terms of real-time decision-making
• there’s a kind of presentation-layer of ‘I’, which is expressed through surface-appearance, through digital-personas and suchlike
• there’s a kind of interaction between each ‘I’ and that presentation-layer – an interaction which is particularly clear in work with Masks, as I’ll return to in a moment
• there’s a distinct identifier-layer for ‘I’, comprised of identifiers acknowledged or imposed by others as well as self, and typically associated roles, rights and responsibilities for ‘I’ – with the identifiers often associated with external or assigned personas (digital or otherwise)
• beneath it all, in most cases, there seems to be a kind of unitary ‘I’ that is experienced by self as ‘I’, and perhaps also experienced by others as one’s ‘I’ – though with reservations on that such as indicated by the classic Johari Window model

So, to identity and Mask.

I’ve just finished re-reading Keith Johnstone’s classic ‘Impro: improvisation and the theatre‘. To me, it’s absolute must-read for anyone interested in the human side of enterprise-architecture: its sections on status, spontaneity and narrative can be real eye-openers for understanding how organisations really work. (Or, more often, don’t work…) Yet for me it’s always been the last section in the book that’s always stood out the most: the section on Masks.

The term ‘Mask’ has a special meaning here – hence the initial-capital on Mask, to distinguish it from a more everyday theatrical mask. In many ways the Mask is just an ordinary half-face mask: the difference is more in how it’s used, not just as a costume-prop but as an active persona or literal ‘per-sona’ – an active filter on ’that through which I sound’.

[There's also another set of techniques that work with full-face Masks, or Tragic Masks, but I won't go into any of that here.]

The context in the book is improvisational theatre, of course – not enterprise-architecture. Yet there are a few themes that are extremely relevant for us.

One is that it’s a real and intensive research-environment. True, it’s subjective-research rather than objective-research, but in essence the principles of of investigation are the same, and certainly the level of discipline required is much the same if they’re to get usable results. So don’t dismiss it out of hand because it’s not IT…

Given that, note what is probably the key theme there: that there’s some kind of interaction that goes on between actor and Mask. It’s not as simple as a one-way ‘I am wearing this prop’: wearing a Mask has definite impacts on the actor, and it seems there’s even some continuity between different people wearing the same Mask:

Another Mask was called Mr Parks. This one used to laugh, and stare into the air, and sit on the extreme edge of chairs and fall off sideways. Shay Gorman created the character. I took the Mask to a course I gave in Hampshire. The students were entering from behind a screen and suddenly I heard Mr Parks’ laughter. It entered with the same posture Shay Gorman had adopted, and looked up as if something was very amusing about the ceiling, and then it kept sitting on the extreme edge of a chair as if it wanted to fall off. Fortunately it didn’t, because the wearer wasn’t very athletic. It really makes no sense that a Mask should be able to transmit that information to its wearer.

I’ll very carefully make no comment here as to how that kind of information could pass from one actor to another, just through the medium of the respective Mask: just note that it is so, under those types of technical conditions.

Also explained in the book is that the whole thing depends on some quite specific psychological or psychosocial conditions. To translate it into the terms I’ve been using with the SCAN framework, it’s all happening in the real-time space, and it just does not work on the Belief (‘control’) side of the decision-modality spectrum. It only works either on the Faith-side of the decision-spectrum – where conscious choice of some kind is available, though primarily as a kind of ‘intentional surrender’ – or when there’s no conscious thought at all – which also means no conscious choice.

The fundamental point in Mask work is that there is a sense not so much of loss of ‘I’, as a kind of negotiation with the Mask as to what that surface-’I’ will be. And the Mask can impose some fairly severe constraints on what it can allow, its ‘repertoire’ and suchlike: for example, it can be very difficult to do any kind of predefined script whilst doing Mask-work. If there’s no awareness of that negotiation with the Mask, there are two likely outcomes: either the student will attempt to’take control’, which results in poor outcomes and sometimes literally ‘wooden’ performances; or the student will fail to notice the impacts of the Mask, and in effect believe that the results are their own choice of ‘I’, rather than the default sort-of-choices imposed by the Mask. Which might well not be a good idea…

So what on earth has any of this to do with enterprise-architecture?

The answer is this: anything can be a Mask in this sense. Anything.

To be slightly more specific, anything that can act as a surface-level filter or persona – a ‘that through which I sound’ – can act as a Mask in this sense. Whether or not we are consciously aware of it doing so.

And anything that can act as a filter on ‘I’, also in effect changes the surface experience of ‘I’, of how others experience that ‘I’, and also the actions and choices of that ‘I’.

A couple of really simple everyday examples:

– Someone may be the most mild-mannered person face to face, but suddenly an absolute demon behind the wheel of a car.

– Conversations in Twitter often seem artificial, terse, mechanical – the Mask of the 140-character constraint.

Consider all the ‘professional props’ of just about every trade and tradition: the doctor’s stethoscope, the barrister’s wig, the consultant’s clipboard. All of them are Masks: the person’s behaviour, demeanour, stance and language will all change the moment they pick up that prop.

Consider a business uniform, a brand, a shop layout, a user-interface layout: they’re all Masks in this sense too – an active filter for a persona, as ‘that through which I sound’, impacting on and constraining the choices and actions of the respective ‘I’.

Every role is a Mask. Every digital-identity or digital-persona is a Mask. (Think for a moment about the impact of that on the ways that people interact with digital systems – especially when multiple personae intersect.)

Layer upon layer upon layer of Masks, changing continuously throughout every day.

And, if we’re not conscious of those impacts and constraints on ‘I’, will find our ‘I’ seeming to change with each change of Mask, yet not knowing how or why.

In short, the sense of identity may – and probably will – become fluid in the context of a Mask.

And almost anything may act as a Mask.

Often in unpredictable and/or emergent ways.

Affecting interaction with just about everything else.

Hence, also in short, a definitely non-trivial concern for security, privacy, user-experience design, process-design, branding and a whole host of other themes in enterprise-architecture and elsewhere.

Identity and Mask might perhaps seem somewhat abstract at first. A bit less abstract by now, I hope?

Over to you for comment, anyway.

Yeah, I know, sounds like philosophy and stuff – woefully abstract, deep and pointless. Yawn.

But those ‘pointless’ questions are the core – the heart – of a lot of really important everyday concerns for enterprise-architecture: privacy, security, sales and marketing, just to name a few. The core of ‘enterprise’ itself. Abstract, yes; yet also just about as pragmatic as it gets. Hmm…

Where this got started was a post by Brian Hopkins, on his Forrester blog:

• practicingEA: 2012 Predictions – Technology Will Shape Who We Are As People And Businesses

The post itself is a quick summary of some key themes happening in the IT side of enterprise-architecture at the moment: the fading of ‘Big IT’, a new focus on data, the convergence of social, mobile and local, and the ongoing hype around cloud. Fair enough: interesting to IT-oriented folks, certainly. The comments, though, focussed in on questions about identity in that space – and that’s where things got really interesting…

In essence, we ended up with those questions above. There’s a lot in those comments on Brian’s post, and I won’t repeat it all here: go look at it in the original, it’s well worth the read, especially the notes by Stephen Wilson on on digital-identity. What I’d like to pick up on briefly here are four of those themes:

• identity is simple, complicated, complex, ambiguous, unknowable – all at the same time
• identifier and identity are not the same
• identity and persona are not the same
• identity is filtered through many layers of persona

Identity is complex – that’s the shorthand version, anyway. It’s fluid, it stays the same: we can recognise friends after thirty years’ absence, we barely recognise our own face in the mirror each morning. For me, it changes with the clothes I wear, both in my own sense of identity, and how others seem to see and interact with me. I am my car, my house, my phone, my ideas, my memories: I think I possess them, but they also possess me.

Identity is like a hologram: blurry, muddled, indistinct – until the light shines on it in just the right way. For a brief instant, identity is certain, crystal-clear – and then vanishes again. Until the light shines on it from another direction, showing a different facet, a different face – yet of what is still the same hologram of identity.

Identity is multi-faceted, bewildering, chaotic. There’s one sense I have of ‘I’ when I’m at home, another in the office, another when I’m on stage at a conference, yet another with friends or colleagues in the cafe, and different again when chatting online, or chatting with the ‘checkout chick’ at the market or the mall. On the surface, and from the ‘the inside’, those can be very different people: so which one is me? Which one is real? Which is the myth? And when two or more of those myths collide – meeting work-colleagues at home, for example – there’s a kind of ‘mythquake‘, where for a brief panicked moment nothing seems real at all. Is everything just an act, a mask? Is there anything real behind all of those masks? And yet there is a single unitary ‘I’ in there somewhere, the one voice behind all of those different voices – otherwise we couldn’t recognise it as ‘I’. To quote the Cluetrain Manifesto:

…These markets are conversations. Their members communicate in language that is natural, open, honest, direct, funny and often shocking. Whether explaining or complaining, joking or serious, the human voice is unmistakably genuine. It can’t be faked.

Yet Cluetrain is also about another kind of identity-clash: the distinction between individual and collective, the identity of ‘I’ versus the identity of ‘We’. When I’m part of ‘We’, where is ‘I’? Which one is real? Which one is the mask, the myth?

Confusing, to say the least. And if that’s at the core of so much of enterprise-architecture, it’s no wonder that that’s complex too. Too complex: hence no surprise that so many people try to make it out to be simpler than it is – and that’s where things get messy…

Identifier and identity are not the same - an identifier is not identity, it’s a proxy for identity, for when we don’t have other means to recognise identity. An identifier is just information - and information about something is not the same as the thing itself. It seems this should be obvious, yet evidently it isn’t –  especially to many of those who work on Digital Identity and suchlike, designing IT-systems that seemingly assume they are the same.

We talk about ‘identity-theft’, yet in most cases – perhaps all? – it’s theft of identifier, not identity. An identifier links not to identity, but to a persona associated with that identity – the identity as a role, a set of rights, responsibilities, authorities, tasks. In a possession-based culture, an identifier provides ‘rights’ of access to resources, ‘the right to know’, the right to use: if the identifier is hijacked, those ‘rights’ are hijacked too. That’s what all the worry is about: loss of access to resources, loss of control, loss of concealment for key information. That matters, obviously. But it’s identifier-theft, not identity-theft: the distinction is important.

Going the other way, identity is not identifier. I may put on a company-uniform to identify myself to others as a member of the company; my business-card carries both my own name (a personal identifier) and the company-name (a collective identifier); but that doesn’t mean that I am the company, or that the company ‘is’ me. I use the company-identifier as a persona, and others may recognise me via that persona: yet it isn’t who I am. That distinction is important, too.

[A side-note here: in terms of asset-dimensions, relational-assets link to identity, whereas aspirational-assets mostly to the persona - concrete versus abstract. For more on this, see the post 'Relational-assets are not 'possessions' '.]

Identity and persona are not the same – a persona is an overlay of identity, in exactly the same sense that my clothes are an overlay on myself. A persona is literally ‘that through which I sound’ – a filter, a mask. Online, we have many different personas – not just as represented by distinct avatars and the like, but every online account is in a sense a persona, a ‘that through which I sound’ to or with the respective application.

And the same the other way: the application presents a different persona – a different interface – for us depending on whether we’ve logged in or not, and in some cases (such as the Amazon website) may even adapt itself over time to match the changing history of the relationship. Note the ‘identity-confusion’ that can occur when we present a mismatched persona – such as entering the wrong username / password combination, or using the same avatar in different social contexts.

So too in the offline world. Almost everything is or can be used as a persona: clothes, props, language, body-stance, the way we may drive differently in a rental-car compared to a car we consider ‘ours’. And it’s not just one-way, from us outward: we feel different in different clothes, in different cars, in different climates. There’s an interaction between people and place, and the place has choices too – certainly in a metaphoric sense, perhaps in a literal sense as well.

Identity is filtered through many layers of persona. Persona is ‘that through which I sound’ – a Mask. Each of us has layer upon layer of Masks, some of them seemingly our choice, others less conscious, and yet others sort-of imposed by culture, by context, by the impacts of advertising and the like. It’s complicated… complex…

[One of the best sources to get a sense of of all of this is in impro-theatre: for example, see Keith Johnstone's classic 'Impro: improvisation and the theatre' - particularly the later section on Masks.]

In enterprise-architecture, one of the more useful concerns is provide conditions under which the distinctions between identity and persona become more visible – are ‘surfaced’, to use the psychology-jargon. When people become aware of those distinctions, they also become aware that they can choose the extent to which they identify themselves with a persona – and can let it go and choose an alternative that is a better fit to a changing context. Often we might intentionally set up some kind of ‘ritual’ to mark the boundary: for example, donning a safety-helmet on a building site also triggers a more safety-aware persona.

There’s a lot more to explore here, of course – anyone interested in taking it further?

“I don’t understand the recursion you speak of and the real time nature of decision making and how that is different from ‘considered’ decision making.”

I’ll deal with the easy bit first: real-time versus ‘considered’. Let’s use a really simple (and, at present, topical) example: New Year’s Resolutions.

• Did you make any New Year’s Resolutions? If you did, that’s a ‘considered’ decision, at some distance from the point of action – an intent.
• Assuming you did make a New Year’s Resolution, did you actually keep to it, in terms of what you actually do and did? – because that’s a real-time decision.

Given the above, notice how well (or not) the ‘considered’ decision-making lines up with the actual decisions made at the point of action. Overall, that’s an important part of enterprise-effectiveness. That’s what I’ve been working on, with the SCAN posts and the like.

[There's also how review-processes such as PDCA and After Action Review etc link up with all of this: how the review of what we intend versus what we actually did is used to challenge and re-align the linkage between what we intend and what we do next time. If there is a 'next time', of course: it gets even trickier if there isn't... ]

The other point: recursion. For this context, recursion occurs when we use a framework on itself, to review or work with or refine itself. Let’s use the just the sensemaking side of the SCAN frame for this, it should (I hope!) be a safe and uncontroversial example.

So, we would say that this frame has four domains:

• Simple
• Complicated
• Ambiguous
• Not-known, None-of-the-above

And the boundaries of those domains are defined by two axes:

• horizontal: modality – true/false on left, uncertain (‘possibility/necessity’) on right
• vertical: distance in time (or time-available-until-irrevocable-decision) – from point-of-action to potentially-infinite time-available

At first glance, that’s a really simple categorisation. Note the word ‘Simple‘.

Then we notice that our Simple categorisation starts to get Complicated. The boundaries between the domains aren’t as fixed as they might at first seem: although there’s a definite ‘bump’ on the horizontal axis (what I’ve termed the ‘Inverse-Einstein test’), it’s actually a continuous spectrum of modality, from predictable to somewhat-variable to a lot of variation to everything inherently-unique with no pattern at all.

[The Inverse-Einstein test: on the 'order' side (Simple/Complicated), if we do the same thing, we expect to get the same result; on the 'unorder' side (Ambiguous/None-of-the-above), if we do the same thing, we may get a different result, or we may need to do different things in order to get the same result.]

And the vertical axis is always a completely continuous spectrum: there is a clear transition somewhere, between the ‘Newtonian’ (Complicated/Ambiguous) and ‘quantum’ (Simple/Not-known) levels, but we can’t define explicitly where it is.

Then our Simple-but-also-Complicated categorisation starts to get Ambiguous as well: we’ll see this especially when we use cross-maps, such as that one about skill-levels, where each skill-level represents a different mix of ‘order’ or ‘unorder’, again with no clear boundaries, and with a fair few emergent-properties arising as well.

And then we recognise also that there are aspects in this Simple-and-Complicated-and-Ambiguous categorisation that are inherently-unique, scattered all the way through everything we’re looking at, with some bits that are definitely Not-known or None-of-the-above. (In fact that’s the whole point of this kind of exploration, trying to make sense of those Not-known items and come to some useful actionable decisions about them.)

And, yes, once we dig deeper, we’ll find that the same kind of pattern recurs at another level, and then deeper again, and so on.

Fractal, self-similar, recursive; Simple, Complicated, Ambiguous, None-of-the-above, all of them weaving through each other, all at the same time.

That’s what I mean by recursion here: the framework used to explore itself, and explore the exploring of itself, and – of course – of what it is itself being used to explore.

Makes sense? I hope?

• destivia: @ebuise @tetradian @richardveryard Never forget a ‘model’ is always only a preliminary version of how we see or want to see reality.

After which, yes, the whole happy ‘passel o’ rogues’ piled in, all in their different ways:

• richardveryard: @destivia @ebuise @tetradian We can only replace a model with a better model, despite what Saint Paul says (1 Corinthians 13).
• ebuise: @destivia @tetradian @richardveryard Nice! In a way, a (coherent) set of principles is a special kind of model… #insight
• richardveryard: @ebuise @destivia @tetradian I have difficulty with the idea that a set of principles is supposed to represent some aspect of reality.
• destivia: @ebuise @tetradian @richardveryard Indeed.
• ebuise: @richardveryard @destivia @tetradian A few hours ago @krismeukens tweeted: “The core of strategy work is discovering the critical factors and designing a way of “coordinating” and “focusing” actions to deal with them.”
• Aren’t principles derived, directly or indirectly, from this proces? And as such related to reality and steering into future realities?
• ebuise: @richardveryard @destivia @tetradian Can’t aspired directionality of the future be related to reality?
• krismeukens: @ebuise (cc @richardveryard @destivia @tetradian) indeed, that is my current thinking
• krismeukens: @tetradian In near-realtime would sensemaking not just be limited to deal with it as either simple/chaotic?  Sense-catorize or just act?

I caught up with the conversation at this point, and given that my name had been invoked right the way through the above – even though I hadn’t been there – I thought I’d better join in:

• tetradian: @ebuise cc @richardveryard @destivia ‘aspired directionality of future’ – agreed: that’s a primary role of principles

And, of course, the ongoing problem with Cynefin had been invoked as well:

• tetradian: @krismeukens Cynefin’s Act>Sense>Respond is inadequate/incomplete – see later part of http://bit.ly/AxCDSB and posts linked from there

I ought to expand that Tweet here, because the above ‘explanation’ suffers from the dread 140-character limit on Twitter. As described in the SCAN posts – perhaps particularly in ‘Comparing SCAN and Cynefin‘ and ‘Belief and faith at the point of action‘ – I would answer ‘Yes’ to Kris Meukens’ question “In near-realtime would sensemaking not just be limited to deal with it as either simple/chaotic?” (‘Chaotic’ being the nearest Cynefin equivalent to what I’ve termed the ‘Not-known/Faith’ domain for sensemaking and decision-making respectively). The point is that in near-real-time, there isn’t time for anything else: in particular, no time to think, hence, no time for Complicated or Complex (the equivalent of the latter described in SCAN as the ‘Ambiguous/Use’ domain).

The catch is that whilst Cynefin’s definition for tactics for the Simple-domain – ‘Sense-Categorise-Respond’ – does match up quite well with what happens on the Simple/Belief side, the defined tactics for the Chaotic side – ‘Act-Sense-Respond’ – for the most part do not line with what actually happens. Or rather, they sort-of-describe one particular type of tactic that can be used in that domain, but in many if not most cases those tactics are exactly what not to do.

More on that in a moment; for now, back to the Twitter-stream:

• tetradian: @krismeukens one-liner: Cynefin is to Chaotic as SixSigma is to Complex: its basic concepts dont match to the needs of the context
• transarchitect: @tetradian @krismeukens True Tom.
• krismeukens: @tetradian @richardveryard I have the impression that often the ‘dynamics’ aspect of cynefin is forgotten http://bit.ly/sXeDBp [PDF]
• tetradian: @krismeukens it’s the ‘dynamics’ of Cynefin that are the problem… for Chaotic, they all consist of ‘running away’… //  Cynefin’s so-called ‘Chaotic’ is domain of uncertainty in real-time action: ‘running away’ is not sustainable/viable tactic…

This obviously needs some further explanation, so we’ll go to the original source as pointed in Kris Meukens’ link above: Kurtz & Snowden, ’The new dynamics of strategy: Sense-making in a complex and complicated world‘ (2003). The following (presumably (c) Kurtz & Snowden, used here under ‘fair use’) is its Figure 4, ‘Cynefin Dynamics’:

The Simple and Chaotic domains are on the lower-right and lower-left respectively. For now, we’ll ignore the paths that only go between Complex, Complicated and/or Simple (3, 4, 5 and 6), and focus only those that apply at real-time, Simple<->Chaotic (1, 2) and Chaotic<->Complex (7 and the various orange-line paths).

[Path 3 links to Simple, but tends to occur at significant distance from real-time: it's typified by PDCA-style learning-loops and the like.]

Paths 1 ‘Collapse’ and 2 ‘Imposition’ are generally well-known and (fairly)-well-understood. When the expectations of Belief (Simple) don’t match up to reality, there’s often some kind of ‘Collapse’. (That’s actually a failure-mode: it doesn’t describe how we can intentionally move into the ‘Chaotic’ when we acknowledge that the current belief-set doesn’t work.) Once in the Chaotic, and if panic is allowed to take hold, very often there’s an attempt at ‘Imposition’ of order – an assertion of ‘truth’ that pulls the context back into the Simple. (This too is often a failure-mode, by the way – especially if the imposed ‘truth’ likewise doesn’t match up with reality.) That Imposition typically occurs because someone decides to ‘take action’, the Act-Sense-Respond sequence: but what it causes is usually a failure-mode, a collapse back into the over-Simple.

The unnumbered orange-line paths illustrate well what I mean by ‘running away to the Complex domain’. Having arrived in the Chaotic domain, the Act-Sense-Respond tactic is used to elicit and grab at a momentary idea or sense-item and ‘escape’ to the Complex domain, to assess or analyse or analyse what it is or how it could be used. Rather than ‘holding the space’, the Act part of the tactic itself causes the retreat to the Complex. And in doing so, it moves out of real-time: it doesn’t work with the Chaotic as it is.  We might also note that whilst some of the orange pathways dead-end in the Complex domain – for example, ideas that, once assessed, turn out to be unusable – the paths that do ‘succeed’ all end up in the Complicated-domain. In effect, what the Cynefin-dynamics are suggesting here is that the only valid place for new ideas is ultimately in the domain of Complicated ‘control’ – in other words, right back in the same old trap of Taylorism and ‘scientific management’ again.

[This is one of several aspects of Cynefin that make it all too easy to misuse to delude worried business-folk into believing that the the deep complexity and chaos of the real-world can indeed all be subject to 'control'. Still seems to me that there are some real ethical concerns about the structure of Cynefin that really do need to be addressed... but that's just my opinion, of course...]

Path 7 ‘Divergence-Convergence’ indicates a slightly more refined version of the orange-lines paths: iterative rather than ‘one-shot’, but still centred on the Complex-domain, away from real-time action and real-time decision-making. This is what I mean by ‘dipping the toes into the chaos’: it’s a useful and valid way to garner new ideas, yet it still doesn’t work with the Chaotic as it is – like a mouse snatching the cheese, it’s grabbing some tasty morsel and then running away as fast as it can.

What there isn’t in any of the Cynefin-dynamics or other Cynefin descriptions is anything that does work with the actual nature of the Chaotic mode: for example, all the classic tactics for keeping the panic at bay, such as meditation and so on – and also ‘pre-seeding’ the space with principles and the like (which is where we started this long Twitter-conversation ). In fact many of these tactics are the exact inverse of the Cynefin pattern: rather than the “don’t just stand there, do something!” of Act-Sense-Respond, what we often most need is “don’t just do something, stand there”! That’s what I mean when I say that the Cynefin required-tactics are too limited here: Act-Sense-Respond does apply in certain cases, but it only matches up with a small subset of what we need to do (or not-do), and often it is just plain wrong.

Note too that, in terms of the Cynefin-dynamics above, the only pathways that remain in the near-real-time space are the Collapse/Imposition pair – which happen to represent a classic cyclic failure-mode.

In short, the Cynefin-dynamics give us a very incomplete picture and, at best, rather unhelpful picture of decision-dynamics at real-time, and tell us almost nothing about what actually does work in the near-real-time space.

So I hope you can see from this that there are some serious problems here that are just not being addressed in Cynefin: this is serious critique, and certainly not deserving the kind of petty personal putdown-attacks that have been the usual response from that direction. Sigh…

Anyway, back to the Twitter-stream:

• krismeukens: @tetradian it is not exactly running away, it is approaching it for the moment being in a “simpler” way through a reduction of reality
• tetradian: @krismeukens ‘reduction’ – sort of. I’ve gone into this in a lot of detail in my SCAN posts http://bit.ly/wSOAm0 (still a work-in-progress)
• krismeukens: @tetradian categorization versus sensemaking?
• tetradian: @krismeukens categorisation is sensemaking – (mostly Simple-domain sensemaking, in essence, but still a form of sensemaking)
• krismeukens: @tetradian Well yes // But there are 2 things here: 1 categorize in which domain the problem is, the meta-level so to say. 2 how the make sense of it.
• tetradian: @krismeukens ’2 things here’ – yes: recursion. without which Cynefin doesn’t make sense. and which it apparently does not allow. go figure? // ”does not allow” – at least, I’ve been savagely attacked each time I’ve tried to introduce the topic. Your Mileage May Vary etc
• tetradian: @transarchitect addendum to one-liner: Cynefin fits well with Complex, as SixSigma fits well with Simple: problems arise when out of scope
• transarchitect: @tetradian @krismeukens let’s not get too academic about this. C. is just another usable lens. #complexity
• tetradian: @transarchitect yeah, true. it’s just I’ve been attacked so often about trying to make it work that it’s something of a red-rag now…
• transarchitect: @tetradian above understands what’s below; not the other way around. I’ve been defending myself #complexity 2 decades: useless
• tetradian: @transarchitect “defending myself” – my commiserations, good sir… [don't quite agree re 'above/below' - more like mis-intersecting sets?]
• krismeukens: @transarchitect @tetradian yes, lens that is excellent metaphor
• tetradian: @krismeukens @transarchitect “lens” – yes – which brings @richardveryard’s concept/practice of ‘lenscraft’ back into this picture? // problem with Cynefin is that it claims to have full lens-set for all contexts, but does not cover ‘Chaotic’
• krismeukens: @tetradian @transarchitect this must be an attractive discussion as it gains new followers in search of a? date fo?r this w?eekend haha
• tetradian: @krismeukens are there other followers to this? – i thought we were just having a Standard Academic Argument between ourselves…

I had to duck out at that point, to do some promised tech-support for a colleague: we parted, with quick thanks shared all round. But a few other Tweets popped up in the stream somewhat later:

• hjarche: @tetradian just dipping into this discussion but “Act = running away” not an inference I ever made w/ Cynefin // I’ve no time to get too deep on this today but I will dig through all the refs & links later @transarchitect @snowded
• ImaginaryTime: @hjarche @tetradian @transarchitect @snowded Neither did I. Important to note one can also enter Chaotic domain intentionally (innovation).

Innovation is described above: quick summary is that it’s sort-of implied in the Cynefin-dynamics path 7 ‘Divergence-Convergence’, but note that it only links to the Complex: there’s no path described for innovation at real-time, the Simple <-> Chaotic link.

On “Not an inference I ever made w Cynefin” – a valid point, though I hope from this post above that the reasoning behind that inference is now clear. And, in turn, the reasoning why I now strongly recommend to not use Cynefin in its standard form in enterprise-architecture.

Anyway, enough for now: over to you, perhaps?

• simplicableanna: 7 Reasons You Need Architecture Principles http://bit.ly/xqzDkl #entarch

Gerold Kathan retweeted it, and I passed it on again as what I thought of as a useful summary. Nothing unusual there. But then one of my favourite EA thinkers, Richard Veryard, suddenly weighed in, in typically contrarian mood:

• richardveryard: @tetradian @gkathan @simplicableanna Have difficult #entarch decisions ever been resolved by appealing to bland uncontroversial principles?

Which triggered off one of those interesting back-and-forth enterprise-architecture debates:

• EricStephens: @richardveryard @tetradian @gkathan @simplicableanna #entarch Principles provide objectivity for decisions, even if pedestrian in nature
• richardveryard: @EricStephens @tetradian @gkathan @simplicableanna Is there objective evidence that principles improve decision-making? #entarch #groupthink
• chrisdpotts: Yes. #strategy | RT @richardveryard Is there objective evidence that principles improve decision-making? #entarch #groupthink
• EricStephens: @richardveryard @tetradian @gkathan @simplicableanna I have anecdotal stories only. Great question and research topic. Need to define metrix
• tetradian: @richardveryard: @EricStephens @gkathan @simplicableanna Is there objective evidence that principles don’t improve decisionmaking? #entarch
• richardveryard: @tetradian The lack of evidence that something doesn’t work is not a good enough reason to waste time on it.
• tetradian: @richardveryard plenty of anecdotal evidence (eg. I use principles often in my own decisions) – claims of ‘objective’ may be spurious here
• richardveryard: @tetradian I guess there are many popular #entarch beliefs that would be impossible to disprove. #pseudoscience

I would agree there – though it’d be the popular belief in the efficacy or even the possibility of  ’control’ that would be my first pick to question in this sense, with use of principles quite a long way down the list. But never mind – others continued the debate, anyway:

• BakedIdea: @tetradian @richardveryard where i work discussion +agreement on principles is essential part of decision making process… // not sure how youd empirically prove their value though. more, quicker, better decision? no way to measure success
• tetradian: @BakedIdea @richardveryard “no way to measure success” – yes, exactly. (or even ‘non-success’, in many cases)
• leodesousa: @richardveryard @tetradian in the early days of our #entarch practise principles helped us manage complexity – reduced dev platforms 7 to 3
• BakedIdea: @tetradian @richardveryard imo if you view part of #entarch as movin down a funnel of possibility then agreement on principles help movement
• krismeukens: @tetradian (cc @BakedIdea @richardveryard) So we’re actually in the chaos domain? No causality. Just act? Act-Sense-Respond? Mmm #cynefin
• tetradian: @krismeukens (cc @richardveryard @BakedIdea) principles are most use in ‘chaos domain’, as ‘seeds’ to provide equiv. of causality in Simple
• krismeukens: @tetradian (@richardveryard @BakedIdea) ok, makes sense, I’ll think about that.
• tetradian: @krismeukens (@BakedIdea @richardveryard ‘Act-Sense-Respond’ a bit misleading re principles: see http://bit.ly/w5kU1r , http://bit.ly/zQKAWi

I’ll admit that that last point from Kris Meukens about the Cynefin ‘Act-Sense-Respond’ sequence in the ‘Chaotic domain’ is a mild red-rag for me, given that I’ve spent literally years now trying to resolve the consequences of that one subtly-misleading mistake… I’ll agree that the sequence does occur, and is sort-of valid in its own way, as a sort-of method for sensemaking and decision-making in a high-variability context (i.e. ‘chaos’). But in essence that ‘method’ consists of ‘running away’ from the chaos as fast as possible, or preferably never be there at all. Which isn’t really much use for dealing with chaos as it is - and it also kind of defeats the object of the exercise anyway when we need to go into that chaos, intentionally, in order to create new ideas and options.

[For more on this, perhaps take a look at some of the posts on sensemaking with SCAN, such as 'Comparing SCAN and Cynefin', or the posts on belief and faith, decision-making, and the series on linking intent and action (Part 1), (Part 2), (Part 3), (Part 4).]

This is where principles and the like come into the picture, because they provide a means to ‘pre-seed’ the variability, leveraging Gooch’s Paradox that “things not only have to be seen to be believed, they also have to be believed to be seen”. In effect, the principles provide a stabilising anchor in the midst of chaos, reducing the natural tendency to panic and ‘run away’.

The panic-state often triggered by the infinity (or near-infinity) of possibility within a chaos tends to be expressed in the classic adrenalin-responses: fight, flight or freeze.  In practice, the functional purpose of the Cynefin Act-Sense-Respond sequence is to provide a means to shift the response-mode from ‘freeze’ to ‘flight’. What it doesn’t do is allow any option to remain in the chaos-space.

A much more useful approach is to centering-disciplines and the like to keep the panic at bay for as long as practicable, in conjunction with vision, values and more-actionable principles to provide a form of guidance within that space, all of it taking place in real-time.

The Act-Sense-Response sequence is only helpful in a high-variability context where principles are not used, and hence no guidance or ‘pre-seeding’ to re-constrain the variability towards a more useful outcome. As the published dynamics in the Cynefin framework make clear, the real risk of the Act-Sense-Response sequence is a collapse back to over-simplistic concepts of ‘control’; at best, it delivers a rather thin form of iterative sensemaking that kind of ‘dips its toes’ into the chaos and then runs back to the Complex-domain to make sense of what it’s seen – a cumbersome process that really slows things down. Hence, not recommended.

Given all of the above, I still don’t know why Richard Veryard was/is so vehement against the use of principles in real-time sensemaking and decision-making in enterprise-architecture. He didn’t seem to say much in those Tweets, other than that he sort-of regarded them as ‘pseudo-science’, without saying why. No doubt we’ll find out, here or elsewhere? But it seemed a conversation worth recording, anyway – I hope you find it useful!

[Update: later the same day]

Another Tweet came through from Kris Meukens, via Gerold Kathan:

• krismeukens: #principles are invariable inclusive/exclusive statements as a tool to constrain the space for emergence in a complex domain #cynefin

Yes, in Cynefin that’s true, and as far as it goes, I’d agree with it. However, there are a couple of very important points that are glossed over in Cynefin, which to me seem part of the cause for Cynefin’s fundamental flaws in what it labels the ‘Chaotic-domain’.

First, although we might say that “principles are invariable/exclusive statements … to constrain”, that’s not actually how it works in practice: in fact that’s more a Simple-domain true/false concept of principles than a fully-modal Complex-domain one. (Again in my experience, Cynefin’s structure makes it all but impossible to see the recursions that apply here.) Principles are the actionable expression of vision and values, and there’s always a set of trade-offs that we need to make between them – a contextual prioritisation that varies with every context, in line with Requisite Variety and the like. Which means that whilst the principles themselves may purport to be “invariable/exclusive”, the way we use principles is not. That’s a rather important difference.

Second, although Cynefin does work well for ‘considered’ sensemaking (i.e. in what it terms the Complex and Complicated domains), there seems to be no grasp at all in Cynefin that the ‘decision-physics’ change as we approach close to real-time – almost exactly analogous to the shift from Newtonian-physics to quantum-physics at very small scales. (The distinction may not be so obvious with sensemaking, but it’s absolutely crucial in decision-making – summarised by a phrase I used throughout the last series of posts on decision-making, that at the moment of action, no-one has time to think.) Cynefin seems to try to treat the sensemaking/decision-making processes as if they’re exactly the same at ‘considered’ and real-time timescales, which does not work in practice: hence why its handling of the Simple-domain is poor, and its handling of the Chaotic-domain woefully-inadequate.

Unfortunately it’s proved impossible to discuss any of this with Snowden – a fact illustrated all too well in his comments on this website. Since there’s no way to resolve these glaring flaws in the framework, I have, somewhat sadly, had to give up entirely on Cynefin, and restart from scratch. To be frank, I would strongly recommend that others in EA and related disciplines should do the same: useful as Cynefin may be in some other contexts, it’s simply not worth the problems that it creates in ours. Your choice, of course.

]]> http://weblog.tetradian.com/2012/01/13/how-useful-are-principles-in-ea/feed/ 28 http://weblog.tetradian.com/2012/01/10/decision-making-linking-intent-and-action-4/?utm_source=rss&utm_medium=rss&utm_campaign=decision-making-linking-intent-and-action-4 http://weblog.tetradian.com/2012/01/10/decision-making-linking-intent-and-action-4/#comments Tue, 10 Jan 2012 15:07:29 +0000 Tom G http://weblog.tetradian.com/?p=4610 How is it that what we do doesn’t necessarily match up with what we plan to do? How can we best ‘keep to the plan’? Or, alternatively, how do we know how to adapt ‘the plan’ to a changing context? What governance do we need for this? How do we keep everything on-track to intent in this? And what implications does this have for our enterprise-architectures?

What we’ve been looking at in this series of posts is a key architectural concern: at the moment of action, no-one has time to think. Hence to support real-time action, the architecture needs to support the right balance between rules and freeform, between belief and faith, in line with what happens in the real-world context. And it also needs to ensure that we have available within the enterprise the right rules for action when rules do apply, and the right experience to maintain effectiveness whenever the rules don’t apply.

As we saw in previous parts in this series, this implies is that within the architecture we’ll need to include:

• a rethink of ‘command and control as a management-metaphor [see Part 1 of this series]
• services to support each sensemaking/decision-making ‘domain’ within the frame [see Part 2 of this series]
• services to support the ‘vertical’ and ‘horizontal’ paths within the frame [see Part 3 of this series]
• governance (and perhaps also services) to dissuade following ‘diagonal’ paths within the frame

So this is Part 4 of the series, the final part: exploring the architecture of governance – and architecture-governance too – that we need for all of this to work well.

[Those two key reminders again: this is 'work-in-progress'; and all of this is recursive - so you'll likely need to do some work of your own here too.]

Within the architecture, we will need governance and governance-services to cover all of the issues that we’ve seen in the previous parts to this series. This would include guidance and governance on the services that support each of the SCAN sensemaking / decision-making domains and the links between them, and on any changes to those services and facilities.

Governance itself is usually outside of the remit of architecture – or probably should be, even if architecture sometimes ends up being landed with the role by default. A better role for architecture here is to identify what it is that needs governance, what kind of governance it will need, and where in the overall structures and story are the gaps that need to be filled – in other words, the governance to help create and maintain what does not yet exist.

As we’ve seen, the overall themes here that governance would need to cover would include:

• techniques for sensemaking and decision-making at the point of action, across the whole range of modality of possibility and necessity (described in SCAN as a spectrum between Simple <-> Not-known, and between Belief <-> Faith)
• techniques for sensemaking and decision-making at varying distance-from-action – loosely categorised as operational, tactical or strategic – and again across the whole spectra of modality (described in SCAN as between Complicated <-> Ambiguous, and between Assertion <-> Use)
• techniques to bridge across the sensemaking and decision-making at real-time (Simple <-> Not-known, Belief <-> Faith) and at distance-from-action (Complicated <-> Ambiguous, Assertion <-> Use) for operational, tactical and strategic distance-from-action
• improvement-processes that link between techniques at distance-from-action and at real-time action, constrained at distinct levels of modality, from true/false (Complicated <-> Simple, Assertion <->Belief – eg. Six Sigma, Taylorist ‘scientific management‘) to fully-modal (Ambiguous <-> Not-known, Use <-> Faith – eg. OODA, improv)
• processes and techniques to develop skills and competence across the full range of modalities applicable within the context
• validation of, training in and usage of all of such techniques

And as we’ve also seen, the governance would need to maintain a balance across all of these themes:

• theory and experience
• ‘objective’ and ‘subjective’
• ‘science’ and technology
• ‘control’ and trust
• true/false and fully-modal
• organisation and enterprise
• structure and story
• sameness and difference
• ‘best-practice’ and (understanding of) ‘worst-practice’
• ‘sense’ and ‘nonsense‘
• certainty and uncertainty
• caution and agility
• rules (‘the letter of the law’) and principles (‘the spirit of the law’)

Ideally the governance should also cover any applicable management-structures, with a strong emphasis on ‘management as a service‘ rather than as a dysfunction-prone pseudo-hierarchy. At present, though, that’s still likely to be too ‘political’ and problematic for architecture alone to face… – for now, probably best to class it as an architectural-waiver, to be addressed if and when the opportunity should arise.

Decision-physics

There’s a further point that I don’t think has come through clearly enough in the previous parts in this series. This is what we might term ‘decision-physics’, by analogy with mainstream physics.

Mainstream physics has three distinct layers: the very-small, the mid-range, and the very-large.

Most of what we deal with in terms of ‘the laws of physics’ is in the mid-range: Newtonian physics and the like. Everything seems to follow identifiable rules or ‘laws’; classical physics focusses on the direct impacts of those apparent laws, whereas in some cases there are contextual ‘emergent properties’ that arise from interactions between entities – though note that it’s still the same physical-laws beneath those interactions.

Our mainstream ‘decision-physics’ – what I’ve described as ‘considered’ sensemaking and decision-making – likewise seems to make sense across a very broad mid-range, from strategy to tactics to operations. And we see much the same distinction between all-predictable ‘hard-systems’ (Complicated / Assertion, in SCAN) versus complex, iterative, emergent ‘soft-systems’ (Ambiguous / Use) – though note again that’s still ultimately the same ‘laws’ on either side of that spectrum.

Yet some of those key ‘laws’ break down when we move to the far extremes. In cosmological-physics, for example, the speed of light seems to be an absolute constant across almost all timescales – yet not for the first infinitesimal instants of the Big Bang, or for the furthest reaches of time. Somewhere our present physics, there’s presumably some kind of circular self-referential assumption – but we don’t yet have the means to work out what it is.

Much the same applies in our ‘decision-physics’. Most of the time – such as in most enterprise-architecture work – the usual assumptions and decision-methods work well enough. Yet once we move to the scale of the very-large – with longer timescales, for example, or what I’ve termed ‘really-big picture enterprise-architecture‘ – some of those assumptions begin to be more evident, and become much more problematic. When we do have to work at those scales – and some enterprise-architects do so already – then we need to be aware that a somewhat-different decision-physics may apply: for example, conventional notions of ‘possession‘ and the like may no longer make sense.

The certainties of mainstream physics also tend to break down at the scale of the very-small, as we move into quantum-physics and the like. It’s actually the same underlying physics, but all manner of assumptions that we could get away with at the everyday Newtonian scale become visible as assumptions. This applies particularly around certainties versus probabilities, which at the quantum scale gives us seemingly-impossible phenomena such as ‘particles’ that can be in more than one place at the same time. (This also gives us occasional oddities in larger-scale physics, such as in signal-theory, where to guarantee perfect signal-transmission we would need a conductor of infinite size.)

In the same way, many of the assumptions of mainstream ‘considered’ sensemaking and decision-making start to break down once we get at or very close to the moment of action. The key ‘takeaway’ that I hope you get from this multi-part exploration with SCAN is that what happens at the point of action is real: everything else is an abstraction.

And it’s an abstraction that may not have much connection with reality at all. All of so-called ‘rationality’ is an abstraction: hence, for example, why ‘rational-actor theory’ and much of current mainstream economics has been such a disastrous bad-joke, and why ‘control’ is a such a misery-inducing myth in most current forms of business-management.

What we actually have at the point of action are literally-emotive decisions made on belief and faith. Just as quantum-physics underpins the larger-scale Newtonian-physics, all of our abstractions are actually underpinned by real-world emotion – literally, ‘that which moves’.

Thinking is extremely important, of course, because it clarifies intention. But neither thinking nor intention actually do anything on their own: for something to happen, we need to link intention to emotion. Which in most cases also means that we need to link the type of intention to the matching type of emotion-that-drives-action – and likewise match the emotion back to the required intention, to get the maximum effectiveness from expenditure of energy.

[Not every emotion is effective, of course: aggression, panic or 'awfulising' - otherwise known respectively as 'fight, flight or freeze' - can use up a lot of energy without achieving anything useful at all... Likewise the same does also apply to machines and IT-systems, but kind of at one step removed: plenty of motion without emotion as such, it's true, but it's human emotion and human choice that links all of that activity back to intent.]

So at the point of action – the quantum-level of our ‘decision-physics’ – what we actually have is a range of emotion applied across that scale of modality. And it’s here that the Inverse-Einstein Test becomes crucially important, because it provides the key distinction between what I’ve termed ‘belief’ and ‘faith’:

– belief is grounded in certainty, and in the centrality of self

Belief expects the world to work in a specific way: doing the same thing will – or should – lead to the same results. We proceed with the conviction that this is true. An abstract idea – a ‘law of physics’, perhaps, or a more mundane work-instruction or checklist-item – becomes actionable in real-world practice when we attach ourselves to it, as a personal commitment to its ‘truth’.

[Perhaps the starting-point for all belief is faith - as we'll see in a moment - but belief itself provides a stable anchor from which to act.]

For the most part, this how most things are actioned in business and elsewhere: we follow the rules, to get the same results. For the most part, and in many if not most everyday contexts, this is what we want in business and the like: the right beliefs deliver the right results. Yet there are couple of important catches that we need to note here, both of which have their roots in that personal commitment, and both of which are common causes for ineffectiveness and overall failure.

The key to both of these is the Latin word ‘credo’ – literally, ‘I believe’. Note the ‘I’ here: I, me – the commitment of self to the belief. The commitment is what creates the drive to action, power as ‘the ability to do work’. Yet if we shift too far over to a self-centred view, ‘I’ as the centre the world, we risk falling into the social misperception that power is the ability to avoid work: ‘the rules’ are deemed to apply to others, and to drive others’ actions – with those others being viewed as extensions of self that ‘should’ be under our control yet without requiring any actual action or responsibility on our part. Hence those endless ‘shoulds’ – applied to the world in general, to machines and systems, and even more to other people. (‘They should’; ‘everyone ought’; ‘it must’; so many phrases like that – though noticeable is the relative rarity of ‘I should’…) In effect, the emotion shifts away from doing useful action, and toward trying to ‘control’ others instead – a well-proven recipe for wasting all one’s energy in ineffectual anger… There are some real governance-issues here, and some useful tools for this, such as the SEMPER diagnostic I developed some years back.

The other side of this is a classic give-away for dubious discipline in the sciences and elsewhere: getting overly emotional about the ‘truth’ of ideas, theories and beliefs. Belief is emotional, a driver for action; yet in itself, thought is neither emotional nor actionable. So when we see someone getting emotional about ideas, aggressively asserting that their ideas are ‘the truth’ – or, more especially, that someone else’s ideas are ‘wrong’ – it’s not actually about the ideas at all: it’s about that person’s ego, a demand that others’ action should place that person at the centre of their world. This is the basis of ideology, where the ‘truth’ of the belief-structure deemed to be more ‘true’ than the messy complexities of the real-world – and where those who hold that ‘truth’ deem themselves to be ‘better’ than any others, solely because they hold to that ‘truth’. (There’s a nice Freudian pun here: ideology as ‘id-eology’…) Hence, again, why ‘office-politics’ is actually a hugely-important governance-issue in enterprise-architectures.

The key effect of both of these is a disconnect from the real-world: a demand that the world ‘should’ conform to our expectations, and an assertion that the world itself is ‘wrong’ if it fails to conform to those expectations – all often coupled with a daft dependence on circular-proofs and ‘other-blame’. So whilst emotion and ego are essential to get things going, we do need to keep them in their place… hence, again, the need for appropriate governance right down to this level, all the way across the whole enterprise.

– faith is grounded in uncertainty, and in relation to ‘that which is greater than self’

Faith is what happens when we’re in the Not-known – where doing the same thing leads to different results, or to get the same result requires that we do different things. Faith is the emotive mechanism that we use when we don’t know what to do, yet don’t allow ourselves to get caught up in the classic Belief-driven panic-responses of ‘fight, flight or freeze’ – in other words, to use Susan Jeffers‘ phrase, we ‘feel the fear and do it anyway’.

Whenever we come across any context that has some component of Not-known or None-of-the-above, this is what we have to do. Somehow. Some people find this easy; yet for many people, so important is the sense of safety that comes with certainty, that this kind of ‘letting-go’ can be very hard to do… and organisations and organisation-structures that assert the absolute primacy of ‘The Rules’, and deny the inevitability of the Not-known, will make that letting-go that much harder. Hence there are some significant design and governance-issues here for enterprise-architecture.

What doesn’t work well in this space is ‘flailing’ – doing something just for the sake of doing something. Often what’s needed first is the exact inverse of the old adage: “Don’t just do something, stand there!”. We keep the panic at bay – and avoid a fallback to literally-incompetent Belief – by coming to a calm centredness within the space, and (usually metaphorically, though sometimes almost literally) allow the space itself to speak to us, to show us what to do. And at that point, take action – all in real-time.

At the first point of contact – and especially so at the further extremes of modality – this is literally a context of chaos: in principle at least, anything is possible there. That’s the advantage of the Not-known; it is, obviously, also its disadvantage, since any number of things that we don’t want to happen also become equally possible at that point. Hence the need for appropriate tactics that work within the chaos, and provide guidance towards the results that we need.

There are any number of well-known tactics that don’t work well here: for example, ‘take control!’ might be the preference for any Taylorist manager, but in practice all it does is pull us back over to Simple Belief – which is not where the solution to a Not-simple problem is likely to reside… And there are a fair few would-be ‘The Answer’ options that contain fundamental flaws in this regard – a point we’ll come back to later.

Although there’s an element of Schrodinger’s Cat in this, what does seem to work is ‘seeding the chaos’: bringing explicit aims and intentions into the space, yet also allow the space to be what it is. (I’m at some risk of making this sound a bit like “hey, ’60s counterculture, man”, but actually there’s a lot of practical sense in Timothy Leary’s notion of ‘setting and set‘, even within everyday business-contexts.) Hence, in enterprise-architectures, the real importance of ‘setting the scene’ with vision, values and more-actionable principles – all of which provide an anchor of a direction and intent which is ‘greater than self’. ‘Success-stories’ in business – especially those about the grass-roots operational levels – will often revolve around use of such ‘seeding’ to guide context-appropriate action in unexpected circumstances.

Dysfunctional diagonals

One of the key points that came up in the previous post was the importance of having explicit processes and methods to link intent and action, and also to link across the modalities. In SCAN, we would describe these as ‘vertical’ and ‘horizontal’ links:

What we don’t want, though, are ’diagonal’ transitions that link one type of modality at the ‘considered’ level with a different modality at the point of action – such as Assertion misapplied to a Not-known context, or introducing the Ambiguous at the very moment of Belief-based action:

Probably the classic example of this is the myth of ‘control’, typified by the many, many misuses of Taylorism and its descendants and derivatives. For example, Six Sigma makes perfect sense, and is very valuable, when applied to contexts with very low variation; but it doesn’t make sense, and is often dangerously misleading, when attempts are made to apply it to anything other than a context consisting solely of literally millions of nominally-identical events. Business-process reengineering was another infamous example: one of its leading proponents, Michael Hammer, is quoted on the Wikipedia-page as later admitting that:

“I wasn’t smart enough about [the human impact]. I was reflecting my engineering background and was insufficiently appreciative of the human dimension. I’ve learned that’s critical.”

In SCAN terms, each of those is a ‘diagonal’ link of Complicated <-> Not-known – which doesn’t work. We also get the same effect, though, if we take something that does work well as a link of Complicated <-> Simple, and implicitly apply it to a modality beyond its specific true/false constraints. One example that comes to mind here is Roger Sessions‘ work on Simple Iterative Partitions as a method to reduce or eliminate ‘complexity’. It does work extremely well within the relatively-narrow scope of IT-systems themselves – where, in SCAN terms, ‘complexity’ is an undesirable excess of Complicated, leading to system-applications that are not Simple enough to work effectively in real-time action. Yet it’s misleading if we use the same concepts to talk about the application of IT-systems in real-world contexts which, because they’re real-world contexts, frequently must deal with a different type of ‘complexity’ that can’t and sometimes shouldn’t be ‘eliminated’. In effect, that’d be Complicated <-> Simple applying an Assertion that Ambiguous <-> Not-known doesn’t actually exist – taking us straight back to the Taylorist myth of ‘control’, which is not a wise move.

[A quick somewhat-personal note here: Roger has always been a great sparring-partner on this question - perhaps best described on my part by the old phrase "I disagree with every word you say, but I will defend to the death your right to say it"? ]

Going the other direction, we could use the example of Andrew McAfee’s ‘Enterprise 2.0‘, ”the use of emergent social software platforms within companies, or between companies and their partners or customers”. Nothing wrong with that definition itself, but the point here is that the application is about collaboration across the organisation – Ambiguous <-> Not-known, or Use <-> Faith – whereas McAfee placed inordinate emphasis on the technologies instead, or Ambiguous <-> Simple. Ignoring the real complexities of the human-factors was exactly the same mistake that caused so many business-process reengineering projects to fail – a point which was quickly picked up by many practitioners with real-world experience. Surprisingly, McAfee took a long while to acknowledge the problem, eventually coming out with a blog-post ‘It’s not not about the technology‘ – which was true, but still kind of missed the point.

Another example has been a bane of my professional life for the past few years: David Snowden’s Cynefin framework. In SCAN terms, it purports to cover the Ambiguous <-> Not-known link – somewhat like McAfee’s ‘Enterprise 2.0′, but with more emphasis on complexity-theory and social-systems in general rather than in one specific application. The problem here – and despite many, many explanations of this, Snowden still emphatically refuses to acknowledge the problem – is that Cynefin explicitly locks out the linkage to the Not-known / Faith space, for which the nearest equivalent in Cynefin is termed the ‘Chaotic domain’.

The Cynefin framework states that the standard tactic in the Chaotic is ‘Act > Sense > Respond’: which in principle might seem fair enough, except that in many cases – as described above – ‘doing for the sake of doing something‘ is exactly what we should not do as a response to ‘chaos’. Even when action is appropriate, the catch is in what happens next, because the documented ‘Cynefin dynamics’ in effect insist that our only method of dealing with the Chaotic domain is to not be there: our only apparent options are to ‘take’ control’ and collapse back to the Simple domain, or return to ‘considered’ sensemaking in the Complex domain. In SCAN terms, the former is a diagonal-link of Ambiguous <-> Simple, which is clearly not a good idea; the latter is a self-referential loop of Ambiguous <-> Ambiguous, which looks impressive and gives us more and more information about complexity and emergence and the like, yet clearly is not going to go anywhere that’s any actual use. In that sense, Cynefin actively prevents us from applying its insights in real-world practice: it’s valuable for ‘considered’ sensemaking, but literally useless for real-time decision-making. So although Cynefin does claim to cover the whole ‘complexity’ space, the only way to use it in practice is to not use it – which is not exactly helpful…

[There's more on this in other posts here, if you're interested: for example, see 'Using Cynefin in enterprise-architecture' and 'Comparing SCAN and Cynefin'.]

For a final example, we could turn to something that’s perhaps more familiar to many enterprise-architects: Agile software-development. In principle, it’s a good response to the reality that software-development takes place in a world that has a great deal of Not-known about it. And it’s also a response to the ‘traditional’ Taylorist-style Waterfall model of software-development, in which everything would be rigidly defined ‘up front’ without acknowledgement of the reality or probability of changes in the context. In effect, it aims to take the Assertion <-> Belief link on which all conventional IT-systems depend, but apply it via a disciplined Ambiguous <-> Not-known link such that the overall development-process can adapt in near-real-time to changing needs.

That’s the principle: and with experienced, adaptable developers who know what they’re doing and how to work with inherent-uncertainty – in other words, Master skill-level, or Journeyman with a bit of mentoring from Master – it does work well. Unfortunately, it doesn’t work well with developers who don’t have that kind of skill or experience – the Apprentice or, worse, the Trainee. So what we get there instead, all too often, is an undisciplined mess: not enough skill or discipline to work with Faith-style uncertainties and the Faith <-> Belief axis, coupled with a rejection of the formal disciplines demanded by the Complicated / Assertion domain. In other words, not only a problematic ‘diagonal’ of Complicated <-> Not-known, but the worst of both as well. Oops…

And yet somehow we do still need that agility: hence this is one aspect of enterprise-architecture governance where the need for balance is perhaps better-known and better-understood. You’ll find various posts here on what I’ve termed the ‘backbone’ – for example, see ‘Agility needs a backbone‘ and ‘Architecting the enterprise backbone‘; there’s also a good summary by Vikas Hazrati on the InfoQ website, ‘Agile and Architecture Conflict‘. But perhaps I ought to leave the last word here to a software-architect I greatly respect, Simon Brown, who’s frankly brilliant at describing the practice of how to ‘seed the chaos’ to get the best results in agile-development: see his presentations and videos to explore the trade-offs that we need so as to derive an agile-architecture that works, and how to resolve the architecture-challenge of “How much architecture is ‘just enough’?”

—

Okay, that’s it for now. Plenty more to say on all of this, of course, but I’d guess it’s been more than enough already?

And many thanks reading this series: hope it’s been useful? Over to you for any comments and questions, anyway.

What we’ve been looking at in this series of posts is a key architectural concern: at the moment of action, no-one has time to think. Hence to support real-time action, the architecture needs to support the right balance between rules and freeform, belief and faith, in line with what happens in the real-world context. And it also needs to ensure that we have available within the enterprise the right rules for action when rules do apply, and the right experience to maintain effectiveness whenever the rules don’t apply.

As we saw in previous parts in this series, this implies is that within the architecture we’ll need to include:

• a rethink of ‘command and control as a management-metaphor [see Part 1 of this series]
• services to support each sensemaking/decision-making ‘domain’ within the frame [see Part 2 of this series]
• services to support the ‘vertical’ and ‘horizontal’ paths within the frame
• governance (and perhaps also services) to dissuade following ‘diagonal’ paths within the frame

So this is Part 3 of the series: exploring the architecture of how we link together the various domains of sensemaking and decision-making within the enterprise.

[Two key reminders here: this is 'work-in-progress', so expect rough-edges and partly-baked ideas; and although I'll aim to keep the descriptions as simple of possible, note that all of this is recursive, with many intersecting layers of simple and definitely-not-simple - so please do expect to have to do exploratory-work of your own here too.]

On services to support the ‘horizontal’ and ‘vertical’ transitions:

We can summarise this part in terms of the following diagram:

Although sensemaking and decision-making tend to be blurred together within these transitions, there’s usually a clear set of distinctions:

• services that work across the modalities in real-time action
• services that bridge between certainty and uncertainty in planning for action and reflection on action
• services that improve how we apply certainty in action
• services that improve how we work with uncertainty in action

The first two sets of services are primarily ‘horizontal’ across the SCAN frame, linking across the modalities but at a single timescale; the other two sets are primarily ‘vertical’, crossing timescales but on either side of the Inverse-Einstein boundary. There’s obviously enormous scope here, but to keep things simple I’ll stick to a single scenario for each.

For real-time, imagine starting this off with a checklist – a pilot’s pre-take-off check for an aircraft, perhaps.

This gives us a Belief-based structure for decision-making – ‘belief’, because the ‘correct method of working’ is embedded in the sequence of the list. It also gives a Simple true/false method for sensemaking – ‘simple’, because either something checks off against the list, or it doesn’t. After much repetitive practice, using this checklist is ‘second-nature’ to the person doing this work – yet the list is also followed with care and attention.

And because the checklist is followed with care – as ‘the truth’ – the pilot notices that something doesn’t check off correctly. For this example, we’ll assume it’s the radio: there’s no response and no apparent signal from the control-tower.

The moment that we hit something that ‘doesn’t fit’, by definition that throws us across the other side of the SCAN frame, into the Not-known. Notice that for a (very) brief moment, there’s a sense of panic – at which point all the previous training and skill and experience should kick in, together with Faith-based decision-making, to cope with ‘a context larger than that covered by the rules’.

[I've deliberately chosen a fairly minor yet everyday example here: an incorrect radio-setting. For a far less everyday example where the same principles and processes apply, moving back-and-forth across the real-time spectrum, see the section 'Sensemaking in real-time' in the post 'On sensemaking in enterprise-architectures [Part 2]‘.]

In a fully-structured process, there would be another checklist here, specifically to guide sensemaking and then decision-making around what’s (not) happening with the radio – in other words, a tool to pull this back over to the left-side of the frame again, with Simple / Belief. But if the checklist doesn’t exist, or isn’t found, the sensemaking and decision-making remains over on the Not-known / Faith side of the frame.

It’s a high-risk context, so the pilot can’t afford to ignore the problem, and also can’t ‘go on faith’ – the checklist makes it clear that that radio must be working correctly before take-off can be allowed. So notice what happens next: the sensemaking remains on the unorder side, but drops out of real-time. Everything slows down: the pre-take-off process has to stop whilst the pilot carries out a quick series of experiments – in other words, moving somewhat up into the Ambiguous / Use space.

Most of these are Simple true/false tests (is the radio switched on? is the headset connected? is the frequency-setting correct?), which in principle are rule-based, except that the pilot is creating these tests on the spot, from past experience and knowledge of the equipment, rather than following a (non-existent) checklist. One of these tests shows that the frequency has been set for the destination airport rather than this one. The pilot looks up the correct frequency from a reference-chart – another Simple tool – and then changes the channel – a Belief-based decision.

Going back to the original checklist – in other words, now back in real-time again, over on the left-side of the SCAN frame – the pilot re-checks the radio-call: this time it does confirm correctly. The pilot then completes the pre-take-off checklist without any further Not-known interruptions.

From an architecture perspective, notice two points here.

The first is that real-world sensemaking and decision-making at the point of action will often bounce back and forth between Simple / Belief and Not-known / Faith. Most typical business-processes will start over on the Simple / Belief side of the frame – in other words, ‘follow the plan’; yet anything unique, anything different, anything unexpected that doesn’t fit the predetermined ‘the Rules’, will automatically force a transition over to the Not-known / Faith side of the balance. And in most cases, only skill and experience will bring it back over to the Simple side again, to deliver the required result. That’s what skill is, and largely what it’s for.

The second point is that systems which can only work with rules – which in practice includes almost all machines, and most IT-systems – cannot actually cope with that transition into the Not-known. And many if not most real-world contexts do include uncertainties of some kind or other. In such cases – which, again, is most cases – rule-based systems cannot be used to address the whole context: there must be a human skill-based component both to identify when the rule-based system is out of scope, and to take over when it does go out of scope.

The danger here is that IT-systems can sometimes simulate full-context capability from sheer speed applied to a sufficiently large rule-base – which gives the illusion that it can cope with the full context. Fact is that it probably can’t – that uncertainty again – but if we design on the assumption that it can, we’re going to be in real trouble when (not ‘if’) it fails. The architecture needs to take great care on this point: yet the sad fact is that most current architectures – especially IT-centric ones – don’t take anything like enough care with fallbacks and the like here. You Have Been Warned?

For reflection-time – moving back-and-forth across the frame, but at some distance from real-time – what we need are processes that focus on pragmatics and praxis: distilling theory from practice (right-to-left on the SCAN frame), and applying theory to preparation for practice (left-to-right on SCAN) in the unordered-realms.

This is the transitions between what’s described in SCAN as Complicated / Assertion and Ambiguous / Use. What we’re looking for here in the architecture is support at various different timescales – strategic, tactical, operational – for a whole swathe of interactions and trade-offs across the two sides of the frame. As mentioned back on the post ‘Decision-making – belief, fact, theory and practice‘, some of the keywords we’d look for on each side of that balance would include:

• theory versus experience
• ‘objective’ versus ‘subjective’
• ‘science’ versus technology
• ‘control’ versus trust
• true/false versus fully-modal
• organisation versus enterprise
• structure versus story
• sameness versus difference
• ‘best-practice’ versus (understanding of) ‘worst-practice’
• ‘sense’ versus ‘nonsense‘
• certainty versus uncertainty
• rules (‘the letter of the law’) versus principles (‘the spirit of the law’)

For example, this is – or should be – the ‘applied science’ transactions between the assertions of science and the usefulness of technology, each lifting the other to new levels of capability. And we’ll only achieve a real effectiveness via a fully-nuanced ‘both/and’ balance across all of these dimensions, and more – which is what the architecture needs to support.

At present, though, most enterprise-architectures and their subsidiary domain-architectures will be hugely skewed towards the left-side of that balance: theory and ideology, ‘objective’, ‘science’, structures, sameness, ‘sense’, rigid rules, near-random re-use of others’ supposed ‘best-practice’, true/false ‘proof’, abstract organisation (rather than human enterprise), and, above all, certainty and predictability. Yet the end-result of such imbalance is an architecture that is all but incapable of coping with either uncertainty or change – and relies instead on a stream of management-fads to give a spurious sense of certainty where none actually exists. Which is not a good idea, especially in the increasing uncertainties of most present-day business contexts. We need that balance…

The simplest way to work towards a better balance is that, for each item that seems to fit in either the Complicated / Assertion domain or the Ambiguous / Use domain:

• what is its counterpart in the opposite sensemaking or decision-making domain on the other side of the frame?
• what processes link these two items together, such that each can learn from and support the other?
• how do these processes vary at different distances from the point of action?
• how do these processes vary for different skill-levels or for use with different real-time process-implementations?

(We’ll come back to that last question shortly.)

So, for example, Complicated-domain analytic, algorithmic hard-systems theory has its Ambiguous-domain counterpart in experimental, emergent soft-systems theory: in what ways do these link together? How do they support each other, inform each other, conflict with each other, enhance each other? How do we identify (make sense of) which approach would apply better to any given context? What are the trade-offs that would guide such decisions?

[For some great examples of how this kind of interaction works in scientific research, see WIB Beveridge's 1950 classic The Art of Scientific Investigation.]

Using those tests and guidelines, work your way across all aspects of the architectures, to identify gaps and imbalances across the SCAN domains.

For improvement of real-time action, the processes would, in principle, be partitioned across either side of the Inverse-Einstein test: those processes that focus ensuring that the same actions lead to the same results, versus those processes that focus more on skills-development, such that we can achieve the required variation in similar contexts or the required ‘sameness’ in different contexts. In very quick summary:

• improvement on the left-side (‘order‘) will focus primarily on efficiency (typically described in quantitative terms, and often regarded as synonymous with effectiveness)
• improvement on the right-side (‘unorder‘) will focus more on broad-spectrum effectiveness (with an emphasis on qualitative factors and human-concerns)

That order-versus-unorder partitioning is valid in itself – the Simple true/false methods used by machines and IT-systems, versus the full modality of methods available within skills-work. Yet it’s also in itself too simple, or too simplistic, rather: we need the framework to give guidance on skill itself.

This is where we come back to that question about reflection-processes that vary according to skill-levels. In essence, it’s not really a skill unless there’s some inherent-uncertainty involved in the context: before that, all the way over onto the Simple side of the spectrum, everything is literally mechanical, rule-based.

For this, we can turn to a cross-map of the SCAN frame with a spectrum of variability or predictability – shown as the blue curve in the diagram below:

The diagram is perhaps slightly misleading here, because the impact of variability doesn’t come out well enough: the blue line is itself another kind of continuous spectrum, rather than the Simple true/false implied by the colour-shading here.

[Part of the reason is that I don't yet know how to how to do multi-layer multi-colour graded-shading in Visio: accept it as it is for now, if you would?]

What is relevant here is the the way in which skills-development follows the same effective path of increasing variability – including that increased distance-from-action in the middle of that curve.

What we actually have in skills is not so much a Simple ‘either/or’ – Simple or Not-simple, order or unorder, as implied on the diagram – but more a ‘both/and’ mix of order and unorder. Higher levels of skill also implies or requires the ability to cope with higher levels of modality, variability and unorder. We can split this in terms of five distinct skill-levels:

• Robot: no skill as such – Simple rule-following only
• Trainee: low level of skill – mostly Simple / Belief, aware only of ‘here and now’, requires active supervision to cope with variability
• Apprentice: some level of skill, still primarily order-based but able to manage more Complicated / Assertion contexts with broader factors and feedback / feedforward loops, with some active supervision
• Journeyman: significant skill, able to cope with higher levels of Ambiguity and context-dependent Use, with supervision mainly in the form of mentoring
• Master: high skill, able to cope with inherent-uniqueness, balance of ‘big-picture’ with ‘here and now’, and ‘supervision’ only in the form of peer-review

So when we look at the ‘vertical’ improvement-processes implied by the SCAN frame, we tend to find that they work best when they act on specific mixes of order and unorder, sameness and uniqueness – in other words, in alignment with these skill-levels.

We can also see the classic ISO-9000 quality-system derivation-sequence at work here, between each of those steps:

• work-instruction: context-dependent rules used by Robot and initial Trainee – emphasis on What and How
• procedure (basis for new work-instruction): used by Apprentice and above, defined by Journeyman and above – emphasis on Who, Where and When
• policy (basis for new procedure): used by Journeyman and above, defined by Master – emphasis on Why
• unchanging-vision (permanent-anchor for quality-system, used as basis and cross-check for new policy): used by Master, defined by Master in peer-review – the ‘Because.’ behind the Why

There are many, many types of review / improvement-processes – PDCA (Plan, Do, Check, Act), for example, or AAR (After Action Review) or OODA (Observe, Orient, Decide, Act). Yet almost all of them have this ‘vertical’ character, to link:

• from real-time action – where there’s no time to think
• to distance-from-action – which creates thinking-space and review-space, to enable improvement
• then back to real-time again – to apply that improvement in real-world practice

There’s a usually a slight sideways-move in there somewhere – because wherever practicable the aim should be to enhance those skill-levels, not leave them solely as they are. But what we don’t want are ‘diagonal’ moves that try to link one type of order / unorder mix at ‘thinking-time’ with a very different mix at real-time – because it all but guarantees failure in practice. We’ll explore that point in more detail in the next part in this series: for now, we’ll focus more on the ‘verticals’.

We can again summarise these processes in terms of those five distinct skill-levels:

– Robot: Simple / Belief only (typically machines or real-time IT-systems) – aim is to optimise efficiency within a specific defined context

This is the classic realm of Taylorist time-and-motion study, of Six Sigma and suchlike: if we assume that everything in the work-context remains the same, what can we do to improve the efficiency of that ‘sameness’?

The crucial point here is that the Robot can only follow the rules that it’s given: it can’t change anything by itself – or even adapt to any significant change in its context. The Robot must rely on an external ‘expert’ to redefine its rules whenever the context undergoes any significant change, yet the ‘expert’ does not have to deal with real-world consequences: a fact which, if misused, can lead to a dangerous co-dependent relationship between Robot and ‘expert’, based on mutual evasion of responsibility – something that we see far too often as an outcome of dysfunctional blame-based management-structures.

– Trainee: Simple / Belief <-> Complicated / Assertion – aim is to develop ‘rule-following’ efficiency and to develop awareness of the ‘larger picture’, to place own work in context, and to begin to cope with variability

We typically see two types of review-processes here. One type concentrates on practice – embodying ‘the rules’ through constant repetition, mainly focussed on method, on the ‘what’ of those rules as applied to real-time action. The other type, typified by the US Army’s ‘After Action Review’, begins a focus on enhancing personal ‘response-ability’ – a concern that will continue all the way through the skills-development sequence.

– Apprentice: Complicated / Assertion <-> Simple / Belief (with some bridge over to Ambiguous, e.g. via experimentation) – aim is to develop ability to use formal-theory to redefine own rules as the context changes

This is the classic realm of formal education, with an emphasis on theory and on the mechanics of the skill, the ‘how’ behind its processes and methods. However, the focus is almost more on ‘order’ than at the Trainee level, defining rules as ‘objective truth’ to be applied by others in real-time action. The main contextual-shift is a developing awareness of more and more Complication in those ‘rules’ – a layering nicely described by Jack Cohen and Ian Stewart as an increasing sophistication of “lies-for-children” – in which additional factors, interaction-loops and delay-impacts are added to the rule-definitions. One of the hardest parts of this stage is re-simplifying these ever-more-complicated algorithms and ‘rule-sets’ down to a form that can be used in real-time action…

– Journeyman: Ambiguous / Use <-> Not-known / Faith (with some bridge over to Complicated, e.g. as ‘applied science’) – aim is to enhance ability to work with increasing levels of variation and near-uniqueness, such as by applying patterns and guidelines

This is typified by the crucial shift in awareness that theory alone is not enough: in the real world, ‘truth’ is often highly contextual. This is the realm of ‘real’ complexity, of emergence, of iterative exploration and experimentation, and also a more explicit acknowledgement of the inherent unorder that underlies wicked-problems and the like. It’s also a realm of probability and improbability – hence a strong focus on concerns such as the uncertainties of statistics, on kurtosis-risks, long-tail opportunities, and so on.

[Note the danger of failure to understand the probabilistic nature of statistics - that they always embed and embody some degree of unorder and uncertainty. It has its rules, but they're not the same order-based rules as in the Complicated domain: for example, it's true that chaos-mathematics can enable us to be very precise about the degree of uncertainty in a context - but it does not remove the uncertainty itself. Another important 'You Have Been Warned' that we need to pass on to our architecture-clients?]

There would also be a stronger emphasis here on guidelines and patterns, and on what we might describe as the approaches to each skill – the unorder of the ‘other mechanics’ of the skill, such as in the psychological and emotional drivers, and in ergonomics and individual difference. Continuing and expanding the theme of the After Action Review, this is the realm of responsibility-oriented continuous-improvement processes such as PDCA and kaizen, of simulators and ‘sandboxes’ and other ‘safe-fail’ learning-spaces, and also of context-exploration tools such as the skills-labyrinth.

– Master: Not-known / Faith <-> Ambiguous / Use – aim is to enhance effectiveness, being able to work with any level of variability and uniqueness at real-time, in line with overall vision and values

It’s at this level that we return to real-time practice, but this time aiming to be able to work with unorder, rather than fight against it (or even pretend that it doesn’t exist…), as in the rule-based assumptions of the Robot space. Here there’ll be a strong emphasis on enhancing capability for improvisation, and for coping with inherent uncertainty, such as with innovation and with Black Swans and other opportunities and risks at the extreme end of unorder. For skills, this would also bring together the previous themes in active acknowledgement that method = mechanics + approaches – hence true skills are both same and different for everyone at every time. On a practical level, there’s also a strong emphasis on the use of principles, vision and values to provide a stable anchor for guidance amidst inherent-uncertainty.

[Notice that, again, all of the above sequence is recursive: we may well be at Master level in some skill-domain, but barely at Trainee-level in another - a fact that can at times be somewhat challenging... ]

Implications for enterprise-architecture

For enterprise-architects, there’s a lot to review here, because all of those items need to be in place if the overall architecture is to work well for the organisation and enterprise:

• services that bridge across the modalities of certainty and uncertainty in real-time action
• services that bridge between certainty and uncertainty in planning for action and reflection on action
• services that improve how we apply certainty in action, how we work with uncertainty in action, and the skills of each person to work with these

We’ll need to identify each of these items, for each of the respective ‘horizontal’ and ‘vertical’ contexts; and wherever there are gaps in the needed support, identify what needs to be done to create and embed the respective items.

We also need to be aware of and act on some really nasty booby-traps that, if we’re not careful, can damage or even destroy the entire enterprise. Dysfunctional management-structures and misapplied Taylorist ideas are well-known examples of these: the real problem there is that the illusion of ‘control’ is so comforting to so many that these muddle-headed mistakes keep on coming back to bite us time and time again, like the proverbial ‘bad penny’.

Another serious danger that’s a bit more subtle can arise from those seemingly-relentless demands to do more and more, faster and faster. Part of this is that the sheer pressure to produce can cause a disconnect between strategy and tactics and even between tactics and operations: when everything has to happen now, there’s no time to think about what’s being done, or why. Not a good idea…

But a corollary of that is that if there’s no time to think, there’s also no time to develop skills – a point which again is made clear in that cross-map between SCAN and the variability-curve above. All too often we’ll come across an organisation that in essence consists of Masters and Robots (such as machines or IT-systems, or ‘crowdsource’ structure such as Mechanical Turk which in effect treat real-people as Robots), with nothing in between – perhaps a few Trainees to do the grunt-work, but that’s about it.

There’s little question that this can be highly profitable in the short term. Yet it’s a model that, almost by definition, cannot and does not scale – hence the constant complaints we see about ‘skills shortages’ and the like – and why so many startups seem to crash-and-burn so soon after their first flush of sweet success. And if there’s no means within the organisation’s architecture to develop those skills, there’s also no way to learn the contextual information needed to create the next generation of Masters – see the post ’Where have all the good skills gone?‘. Ignoring the skills-development issues may seem profitable at first, but it’s actually a guaranteed path to commercial suicide. Once again, You Have Been Warned?

Anyway, enough for now: more on this and other related themes in the final post in the series.

Any comments or questions so far, anyone?