Tom Graves / Tetradian

Earlier today I came across a Tweet from the Open Group that pointed to an interview with Dr Leon Keppleman at University of North Texas. Given that the note was from Open Group, no surprise that it was mostly about IT, but to me, the headline was somewhat of a breath of fresh air, and I said so when I reTweeted it:

• tetradian: RT @theopengroup: On @infomgmt about “Getting Holistic with Enterprise Architecture” http://shar.es/fWDYZ >strong recommend #entarch

To me the article is a very good illustration of the crucial distinction between IT-oriented versus IT-centric.

In essence, the whole interview is all about IT, and IT-education: nothing much more than that. And parts of it show the usual IT-type errors, such as ‘information-systems’ solely in terms of software and the like, without any apparent reference to the human side of information. And it doesn’t exactly off all that well, either:

We have a pretty strong and broad curriculum, the students get several different programming classes, good grounding in network technology and database technology and software.

Which is not exactly what those of us in whole-enterprise architecture would be likely to regard as a ‘broad curriculum’. At first glance, it can seem so much “Oh no, not again…” that I wasn’t much surprised when a colleague complained at me for reTweeting it in such glowing terms.

Yet there are several points that make it stand out from the crowd. Keppleman continues the above with these comments (with the interviewer’s question in italic):

But we also try to bring in the big picture, how it really fits together. Though most of our students take entry-level jobs working on a particular project or part of a system, whether it’s infrastructure or software or some combination, we want them to leave with some sense that the things they work on are actually part of a much larger enterprise. That piece they are working on needs to be not just a good piece, but a great piece that creates value for the whole.

That sounds like a sales pitch for enterprise architecture.

Yes, and in my career it came to me backwards, too. My original focus was software development and obviously the importance of getting the requirements right. Well, it turns out that to have the requirements right, you need what you are working on in the context of the whole because otherwise you might build a great system but it doesn’t create value. It might be adding redundancy or be the 73rd system to connect 72 other systems. Even if those other 72 systems are part of stovepiped business units and are perfectly aligned with them and serve their needs, as a whole the enterprise is wasting a ton of money and a ton of resources and talent. That experience is what brought me to the enterprise architecture space.

The way I read that is that whatever you’re doing in software or whatever, there’s no point in doing it if it doesn’t support the overall big-picture. Whatever we’re doing, it’s always part of the whole – so we have to be aware of the whole, at all times. Hence the need for enterprise-architecture – which, as can be seen from above, has to be a real ‘architecture of the enterprise’.

In many people’s view of ‘enterprise’-architecture, IT presents itself as the centre of the business-world, the one undisputed core around which everything else revolves. ‘The business’, if mentioned at all, is described solely in terms of ‘anything not-IT that might affect IT’. (If you don’t believe me, go ask anyone not from IT whether TOGAF’s so-called ‘Business Architecture’ makes any sense to them in business terms…) That’s IT-centrism, and it’s a really serious problem in current enterprise-architecture.

But the article above, and the overall mood of the piece, is not IT-centric.

Sure, it’s unashamedly IT-oriented – no doubt about that. Dr Keppleman’s unit is nominally part of a business-school, but as he says, “most of our students take entry-level jobs working on a particular project or part of a system… infrastructure or software or some combination”.  (There’s a mild mis-labelling there, perhaps – it’s not what many of us would think of as ‘business’ – but that’s about the worst that I can see of it.) It is what it is: it’s just IT – and it doesn’t really claim to be anything else.

And yet it does maintain a broader awareness beyond itself. It’s clear that IT is seen as an important role, yet also that it’s just one part amongst many within that greater whole:

“…help us change how we work together and communicate within organizations to be more integrated, more holistic”.

I’ll admit that I really don’t like IT-centrism: it’s been the bane of the EA industry for far too many years. But I’m definitely not ‘against IT’, as some people have portrayed me to be. In a true ‘architecture of the enterprise’, everything matters, in depth as well as in breadth: so I’m very happy to see a piece that’s as IT-oriented as this, and yet does also know how to play its part within them whole.

IT-oriented is not the same as IT-centric.

This one is a pick-up from a Tweet by Bert van Lamoen:

• 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!

Who or what is ‘I’? How does our experience of ‘I’ change as we interact with our world?

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.

Who or what is ‘I’? How do others recognise that ‘I’? How does that ‘I’ express itself? – with what voice does that ‘I’ speak? And how do others recognise that voice?

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?

This was such a good question from Paul Beckford, in one of his comments on the previous post, that I thought it was worthwhile bringing it out into more accessible form here:

“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?

Seems that that Twitter-conversation about principles and decision-making just keeps on rollin’ on. Stijn Viaene kicked the ball rolling again with the following Tweet:

• 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?

Not quite sure where this one started: probably from this Tweet a few days back by Anna Mar (@simplicableanna):

• 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.

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.]

Read more…

How is it that what we actually do in the heat of the action can differ so much from the intentions and decisions we set beforehand? How can we bring them into better alignment, to ’keep to the plan’? And how does this affect 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, 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?

How is it that what we actually do in the heat of the action can differ so much from the intentions and decisions we set beforehand? How can we bring them into better alignment, to ’keep to the plan’? And how does this affect our enterprise-architectures?

This is Part 2 of this exploration: the first part is in the post ‘Decision-making – linking intent and action [1]‘. (Once again, please note that this is ‘work-in-progress’, so expect rough-edges and, uh, partly-baked ideas in various places?)

What we ended up with the previous post is that we what we do want is strong ‘horizontal’ connections across the modalities at the same time-distance to action, and strong ‘vertical’ connections across the time-scales at the same modality:

What we usually don’t want – unless intentionally, and with considerable extra care – is ‘diagonal’ connections across both timescale and modality in the same link:

The key point for architecture is that at the moment of action, no-one has time to think. Hence everything that we build in the architecture to support real-time action also needs to support the right balance between rules and freeform, belief and faith, in line with what happens in the real-world context.

It needs to ensure that we have the right sets of rules for action when rules do apply, and the right experience such that the fallback into faith is as effective as possible whenever the rules don’t apply.

What this implies is that, within the architecture, we’ll need to include:

• services to support each sensemaking/decision-making ‘domain’ within the frame
• services to support the ‘vertical’ and ‘horizontal’ paths within the frame
• governance (and perhaps also services) to dissuade following ‘diagonal’ paths within the frame

It also implies the need for a radical rethink of ‘command and control’ as a management-metaphor, which is where we finished in the previous post. What we’ll turn to here is the other items in that list immediately above.

Before we start, though, one important point to note: all of this is recursive. For sanity’s sake, I’ll need to keep things as Simple as possible here, using bullet-point lists and the like: but in reality all of it is also Complicated, Ambiguous and None-of-the-above – and each of those aspects likewise has components that are simple, not-so-simple and so on. It’s clear-cut and simple, and it’s blurry and messy – all of it recursive, ‘self-similar’ and different, all at the same time. Which gets more than a bit complicated or complex or even chaotic if we try to describe it all in one go…

So for now I’ll take the easy way out: I’ll aim for just a brief-as-I-can-make-it summary, and go into more detail where necessary in later posts. Or you can ask for clarification in comments here: it’s up to you. Point is that, of necessity, this is only scratching the surface: I’m well aware that it ain’t as Simple as I may make it seem, and I’ll trust that you’re aware of that too.

On services to support each domain:

For this section we’ll explore both sensemaking (left) and decision-making (right) together:

In both cases, the domains here split into two distinct sets, ‘horizontally’ either side of the Inverse Einstein test:

• on the left-side (‘order‘), our sensemaking and decision-making tactics (Simple / Complicated, Belief / Assertion) assume that things are predictable – and hence that doing the same thing should lead to the same result
• on the right-side (‘unorder‘), our sensemaking and decision-making tactics (Ambiguous / Not-known, Use / Faith) assume that things may not be predictable – and hence that doing the same thing may lead to different results, or achieving the same results may require doing different things

The vertical distinctions between the domains are often rather more subtle, but it’s crucial that our architecture does provide support right down to the exact moment of action. We need to make a point of this, because there’s an all too common tendency to assume that what works well distant-from-action – Complicated analysis and Complex experimentation, for example – will also work well at the point of action. Yet as the old joke warns us:

In theory there’s no difference between theory and practice. In practice, there is.

‘Distant-from-action’ and real-time action are related, yet qualitatively different, in much the same way as Newtonian physics differs from quantum-physics. Hence these pairs of domains in the ‘vertical’ dimension as well.

So: order-domains:

What support do you have for Simple sensemaking: ordered, ‘controlled’, at real-time? What kinds of sensemaking are needed within the work at or close to the exact moment of action?

• examples: checklists, comparison-charts, mechanical sensors, real-time signals

What support do you have for Complicated sensemaking: ordered, ‘controlled’, predictable, but some distance away from real-time – either before the event as preparation, or after it, to make sense of what happened? What different types of support do you need for different ‘distances’ from real-time, from seconds to minutes to hours to days to months to years to decades and beyond?

• examples: analytics, dashboards, computational filters, aggregation

Going back the other way, from sensemaking to decision-making:

What support do you have for Assertion-based decision-making: decisions that assume the existence of order, ‘control’, predictability, yet also are some distance from – usually prior to – the moment of action? What different types of support are needed over the different timescales that we might describe as strategic, tactical and operational?

• examples: algorithms, hard-systems theory, computation or business-rules IT-systems

What support do you have for Belief-based decision-making: real-time decisions based on certainty, on rules, on assumed predictability? In what ways does this decision-making differ when there’s no time to think, no separation between decision and action?

• examples: rule-sets, rote-learning, step-by-step checklists and work-instructions, physical machines, real-time IT

And: unorder-domains:

What support do you have for Ambiguous sensemaking-contexts: some distance from the action, yet still known-uncertain? What different types of support do you need before and after action, and for different ‘distances’ from real-time?

• examples: experimentation, pattern-matching, statistics, trend-analysis, futures techniques, crowdsourcing

What support do you have for None-of-the-above sensemaking-contexts: right at the moment of action, yet inherently uncertain in some or all aspects? What kinds of sensemaking need to take place here?

• examples: listening, ‘flow‘, managing panic, social structures for ‘safe to fail’

(Note that most of that last set of examples would address not so much the sensemaking itself, but providing appropriate conditions for real-time sensemaking in inherent-uncertainty.)

From sensemaking to decision-making:

What support do you have for Use-based decision-making: decisions that are some distance from the action, yet do not assume certainty or predictability? What different types of support are needed over the various different timescales of distance-from-action?

• examples: patterns, guidelines and values, soft-systems theory, prioritisation, probability and necessity (modal-logic), social methods (from meetings to voting-systems etc)

What support do you have for Faith-based decision-making: decisions that must be made in the heat of the action in the midst of inherent-uncertainty?

• examples: principles (i.e. actionable values), skills and experience, context-design to maximise safe-fail or ‘graceful failure’, trust in ‘that which is greater than self’

(That last item is by far the hardest to describe, but it’s a key reason why I use the term ‘Faith’ here. I suppose this might perhaps be a kind of ‘hive-mind’ effect, but the point is that decisions here will often carry a feeling of ‘it was the right thing to do’, an ‘intuitive’ decision that aligns with a broader collective-purpose without conscious knowledge or certainty of how it does so. Deep familiarity with shared principles and values is a known key driver and anchor for this type of decision-alignment – hence their importance as and at the core of an enterprise-architecture.)

Review those lists above: which of those items would you currently include in your enterprise-architecture or process-architecture? Most conventional architectures will describe only the left-side (‘order’) items – yet support for all of these forms of support will need to be in place for the enterprise and its architecture to work well. Note any gaps in the architecture, and, even more important, gaps in support; and then move on.

In the next part of this series we’ll explore the architecture of how we link all these domains together. Any questions for now, though? Over to you, anyway.