Tom Graves / Tetradian

In the previous articles about context-space mapping with the Enterprise Canvas, we looked at the topmost layer, the extended-enterprise and enterprise-descriptor or vision; then the next layer down, summarising all the player in the enterprise ecosystem; and took a first high-level look at the organisation’s business model with an exploration of value-proposition and business-relationships. All of that was moving ‘top-down’ through the enterprise, so we took a brief detour to see how the same principles can be used for ‘bottom-up’ strategic review, where a re-think of existing technology can lead to a new strategy and even to a new enterprise.

We now do another sideways move, to explore how we might use a modified version of the classic Zachman framework to assess the content and activities of each entity (or service) in scope.

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So far in this series we’ve explored the key concept of the extended-enterprise, used that to summarise the ecosystem in which the organisation operates, and started to model the organisation’s value-proposition and business-relationships.

Up until this point we’ve been working top-down, starting from the most abstract layer, the ‘extended-enterprise’. But we do need to to remember that there’s no reason why we have to work only in this direction, and often many reasons why we should make use of the more freeform approach that context-space mapping will allow. And in the usual serendipitous way – via an article in IndustryWeek, ‘Assessing Product Innovation Assets: What’s in your attic?‘ – we now have a useful reminder that the vision and strategy for an organisation may also be reconstructed bottom-up.

Low-cost innovation doesn’t have to be boring or incremental. Sometimes true innovation is as easy (and inexpensive) as evaluating the technologies and capabilities you currently have and expanding them to a new industry or customer base. It is a particularly powerful product innovation strategy during an economic downturn, yet too few companies today are taking advantage of it.

[An] important message for business leaders: “Use something you already own to generate income in a whole new way.” Truly innovative and resourceful manufacturers can embrace this message by reevaluating their existing assets, intellectual property, and product lines to develop completely new streams of revenue with little investment. The assets are already in their “corporate attics.” All a company has to do is unlock the revenue-generating power of those assets.

So let’s use the examples from that article – and a couple of others – to see how this works, in terms of context-space mapping and the Enterprise Canvas.

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So far in this series we’ve explored enterprise-vision (Enterprise Canvas row-0) and high-level business-context (row-1) in a fairly straightforward way. It’s been much the same as any other conventional ‘top-down’ strategy-development, except that we haven’t really mentioned our own organisation at all as yet. (That’s coming shortly. )

A few important points have come up in the comments to those two articles, though, which are worth reiterating here before we move on.

One is to remember why we’re doing all of this. It’s not about abstract ‘blue-sky’ thinking: it’s about building a stable platform for organisational change. In enterprise-architecture, this needs to be a platform in which all of the other architectures – business-architecture, process-architecture, skills-architecture, values-architecture, security-architecture and, oh yes, all the IT-architectures too – can all interweave and interlink and intermesh into a single unified, dynamic whole. But although we talk a lot about the extended-enterprise here – especially in these ‘higher’ layers – this isn’t actually for anyone else at all: unless someone seriously-senior decides otherwise, all of this is solely for our own organisation (or client, if we’re doing this work as external-consultants). Working this way, whatever we develop is always in the context of this broader extended-enterprise: but our own organisation (or client) becomes more and more the centre of our attention as we move down the layers. That transition of emphasis starts to happen here. In short:

In enterprise-architecture, we create an architecture about an enterprise, but for an organisation.

It’s really important to remember that point – not least because it’s the organisation, not the extended-enterprise, that’s paying our bills!

Another point that came up in the comments is that the usual nine-cell structure of the Enterprise Canvas can be a bit misleading in these upper levels. The nine-cell structure is really a kind of functional-decomposition – who’s handling what interfaces, and why. But functional-decomposition assumes or describes specific interfaces and relationships – and we haven’t even got that far yet. In row-0 and row-1 we only deal with each entity as a whole, without any internal subdivision into cells. It’s only here, in row-2, that we start to introduce the idea of relationships and roles between entities, which eventually leads us to relationships and roles within entities, which leads us in turn to that nine-cell structure. If you try to use the nine-cell structure in rows 0 or 1, or in most of the work in row-2, you may have missed the point somewhere: at those levels, it’s only about each entity as a whole.

And finally, I would hope that by now you’ll have realised that this can be a lot harder to do than it might seem at first glance. It’s so easy to fall back to organisation-centric habits, where the organisation is placed as the sole centre of everything. The blunt fact is that it isn’t that ‘sole centre’ at all: in fact, the organisation only has a reason to exist if it’s placed within the context of its extended-enterprise. If we don’t understand that broader context, we would have nothing to guide us when that context changes – which, these days, can happen on a literally moment-by-moment basis. One of the keys here is that the description of that enterprise is literally emotive – it drives change. So although a lot of thinking and analysis will be needed here, ultimately it’s not a rational matter – it’s about what feels ‘right’, about identifying what is valued. This is especially true of the vision-descriptor: we need to keep exploring that context-space until we hit upon a phrase that can engender emotions and commitment that are literally strong enough to get people out of bed in the morning.

Anyway, time to move on: time to start looking at the business of the enterprise, and of the organisation itself. To summarise where we’ve gotten to so far with this example, we’d established a row-0 ‘Enterprise’:

We then started a Zachman-style row-1 ‘Context’ with a conventional market-based view of our enterprise, with our own organisation as its centre:

Which didn’t show us many options. But as we started to explore what that enterprise-vision meant in practice, and what kinds of stakeholders would be engaged in that vision, we realised that the actual enterprise was much broader than our current market:

Which should create many more strategic opportunities than we were able to see before. To make this work, though, we first need look more closely at the meaning of a common business-term: value-proposition.

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In the previous post in this series we did a quick review of context-space mapping and the Enterprise Canvas, and set out this into practice with a real-world example that, for me, is very close to home: rethinking my own enterprise-architecture consultancy business.

We started at the top layer, aiming to identify the core ‘enterprise’ within which I work. From exploring my own professional history, it became clear that the main focus of my work is about enterprises themselves, of any size, and always with the aim of enhancing enterprise effectiveness. From that, we ended up with an initial enterprise-descriptor – or ‘vision’ – of “creating more-effective enterprises”.

Notice, though, what’s happened right here, in that paragraph above. In trying to summarise that initial rather clunky vision-statement – ‘creating more-effective enterprises’ – we’ve accidentally hit upon a better one: ‘enhancing enterprise effectiveness’. It reads better, has a smoother flow to it, a poetry almost. It does describe what I’m passionate about – and finding that passion is central to the success of an enterprise. And ‘enhancing’ is actually a much more accurate term for what I do: I don’t often create enterprises in the sense that, say, an entrepreneur would do, but I do work to enhance their effectiveness. So note that this process is typical of what happens in context-space mapping: for example, we arrive at a ‘solution’ – in this case, the initial ‘vision’-descriptor – which itself quietly dropped us back into the ‘sensemaking’ space. So the trick here is to notice what’s happening, notice these little serendipitous events – and learning how to do that is a real skill in itself. To quote one of my favourite books, William Beveridge’s The Art of Scientific Investigation:

If these discoveries were made by chance or accident alone, as many discoveries of this type would be made by any inexperienced scientist starting to dabble in research as by Bernard or Pasteur. The truth of the matter lies in Pasteur’s famous saying, “In the field of observation, chance favours only the prepared mind.” It is the interpretation of the chance event which counts. The role of chance is merely to provide the opportunity and the scientist has to recognise it and grasp it.

Anyway, that’s what we now have as the ‘row-0′ or ‘Enterprise’ layer for the Enterprise Canvas model of my own enterprise:

Now what? Very pretty and all that, but what do we do with this?

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Over on the LinkedIn Business Architecture list, my colleagues Pat Ferdinandi, JD Beckingham and Ron Segal have all helped a lot in challenging me on the Enterprise Canvas concepts. Pat in particular has been has been pushing hard for some more concrete examples of how it all works in practice.

On the other side, I haven’t really posted anything here as yet on the ‘final’ version of the context-space mapping methodology. There are a few scattered posts from a few months back, but the main description is in the chapter ‘Day 8: Putting it into practice’, in my most recent book, Everyday Enterprise-Architecture [at present you can still download the complete PDF e-book via that link].

So it seems worthwhile to develop a worked-example to show how all of these tools and techniques fit together in real-world use.

And for me, right now, the obvious example to choose would be my own work and business. I’m a futurist and maker of conceptual tools, working mainly with the arcane abstractions of enterprise-architectures: none of those attributes and emphases are exactly conducive to fame and fortune… It’s true I do get by well enough at present, yet I would like my work to be better known and more commonly used, and – no surprises here – it’d be good if it could bring in a better income, too. So how can I make that happen? What do I need to do that’s different from what I’m doing now? What do I need to change in the architecture of my own enterprise?

And I’m not alone in this: I know a lot of enterprise-architects and others – especially those of us working in the very new field of whole-of-enterprise architectures – who are in much the same boat at present. In our own quiet ways, all of us are wrestling with much the same questions:

• What business am I in? – really?
• Who else would be interested in what I’m working on? What value do I add right now? – if any?
• Where could I add value? In what contexts?
• With whom would I need to work with in on this? Who would be my prospective partners, clients and other business-relationships?
• For whom could I most add value? Who would pay for it? – and why would they pay for it?
• How can I describe that value? How could I prove that value?
• How would I deliver that value? How would I prove that I’ve delivered it?
• How much could, would or should I charge for this?

And so on: all pretty fundamental questions, really – especially in business. Sounds like a good candidate for some serious exploration – which is where context-space mapping and the Enterprise Canvas come into the picture.

This’ll probably take several posts, but let’s get started.

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Reading James Taylor’s recent piece “Business rules are king“, pretty much every one of my enterprise-architecture alarm-bells went off.

Yes, it’s a good article – recommended reading. And I would strongly agree with its implication that there’s a real and urgent need for discipline around business-rules. But the reason for the alarm-bells is that it’s promoting business-rules as ‘the answer’ – and for the most part IT-based ‘business-rules engines’ at that.

Which us places straight back in Taylorist territory, along with all those other classic IT-driven business failures such business-process re-engineering. Not a good idea…

The reasons why it’s not a good idea are three-fold:

• placing all the business-rules into an automated system will lead to a ‘fit and forget’ attitude unless there is a very strong emphasis on rule-maintenance – one of many ‘human factors’ that were forgotten about in BPR’s rush to ‘IT-ise’ all business processes
• identification and codification of business-rules assumes that the rules that can be derived from the people who run the existing processes are sufficient, invariant, accurate and complete – which, as early-generation knowledge-management also discovered, they rarely are…
• the viability of using automation for decision-making is dependent on the context – a fact of which frighteningly few IT-system designers seem to be aware

There seems to be a view that everything can and must be reduced to simple rules, following a cart-before-horse thinking that everything should be done by IT, and simple rules are what IT handles best. In other words, dangerously back-to-front. It’s bad enough trying to get anything useful out of IT for decision-support; but using IT for all decision-making – which is the ‘nirvana’ that the article would evidently prefer – is likely to be lethal. And I don’t quite know what we as enterprise-architects can do to prevent this headlong rush into repeating the exact same mistakes as in BPR and the rest – all that’s different this time is that it’s more explicitly coming from the ‘rules’ part of the process, rather than process-implementation overall.

This is clear if we look at it from the perspective of context-space mapping:

The point is that there’s a spectrum of abstraction of rules: principles sit at the low-abstraction end of this spectrum, rules sit at the high-abstraction end – in fact a conventional ‘rule’ is actually an extreme abstraction of a principle that applies to a specific context. If we try to use the wrong level of abstraction, especially in the wrong context or wrong type of context, we are all but guaranteed to hit serious trouble. And I see little to no awareness of that fact in most of the current literature on business-rules: instead, there seems to be an assumption that just about everything can be reduced to simple binary rules that can be implemented by simple IT, because that’s what we want to happen. In other words, the entire approach seems driven by little more than wishful thinking – which again is not a good idea…

IT-systems and simple business-rules work well together: both operate on a binary true/false logic, and both will enable high-speed binary-logic decision-trees – in other words, over on the lower right-hand side of the usual Cynefin-derived context-space base-map.

Most IT-based analytics – over on the upper-right of the base-map – work on the same binary logic as the simple systems, but introduce the ability to handle more and more layers of complication. The catch is that each layer of analysis takes a finite amount of time – which takes it further away from the ‘Now!‘ demanded by real-time decision-making. And the only real result of increased computing-power has been to increase the levels of complication in the analytics, sometimes beyond anyone’s ability to understand it – as was the case with the software systems used in many of the risk-calculation models that drove the current financial crash.

IT-systems are still not good at handling non-binary modal-logics – “the logic of probability, possibility and necessity”, such as expressed in the MoSCoW set of requirements-priorities of must, should, could and can wait. Humans are very good at modal-logic; IT isn’t. James Taylor’s article refers to pattern-based decision-making, which places it somewhat on the upper left of the base-map – but note again that each pattern-match must always take a finite amount of time, and it does not fit well with the underlying binary-logic of current IT-systems. Using IT as decision-support for human decision-making is generally okay, but the more that IT is involved, the higher the risk of what Dave Snowden describes as ‘pattern-entrainment’ – in other words, premature selection of a pattern, trying to force-fit a pattern to the context rather than ‘listening’ to the context itself. Current IT is getting much better at near-real-time pattern-matching, such as face-recognition or smile-recognition on most present-day digital cameras. Yet as anyone who’s used such systems would know, they’re nowhere near accurate enough to decide when a picture is actually any good – and sometimes we don’t want a smile in the picture. Much the same applies in business: using automated pattern-matching is great for decision-support, but extremely dangerous for decision-making.

And no IT-system is likely to be much good at dealing with real-time chaos, ‘the new’, where no possible pattern exists because it is new – but again, real people can handle decision-making in such contexts via skills and principles. In those contexts, there are no rules – and yet business-rule proponents seem to promote the delusion that their ‘business-rule engines’ can handle everything.

So I’m wary: very wary. Before letting any of such systems loose on any real-world context, I would want to make very sure that they’ve done the appropriate context-space mapping, and matched the decision-making methods to the respective contexts. But I don’t see much evidence of that: what I see instead is way too much wishful-thinking, and an almost desperate desire on both the business-side and the IT-side to try to force the world to fit their respective delusory dreams of ‘order’ and ‘control’. Oh well… Guess we have to wait and let them fail yet again, even more expensively, and then set out to tidy up the mess? – though I do worry that we’re getting close to the point where we’re no longer able to afford such expensive mistakes, in any sense of the word…

(This series of posts explores a concept of ‘context-space’ which in part draws on a categorisation immortalised in a certain well-known diagram. It must be emphasised that this is not about ’That Welsh Framework‘ (aka twf) which that diagram illustrates: for details on twf, please contact this company. I apologise for these absurd aliases, but regrettably their necessity has been forced upon us by others.)

We seem to be iterating steadily towards a full description of what I’ve termed context-space mapping (as a more permanent name than the temporary label ‘tinc‘). For example, there’s been some very useful discussion on the previous post, especially by enterprise-architects Paul Jansen and Sally Bean. Paul Jansen followed this up with another Tweet:

@tetradian May the ‘chaotic approach’ be the key to #tinc? http://bit.ly/amJa1o

In fact this leads to what is probably the fundamental difference between twf and context-space mapping (aka tinc): the role of the Chaotic domain. This particularly applies in terms of the respective views of repeatability within the context.

In the hope of preventing yet more repercussions, I won’t say anything about twf‘s approach at this point, other than to express my opinion that, in the terms of context-space mapping, its focus is primarily on the Complex domain, which in turn leads to an emphasis on contexts that are ‘partly-repeatable’ in highly complex ‘unordered’ ways.

Context-space mapping, however, needs to cover all repeatability-types. As twf‘s proponent indicates, the Simple domain of presumed-repeatability is covered by Taylorism et al.; the Complicated domain of analysed-repeatability by hard-Systems Thinking and the like; and the Complex by twf and so on. But there’s so far been little or nothing to cover the Chaotic domain of ‘barely-repeatable’ events and processes. So in practice it’s likely that that’s where whole-of-scope techniques such as context-space mapping will have the most impact.

The central theme in the Chaotic domain of practice is low- to zero-repeatability: some part(s) of the practice cannot be repeated, either because the conditions have changed – including the awareness and experience of the person doing the work. Conventional ‘scientific-analysis’ approaches (Complicated-domain) rely on repeatability, so they’re actually not all that much use in the Chaotic components of any real-world task – in fact will often be misleading because they provide an illusion of predictability. In a way, the same is true of many Complex-domain techniques: they give us a much more reliable picture of an overall uncertain context, but we can’t reliably apply that in reverse to tell us what to do for a specific ‘market-of-one’, such as a specific medical diagnosis.

Ability to engage appropriately in the Chaotic-domain in this sense is almost a definition of skill. It’s also a key component of almost all knowledge-work – which is why this concern is coming much more to the fore, as knowledge-work becomes an increasingly important part of the overall economy.

At the business-process level, one of the key figures is Sigurd Rinde, whose concept of ‘barely-repeatable processes’ is the focus for his Thingamy business-process-execution software. The whole point of Thingamy is that the processes themselves are made up as they go along, by the people doing the work, expressing and applying their expertise. Underneath this, however, is a consistent Simple structure that records every decision, every artefact, every transfer of responsibility – which makes it possible to create any required reports from the process, including conventional statistical analysis. The result is nicely summarised on Sig’s other website, 30megs.com – so-called from his tag-line “Here’s 30 Megs. Now go run Germany”, which in principle is entirely feasible with this kind of decision-support/decision-tracking software. Sig is not alone in this, of course – for example, Stafford Beer developed something similar that in effect ran the entire economy of Chile for a while, way back in the early 1970s – but Thingamy is probably the best example of a software package available today that is designed for true Chaotic-domain processes.

Context-space mapping is part of what needs to happen before we settle on any technique or tool such as Thingamy. It’s about mapping the options available to us, and the decisions that we make within ‘solution-space’, as part of an overall process of sensemaking in order to arrive at appropriate actions for the context. One of the key points in this is an awareness that we are part of the context, part of the ‘solution’: in the classic Chaotic-domain sense, there is a boundary, and there is no boundary, always in the same moment.

We always start from ‘reality’ – that which in twf is termed the ‘disorder’ domain. (Everything does in fact take place within that domain: any purported subdivisions – such as Simple, Chaotic and suchlike – are sensemaking-abstractions that we place onto that domain, but are not actually ‘real’ as such.) From there, we would move into some kind of recursive OODA loop (Observe/Orient/Decide/Act), where sensemaking itself forms one or more of the earliest iterations. In those terms, context-space mapping would typically proceed as follows:

• Observe: What is ‘the context’ here?
• Orient: How do I make sense of what I’m seeing?
  1. What parts of the context appear to be unique (Chaotic), unordered or ‘wicked-problem’ (Complex), complicated but repeatable (Complicated) or universal (Simple)? Using that categorisation, map out the ‘problem-space’.
  2. Given that categorisation, what cross-maps would be useful for sensemaking?
     Note: There are an infinite number of cross-maps that could be used: some examples shown in this series include:
     • here: repeatability and action-tactics; domains and tetradian asset-dimensions; time versus focus; Jungian domains
     • here: twf tactics and types of practice; timescale versus ‘bindedness’; development of embodied ‘best-practice’
     • here: repeatability and ‘truth’; marketing versus sales; the ‘plan / do / check / act’ cycle
     • here: ISO-9000 quality-model; skill-levels; automated versus manual processes; asset-types; data, information, knowledge, wisdom
     • here: cause/effect relationships; decision-mode, timescale and level of abstraction
     • here: nature of boundaries between domains
     • here: phases of matter
  3. Using the categorisations from the cross-maps, what available tools and techniques are ‘situated’ in what regions of the maps’ ‘solution-space’? What can we learn from this?
• Decide: Given what I have learned from sensemaking, what should be my ‘action-plan’?
  1. Select from the available tools/techniques.
  2. Decide on a plan as to how, why, when, where, by whom, with what, and in what order each of the selected tools or techniques should be used.
• Act:  What am I doing as I am doing, and what do I see as I am doing?
  1. Enact the desired action.
  2. Apply the same overall OODA-loop to the action taken – recursively, where appropriate – for review, further sensemaking, decision and action.
• Repeat as appropriate.

(Some people might suggest that this kind of OODA-loop fits more within a twf-style Complex-domain mode than Chaotic-domain. True, there are important similarities, such as the shared focus on ‘unorder’ versus the Complicated/Simple notion of ‘order’. But the key distinction is that this acts on a single, individual, specific context rather than a Complex-domain collective – and is often also much closer to real-time than most Complex-domain decision-making.)

The above is a start towards how we would use context-space mapping, anyway. I’ll leave it there for now: any constructive comments, ideas and suggestions would be most welcome, as usual – over to you?

Previous posts in this series:

• Complexity, chaos and enterprise-architecture
• More on chaos and Cynefin
• Alternatives to the ‘Cynefin’ term, please?
• Solution-space: beyond Cynefin?
• On meta-methodology
• Using ‘Cynefin-like’ cross-maps
• More ‘Cynefin-like’ cross-maps
• And more ‘Cynefin-like’ cross-maps
• More on meta-methodology
• ‘tinc’ – a Temporary Inconvenience
• Context-space mapping and enterprise-architecture

Related:

• ‘Two Cryptic conversations‘