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…

So: what can we learn if we tackle economics as enterprise-architecture? In other words, as if it was just another exercise in whole-of-enterprise architecture, the same as we would do for any large organisation (such as described in my book ‘Doing Enterprise-Architecture‘)? After all, ‘the economy’ is just another enterprise – it happens to be at a very large scale, but the exact same principles should apply.

(This’ll be another long one, hence I’ll place a ‘Read more…’ link here.)

An enterprise-architecture develops in five distinct maturity-levels, which in turn define five distinct groups of work:

1. What business are we in? – core vision, values, resources, decisions etc
2. Clean up the mess – horizontal optimisation of facilities, capabilities and resources
3. What’s our strategy? – top-down definition and implementation
4. Welcome to the real world – bottom-up constraints and localisation
5. Keeping it clean – ’spiral-out’ to tackle ongoing ‘wicked-problems‘

We can do work from any of those maturity-levels at any time, and sometimes relative-priorities will force us to do so. The point is that each layer depends on those that precede it: we can do ‘later’ work, but the results are unlikely to be viable, especially in the longer term. For example, trying to tackle a clean-up before we have any clear idea of where we’re trying to go – which is what most standard IT-centric ‘enterprise-architectures’ try to do – will result at best in a system that’s well-optimised for, uh, something… And although the ‘wicked-problems’ are what the enterprise’s stakeholders will most want us to tackle, we won’t be able to do so successfully without a ‘palette’ of techniques and tactics that will allow us to iterate towards ‘re-solutions’ – and we create that ‘palette’ by working through each step of the maturity-levels in a disciplined way. (By definition, ‘wicked-problems’ are never ’solved’: the best we can do is to create processes by which they are continually ‘re-solved’.)

Any sane observer would recognise that our present economic models not only don’t work well, but at present are still teetering on the edge of catastrophic collapse. Many people’s response has been to rush out and try to create some kind of ‘alternate currency’; but it should be clear from the above that that’s a level-4 or level-5 tactic that’s being applied without any of the ‘upper’ architectural-levels in place – not a good idea, because all it does is further embed the existing ‘wicked-problems’, and often create new ones as well. So let’s turn this round, to do it properly from an architectural perspective:

• Before we can tackle level-5 wicked-problems, we need a solid grasp of what the real-world looks like – in other words, level-4.
• Before we can tackle level-4 real-world problems, we need a framework of law and the like – level-3 – in which those solutions can take root.
• A level-3 framework operates through institutions – so to apply that framework well, we need to do a level-2 clean-up of those institutions to make them more efficient and effective.
• For that level-2 clean-up to work, we need to have a good idea of where we’re going, and, most importantly, why – in other words, level-1.

So to have any chance of success, we need to go right back to the start: in architectural terms, what is ‘the economy’?

If we do it ‘by the book’ (literally – see pp.44-87 in the sample-ebook [PDF] of ‘Doing EA‘), we split that level-1 work into four distinct parts:

• Step 1: Vision, values, principles and purpose
• Step 2: Enterprise context – including assets and resources
• Step 3: Functions and services
• Step 4: Architecture governance

Vision, values, principles and purpose

The word ‘economy’ literally translates as ‘the management of the household’. In the usual sense of ‘the economy’, the ‘household’ in scope is the entire world; ‘economics’ is thus the management of every aspect of that ‘household’.

An enterprise is a ‘community of commitment’: unlike an organisation, it is held together more by internalised shared-beliefs and values than by externalised rules and regulations. The term ‘enterprise’ therefore fits well with the concept of ‘an economy’: in essence, ‘the economy’ is the expression of the internal operations and external interfaces of ‘the enterprise’ that represents the overall ‘community of commitment’ at a global scale.

The vision is a single unifying theme that links all enterprise stakeholders; this includes stakeholders beyond the nominal enterprise itself (see ‘What is an enterprise?‘ on Slideshare), who in this case would include ourselves, other peoples at other places and times than the present here-and-now, the other animals, plants and other ‘actors’ in the broader ecosystem, and the planet itself as a whole. A suggested vision for this context might be appropriate and sustainable utilisation of the available ecosystem resources, functions and capabilities. (In a business enterprise-architecture we would then derive a sequence of ‘Vision, role, mission, goal‘, but I’ll skip over that for here.)

The values are what link the actors to the vision of the broader enterprise. (For this context it’s simplest to focus on the human actors at first, though Deep Ecologists would insist that we should extend that scope indefinitely.) Typical values here would include such notions as fairness, equitability, long-term sustainability, efficiency, reliability, appropriateness and so on.

The principles are practical expressions of the values: values are more about how we feel, principles more guidance for what we do. In effect, principles are the reference-prototypes for all implementation-rules, regulations and the like, and should always be concrete, actionable and verifiable. In this case, that means that we need explicit principles to enact and verify the economy’s alignment with those core values, such as fairness, equitability, sustainability, etcetera. (Again, I’ll skip over the detail there – yes, it needs to be explored in depth, but not in this quick overview.)

Finally, we do a cross-check to compare this nominal-purpose against the ‘effective-purpose‘ of what we currently have, using Stafford Beer’s acronym POSIWID, ”the purpose of the system is [expressed in] what it does”:

“According to the cybernetician the purpose of a system is what it does. This is a basic dictum. It stands for bald fact, which makes a better starting point in seeking understanding than the familiar attributions of good intention, prejudices about expectations, moral judgment or sheer ignorance of circumstances.”

To be blunt, this is where it all gets seriously scary, because a mere few moments’ thought and observation would show that our present money-based ‘possession-economy’ fails virtually every possible test against the necessary values. It is demonstrably unfair; its natural ‘gravitation’ creates and reinforces all manner of inequities; it is clearly not sustainable; it is frighteningly inefficient (so much so that in order to prop up ‘the economy’ we are urged to be as wasteful as possible); and, increasingly, less and less reliable. The foundational principle of this concept of ‘the economy’ is a notion of ‘personal right of personal possession’ – with ‘corporations’ classed as virtual-persons that are assigned greater ‘rights’ and fewer responsibilities than any ‘natural person’ – and implemented by a standardised form of barter called ‘money’. A brief POSIWID assessment shows just how successful the ‘money-economy’ really is(n’t):

• It only deals with point-to-point transactions, not network-effects – especially at a societal level.
• It’s designed to work with ‘alienable’ physical objects, but now no longer has any actual anchor in the real world – instead, we have literally trillions of supposed ‘money’ in imaginary ‘derivatives’ sloshing around the globe.
• It’s very easy to ‘game’ via artificially-constructed price/value mismatches (such as in ’scarcity economics’).
• The implied ‘gravitation’ structure of money-based capital tends to create ‘winner-takes-all’ accumulations – exacerbating social imbalances, often in the extreme, requiring separate sociopolitical action to try to redress the balance.
• Attempts to link ‘intellectual property’ into the money-system have resulted in a system which purports to match finite ‘alienable’ entities (physical ‘things’) with potentially-infinite ‘non-alienable’ entities (information) – which by definition cannot balance.
• Many organisations – particularly banks – are legally ‘entitled’ to invent money from nowhere, in effect assigning themselves an ever-increasing share of the society’s resources.
• A currency, by definition, relies on trust in the institutions that manage that currency, which in this case is the banks – yet much of that trust has been lost, and at present remains at an all-time low (hence the strong societal interest in options for ‘alternative currencies’).
• There are no built-in mechanisms to manage assignment of resources to those ‘outside’ of the monetary exchange-system (particularly children, parents, elderly, disabled and their carers, but also artists, scientists, thinkers, futurists, ‘creatives’ of any kind) – these stakeholders can only be served by ‘external’ mechanisms such as taxation, grants and benefits (which are clunky and kludge-ridden at best), or by forcing them to do work within the money-economy (which means that their actual needed work can no longer be done).
• There is a very strong tendency towards short-termism.
• There is a very strong tendency to try to force everything into a crude, ludicrously-simplistic ‘double-entry life-keeping’.
• There is a very strong tendency to assume that ‘value’ exists only in monetary terms, as ‘valuations’ of ‘resources’ – hence, for example, a forest supposedly has no value until it is cut down, a mountain has no value until mined for its minerals, and so on.
• There is a very strong tendency to assume that anything which cannot be counted and ‘valued’ in monetary terms either does not matter or does not exist.

In effect, POSIWID tells us that the ‘effective-purpose’ for the system we have at present is to create catastrophic failure of the economy in the medium- to longer-term – and that ‘longer-term’ seems to be taking place right now. The current economic system does not and cannot work in relation to the actual vision, values and principles needed to underpin a functional economy for the overall ‘human enterprise’.  Which is not good news…

In architectural terms, that’s the ‘as-is’; the real vision, values and principles provide the desired fundamentals for any ‘to-be’. To begin to define a ‘roadmap’ from ‘here’ to ‘there’, we next need to identify what we have available to us, what the constraints are, and what we can use – starting with the overall context for the enterprise.

Enterprise context

This section of the architectural analysis has two parts: compliance, constraints and standards, and assets, locations and events.

There are two categories of constraints on the system: physical, and social.

The social constraints and implied standards and compliance are invented, by people, in a myriad of forms. In practice, all of these are negotiable, although there is an evident need to construct frameworks that align well with what is ‘not negotiable’ within human nature. Of these, perhaps the core tension is between the individual versus the collective – in network theory, the node versus the network - in part paralleled by the tension between present versus future and/or past. The usual analogues for these are Darwinian (’selfish’ individual) versus Kropotkin (collective ‘mutual aid’). The current ‘Western’ system of ‘private property’ – ‘personal right of personal possession’ – privileges the individual and the present-time, almost to absurd extremes, against the collective and/or elsewhen.

Most of the physical constraints on the economy are absolute and not negotiable. These include finite limits on resources, finite limits to system recovery, and a variety of system factors known to be capable of spiralling positive-feedback loops leading to catastrophic collapse. However, a POSIWID assessment shows very quickly that the present economic system depends on an assumption that growth and resources are infinite, and that there is no fundamental difference between farming (which can be sustainable) and mining (which by definition cannot). This means that by definition the existing economic architecture is non-viable in the longer-term: the question is not if it will fail, but when, and with what structural and other impacts.

The available assets or ‘resources’ include not just physical ‘things’, but also many other entities such as ideas, social-networks, beauty, art, hope and faith. These can be categorised in terms of (at least) four fundamentally-distinct dimensions:

• physical (‘things’; content): independent-existence; alienable; transferable; often destructively consumed
• conceptual (ideas, information; context): semi-independent existence; non-alienable; transferable; non-destructive consumption
• relational (relationships, connections): existence is between two entities; non-alienable; non-transferable
• aspirational (belief ‘in’ something, faith, drive; purpose): existence is from an entity to a conceptualised ‘Other’; non-alienable; non-transferable

Many (most?) real-world entities combine these dimensions: e.g. book = physical+conceptual; shared narrative-knowledge = conceptual+relational; product-brand = aspirational+physical (and/or conceptual), etc. Some people suggest that, architecturally speaking, money is itself another distinct dimension: but in practice it is best understood as a straightforward composite of conceptual+aspirational – a symbol of a belief.

Because of the fundamental differences between dimensions, a ‘currency’ will typically only work well with one dimension. Trying to use a currency in another dimension than that for which it was designed causes serious problems: famously, “money can’t buy me love” – although it can buy an illusion of ‘love’, which is not the same at all. Monetary currencies fit well with physical (alienable) objects, but do not fit well with non-alienable entities; ‘time’-type currencies do not work well with physical objects, especially manufactured objects that accumulate embedded-time; and so on. All currencies tend to create individual-focussed ‘double-entry life-keeping’, which blocks resource-flows at a societal scale, especially over longer timescales. In architectural terms, a currency is a ’solution’ that tries to force all contexts to fit in with its own severe limitations: as a result, ‘currencies’ as an entire class contribute more to ‘the problem’ of economics than to its solution.

The locations of these assets are worldwide – yet, importantly, scattered very unevenly across the physical globe and in social-space, with considerable impacts on core values and principles such as equitability and efficiency. The ‘gravitation’ of the possession-economy tends to exacerbate these structural problems in many complex ways (which I won’t attempt to describe in detail here).

The key events in the economy include births, deaths and many types of interactions between (and within) the respective actors. Births and, especially, deaths indicate with bald finality of one of the many fundamental flaws in the concept of ‘personal property’: in an all too literal sense, we cannot take it with us when we die. (True, historically speaking, many people have tried to do so, but the only real result has been often-serious damage to the respective economy for the survivors and their descendants.)

Transaction-events in practice only make sense for exchangeable entities (physical and/or conceptual), yet even these operate under fundamentally different constraints:

• physical: zero-sum, often leading to a scarcity-based win/lose transactional model; potentially leads to a ‘tragedy of the commons‘
• conceptual: potentially-infinite, for which a scarcity-based model makes no economic sense, and in which the only transactional options are win/win or lose/lose; potentially leads to an inverse ‘comedy of the commons‘, but if misused may instead lead to a ‘tragedy of the anticommons‘

Relational and aspirational assets cannot be directly exchanged, but may undergo transaction-like events in which they are created, ‘read’, updated or destroyed. For example, a brand-relationship (aspirational-asset) may be created via various means, is ‘read’ during each transaction by that person in relation to the branded entity, may be transferred to another brand with great ease by the person but only with great care by the brand-holder (if any), and although the ‘relationship’ is one-sided (from the person to the conceptualised brand), it will be destroyed if either party abandons it.

One useful frame to demonstrate many transaction-variants is the market model. To extend the Cluetrain Manifesto:

• markets are transactions – often but not solely of physical ‘goods’
• markets are conversations
• markets are relationships
• markets are shared-purpose

Although these combine in many different ways, the most typical structure is the market sequence:

reputation -> trust -> respect -> attention -> transaction [ -> barter/money -> individualised 'profit' ]

The main part of the sequence occurs in all economic models, both ‘responsibility-based’ (collective-focus) and ‘possession-based’ (individual-focus).  The section within [..] occurs only in the ‘possession-economy’ add-on, which, in network terms, is essentially a parasitic overlay on a functional responsibility-based economy. (In principle the possession-economy provides governance for management of resources, but use of a non-finite ‘currency’ to manage finite resources makes no sense: the only possible result is ‘inflation’, and increasing assignment of finite resources to those who have the purported ‘right’ to extend – i.e. invent, from nowhere – additional ‘currency’.) The individual-oriented concept of personal ‘profit’ masks and ignores network-effects that frequently lead to huge whole-of-system losses. In practice, the possession-economy overlay contributes almost nothing to the economy, yet creates enormous inequities, instabilities and longer-term risks – and hence, in terms of the actual requirements, is neither useful nor desirable. It seems likely that the only viable option is to strip away the ‘possession-economy’ overlay, and (re-)construct a functional responsibility-based economic model.

Functions and services

The functions and services of ‘the economy’ consist of everything that anyone does, did or will do, in any form, at any time, anywhere in the world – so I won’t attempt to list them all here. The very simplest summary is that we dig things out of the ground, do various things to those things, and put them back in the ground again. (Arguably that includes people too. )

A function is a place within the economy where something can change, acting on resources in accordance with specific rules. (Think of ‘function’ in the mathematical sense: a=func(x,y).)

A capability provides the ability to do something to something. It may be implemented by natural processes, or, in the human economy, by a real person, a machine, and/or (for conceptual-assets) some kind of ‘information technology’. Machines are good at dealing with certainty, but not good at dealing with uncertainty; it’s the other way round for real people. (These distinctions aren’t particularly relevant in a high-level enterprise-architecture, but become more and more important as we get closer to where real work happens.)

A service links together a function and a capability to enable real work. (On its own, a function can do nothing; and on its own, a capability literally has no function.) In a service-oriented architecture, each service presents an interface with its own protocols and service-level agreements, and these services are chained together in some form into processes; in a real-world economy these tend to be a lot more fluid and implicit than in an IT-services architecture, but the principles involved are essentially the same.

Best leave this part of the ‘economy architecture’ at that, but there’s more detail in the Doing EA book (pp.65-76 of the ebook [PDF]) if you want it.

Architecture governance

Viewing the overall economy as an enterprise-architecture, it’s clear that there is almost no integrated governance for the economy as a whole – which immediately implies a ‘natural’ tendency towards fragmentation and disintegration.

Management of the global ‘household’ is split between ‘economics’, which in essence deals solely with money-based transactions; ‘political economy’, which deals with some aspects of the ‘game-rules’ for the money-economy; ‘politics’, which deals with a fairly random subset of game-rules for the non-money parts of the economy; and general sociocultural background, which attempts to re-integrate the resultant mess.

The continued failure of ‘economics’ to deal with just about anything other than point-to-point transactions means that whole-of-system costs are very poorly understood. Frequently, money-transactions themselves introduce huge unacknowledged whole-of-system costs; and as Gil Friend explains, the decisions we make in the delusion that petrol costs only US$3 a gallon are very different from those we would make once we recognise that the real cost at present is more like US$15-20 a gallon and rising.

So there is an urgent need for something – some social institution – to begin to pull all of these threads together. As to what that could be, given the current socio-political shambles, is just about anyone’s guess: over to you for suggestions on that?

• Social Capital is not the same as Whuffie
• What could the future of money look like?

The first thread started with a very necessary attempt to distinguish between social-capital and reputation-based ‘currencies’ such as Cory Doctorow’s imaginary ‘Whuffie‘ (as described in his sci-fi novel “Down and Out in the Magic Kingdom” – the ‘magic kingdom’ being Disneyland, of course ). The key distinction that Venessa drew – and I think she’s right – is that social-capital is collective, a ‘network effect’ of the social context, whereas reputation is an attribute within the frame of that social-network, typically attached or attributed to the individual: in other words, they’re not the same, and should definitely not be treated as being the same.

This lead to the second thread, about ‘the future of money’, because much of the discussion in the ‘Whuffie’ thread was about the supposed need for some kind of ‘alternative currency’. (Clearly some people in the thread had hoped that ‘Whuffie’ would be it, but despite the efforts of well-meant initiatives such as The Whuffie Bank, it became evident quite quickly that it wouldn’t and couldn’t work in a ‘currency-like’ way.) There was – and at present, still is – a lot of discussion about various ‘currency-like’ proposals, such as TimeBanks, ITEX cashless payment, ‘Quids’ alternate-currency, and so on.

But what I found immensely frustrating was that almost none of them were thinking in true economic terms – and I wasn’t very popular for pointing out this unfortunate fact. Instead of enquiring what an economy is, what it needs to do, what purpose it serves, and so on – what would seem to be essential first-principles concerns about the context – they’d all assumed automatically, without question, that some kind of currency was ‘the answer’, and hence rushed off to create it. In other words, exactly the same mistake as far too many IT-folks: “here’s the solution – how can we force your problem to fit it?”

Ready? Fire!!! … aim…?

oops…

Yeah… really frustrating…

No-one with any sense would doubt that there are serious problems with the present ‘money-economy’ – not so much ’serious problems’ as ‘close to catastrophic failure’, in fact. Everyone in that conversation recognised this – which is why they were pushing so hard for alternatives. But the catch was that none of the alternatives actually resolved the core reasons why a money-economy won’t work; most of the proposed ’solutions’ not only replicated those problems, but actually made some of them worse. What was so frustrating was that in each case it took no more than a couple of minutes’ analysis not only to show that it wouldn’t work, but why it wouldn’t work. Yet no-one, it seemed, wanted to hear this: instead, off they want, charging off down their respective blind-alleys in the blind certainty that they’d found ‘the solution’.

What’s wrong with money, then? Short answer is: a lot. To give just a few examples:

• It only deals with point-to-point transactions, not network-effects – especially at a societal level.
• It’s designed to work with ‘alienable’ physical objects, but now no longer has any actual anchor in the real world – instead, we have literally trillions of supposed ‘money’ in imaginary ‘derivatives’ sloshing around the globe.
• It’s very easy to ‘game’ via artificially-constructed price/value mismatches.
• The implied ‘gravitation’ structure of money-based capital means that it tends to create ‘winner-takes-all’ accumulations – exacerbating social imbalances, often in the extreme, requiring separate action to try to redress the balance.
• Attempts to link ‘intellectual property’ into the money-system have resulted in a system which purports to match finite ‘alienable’ entities (physical ‘things’) with potentially-infinite ‘non-alienable’ entities (information) – which by definition cannot balance.
• Many organisations – particularly banks – are legally ‘entitled’ to invent money from nowhere, in effect assigning themselves an ever-increasing share of the society’s resources.
• A currency, by definition, relies on trust in the institutions that manage that currency, which in this case is the banks – yet much of that trust has been lost, and at present remains at an all-time low (hence the strong societal interest in options for ‘alternative currencies’).
• There are no built-in mechanisms to manage assignment of resources to those ‘outside’ of the monetary exchange-system (particularly children, parents, elderly, disabled and their carers, but also artists, scientists, thinkers, futurists, ‘creatives’ of any kind) – these stakeholders can only be served by ‘external’ mechanisms such as taxation (which are clunky and kludge-ridden at best), or by forcing them to do work within the money-economy (which means that their actual needed work can no longer be done).
• There is a very strong tendency towards short-termism.
• There is a very strong tendency to try to force everything into a crude, ludicrously-simplistic ‘double-entry life-keeping’.
• There is a very strong tendency to assume that ‘value’ exists only in monetary terms, as ‘valuations’ of ‘resources’ – hence, for example, a forest supposedly has no value until it is cut down, a mountain has no value until mined for its minerals, and so on.
• There is a very strong tendency to assume that anything which cannot be counted and ‘valued’ in monetary terms either does not matter or does not exist.

The societal impacts of these problems are rapidly approaching catastrophic levels. Yet none of the proposed ‘alternative currencies’ tackle more than a minute fraction of that list: most offer at best a localised kludge that might address a couple of issues whilst creating several more.

Let’s be blunt about this: the present system does not work. It actually never has – and that’s not surprising, because it was only ever intended to deal with point-to-point ‘trade’-transactions between fairly large groups (tribes, communities etc), hence it’s bit unfair to expect it to be able to run the entirety of an economy. But to create something that does work, we do need to go right back up to the level of the entire economy, and work our way back down from there. Which, yes, might – might – include some kind of ‘currency’ to tackle specific types of transactions: but not as the core of the economy itself.

This is actually no different from any other whole-of-enterprise architecture. (The only distinction is that it’s an ‘enterprise’ at the scale of an entire society, but that’s all.) So we would use the same overall approach:

• Who (and/or what) are the stakeholders in this enterprise?
• What are the core values? What is ‘value’ in this context? What is valued, and by whom? In other words, what determines ‘appropriate’ in this enterprise?
• What are the assets, functions, locations, events, capabilities and decisions within this enterprise? – in other words, the resources of the enterprise that need to be managed, distributed, shared and used in the most appropriate manner.
• What are the value-propositions that this enterprise needs to offer to and with its stakeholders?
• What mechanisms and responsibilities would be needed to create, deliver and monitor those value-propositions?
• What governance would be needed to ensure that all activities within the enterprise are optimised to be ‘on purpose’?
• …and so on.

To me, every attempt at a currency will inherently fail because it cannot take network-effects into account: by its nature, a currency is a mechanism for governance of point-to-point transactions, without any direct means to link to whole-of-system impacts. So I honestly believe that all of these attempts at ‘alternative currencies’ are a waste of time: we should be far better served by putting the same effort into understanding how an economy actually works.

And the key to that, to my mind, comes down to perhaps the scariest fact of all: there are no rights. ‘Rights’ are a social fiction; but the mutual, interlocking responsibilities that underpin those purported ‘rights’ are a social reality. If we want those purported ‘rights’, where we need to start is with creating a better understanding the ways in which those real responsibilities need to interlock: a focus on ‘rights’, like a focus on ‘currency’, is at best an unhelpful distraction from this requirement.

Where this gets gets scarier still is that our entire present economic model is based on a concept of ‘right of possession’ – hence a ‘right to personal property’. But there are no rights: only responsibilities are real. And in a network, there is no ‘personal’: only the network is real. Right at the fundamentals of economics, ‘personal property’ is just another fiction – and a very dangerous fiction at that. Yet personal responsibilities for societal resources – the appropriate management, maintenance and use of those resources – are real. And as with ‘rights’, those interlocking responsibilities result in something that looks almost exactly the same as ‘personal property’ – but we now know how we get there, via those responsibilities.

If we turn it this way round, we end up with something that looks very similar to what we have at present: but it resolves all of the structural flaws of a ‘money-type’ economy, and we also know exactly how we get there.

Once we know that that’s what we need to aim for, then we can start talking about ‘intermediate currencies’ and the rest, as part of a transitional ‘roadmap’ towards that more workable model. But those ‘alternative currencies’ are only an intermediate step, and we don’t start from there.

That’s what would change these sad attempts at ‘Ready? Fire! Aim…’ into a more viable ‘Ready? Aim? Fire!’ – and rekindle the fire in our social economy.

Who or what is a ‘business-anarchist‘? Anyone who works with inherent uncertainty in business in an intentional, disciplined way – working with the uncertainty rather than trying to ‘control’ it. Often it’s not so much a person as part of a business-role – a necessary part of that business-role. (Most of the examples in the book will come from my own field of whole-of- enterprise architecture, but the same principles apply in just about every other type of business-role.)

Why ‘anarchist’? Anarchy is about working without rules, working ‘outside the box’. When ‘business as usual’ breaks down, a disciplined form of anarchy is probably the only way through to something new that works well in the new business context.

‘Kiddies-anarchy’ and real anarchy: Anarchy has had a very bad press in the past, mainly because of what I describe as ‘kiddies-anarchy’ – an overdose of presumed ‘rights’ without responsibilities, especially in terms of causing disruption and destruction without any awareness or respect of the consequences for anyone else. Real anarchy is very different – arguably the most difficult of all political forms, because there are no easy rules to fall back on or to blame. Some entire organisations have been run on anarchic lines – the Quakers have done so for centuries – and even some businesses – such as Ricardo Semler’s Semco Group – but here we’re mainly focussing on an often-unnoticed yet everyday set of roles and responsibilities within an ordinary, everyday type of business.

What kind of business? Any business, and any type of business – for-profit, not-for-profit, government or social – from a huge global conglomerate right down to the local bridge-club or the school parent/teacher association.

Business-analyst and business-anarchist: Business-analysts deal with certainty and predictability: they refine the figures, crunch the numbers, track the trends. When your business world is reasonably stable, you need your analysts to help you optimise efficiency and maximise returns. But when your business world is not certain, not predictable, that’s when you’ll need your anarchists. And you’ll need your anarchists then, too. Your analysts can only tell you how to do more of the same, better – which is good, of course, in its own context, but it doesn’t help when what you really need to do is something different.

What’s different about how business-anarchists work? The quickest one-line answer is that analysts rely on rules and algorithms; anarchists rely on guidelines and principles.

What principles should business-anarchists rely on? Obviously this varies from one context to another, but from my work in whole-of-enterprise architecture the three most important design-principles seem to be these:

• There are no rules;
• There are no rights; and
• Money doesn’t matter.

These three principles, and a fourth follow-on principle, Always enhance adaptability, provide the overall structure for the book.

There are no rules: Rules provide a spurious sense of certainty that can let us down badly when our business-world changes around us. The real world is much messier and more complex than any system of rules that we could devise. Hence at times it’s necessary to start off from the assumption and expectation that there are no rules: instead, we have to rewrite the rule-book, by working back to the core-principles from which the rules originally arose. A simple everyday business-example of this is embedded in the ISO-9000 standard on quality-systems:  work-instructions provide ‘the rules’ that we need for real-time practice and process, but when the world changes, we need to rewrite the work-instructions by working upward to procedure, policy and, if necessary, overall vision.

There are no rights: ‘Rights’ are an important social fiction, but as with rules, they don’t actually exist in the real world, and in themselves they tell us almost nothing about how to create the conditions that such ‘rights’ would require. In practice, apparent ‘rights’ arise from mutual, interlocking responsibilities – so it’s those responsibilities, and not the purported ‘rights’, that are where we need to start. This has important implications for business-architecture and enterprise-architecture that will be explored in some depth in the book – for example, we need to ask serious questions about “What do shareholders own?” if they possess all the ‘rights’ for the business but without any real responsibilities.

Money doesn’t matter: Money is important for every business, of course, especially in a commercial context – but as with rules or ‘rights’, it’s not the place where we need to start. Money is also only one small part of the overall economy in which the business operates: reputation, trust, attention and respect all need to exist before any money will be placed on the table. And if we state – or show – that we’re only interested in ‘making money’ from our customers and community, why would anyone want to engage with us? As with other ‘rights’, money is solely a social fiction, and profit is an outcome of being ‘on purpose’ to values: to achieve the profits that we may desire, we first need to start from values, with a values-architecture that describes how we engage with everyone within the extended-enterprise of the business.

Always enhance adaptability: Change is the only certainty: we therefore need to design for that fact. Mistaken notions about rules, rights and money often serve only to slow us down, placing the business at risk as the world changes around us. This sections of the book explores how to embed the ‘business-anarchist’ principles into everyday business-practice, especially in business-architecture and enterprise-architecture.

—

More details to follow over the next few days, including book-cover, cover-blurb, ISBN numbers and so on. Publication-date is fixed as late-April, so I need to keep moving!

Various urgent online and in-person conversations have ensued. The only directly-meaningful name we came up with was ‘solution-space mapping‘, but several people have disagreed with that, and in any case there is already a well-established usage of the acronym ‘SSM’ in this context, namely Checkland et al’s Soft Systems Methodology.

There’s a long-standing software tradition of assigning arbitrary names as working-titles for projects. Someone suggested ‘Eric’, which was a name they’d used when developing an IT system for an airline, and which reminded me of a nonsense-phrase I’ve often used, that “anything unknown is called Fred”.

But even an arbitrary proper-name seems too concrete for something that is necessarily abstract and, as a name, necessarily temporary. We couldn’t think of any meaningful acronym, so we played with sounds for a while, until someone came up with this:

tinc

It’s the sound of the penny dropping, as someone ‘gets it’; the small bright sound that the imaginary light-bulb makes at the ‘Aha!’ moment in solution-space. A quick, recursive echo of a sound. And it’s also a contraction of what this name really is: a temporary inconvenience.

Since it’s clear we’re not even allowed to use the name of the framework that this isn’t in order to describe what it isn’t, we would have to apply the same process to give us a temporary name for that. So we might note that in Welsh the plosive sound ‘toof!’ would be spelt as twf, which should give us a relatively-safe acronym for That Welsh Framework. (‘Twf‘ is also the name of the Welsh Language Board website, by the way – “Cymraeg o’r Crud, Two Languages from Day One”.)

So there we have it: tinc, for the framework, and twf, for the-framework-that-it-isn’t. A temporary inconvenience, but it’ll have to do for now.

Anyone have any suggestions for an alternate term that could be used for this purpose, please?

Many thanks.

Cynefin framework (original (c) Dave Snowden / Cognitive-Edge c.2003)

Cynefin is probably one of the most useful conceptual tools that I hold in my ‘consultant’s toolkit’. It is an enormously powerful and enlightening framework to understand the relationships between the simple, the complicated and the complex, and to understand why long-proven approaches such as Taylorism and Six Sigma can sometimes (or often, these days) go spectacularly wrong.

Yet for several years now – in fact pretty much since I first encountered Cynefin – I’ve been concerned that there’s been very little attention paid to the role of the Chaotic domain. So that’s the theme I want to tackle here: how may we reclaim the Chaotic, to make Cynefin more complete?

(I’d better say upfront that there’ll be a fair amount here that Dave and others may disagree with, sometimes quite vehemently – and that’s okay, because this is definitely a ‘work in progress’, and probably with gaping holes in the reasoning in places. I need that critique if this is going to work in practice. In no way do I consider that any of the other work in Cynefin is somehow ‘wrong’ – particularly not the work that Dave and others have been doing in the Complex space, which I regard as crucially important in business and elsewhere. All I’m suggesting here is that perhaps we need to approach the Chaotic domain with the same degree of discipline as we do with the others – and not simply ‘run away’ to the Simple or the Complex as soon as we hit the Chaotic, which is about all that standard Cynefin offers at the moment.)

This one will again be long (my apologies…), but should be useful to anyone who’s familiar with Cynefin, or has any practical concerns about how to handle inherent uncertainties in business and elsewhere. More after the ‘Read more…’ link, anyway.

As I understand it, the Cynefin framework describes a ‘diagnostic/solution space‘ – four distinct categories of tactics to filter impressions of an unknown (‘disordered’) context, so as to support sense-making and then decisions for appropriate action. To put it at its simplest if perhaps most tangled, Cynefin is a decision-support framework to support the decisions needed to support subsequent decision-support.

These four sense-making modes or ‘domains’ are usually presented in flat two-dimensional form, as in the diagram above. But for reasons I explained in the previous post, they also fit well with the traditional Western ‘four elements’, which, roughly speaking, equate to physical, conceptual, relational and aspirational. These represent intersections of fundamentally different properties:

• physical: entity or entity-property, transferable, alienable (if I give it to you, I no longer have it)
• conceptual: entity or entity-property, transferable, non-alienable (if I give it to you, I still have it)
• relational: exists between entities, not transferable, requires active support from both ends
• aspirational: exists between entities, not transferable, requires active support from one end only (but may be dropped at the other end)

(In business, a simple example of an aspirational property is a brand: the commitment to the relationship comes from one end only – the ‘consumer [I hate that term, but it does apply here...] – but the relationship is destroyed if the brand is lost, and may not easily be substituted fro another.)

If we view Cynefin from that perspective, the four domains can also be understood as dimensions that mark out a ’solution-space’ surrounding the initial ‘disorder’ of the unknown:

Cynefin domains as tetradian dimensions

To find appropriate techniques for solutions (responses) for the context, we need to be able to move around the solution-space in an intentional, integrated way. The Cynefin dimensions align somewhat with the ‘four elements’, so we can use the latter to suggest probable places to start: if we’re dealing with physical things, Simple is probably best, if it’s conceptual we would start with the Complicated, and so on. But the catch is that pushing hard in one dimension tends to preclude use of the others – hence Taylorism, which works so well in the predictable physical world, would instead be a flat-out disaster if we assume that it will work just as well in the complex messiness of interpersonal relations (the Complex domain).

Which brings us back to Dave’s slide from the seminar, about the lifecycles of scientific modalities in the Cynefin space:

Concept Lifecycles ((c) Dave Snowden / Cognitive Edge 2010)

Dave here implies that there’s something close to a linear development of management-science, with each modality superseding the next. But that’s actually not what happens: instead, each new modality becomes the ‘scientific fashion‘ for a while, following much the same adoption-pattern as the well-known hype-cycle. The slide above only shows the first part of the hype-cycle, the initial trigger, and then the rise to the ‘plateau of inflated expectations’ – where attempts are made to use the techniques for everything (as in the old adage that “if all you have is a hammer, everything looks like a nail”) - followed by the descent into the ‘trough of disillusionment’. In the later part of the hype-cycle, we reach the ‘plateau of productivity’ – which, in essence, means that we learn to use the techniques only in contexts where they are appropriate. Hence, again, Taylorist time-and-motion analysis does work very well in certain specific contexts; likewise Six Sigma, and so on.

The danger with the ‘ascent’ notion implied in the slide above is that it risks leading us to the same kind of deluded ‘holier-than-thou’ supremacism. In other words, much the same that we can see, for example, in Don Beck and Ken Wilber’s so-called ‘Integral‘ version of Spiral Dynamics – initially a set of tools that are very useful in certain specific contexts, but one that’s been mangled beyond sense and context into an overblown cult-like ‘Theory That Explains Everything’, that has understandably triggered Dave’s ire on more than one occasion. Yet we can see the same risk also applies here: that initial excitement and exuberance at breaking free of the constraints of the ‘old regime’ are what drive the mistaken millenialism of the hype-cycle. And would not be helpful if Cynefin too becomes a cult, in the same way the Taylorism and Six Sigma have done in the past.

One way to prevent that from happening is to recognise that the S-curves in the slide aren’t a linear development: rather, they’re explorations into solution-space, with a specific emphasis in each case along a specific dimension of that solution-space – Scientific-Management for Simple/Physical, Systems-Thinking for Complicated/Conceptual, Dave’s Sense-Making for Complex/Relational, and so on. Right now, it’s the “and so on” bit that interests me – because right now there isn’t an equivalent science for the Chaotic/Aspirational segment of the solution-space – yet it’s something we definitely do need.

The reason why it’s important should become clear once we look at Cynefin in relation to time:

In real-world practice, the closer we get to the real-time of ‘NOW!‘, the less time we have to think – all we have time for is to do. In effect, this forces us towards a very limited range of choices across a spectrum of ‘truth’ to ‘value’ – in Cynefin terms, either Simple or Chaotic, because the time needed for Complicated analysis or Complex experiments is a luxury we simply do not have.

But Cynefin at present does not have any means to operate within the Chaotic domain. Instead, we’re told, we must ‘act > sense > respond’, either ‘taking control’ so as to push the context into the Simple domain, or grab hold of a few random nominally-unrelated items as the content for subsequent abductive reasoning in the Complex domain. As can be seen in the later part of the seminar, Dave has done brilliant work with fitness-landscapes in his SenseMaker software to bring the Complex closer to real-time – but it’s still not actually the in-the-moment ‘now-ness’ of the Chaotic, and arguably never will be, because by definition the assessment always happens after rather than during the event.

So we need something in Cynefin to fill that hole – because on the one hand the Simple-domain ’solutions’ are likely to be too simplistic, and on the other we don’t have the time we need to do anything else.

As for why we need it, contrast marketing with sales.

Almost all the classic marketing techniques sit either in the Complicated-domain – trend-analysis, market-segment analysis and so on – or somewhere near the Complicated/Complex border – test-marketing, the dreaded ‘focus groups’ and the like. More recently there’s been a lot more emphasis on viral-marketing, ‘social CRM‘ and the like, which is more solidly into the Complex-domain regions of the solution-space. The point is that it takes time, and it works with large numbers of actual and/or potential events.

But at the point of action, sales is always dealing with ‘market-of-one‘ – an individual quantum-decision to either buy or not-buy. Marketing helps us before that event; it will probably help us after the event; but by definition it can play no part at the immediate instant of the event. Each sale is an internalised quantum-event, a literally one-off decision in the midst of chaos – and no amount of external analysis or assessment is going to change that.

Using this concept of a Cynefin ’solution-space’, the preferred approach for marketing/sales for most of the past century was to prevent the apparent ‘need’ for a decision – in other words, to ‘take control’ of the market, and force everything into the Simple-domain. A single monopoly for every industry; you can have any colour you like as long as it’s black; no choice, other than to buy or not-buy – and marketing-pressure, peer-pressure and blanket advertising aimed to remove even that apparent choice. Yet these days that Simple option has been eroded by factors such as proliferation of vendors, globalisation and, especially, the internet – so much so that sales-folk might well say “it’s Chaos out here in the market”. In other words, it’s shifted from Simple to Chaotic – from ‘truth’ to value.

(Hence, in my own field of enterprise-architecture, the importance of values-architecture, as summarised here, here and here.)

This is the point where Dave and I diverge, philosophically speaking.

Dave’s background is in physics, and thence to cognitive-science. I would say that he is, without question, one of the few real masters that we have at present in applying that category of knowledge and experience to real-world problems. As someone with such a strong sciences background, I would imagine his natural reflex when faced with any methodological difficulty is to go back to ‘truth’, go back to the science – and in most cases, that’s probably the most reliable approach to take. Yet by definition, it cannot succeed with the Chaotic domain, because in every science, all sensemaking is fundamentally dependent on repetition – and again by definition, there is no real repeatability in Chaos. The cross-over point varies from one context to another, but conventional physics suggests that Heisenberg uncertainty is only resolvable once we move above ten quanta or so; below that point, conventional ‘truth’-based scientific analysis no longer makes sense. Dave in fact alludes to this in one of his comments to the previous post:

I have a strong bias towards the natural sciences and the Cynefin framework is built from a science based position. However … I have seen too many examples of dowsing not to believe it works in some way, I can also see that in all the cases it is a deeply embodied skill that cannot be taught. …  I also have to respect the fact that all controlled tests have failed to establish authenticity. This provides an interesting dilemma. On the one hand I have seen it work with water engineers, and with the man/jcb symbiosis that dug out the drive to the side of my house, on the other hand controlled tests have failed to validate. That means we have a really interesting anomaly that requires investigation – but it does not allow a strong claim for authenticity and the solution will [not?] be scientific.

Dowsing (or ‘water-witching’, in the US) is a good example of a Chaotic-domain context – one which we’ll come back to shortly. Yet as Dave implies, it seems that the only available option in the scientific approach is to force an immediate break-out from the Chaotic domain, into somewhere where repeatability can apply. This would usually be a move to the Complicated domain, such as with statistics-based ‘chaotic attractors’ and the like; or, as Dave has demonstrated so well, into the Complex domain, with fitness-landscapes and ‘outlier-detection’. But it still doesn’t work on the Chaotic domain as itself: from the scientific frame, it seems that the only way we can work with Chaos is by not being there. Which, these days, is hardly a realistic option, because it’s chaos everywhere. And yet we’re still stuck with no way to fill that gaping hole in Cynefin’s solution-space.

My own background is almost the opposite to Dave’s. Although I majored in sciences all the way through school, at university-level I switched over to the arts: specifically, to graphic-design – typography and the like – which is why some years later I became one of the pioneers in creating what is nowadays called desktop-publishing. In essence I’m a technologist, not a scientist; I place much more emphasis and much more trust in usefulness than purported formal ‘proof’. Hence perhaps unlike Dave, my natural reflex when faced with any methodological difficulty is to go to the ‘value’-side of the spectrum – Complex or Chaotic – rather than the ‘truth’-side – Complicated or Simple. Where Dave would, I presume, turn to the peer-reviewed journals, my reflex is to go back to first-principles, usually by direct observation of the context. I’ll freely admit that in Complicated-domain contexts my approach is arguably less reliable than that of the scientist; but because it makes no assumptions about repeatability, it can work within the Chaotic domain on its own terms. That’s the crucial difference.

The other key difference is that I approach the Cynefin frame not as a scientist, but as a methodologist – which is not necessarily the same thing! I’ve been working on various aspects of these themes for probably more than forty years; for example, it’s almost a quarter of a century since I first published my book Inventing Reality, which addresses the same overall space in a rather different way. So when I first came across Cynefin, way back in 2003, I already had a lot of background to connect it with – and that background did include the Chaotic domain. For example, to me it makes useful sense to cross-map Cynefin with a variety of Jungian concepts:

I suspect Dave might not approve of this cross-map, but the point is that it’s useful; unlike a scientific context, it’s neither necessary nor appropriate to claim that it is in some way ‘the truth’. (Which from Dave’s perspective it isn’t, of course: it’s doubtful that there’s any direct scientific cross-map between the two.) And the reason it’s useful is that this kind of cross-map gives us pointers as to how to fill that Chaotic-domain gap in Cynefin – by focussing on usefulness rather than ‘truth’.

As Dave implies, dowsing is probably a good place to start. I’ve been involved with dowsing in various forms since studying with Keith Critchlow at the Architectural Association, many decades ago; I’m probably one of the very few people doing systematic methodological study of the field, and likewise one the few people who can formally identify the fundamental flaws  in every so-called ’scientific’ study of dowsing to date by self-styled Skeptics. To put it bluntly, I do know what I’m doing there; most people don’t (and many – especially from the so-called ‘New Age’ of the market – frankly don’t have a freakin’ clue… ) Which means there’s a real need for discipline there – and in many other contexts too.

So whilst Dave might be horrified at what I’ve done, in fact Cynefin provides a very powerful base-frame for a systematic approach to methodology in dowsing – including the Chaotic domain. (See the book Disciplines of Dowsing – you can download the full e-book for free from here. There’s also a two-page reference-sheet that summarises all the basic principles and practice.) The same principles apply in other fields: for example, I’ve recently been working with a number of well-known archaeologists to develop formal methodologies for subjective archaeology. And the same principles also apply in business – as in the discussion above about marketing versus sales.

Very short summary from all of the above:

• the Cynefin framework defines a ’solution-space’ within which to select tactics to resolve problems in business and elsewhere
• Cynefin, as currently defined, severely constrains the solution-space by providing almost no means to manage the Chaotic domain
• if we include the Chaotic domain in a disciplined way, it greatly expands our range of options in the solution-space

So, how do we include the Chaotic domain? Here are a few suggestions to start with:

Don’t panic! In the extremes of the Chaotic domain, everything and nothing is true; nothing is certain, nothing stays the same for long. Hence Douglas Adams’ immortal catchphrase may prove very useful here… Standard Cynefin asserts that the appropriate tactic here would always be ‘act > sense > respond‘, to push us into another domain as quickly as possible: but that kind of panic-response may well lose us the information that we most need. Often the best advice here is the exact opposite of that: “Don’t just do something – stand there!”

Find the still-point, ‘the calm at the centre of the storm’. Every tradition asserts that there is such a still-point; every tradition also admits that finding that still-point ain’t easy… Hence the importance of practice, practice, more practice, and yet more practice. Which brings us to…

Repetition. In the Complicated domain, doing the same thing and expecting it to come up with different results is considered crazy; but in the Chaotic domain, it’s one of the few tactics that really helps. In a truly chaotic context, doing the same thing will always lead to different results: so here, repeating the same thing over and over provides us at least with something that will remain the same each time. That kind of repetition may technically be subjective, but it’s about the closest that we can have to scientific-style ‘controls’ here. Repetition works.

Use principles as a focus. Principles provide a stable point of reference amidst the chaos. In the business-context, this is the vision and values of the organisation. (By which I mean ‘vision’ in the ISO-9000 sense, as a stable anchor for the quality-system – not the flaccid marketing-puff that’s usually passed off as ‘our vision’, and about which Dave rightly complains.) “When in doubt, go back to first-principles”: that will help a lot here.

Allow serendipity. In the seminar, Dave describes abductive reasoning as “the logic of hunches”, a bringing-together of “seemingly unrelated items”. In the Chaotic domain, it becomes clear that everything is related in some ways to everything else: the patterns that we find there – and that we then evaluate via abductive reasoning in the Complex domain, as Dave describes – are actually little more than our choices, about connections that we choose to perceive between ’seemingly unrelated items’. But we first need to create space for those ‘unrelated items’ to arise in the first place. In his classic Zen and the Art of Motorcycle Maintenance, Robert Pirsig describes this as ‘fishing for facts’; and likewise William Beveridge includes chapters on the role of chance, the use of intuition, and the hazards and limitations of reason, in his equally classic The Art of Scientific Investigation. Yet to quote Louis Pasteur, “chance favours the prepared mind“: in the Chaotic domain we create space for the unexpected to happen, yet prepare the space with principles, with repetition, and ‘the calm amidst the storm’. But there’s also one other essential instruction…

Listen. Probably the single most important advice for any consultant – and for any salesperson, for that matter. Stop. Don’t talk. Just listen. “Nature abhors a vacuum”: if you provide a ’still-point’, a quiet calm, you may be surprised at what comes in to fill in the empty space. And very useful, too. Create the space. Listen. That’s almost all we need to know about working in the Chaotic domain.

To conclude…

My apologies that this has been such a long post: I hope it’s been worthwhile for you. But I guess what it comes down to is this:

Dave’s view of Cynefin is, as he puts it, “built from a science based position”. The advantage is that it is rigorous, largely context-independent, and firmly grounded in current cognitive research. The disadvantage is that, almost by definition, it can provide no real guidance on how to operate in the Chaotic domain.

My view of Cynefin is based in methodology-practice rather than formal scientific theory, and focusses more on individual difference and individual skill. The disadvantage is that it is less rigorous, and often highly context-dependent, hence arguably less reliable in the Complicated domain, and perhaps the Complex domain too. The advantage is that it does provide consistent means to operate in all domains, including the Chaotic domain – and hence can provide more options and opportunities in the overall Cynefin ’solution-space’.

Which approach is best? I would argue that it depends what you want to do: hence neither and both, really. But I hope this exploration helps in the choice of how to move around within the Cynefin solution-space, and that it provides some useful suggestions about other ways to use the real power of Cynefin.

Over to you for comments and suggestions, if you would?

From Induction to Abduction: a new approach to research and productive enquiry

This seminar will provide a summary of both the theory and practice of a new approach to research based on the large scale capture of self-interpreted micro-narrative.  The approach has been described as the first technique for distributed ethnography and has been developed over the past decade with project based funding from the US, UK and Singapore Governments in the context of risk assessment, horizon scanning, cultural mapping and weak signal detection.  It allows the linkage of research with knowledge management and impact based measurement.  Current projects involve measuring the impact of development projects in Africa, narrative based knowledge management for the US Army in Afghanistan and cultural mapping of various inner city communities within the UK.

The theoretical origins lie in the application of complex adaptive systems theory to social systems together with new understanding about the nature of human decision making from the cognitive sciences. The seminar will summarise the theory, but will also use a series of projects to combine theory with practice.  One of the goals is to create learning systems that work on continuous capture of material in the field as it happens linked with a capacity for feedback loops and sophisticated representations that allow people to learn by doing, building on the micro-narratives of day to day experience.  Narrative forms of knowledge lie between the experiential and the symbolic, allowing complex interactions and interventions in multiple social situations.

Abductive reasoning is, as Dave explains, “the logic of hunches”, and plays a key role in helping to develop understanding of how themes emerge in social contexts such as in business and elsewhere. It’s all fascinating stuff – very strongly recommended. The depth and versatility of the techniques will be a real eye-opener to anyone who hasn’t previously seen Dave’s work, and its applicability to whole-of-enterprise architecture and the like should be self-evident.

I will admit I do have mixed feelings about the way Dave develops and presents his work. On the one hand, he has a brilliant mind and is a brilliant presenter, and there’s no doubt at all that his tools and techniques, such as Cynefin and the theory and practice behind his Sensemaker software-suite represent real paradigm-shifts in the way we think about organisations and enterprises (in the broadest sense of those terms). But I do find it beyond tedious that he spends so much effort denigrating other people’s work – for example, Nonaka, Weick and Six Sigma (endless derided by Dave as ’sick stigma’) all come in for attack in the first few minutes of the seminar. And I too have been on the receiving end of that same… well, I would have to describe it as an odd kind of sort-of-scientific bigotry… which is more than just annoying at times. And annoying not least because pretty much everything I’d tried to explain to him and that he’d dismissed with such vehemence – such as the nature of ‘magical’ processes and the role of ritual – Dave in fact now incorporates (though probably unconsciously) as significant if unacknowledged sub-themes in his work (as can be seen in various places in the video). But we have to take the ‘Dave Snowden’ package as a whole, I guess: and most of the contents of that package are important – definitely.

But there’s one slide, right at the start of the presentation, that I find especially fascinating:

Concept lifecycles (image (c) Dave Snowden / Cognitive Edge 2010)

There is indeed a clear historical sequence here, paralleling the shifts in the underlying scientific paradigms, from Newtonian to hard-systems to complex-systems in the present day. But there are two important points that are easy to miss here:

• in each case the old dominant paradigm remains useful, though is seen to describe a distinct set of special-cases rather than a grand ‘Theory of Everything’;
• the sequence does not stop here, with Dave’s ’sense-making’ – it continues on to at least one more layer, and possibly two.

The reasoning for those assertions comes from Cynefin itself, plus a cross-map to this diagram above. As Shawn Callahan of Australian consultancy Anecdote explains in his excellent intro on the same web-page, Cynefin has a central (and ‘initial-state’) domain of ‘disorder’, and has four distinct domains of sensemaking and action:

• Simple: assumes simple cause-effect rules; sensemaking tactic is ’sense -> categorise -> respond’
• Complicated: assumes linear causality, but accepts that these may include many factors, delays, feedback-loops etc; sensemaking tactic is ’sense -> analyse -> respond’
• Complex: accepts that cause and effect are intertwined, leading to non-linearity and non-reversibility; sensemaking tactic is ‘probe -> sense -> respond’
• Chaotic: no identifiable cause-effect relationships; sensemaking tactic is ‘act -> sense -> respond’

Dave links the first three of these to the respective S-curves: Scientific Management is Simple, ‘classic’ Systems-Theory is Complicated, and his version of Sense-Making is Complex. Yet he provides no equivalent linkage for the Chaotic domain, and the listed tactic of ‘act -> sense -> respond’ literally consists of running away from the problem. Which is hardly a valid approach if the chaos insists on being sustained. Which, in the real world, it all too often does…

It’s often struck me that Dave’s great strength in the Complex domain seems also to create a real inability to describe any means to tackle the Chaotic domain. In this sense it does seem that, to use his own words, ”the old dominant paradigm suppresses the new idea” – where the ‘new idea’ is that the Chaotic domain does need to be respected in exactly the same depth as we now do for Complex and the others.

To me there are two key clues here.

The first is a direct warning from the classical tradition and elsewhere that running away is not a viable response in the Chaotic domain. The clue here is the Greek-derived word ‘panic’, which is what many people will experience when facing any kind of chaos. But the ‘pan-’ root literally means ‘the everything’ (hence panorama, pandemonium, and so on): what’s happening in panic is that everything and nothing is true at the same time. Yet that’s exactly what we need when we’re striving for innovation, or any other kind of search for new ideas: we need the ability to bring apparently unrelated themes together in new ways. And in practice we do that by not running away, but instead by ‘holding to the centre’, ‘finding the still-point’, ‘the calm at the centre of the storm’, and so on.

To find that centre, we turn to the other clue in what’s not in Dave’s diagram above.

The Simple domain is about control of Function, says Dave – in other words, the physical world, the physical dimension. Hence scientific-management came to the fore in the heyday of the assembly-line – and it still makes perfect sense within that type of context, where everything remains exactly predictable, exactly the same, just like most physical objects do.

The Complicated domain, says Dave, is about control of Information, the conceptual dimension. Hence ‘hard-systems’ thinking came to the fore in the heyday of the mainframe and the supercomputer, massive number-crunching and the like – and it still makes perfect sense in that context, of massively complicated cause-effect relationships between information-items.

The Complex domain, says Dave, is about control (or ’situating’, rather) of the Network – otherwise known as the relational dimension. Hence Dave’s ‘Sensemaker’ and the like come to the fore in genuinely-complex social contexts, where meaning and ‘truth’ emerge from the interweaving between the individual and the collective in the respective physical, conceptual, social and aspirational milieu, in which everything and anything may become both cause and effect of everything else.

But what’s not there in Dave’s model is any consistent framework to tackle the Chaotic domain – instead, we’re just told to run away back to the safety of one of the other domains. And yet, following that same logic above, we can see straight away what its base would be: the aspirational dimension, the explicit choice of meaning and purpose – otherwise known in the enterprise-architecture as vision, values and principles.

From my discussions with him, Dave seems to dismiss this whole domain because to him it appears to have no identifiable science behind it. Yet I would suggest that this too may be the result of a too-close identification with his own concept of ’science’, because as soon as we allow ourselves to move outside of the constraints of Western tradition of science, we will immediately find other traditions with at least the same levels of precision and discipline, if not more. The Australian Aboriginal concept of the Dreaming is one obvious example, an extremely sophisticated study of relationship with the land that is only now beginning to be understood in Western terms; likewise the Tibetan research into the period immediately before and after death; or, to give a more tangible example, the Polynesian science of navigation:

‘The Wayfinders’ [lecture-series] is a profound celebration of the wonder of human genius and spirit as brought into being by culture.

The entire science of wayfinding is based on dead-reckoning. You only know where you are by knowing where you have been and how you got to where you are…that your position at any one time is determined solely on the basis of distance and direction travelled since leaving the last known point… If you took all of the genius that allowed us to put a man on the moon and applied it to an understanding of the ocean, what you would get is Polynesia.

The consistent theme in each of these traditions is a very strong sense of purpose, intentionally embedded by and within the individual to act as a personal ‘guiding star’ that provides a known, certain ’still-point’ under conditions on uncertainty and chaos. Hence, although Dave somewhat characteristically dismisses and debunks vision in the business context, I do believe he’s missed the point. Those are genuine skills, genuine sciences, every bit as valid as as the sciences behind scientific-management, systems-thinking and complexity-theory – and their niche of greatest applicability is the Chaotic domain.

Which, once we think of it that way, makes Cynefin complete.

Or rather, there’s one more layer to this. Each of the Cynefin domains has its own respective science, its own technologies and so on. But there’s also a need for a ‘meta-discipline’ to switch between the Cynefin domains, linking them together into a unified whole.

Checklists can provide some of that discipline; likewise a consistent iterative methodology such as the extended TOGAF-like cycle that I use in my own enterprise-architecture work. An explicit multi-dimensional model such as the tetradian can also help in this. And we have much that we could learn from the many non-Western traditions – or even from a better understanding of how science really works in practice.

But perhaps more, for here, we perhaps need to note that whilst Dave’s complexity-theory is useful – very useful indeed – it’s unlikely to be ‘the last word’ in the sciences that we need in enterprise-architecture. There’s still some way to go: and a more consistent, more honest approach to how we handle the Chaotic domain would seem to be the necessary next step in that journey.

Danny Greefhorst of Netherlands enterprise-architecture consultancy ArchiXL emailed me with a query about my book Doing Enterprise Architecture:

I was especially interested in the part where you talk about architecture principles given that I am currently writing a book on that topic. You specifically mention the relationship between values and architecture principles. Do you have specific examples of these values and architecture principles that were derived from them?

The key distinction between values and principles is that values are about emotion - a feeling about something – whereas principles are expressions of thought – a rationalisation, followed by decisions about what to do about that something.

A value is often expressed as a single word, such as ’safety’ or ‘trustworthiness’ or ‘fairness’.

A principle is usually expressed as a more considered structure: for example, the TOGAF section on Architecture Principles suggests the following:

• an assertion or label such as ‘Business Continuity’
• a descriptive statement (in that example, “Enterprise operations are maintained in spite of system interruptions”)
• a more detailed rationale (e.g. see that TOGAF example)
• a summary of architectural and design implications (ditto)

In thiscase, the principle of ‘Business Continuity’ devolves in part from the value ‘Trustworthiness’: to ensure that we can trust the business to deliver what it says it will deliver, one aspect is that we will need to plan and design for business continuity. The practical implications include concerns such as design for fail-safe and safe-fail (‘brown-out’), monitoring for failure, real-time or near-real-time failure impact-analysis, failover process-choreographies and so on.

(TOGAF v9 ch.23 asserts that “Architecture principles are a subset of IT principles”: this might make sense for IT-architecture, but makes no sense at all for a true whole-of-enterprise architecture. More accurately, architecture principles and IT principles are orthogonal sets which intersect in IT-architecture principles; courtesy of its unhelpful IT-centrism, TOGAF unfortunately treats higher-order architecture-principles and IT-architecture principles as if they’re at the same level in the values/principles hierarchy, which they’re not. This can be seen most clearly in the first principle in TOGAF’s example set, ‘Primacy of principles’: it should be immediately obvious that this would have a broader scope than solely IT.)

Note that there may be a many-to-many relationship between values and principles – for example, ‘Business Continuity’ also has some links to the value ’safety’ as well as ‘trustworthiness’; the TOGAF principle ‘Compliance with law’ links to both ‘fairness’ and safety’; and so on. Some principles may also have only indirect links to values: the principle ‘Primacy of principles’ is one such example, which in effect applies more to the way in which all principles devolve from values.

Back in March I wrote a fairly lengthy post on ‘value-trees’ in enterprise-architecture‘, which includes this general theme. The example I gave there was a simplistic one about profit as a key value for a commercial organisation:

A suite of principles devolve from this value: for example:

• the outcomes of value-chain processes shall be measured in monetary terms;
• costs of all activities shall likewise be measured in monetary terms (hence techniques such as Activity Based Costing);
• verifiable mechanisms shall be used to contrast these two sets of measurements, to derive a measurement of the value in its specified terms – i.e. profit, in this example.

To do this, we’ll need to:

• aggregate (‘roll up’) all the outcomes and costs; and for management purposes
• disaggregate (‘drill down’) through the business-units and groups and clusters, all the way back down to individual activities.

The connections and transforms for aggregation and disaggregation are the branches for the value-tree.

There’s more detail on this and how to work with value-trees in practice in the chapter on ‘pervasive’ services’ in my book The Service Oriented Enterprise. If anyone wants me to do a reference-sheet on this, please let me know?

Key point is that:

• vision/purpose is the emotive (literal?) ‘wake-up call’ for the overall enterprise, the means by which we connect with or belong to the enterprise
• values are what we feel about/from that purpose
• principles are what we think about those values (i.e. what we think about what we feel); which in turn lead to
• missions, goals and objectives, that describe what we intend to do to express what we think about what we feel.

Obviously, there is some interaction between those dimensions – what we do challenges what we think and feel, and so on – but there is a sort-of hierarchy here that’s best expressed in that sequence of ‘belong > feel > think > do’.

Hope this helps for now?