That’s perhaps the shortest summary to a request by Anthony Draffin, in a comment to my previous post ‘Not quite bus-pass day‘:

On a selfish note… It’s apparent that the common thread to dowsing, printing and enterprise architecture is your ability to look at a field holistically and apply logical thought to extract inconsistencies and errors, as well as looking at new ways of doing something more efficiently to meet the original aims. That’s a rare skill. Have you given thought to documenting how you go about doing this? While I imagine it’s the application of a number of taught skills, the way you put these together must be far from ubiquitous. Have you considered teaching this? Personally, as a 27 year old, I want to soak up as much of your approach and thought process as you’re willing to offer.

(Warning, this is going to be another (very) long one, mainly because there’ll be several case-studies.)

Amused that Anthony says he’s 27, because that’s about the age that I really got going on this. (A little earlier, actually: the first dowsing book came out when I was still 24. I used to have to apologise for not being the age people expected me to be, namely at least 75! )

I wouldn’t say that any of what I do is a ‘rare skill’, although it’s true that it’s not often acknowledged or respected – perhaps because, by its nature, it necessarily tends to be disruptive to any comfortable status-quo. I’ve been doing it since a very early age – for as long as I can remember, anyway, certainly way back in primary school – but it’s actually the standard approach used in most forms of design-thinking and the like, as taught in art-college or architecture-school or good engineering courses or even in the US military. It’s also what really happens in scientific research – see, for example, WIB Beveridge’s classic The Art of Scientific Investigation.

My own particular twist on it arose because I’m not much good at doing things, or making things (I tend to describe myself as ‘ambi-sinistral’ – the opposite of ‘ambidextrous’… ). Hence I tend to focus instead on the thinking behind the doing or making or whatever, always searching for the simplest way to do things, the most effective way, and so on. Kind of recursive, if you like, but it works well. Except for that little problem that it tends to be so darn disruptive…

Methods, mechanics, approaches

One place to start would be around skill itself, and the key themes of my Masters thesis, way back in 1976. Back there, I described a skill – any skill – as being made up of three components:

• the methods used in the skill
• the mechanics and other real-world constraints of the ‘objective’ context of the skill – that which is common to everyone
• the approaches, assumptions, mindset, paradigms, physical dexterity and other ‘subjective’ context for the individual (the ‘operator’) – that which is specific to the individual

What I found, very quickly, was that most people seem to focus on the methods used in any skill. But that actually misses the point: the methods used by any skilled operator arise from their own personal resolution of the mechanics and the approaches – the ‘objective’ and ‘subjective’ components of the skill. This is why using someone else’s methods doesn’t always work, and why ‘best practice’ can be dangerously misleading: the mechanics of the issue remain the same, by definition, but the context is different, and hence may well need different methods.

Focussing on method also makes it much more difficult to tease apart the separate threads of mechanics and approaches. It should be obvious that blurring the objective and the subjective is not likely to be a good idea, and yet that’s exactly what happens whenever we focus only on method.

In all skills-work – in fact in just about every human context – we also come face to face with Gooch‘s Paradox: “things have not only to be seen to be believed, but also have to be believed to be seen”. In an all too literal sense, in skills-work, reality is what we say it is: we actually create it, from nothing, or rather from a combination of imagination and hard work. (In this kind of context, it doesn’t really make sense to ask the question “Is it real or imaginary?”, because the only possible answer is ‘Yes’ – both, therefore neither.) To resolve Gooch’s Paradox, we treat the approaches – our assumptions and beliefs – as if they are part of the mechanics of the context. The danger is that we may forget that point about ‘as if’, and – if we think about those assumptions at all – think that they are part of the fundamental mechanics of the context, rather than an arbitrary choice to achieve some particular purpose.

Once assumptions creep in – in other words, whenever the subjective is blurred into the objective without conscious intent to do so – what we have is a context to which arbitrary constraints have been applied. Which places arbitrary limits on possibility. Which is kinda pointless, really. But the only way that we’ll be able to see that the constraints are arbitrary is to step back a bit, and re-separate the subjective from the objective. Hence a kind of recursive methods-to-look-at-methods, analysis-to-unpack-analysis, and so on. Which is what I do.

As I mentioned in my reply-comment, much of the ‘how I do what I do’ is already documented in various ways throughout the books, such as in Everyday Enterprise Architecture (which focusses on method in a business context) and The Disciplines of Dowsing (which looks more at ‘thinking about thinking’). The core of the latter book is the ‘four disciplines’ section (see the summary on the separate two-page reference-sheet) and the ‘seven sins of dubious discipline’ (currently listed only in the book): it wouldn’t take much work to translate those into almost any other context.

What I’ll use here is the Five Element / effectiveness framework that I use in a lot of my client-work these days (though often in somewhat covert form). It’s nothing special, in fact it’s little more than a recursive use of a pair of matched checklists. The first of these, as summarised in the ‘Five Elements’ chapter in SEMPER & SCORE, is a set of perspectives on the overall context:

• Purpose – what are we aiming to do here? and why? (see also the slidedeck ‘Vision, Role, Mission, Goal‘)
• People – who would be needed for this purpose? what skills and relations do they need? what are their mutual responsibilities?
• Preparation – what planning and logistics would be needed for this purpose? what assumptions and mindsets apply here? what are the key events that trigger action?
• Process – what needs to be done to achieve the purpose? when, how and with what would this be done? when is each process complete?
• Performance – what constitutes ‘success’, and for whom? what information and metrics are needed to keep everything on track? what would be needed to support continuous improvement?

The other checklist is a set of keywords on effectiveness, which are sort-of orthogonal yet also sort-of linked to the Five Element set. Listing these in the same order as above:

• Appropriate – is this on track towards the purpose?
• Elegant – does this support the human-factors in the context? (e.g. simplicity, ergonomics etc)
• Efficient – does this make the best (e.g. least-wasteful) use of the available resources?
• Reliable – can this be relied upon to deliver the required results?
• Integrated – does this help to link everything to everything else in a consistent way?

To assess a context, we can start from anywhere at all. The point is that we use these checklists not as linear lists, but as a reminder to keep looking round, bouncing back and forth between each of the interconnected themes in the two lists, looking at the context from every possible angle, and at every level from really-big-picture to finest-detail, building up a kind of hologram of the overall context, using one form of sensemaking to bounce off others, and so on. The book Real Enterprise Architecture provides a complete worked-example of this kind of recursive process as applied to whole-enterprise architectures.

Questioning everything

Looking back at the various areas I’ve worked in or with, there’s a fairly consistent pattern about what I’ve done and the sequence in which I’ve done it.

The first stage is just getting involved at all: taking the ideas and practices at face-value, and putting them into practice as if they are entirely ‘true’. That usually works for a while (not least because that’s what everyone else is doing).

I then allow myself to start to notice the niggles, the things that don’t quite seem to work, where ‘what it says on the tin’ doesn’t actually deliver what it says on the tin. The problem, of course, is that we can’t assess the validity of a logic from within the logic itself. Yet we also can’t actually work on the context without being inside the logic (or some form of the logic). This is where we hit Gooch’s Paradox head-on: we have to see it to believe it, yet also have to believe it to see it. The only way out of that dilemma is to start to use beliefs as tools – which can be kinda challenging…

In my experience, there are two parts to this:

• identify the big-picture theme for the overall context (the ‘vision’ or, as architects would put it, the unifying ‘parti‘)
• apply design-thinking tactics to question everything, switching beliefs in order to experience the context in different ways, and test the apparent results

The tactics to identify the key-theme(s) are usually straightforward. A classic example is the ‘Five Whys’: just keep asking “why?” until eventually we hit a ‘Because.’ – or rather, a real ‘Because.’ that makes some degree of sense, rather than one that’s just used to get people to stop asking awkward questions! These days I tend to look for a brief overview-statement – usually only about three to five words – that has a distinct three-part structure: it identifies the ‘things’ or concerns that matter to everyone in the context, what’s being done with or to those items, and why it’s deemed to be important. This gives us a stable anchor to which we know we can return, and against which we can test anything in the context.

Then, following standard ‘design-thinking’ tactics, we use a suite of ‘disruptive’ questions about the context – for example:

• what’s another version of this?
• what does this look like at a smaller scale, or a larger scale?
• what happens if we substitute something else for this?
• what happens if we invert some or all of the rules?
• is there a ‘term-hijack’ here? – does a small subset purport to be the whole, blocking the view to any other aspect of the context?

This is where things often get to be, uh, fun… – because it’s very common to find aspects of the context that a) don’t and can’t make any sense, b) clearly don’t work ‘as advertised’, in fact usually work against the nominal aims of the overall enterprise, yet c) there are key players with a lot of vested interest in ensuring that the status quo remains unquestioned and unchallenged. Don’t be surprised at this: it happens every time.

This is where a certain amount of dogged determination becomes essential… Also essential is a very clear, insistent emphasis on the big-picture, on holding to the overall vision for the shared-enterprise, because that’s often the only thing that will persuade people that there’s no ‘personal attack’ here, that instead the only purpose of the challenge and the enquiry is to make things work better, for everyone. (We have to be real about that, too: we need belief in ourselves in order to keep going, it’s true, but we need to keep questioning ourselves as well. It’s one reason why serious self-doubt is a chronic yet necessary occupational-hazard here.)

We need to keep hammering at this until we do start to get a clear separation between the mechanics of the context – which usually turn out to be surprisingly simple – and the approaches to the context – which are, by definition, individual and subjective. Then we can start to work towards new methods that work with the context under the current conditions.

The same seems to apply to just about any type of context: an individual’s personal challenges in developing their own skill, a business, a social context, a single conceptual tool, or an entire discipline.

Scattered throughout this weblog and the sister-weblog Sidewise, you’ll find examples of those techniques in use. Sometimes it’s reasonably straightforward, sometimes rather more controversial, but you’ll see in each case that’s it’s essentially the same principles, the same tactics.

I’ll also summarise here those same techniques in use in four different large-scale domains that I’ve been involved with over the decades: dowsing, desktop-publishing, domestic-violence resolution, and enterprise-architecture.

Example: Dowsing (1970s)

Big-picture theme: finding things, particularly where conventional (mechanical/physical) techniques either won’t work or are unavailable.

History: as a discipline, has been around ‘forever’, and often highly controversial – first from priests who regarded it as ‘the work of the devil’ etc, then later from would-be scientists who wanted to ‘explain’ it and couldn’t. When I first got involved, in the late 1960s, the field was pretty much moribund, with a random mixture of wild claims, erratic discipline, no formal methodology or theory-base as such, a long history of inconclusive scientific experiments, and the first flush of hype-laden New Age ‘thinking’ (if that’s the right term…). Most of the people involved were well into their sixties, seventies or more (which I, uh, wasn’t…). The key players consisted of a kind of closed ‘military club’ (water-finding being very important to an army on the move), a few variously-erratic practitioners (often with wild-eyed ideas about health and the like), a swathe of armchair-theorist camp-followers who talked a lot but did nothing, and a few people who really did know what they were doing and wisely kept themselves well away from the mess.

Conceptual mismatch: The most common assertion was that it was a special ‘innate’ skill that only certain ‘special people’ could do. Methods that often clashed or even flatly contradicted each other could lead to the same result; the same method used by different people would lead to wildly different results. Most of the theory in use – such as notions of ‘waves’ or vibrations’ or ‘radiations’ – was either meaningless or just plain wrong in terms of conventional physics. (Much of it did sort-of make sense as metaphor, but there seemed to be little understanding of the difference between active-metaphor and concrete fact.) Muddle-headed ‘New Age’ ideas merely added to the overall mess.

Vested interests: On the one side was the moribund ‘military club’, who liked the idea of being ‘special and different’, and/or the ‘right’ to tell the ‘lower ranks’ what to do, whether it made any sense or not. On the other side were the upcoming ‘New-Agers’, who were not going to let anything block their path to potential fame and fortune. (I’m being cynical, I know, but that’s exactly what happened.)

Assessment and action: Assess the purported theory, and scrap most of it: it’s meaningless. The only parts of the theory that do make sense and do have solid experimental backing revolve around perceptual psychology and physiology – particularly around weighted-sum merging of multiple channels (which is why there’s no single ‘the method’) and around edge-triggered reflex-response (which is why some experienced water-finders can’t find static water even when they’re standing on top of it). If some kind of tool is used, almost all of the tools act as some form of mechanical amplifier – if I move my hand a little, the tool moves a lot. (I’ve only ever found one case where that principle didn’t apply at all.) Materials, structures, theories and so on seemed to matter only because people believed that they did: in most cases, a simpler alternative would work just as well, if not better. Keep stripping it back to the bare essentials.

It is a true skill – but it’s not one that’s restricted to only ‘special people’. Instead, it’s a learnable skill: anyone can do it – though whether they may or will do so are entirely separate questions! (There was quite a lot of pushback from the ‘military club’ against the idea that ‘anyone can dowse’.) It’s also a skill that requires a lot of practice and a lot of discipline to get right. (Unsurprisingly, there was a lot of pushback from the ‘New-Agers’ on that point, and there still is – see the book Disciplines of Dowsing.) It’s also a skill which often requires a wide range of psychological ‘tricks’ to help people slide past Batcheldor’s ‘witness-inhibition’ and ‘ownership-resistance’ – in other words, “this isn’t happening, and if it is, it isn’t me”.

End-result: After a few months’ experimentation and subsequent practice over several years with a wide range of students, I’d stripped it down to the point where I could get most people started on the basics within less than two minutes, using two bits of fencing-wire from the garden as simple instruments. The notion that ‘anyone can dowse’ is now firmly established in the canon, and the teaching-methods that I developed (based on, self-responsibility, self-critique and continual-improvement) are still some of the most common currently in use.

Example: Desktop-publishing (1970s-80s)

Big-picture theme: getting ideas and information out into the public space.

History: I trained as a graphic-designer/typographer, and became professionally involved in typesetting in the late 1970s, with the early developments in smaller phototypesetting machines. (‘Smaller’ being a relative term here: the first system we bought required a room of its own and a separate darkroom, and cost more than my house.) The big bottleneck was keyboard input: the typesetting unit was capable of running much faster than a single operator. Although the internal technology was extremely complex, the input was not: some machines still relied on a very simple 6- or 7-channel punch-tape reader, using control-codes to extend the effective size of the character-set.

At the same time, simple but usable microcomputers were just starting to come onto the market. (My first microcomputer had only an 8-character LED display, hexadecimal keypad and 256 bytes of memory; the more usable Ohio Scientific systems that we first used for real had a proper keyboard but still only 8kbytes of memory, and the only storage was on audio-cassettes.) Almost all of these machines used a 7- or 8-channel character-set (ASCII or extended-ASCII); most also provided some form of direct data input/output for interfacing to other systems.

It seemed to me that there should at least be some way to use a basic micro as a much cheaper input-terminal, using simple code-translation and a standard hardware-interface. It also seemed probable that other people would want to do the same – taking control of their own publishing, driving a typesetter direct, or both. In the longer term, that could well be quite a large market.

Conceptual mismatch: This is best summarised by the phrase (exact quote, in fact) that “there is no interest in typesetting from microcomputers, and there never will be”. There were all manner of arbitrary demarcation-lines across the whole context, both on the pre-press side – such as between authors, publishers, unions and printers – and on the technical side – particularly between typesetter-manufacturers, computer-manufacturers and various hobbyists and hackers – most of which arose more from historical ‘turf-wars’, ‘positioning’, and mutual misunderstanding than from any concrete distinctions. On the union side especially, there were many arbitrary assumptions, based on the belief that technology could not and would not change, or if it did, it could not and would not be allowed to make any difference to existing processes or roles.

Vested interests: The entire context was riddled with vested interests, almost all of which were in conflict. A stream of intermediaries – agent, publisher, pre-press, press, retail – stood between author and audience. Typesetting-systems were expensive pieces of equipment, yet with not all that much to justify their cost: there was lot of money to made there, both from machinery-sales and from fonts and other consumables, and hence a lot of ‘need’ to protect those sources of income. Until IBM eventually stepped in, most of the microcomputer manufacturers were trying to establish themselves as ‘the manufacturer’, resulting in a plethora of mostly-proprietary, mostly-incompatible hardware and software non-’standards’ – at one point we had to buy two machines whose sole function was to read the two hundred or more different disk-formats used on the four distinct disk form-factors then in common use: 8″, 5.25″, 3.5″ and 3″. Weaving a path between all the different vested-interests and proprietary structures was, frankly, a time-wasting nightmare.

Assessment and action: On our first machine, we’d been told emphatically that it was physically impossible to connect a microcomputer; a weekend spent poring over technical specs and waving a soldering-iron around a bit on a prototype-board soon proved that ‘fact’ wrong, whilst the only software we needed at first was a straightforward lookup-table to translate between character-sets. It really was that simple. (We avoided warranty risks by using opto-isolators, so there was no electrical connection between the two machines.) For our later, larger systems – which were capable of typesetting a reasonable-sized book in less than an hour – the hardware-interfaces were already built in. This gave us ‘direct typesetting’ capability, but it still required operators to know – and use – the distinct formatting-codes for each type of machine.

The next step was to hide the complexity, using the format-code in common word-processors such as WordStar to trigger font-changes and the like. (I believe we were the first people to use style-codes, such that a single hideable code – *F1, for example – would change the entire style, including paragraphs, indents, font-family and so on.) At that point, people could use ordinary word-processors to typeset text: the first true precursor to desktop-publishing.

It worked, but there were still limitations. (Our main competitor, meanwhile, was using a mangled form of SGML which still required people to embed hard-codes in the text; in our system, all of the formatting could be invisible.) The main problem was that people couldn’t see beforehand exactly how much space any text would take up – a very important concern to two of our customers, who were producing page-spread books and partworks, Dorling-Kindersley style. Hence some serious code-hacking (all assembly-language, with multiple overlays to squeeze into no more than 40kb of memory) to create a post-processor that would copyfit line-by-line for the correct fonts and sizes, and output a symbolic result to a dot-matrix printer. This was probably the first viable attempt at a true desktop-publishing system – several years before Macintosh and, later, PageMaker.

End-result: I’m good at creating ideas and markets, and all the preliminary work that gets things going, but I’m not good at running businesses – that’s a different mindset entirely. Eventually we sold out to another pre-press company and (in an all too literal sense) I ran away, first to the US, and then onward to Australia. I believe it’s still running, and certainly made millions for the new owners. (I didn’t, of course.)

Example: Domestic-violence resolution (1980s-90s)

Big-picture theme: reducing and repairing the damage from social harm, particularly between individuals.

History: Fights and power-games between individuals in a domestic context have been part of the human story since forever, but had usually been largely covert and ignored as ‘a private matter’ for most of that time. It was brought into public notice in 1970s by women’s activists, most notably Erin Pizzey, founder of Chiswick Women’s Aid. Unlike Pizzey herself (who has always insisted that domestic-violence (DV) is a human problem, not a gendered one), most activists purport that DV is something that happens almost exclusively to women, and caused almost exclusively by men – so much so that some have called for the term ‘domestic-violence’ to be replaced always by the term ‘violence against women’. Most current law (e.g. US ‘Violence Against Women Act’), support-structures (domestic-violence help-lines) and formal theory (e.g. Duluth) reflect this assertion. I became involved in the field during the 1980s as a member of a pro-feminist men’s group who were taking up the feminist challenge that all violence was caused by men alone, and therefore men’s responsibility alone to resolve the (purportedly) ever-rising tide of men’s violence against women. The issues became more personal later when two of my lesbian friends asked me for advice after they had ended their relationship with a knife fight (without injuring each other, fortunately) but had been explicitly shut out from any help because no man could be blamed for the violence.

Conceptual mismatch: The theory was straightforward: men are the problem, women are the solution, and the only useful thing that men can do is blame themselves for everything that goes wrong in the world. Everything in my background supported that assertion, hence it seemed to make sense: self-blame had been a very deeply ingrained habit for me, going right back to earliest childhood. Yet the whole field seemed riddled with gendered special-cases: behaviours that were definitely violence if done by a man were, if done by a woman, either deemed ‘not violence’ or ‘indirectly caused by men, therefore men’s fault’. In the Duluth model, blame itself was classed as a form of violence only if done by a man, and only if the person being blamed was an adult woman: blaming of men (or in essence almost any other form of abuse of men), was explicitly not classed as violence. And the real catch was that, in terms of outcomes, it clearly wasn’t working: no matter how much we blamed ourselves, and blamed other men, the overall level of violence in the culture around us still seemed to continue to rise.

Vested interests: Looking around, it was very clear that there were a large number of players – mostly but not all women – whose identity and self-worth depended on putting men down, regardless of whether or not this actually helped women in general, or anyone in general. There were also very large sums of money, and large numbers of jobs, that depended on maintaining the assertions around women’s purported exclusive victimhood in this context.

Assessment and action: The first warning-signs appeared in one of our standard text-books, Paul Kivel’s Men’s Work: How To Stop The Violence That Tears Our Lives Apart, which is designed around a series of workshops for senior-school students. The book includes many oddly-unrealistic role-play scenarios in which an adolescent boy or young man is suddenly violent or abusive to a woman; yet the only real example of violence described in the whole book is an actual incident in which two girls had a full claws-out fight when one insulted the other in the classroom – and in which no boys were involved at all, other than to separate the warring parties.

After my lesbian friends had their knife-fight, we discovered that no violence-resolution material was available that acknowledged even the possibility that a woman could be a perpetrator of violence. The standard Duluth model defines violence as inherently ‘male’; on the Duluth Wheel, female pronouns are used exclusively throughout to indicate victim, and male pronouns exclusively for perpetrator, and mutuality (where both parties are both ‘perpetrator’ and ‘victim’ of each other and of themselves) – which clearly applied in my friends’ case – is explicitly denied. I decided to try a very simple thought-experiment: swap the gender-pronouns throughout, and see if it still makes sense in terms of real-world evidence and experience. It did: in fact for most of the Duluth categories of abuse it made more sense than the ‘official’ way round. Also – importantly – two key categories of abuse were absent from the original model: sexual abuse, and third-party-abuse. It became immediately clear that the Duluth model itself was structured as third-party abuse, primarily leveraged through other-blame – in other words, far from reducing violence and abuse, it was actually designed to increase it. (Whether that mis-design was intentional, or merely arose from incompetence and excess zeal, is a separate issue that I will not discuss here… – but the fact of its unfitness for purpose cannot be in any doubt.) A simple ‘de-gendered’ redesign resolved almost all of the structural problems, sufficient at least to satisfy my friends’ immediate needs.

That exposure of the extreme inadequacies of the original Duluth model forced our group to reassess all of our previous assumptions about gender and violence, and thence to look again at the research on whose purported facts we’d based those beliefs. I did two analyses of a much-published study on which Australian public policy was based – the first analysis on the public version of the paper and political assertions from it, and the second analysis on the original academic study, which took quite a bit of work to obtain, since it was not publicly available. Another colleague, as his MA thesis, undertook a meta-analysis of domestic-violence studies in Australia. The results were shocking. None of the original studies were based on defensible methodologies – in fact many were so riddled with basic methodological errors such as circular-reasoning that they were essentially meaningless. And in all cases, all of the methodological errors either inflated the female injury-rate or risk, diminished or denied the male injury-rate or risk, or both: there were no exceptions. In short, almost none of what we’d previously taken as ‘fact’ was fact at all. The only genuine facts we could establish was that domestic-violence was a systemic issue with some gendered overtones, and that although it that affected both sexes in different ways, overall it seemed to do so almost equally – though there were strong indications from hospital data and the like that the majority of victims were male, not female.

We then looked at public policy, and the provision of domestic-violence support-services. These too were based on the same fundamentally-flawed assumptions and the same unquestioned circular reasoning: women are the only victims, hence support-services are only available to women; and since only women use these services, this proves that women are the only victims. In some of our interviews we discovered that men who’d been abused – knifed, in one case – were referred to police for charges, simply because the models in use automatically deemed men to be the sole perpetrators, regardless of the actual context or evidence. In short, the entire domestic-violence resolution ‘industry’ it was, and still is, an unworkable and fundamentally dysfunctional mess whose structures and methods are all but guaranteed to cause far more harm than good: an archetypal example of the Shirky Principle that any institution will attempt to preserve the problem to which it purports to be the ‘solution’.

End-result: The domestic-violence ‘industry’ is the outcome of a classic example of a ‘term-hijack‘, in which a small subset of systemic issue is misframed as the whole, and strenuous efforts are made to deny or conceal any other aspect of that issue. In effect, the term-hijack converts a resolvable systemic context into a non-resolvable ‘wicked-problem‘, in which every attempt to resolve a problem is constrained by the structural myopia, inevitably making things worse with each iteration. Unfortunately, there are huge vested-interests in maintaining the term-hijack. Anyone who challenges it – as I and many others have learnt to our cost – is likely to come face to face with extreme violence from women who somehow purport that no woman is ever violent. It seems clear that resolving these structural problems would require a high level of honesty and humility from those players – an honesty that in most cases at present seems conspicuous only by its absence…

Some of the material I wrote is out there and in daily front-line use by others – with real success, according to the occasional emails I still receive on the subject. But to be blunt, after a decade of relentless ongoing abuse from almost all sides, I just gave up and literally threw away most of the work that I’d done… the structural dishonesties in this mess are so entrenched and so ‘political’ that I found it just too painful to be involved at all, and it still seems that resolving the mess would require fundamental shifts in societal attitudes and beliefs that would be unlikely to occur within my own lifetime. Oh well.

The issues are generic, though, and can be resolved at a more generic level. You’ll see how some of these exact same issues are addressed in the business-context in my book Power and Response-ability: the human side of systems and its accompanying ‘manifesto‘.

Example: Enterprise-architecture (2000s-to-present)

Big-picture theme: helping organisations and overall shared-enterprises become more efficient and effective (‘doing the right things right, on purpose’).

History: The main focus of enterprise-architecture is around the relationships between structure, purpose and business-execution.As a discipline, it’s been around for at least a century in various forms, such as Taylorism (‘scientific management’), operations-research and organisational cybernetics. I often describe it as based on a single, very simple idea: that things work better when they work together. Although my work often touched on it over the decades, I first became actively involved perhaps fifteen years ago, when trying to tackle issues around long-term knowledge-management in aircraft research. Over the past decade, most of my work has revolved around various aspects of enterprise-architectures.

Conceptual mismatch: The term ‘enterprise-architecture’ implies a very broad whole-enterprise scope. In recent decades, though, the term ‘enterprise-architecture’ has often been (mis)used to denote a very small subset of the real scope, relating to IT-infrastructure or IT-systems in general. This (mis)usage probably arose from a simple conflation of the term ‘enterprise- or organisation-wide IT-architecture’. The result, however, is a very serious term-hijack: the tiny subset of the overall enterprise represented by IT purports to be the whole, with all other aspects of the enterprise – including people, purpose, physical facilities and non-IT machines of any kind – either concealed or denied. In effect, it becomes all but impossible to discuss any aspect of enterprise-architecture without being forced to describe everything in terms of IT – even in contexts where IT-systems are either not relevant or not available.

Vested interests: There are huge vested interests in maintaining the story that ‘enterprise-architecture’ relates only to IT. Many, many billions of dollars are invested each year on IT-systems that purport to resolve inherently-complex enterprise-scale concerns such as customer-relationships, market-relationships, regulatory-compliance and the like. However, by definition, many if not most of these systems are incapable of resolving all aspects of the respective concerns, in effect converting them into non-resolvable wicked-problems; maintaining the ‘enterprise-architecture’ term-hijack makes it possible to conceal or deny the inherent dysfunctionality of the systems, instead maintaining the faith or fiction that the problems created can only be solved by yet another IT-centric system at yet further cost. There are also large vested-interests in training, certification and the like for IT-centric ‘enterprise’-architectures.

Assessment and action: The starting-point for assessment was a simple review of the term itself, deriving the natural-meaning via term-inversion. The ‘natural-meaning’ of a term is the meaning implied by the individual words of the term. The term-inversion here is ‘the architecture of the enterprise’: hence the natural-meaning is ‘anything to do with the structure and purpose [architecture] that underpin the emotional drivers and actions (the animal spirits of the entrepreneur”) in the shared context [enterprise]‘. The purported exclusive-association of enterprise-architecture with IT does not occur in the natural-meaning: in fact the role of IT in the enterprise-architecture is implied only peripherally, as a minor aspect of support for ‘the animal spirits of the entrepreneur’. In other words, what we’re dealing with here is definitely a term-hijack – and an extremely unhelpful one at that, because the constraint on the scope (i.e. ‘enterprise’-architecture constrained solely to IT aspects of the enterprise) has such a limited connection with the actual scope (which would naturally focus more around people than machines).

Most of my work in the past decade, and particularly the past five years, has been focussed on finding ways to highlight the term-hijack, to resolve the resultant problems and dysfunctionalities, and to create models, methods and frameworks to guide a true enterprise-scope architecture, in some cases all the way out to a global scale. The public outcomes of this work so far include several books, a couple of dozen conference-presentations and other slidedecks, and many, many weblog posts.

End-result: We are getting somewhere with this one. Most ‘enterprise’-architecture conferences these days do explicitly include some discussion of the enterprise-scope beyond IT, usually under a banner of ‘business-architecture’, and there’s much stronger linkage to true business-architecture models and techniques such as Business Model Canvas. The real danger now is there’s a tendency towards ‘business-centrism’ rather than ‘IT-centrism’ – in other words, where the architecture sub-domain of ‘the business of the business’ rather than the sub-domain of ‘the IT-systems’ becomes used as the base for yet another term-hijack. The crucial understanding that we’re still somewhat struggling to get across to most of the players in the field is that in a true enterprise-architecture, everywhere and nowhere is ‘the centre’.

But yes, we are getting somewhere with this one. Slowly…

Summary

So that’s what I do, and how I do it:

• explore a context that is of interest to me
• identify the conceptual mismatches that occur within that context, and that make it difficult to achieve effective results within that context
• identify the vested-interests that drive and maintain the current dysfunctionalities in the context, and, where possible, devise strategies and tactics to disarm and disengage those vested-interests
• assess the details of the dysfunctionalities in the context, and identify or design workarounds for those problems, and methods to work on the context when the dysfunctionalities are disengaged
• document the end-results in various forms, as appropriate

It’s a lot of work, and sometimes very painful work, but someone has do it?

A gentle warning on occupational-hazards

To anyone who might want to do this kind of work, I really ought to add some important caveats.

The work itself is actually not that hard. All it requires is a willingness to let go of assumptions, and tackle each of the issues with a rigorous attention to discipline, following the ever-changing rules of the different disciplines that apply at each moment whilst working in that context. Using beliefs as tools can be kind of challenging at times, but again it’s just another skill, and one that’s not that hard to build up over time.

It’s the social aspects of the work that are hard: sometimes very hard…

For starters, it’s often lonely. Very lonely. Part of that is because there aren’t many people who do this kind of work: at a guess, from what I’ve seen around the net and elsewhere, there may be as few as five or ten thousand people in the entire world who work in this space. Social-media does help to ease the loneliness a bit – the people I work most closely with are scattered literally across the entire globe – but it’s not the same as working in close proximity with close colleagues every working day.

Another part of the loneliness is that the feeling of loneliness – and likewise insistent sense of self-doubt – is actually inherent in the work. It’s almost an indicator of success: as Whitney Johnson put it in her HBR article ‘Disrupt Yourself‘, “If it feels scary and lonely, you’re probably on the right track”. To put it the other way round, the times when we feel most certain are probably the times when we’ve most likely missed the point. It’s hard, and it usually hurts, every single day: so if you can’t cope with a relentless, all-pervading feeling of failure, and yet somehow still create the required results, you really shouldn’t to do this work. There are plenty of other much easier ways to make a living, after all. (This isn’t a macho thing, “I’m tough” and that kind of garbage: in my own case, to be honest, I’m probably not suited to do most other kinds of work anyway. For me, though, there’s a real sense of ‘a calling’, an inner drive to do this work, whether I want to or not: and often that’s the only thing that keeps me going… )

Another crucial point is that whilst there’s a great need for this kind of work, there’s also a huge ‘anti-want’ for it. Every aspect of this work implies some kind of mythquake; and anyone who has a vested interest in the status-quo – which in effect that includes most of our would-be employers, amongst many, many others – will not want that mythquake to occur. It’s disruptive: it is, in a very literal sense, often anarchic. So for much if not most of the time, we’ll need to do the work ‘by stealth’, embedding it in other more conventional analysis-work or the like. Doing it ‘by stealth’ is often the only option if you’re an employee, and even then it can be risky: as one of my ProFuturist colleagues put it, “if you’re employed as a professional futurist, and you’re not being fired at least once every year or so, you’re probably not doing your job properly!”

In my own case, I’ve never been an employee: only ever a self-employed contractor, an independent consultant or running my own business. I’ve survived somehow, though often I don’t know quite know how – it’s certainly not an easy way to run one’s professional-life. But I’m well aware that’s not a viable option for many people, especially those with young families. If you are an employee, and you want or need to do this kind of work, you definitely need a Plan B – and work hard on building and maintaining your professional reputation, such that you can recover from being fired after that ‘one disruption too many’.

Another subtle problem that affects many of us arises from the fact that this work requires us to be very good generalists. The good part of being a generalist is that we’re able to learn fast and be interested in anything, at any level of the enterprise. The disadvantage is that, when people compare us to specialists, we almost always come off second-best – and the fact that we specialise in being generalists doesn’t seem to count, especially where the over-simplistic assessments of recruiters and the like so often come into play. In almost all of my contract- or consultancy-work in the past couple of decades, I’ve ended up doing a different (and much broader-scope) role than the one I was nominally employed for: the problem was that I somehow needed to employed for something in the first place, and that can be a real hurdle. So the catch for us is that we need to be at least as skilled as the typical specialist, whilst also being very skilled as a generalist. It’s not easy, and is one reason why the really good enterprise-architects tend to be older, often into their fifties or more – simply because it takes that long to build up the generalist portfolio and experience whilst embedded in what is (to be honest) often a complete waste of time and effort in a ‘required’ but irrelevant specialist role.

Overall, though, it’s probably the loneliness that hurts the most. But if you can cope with that, and with all of the other challenges of ‘the trade’, then yes, we definitely need you… come and join the club, perhaps?

As I read the article, my heart sank still further – though perhaps not for the reasons you might expect. Yes, the ‘bomb-detector’ has proved to be unreliable: there are huge problems on that score, without doubt. But to me the ‘betrayal’ turns out to be much more complex than it seems on the surface – because despite the ‘military-hardware’ packaging of the device in question, and its impressive-looking dials and cables and the rest, the underlying technology of the ‘bomb detector’ is a plain old ordinary everyday dowsing-rod.

Dowsing has been a serious interest of mine for several decades: over the years I’ve written what are now some of the best-known books on dowsing, in fact. Hence – unlike many of the critics – I do have some solid understanding of what’s going on in this case. And because of that longstanding background in the field, I’ll freely admit that I have few fundamental doubts about the use of dowsing in this context, not least because there’s plenty of long-documented, long-proven military practice in dowsing for land-mines and the like (contact the British Society of Dowsers for case-studies in Aden, for example, or the American Society of Dowsers for US use in Vietnam).  Like most people, I would much prefer a predictable and reliable machine to do the job, if there’s one available and it actually does work – which many don’t. But when lives are on the line and you don’t have anything else, a dowsing-rod in experienced hands can work wonders: so at least that part of this sad, messy story is no fraud. Yet that point about ‘experienced hands’ is extremely important: in unskilled hands a dowsing-rod can easily be worse than useless – as those on the receiving-end of those undetected explosives would have discovered to their cost…

(This is getting very long: better put a ‘Read more… link in here.)

Despite the protestations of pseudoscientist ‘skeptics’ like James Randi, the blunt fact is that dowsing works. Interestingly, how it works is almost irrelevant, though these days we do have a much better understanding of the psychology and physiology of what’s going on in dowsing – especially how the brain enacts pattern-processing against unconscious cues, much as in some aspects of proof-reading, for example, or ‘reading’ a stock-market ticker or a full-on fire in an apartment-block. But we also know that the instrument itself has very little impact on the quality of dowsing:  the relevant physics are so trivial that good dowsing-work can be done with a couple of bits of bent fence-wire or even a used tea-bag. The physiological constraints are also trivial – so trivial that just about anyone can do it one way or another if they put their mind to it. And the amount of knowledge needed to get started is trivial too – so trivial that most people can pick up the basics in a couple of minutes. But where so many people go so badly wrong with dowsing is that beyond that simple base, everything else depends on personal skill, on observation and self-observation, experience and interpretation – and none of that is trivial at all.

Every true skill depends on the development of judgement and awareness: my real professional interest is around identifying common-factors that apply in every skill, and using that knowledge to improve skills-education in any domain. In that sense, dowsing has been a very good test-case for that research – research which has been applied in a whole swathe of much more ‘conventional’ skills, from archaeology to enterprise-architecture, from software-development to quality-system design, and just about everything else in between. (Except sports, for some reason. I’ve never understood sports. I don’t know why, but there ’tis. )

Any skills-based technology will depend on the specific combination of the equipment and the operator: it needs to be understood as a interacting, interdependent system, not solely in terms of any of its individual components. The closer we get to a ‘pure’ skill, the more important the capabilities of the operator become – and dowsing is actually one of the closest examples we have to a ‘pure’ skill, because it consists of almost nothing but ‘judgement and awareness’. In practice, the choice and characteristics of a dowsing-instrument are often almost irrelevant, because the real ‘instrument’ you’re using in dowsing is you.

So yes, I do have some real concerns about the company selling a dowsing-based ‘bomb-detector’ for £15,000 each (or £45,000 each in Iraq, apparently), because in principle at least the job could have been done just as well with tuppence-worth of power-cable. (Belief and credibility do play an important part in dowsing-success, so there are some arguments for putting a serious price-tag on what is always going to be a very simple piece of kit – but for ethical reasons if nothing else, that price-tag should be measured in tens or low hundreds at most, not tens of thousands!)

Yet what worries me far more is the risk that this has been presented as a ‘deus ex machina’, inducing people to rely on the ‘machine’ itself (which, as the ‘skeptics’ correctly state, has just about zero capability on its own) rather than the personal skills of the operator (who can or may have the required capability, but only if the right skills-development has been applied). If the marketing-literature purports that the ‘bomb-detector’ itself does the task, it would be technological incompetence at best, because dowsing simply does not work that way – and the company should certainly have known this before they sold anything at all. If they knew, and went ahead anyway – especially without a rigorous focus on really solid skills-development – then it would indeed be fraud of a very serious kind. I would hold back any judgement on that until we’d had a chance to scrutinise the training-regime. I’d have to admit, though, that so far it doesn’t look good – which is unfortunate, to say the least.

Yet it’s important to tackle the right target here:  and I’m sure that in this case dowsing itself isn’t it. But you may think otherwise, of course – your comments, perhaps?

Update: 24 Jan

Seems there’s been quite a follow-up on this on the BBC. As usual they’ve tried to make sense of it in conventional ‘deus ex machina’ terms, with the obvious and correct conclusion that it doesn’t and can’t make sense in those terms: see the BBC article ‘Export ban on ‘useless’ detector‘. The ‘sensor card’ turns out to be a very ordinary RFID tag or some such, without any connection to any real electronics: there’s no possible way in which it can work in any conventional physical or chemical sense. But dowsers would recognise this straight away as what’s known as a ‘sample’ or ‘witness’: in effect, it’s best understood as a psychological trick to focus the operator’s mind on only the specified substance, in much the same way as the ‘cocktail party effect’, selecting out a single conversation at a very noisy party – though here the basic signal-to-noise ratio is vanishingly small, and needs to be enhanced in any way that we can. As with all dowsing, it’s based far more on psychology than physics, so attempting to assess in strictly physical terms not only makes no sense, but is literally unscientific. Worse, as with all skills – in fact, exactly as with operation of a conventional sonar/radar mine-detector – the ‘bomb-detector’ process needs to be understood as a complete system, the intersection of equipment and operator: but in this kind of analysis they’ve ignored that fundamental constraint, and instead tested the least-active part of the overall system, which again is flat-out unscientific – applying controls for parameters which are not even in play, and applying no controls for the parameters that do affect the system. Would be good if some of those self-styled ‘scientists’ had any real grasp of what true scientific investigation actually requires, but there ’tis…

Hence bleakly amusing to see the BBC’s evident surprise when the Iraqi Interior Ministry says that it does trust the devices: see ‘Iraqi Interior ministry still backing ‘bomb detector’‘. Part of that trust may come from the fact that they’ve so far spent a staggering $85m on the devices, of course. But at least that article does also make clear that a lot of emphasis has been placed on proper training: so actually there’s a fair chance that the device will work – in dowsing terms at least. And unlike the BBC, they do seem to be aware of the centrality of the operator in the system; but even so,the reliability will always be somewhat in question, especially for tired, scared, bored operators out on the street, day after day, dealing with an endless stream of vehicles and insults.

Judging from the descriptions, I really don’t think it’s fraud: at least, not in the sense of deliberately selling something that they know can’t work, though it may be fraud in other ways, of course. Only a proper investigation will be able to tell on that – and I don’t include the clumsy, myopic BBC hatchet-job as a ‘proper investigation’…

In many ways this whole sad mess is best understood as a clash of worldviews: the Western view, which focusses solely on the ‘objective’ world and tries to remove the person from the equation wherever possible; versus a more systemic worldview – pretty much any ‘non-Western’ worldview, in fact – which focusses far more on the person as an intrinsic and interdependent component of the ‘system’ in scope. The other deeper clash is between science-as-religion, which is obsessed with finding the Ultimate Answer to how everything ‘really works’, but will only accept answers within the confines a very rigid set of materialist assumptions; versus the much more practical technology view, which is less interested in ‘how things work’, and far more in ‘how things can be worked’ – which is not the same question.

The saddest part of this will be obvious to anyone who understands the psychology of skills-education, though will certainlynot be obvious to the BBC or the other ‘skeptic’ critics. This is that a very large part of this overall system depends on belief, and especially on the operator’s belief that the ‘sensing’ is separate from themselves, even though the operator is actually responsible for virtually all of the sensing and sense-interpretation – a complex double-bind described by the psychologist Kenneth Batcheldor as ‘ownership resistance’. The result is that if we ‘prove’ that the device ‘does not work’, in a suitably convincing manner, the belief in its efficacy will be destroyed, and hence the overall system will cease to work. Which would no doubt be taken as vindication of the aggressive ‘investigation’ – but in fact the investigation itself is the primary cause of failure. (Given his evident dislike of this class of technologies, Dave Snowden will no doubt not like me saying this, but this is in fact an exact illustration of his own dictum that “every diagnostic is also an intervention” – in this case, an inherently destructive intervention.) Which, in practice, could well leave Iraq without any form of mass-scale streetside bomb-detection – which would not be a good outcome… yet an outcome that arises directly from the so-called ‘scientific’ investigation.

I’ve no doubt that the BBC investigators were unaware of these complexities or their impacts: but there are real and very serious ethical issues here, which they appear to have failed to understand at all. Religious fanatics like James Randi are beyond the pale, and beyond reason, of course; but given that the only real ‘fraud’ here is the fundamentally non-scientific nature of their investigation, and that the destruction of a dowsing-based capability may well cost far more lives than the inevitable human-based limits on the system’s reliability, I would certainly caution the BBC and others to be a bit more cautious next time of the consequences of their no doubt well-meant but potentially lethal actions.

After Dave Snowden started accusing everyone – especially me – of ‘pseudoscience’ and ‘psychobabble’ – I began to worry. What if he’s right? What if everything I do is just pseudoscience, caught up in a cult?

(Oops – another long one: better split it here with a ‘Read more…’ link)

I re-read Beyerstein’s list of characteristics of pseudoscience in Patrick’s Lambe’s post on “Is KM a pseudoscience?“, and started to worry even more. Here’s that list:

1. Isolation – failure to connect with prior and parallel disciplines
2. Non-falsifiability – no means to invalidate hypotheses
3. Misuse of data – leveraging data out of context or beyond validity
4. No self-correction, evolution of thought – often centred round a single ‘thought-leader’
5. Special-pleading – the claim that this is a special-case that can’t be measured in any other terms
6. Unfounded optimism – unrealistic expectations
7. Impenetrability – an over-dependence on complicated ideology and obfuscation, or bluster in place of debate
8. Magical-thinking – such as “the belief that good things will result from willpower alone”
9. Ulterior motives – particularly ulterior motives of a commercial kind
10. Lack of formal training – including certification schemes that link back to #4
11. Bunker mentality – such as complaints about being ‘misunderstood’ by others, and often linked to #5 and #7
12. Lack of replicability of results – especially replicability by others under controlled conditions

For example, I often work at the places where the IT-industry and consulting-industry converge, so I would need to test both of those against that list, putting a check-mark against any of the criteria that fail:

• #1? Check – not always, but way too often for comfort.
• #2? Check – ditto.
• #3? Check – often. Usually from myopia and questionable competence (“I guess we failed to take enough account of the human factors”: BPR), though occasionally from a rather more deliberate ‘sexing-up’ of the statistics to prop up the purported position (‘In Search of Excellence’ etc).
• #4? Check – often. (All those management fads…)
• #5? Check – again, too often for comfort. (Real business-case for IT-only KM or Enterprise 2.0, anyone?)
• #6? Check. (In fact rarely anything other than ‘unfounded optimism’ – at the start of a project, anyway.)
• #7? Check – lots.
• #8? Check – ditto.
• #9? Check. (Rarely anything else, perhaps? – BPR, anyone? ERP? the dot-com bubble?)
• #10? Check. (Look at most enterprise-architecture training, for example.)
• #11? Check. (It’s usually called ‘the IT/business divide’ – or worse, of course.)
• #12? Check. (Often we don’t want to replicate the results that we actually get…)

And so on, and so on. According to that review, it looks like almost the entire industry is based on little more than pseudoscience. Oops.

And we’ve already seen from Patrick Lambe that knowledge-management is perilously close to a pseudoscience too. Also ‘Oops’, I guess.

But what about Cynefin? Surely that can’t be a cult – especially given Dave’s position on pseudoscience and the like. Better go through that checklist again, just to make sure:

• #1: Isolation? Plenty of reference to cognitive-science and suchlike – but I don’t see any evidence of cognitive-science etc connecting back to Cynefin. Looks suspiciously like spurious science to me, then. Oops.
• #2: Non-falsifiability? References to ‘retrospective causality’ in the Complex domain look a bit questionable in this regard; likewise much of the definitions of the Complex and Chaotic domains, and the interactions therein. Oops.
• #3: Misuse of data? Ditto, it would seem. Oops.
• #4: No self-correction? There is a genuine community-of-practice here, but it seems often to be silenced by a single figurehead who claims to hold ‘the only real truth’ about the discipline. Oops.
• #5: Special-pleading? Tends to be very good about challenging ‘pattern-entrainment’ in others, but not so good at applying the same analysis to itself. Claims to be a ‘sense-making’ framework, but the only way to test the ‘sense’ that’s derived is in terms of the framework itself. Kinda circular, really. Oops.
• #6: Unfounded optimism? Probably. Best let that one pass as only a minor ‘oops’.
• #7: Impenetrability? Lots. There’s the ‘ganglionic cross‘ with its cryptic markings, and the insistent demand that all devotees acknowledge that there are five domains, not four; also near-religious wars as to what each of the domains ‘really means’. Oops.
• #8: Magical-thinking? All we really know is that Dave is almost obsessively against it – which by the usual psychological games probably means there’ll be lots. Complicated pathways between domains that somehow magically change things might be a good example. A bit uncertain, perhaps, but very likely to be ‘oops’.
• #9: Ulterior motives? Lots. Celebrity-status, serious-money consultancy-fees, training-fees (see #10), sales of software that can only be used by registered practitioners (see #10), and consumable-supplies that can only be purchased from the central organisation: sounds a bit like Scientology, doesn’t it? We’d have to be fair and remind ourselves that that applies to much of the IT-trade and consultancy-trade too, but even so that’s a really big ‘oops’.
• #10: Lack of formal training? Would-be practitioners generally need some serious consultancy-time under their belt, but the Cynefin training itself is defined, run, certified and validated only by the central organisation. In other words, worryingly circular and self-referential. Kinda sounds like NLP, doesn’t it? Oops.
• #11: Bunker-mentality? Probably not in most cases, but it’s notable that the figurehead has an unfortunate habit of fulminating about anything else that can’t be forced to fit within the preferred assumptions – such as denigrating Six Sigma as ‘Sick Stigma‘, and so on, regardless of where or how it’s used. So most practitioners probably okay, but the figurehead probably not. Oops.
• #12: Lack of replicability? Lots. By definition, pretty much anything in the nominal Complex or Chaotic domains is going to have limited replicability. (There’s good replicability in the Simple and Complicated domains, of course, but also no real need for Cynefin-style ‘sensemaking’ in those two domains, so we can’t really claim that one as a plus.) Just about any consulting-assignment will be in part unique, too, so again little to no replicability there, again by definition. Also, as Dave puts it, “every diagnostic is an intervention”, so the very act of enquiry changes the conditions of the experiment, impacting on any possible replicability. And if Cynefin experiments are only repeatable by Cynefin practitioners, and everything has to be assessed in Cynefin terms, it somewhat blocks the possibility of proper third-party ‘outside’ review – kinda like the worst of ‘armchair Freudianism’, for example. Another big ‘oops’.

So is Cynefin a cult? Apparently the answer is ‘Yes’, because according to Beyerstein’s criteria, it seems to fail the ‘pseudoscience’ test on just about every count. Almost the only place where it doesn’t fail, in fact, is in the two logic-based domains, Simple and Complicated, where Cynefin isn’t much use anyway. Either way, definitely ‘oops’.

[Brief note to Dave: yup, I'm well aware that that assessment above ain't exactly rigorous and peer-reviewed and the rest, but it's a darn sight more rigorous and honest than the cheap hatchet-job you tried to do on me over the past couple of days... yes, I am indeed still angry over that...]

But that result is kind of odd, because most of us find that Cynefin is a very useful tool in consulting practice – especially in dealing with what Cynefin describes as the Complex and Chaotic domains. Hmm. Seems like something doesn’t quite match up here, does it? And we’re left with two probable reasons for that mismatch:

• either Beyerstein’s criteria do test well for pseudoscience in areas where simple Newtonian-style logic applies, but tend to break down as soon as we hit anything closer to real-world chaos – so we’ll need something other than Beyerstein and the like to validate quality in those areas
• or the whole idea of ‘pseudoscience’ is a red-herring that can be used by superannuated academics to bully others and prop up some vain and misguided ‘mediaeval delusions’ of their own ‘superiority’, in areas where their putative expertise in formal ‘proof’ by definition can no longer apply, because by definition the ‘normal’ rules of replicability and the like are no longer reliable once we move into the Disorder, Complex or Chaotic domains

Both of these could be true, of course. But let’s be polite, and assume that it’s only the first of these: Beyerstein is probably useful in the Simple and Complicated domains, but we’ll need something else outside of that simplistic rule-based world.

But how can we tell when we’re outside of the rule-based world? And what can we use in place of Beyerstein and its ilk?

For the former, the key criterion is, once again, repeatability and replicability. In both the Simple and Complicated domains, there’s always an identifiable ‘right answer’, and if we do an experiment in the same way, we’ll always end up at the same results. (A few special-cases such as symmetries in complex-math give two or more ‘right answers’, but the set of answers in that case is still identifiable, so the basic principle remains sound.) In short, it’s repeatable, which means it’s also replicable. There are definable, straightforward (more or less!) and linear sequences of cause and effect, so if we don’t get the same right-answer under the same conditions, something’s wrong – hence falsifiability. Either true, or false: hence it makes sense to describe Cynefin’s ‘Simple’ and ‘Complicated’ as the two ‘truth’ domains.

In the other Cynefin domains, things get kinda messy. The Disorder domain is where we start, before we do any sensemaking, but it’s probably best to leave it out of this discussion for now. Yet in the other two domains – Complex and Chaotic - doing the same thing in the same way does not guarantee the same results. In the Complex domain, any apparent causality will at best become apparent only after the event (a context which Dave Snowden describes as ‘retrospective causality’); in the Chaotic domain, where everything is inherently unique in some way, even the concept of causality itself makes no sense, by definition. In effect, one way that we know we’re not in the ‘truth’ domains because it’s not repeatable. Clearly Beyerstein isn’t going to be much use to us here.

But there’s a nasty corollary that follows from this. If one test of the Complex or Chaotic domains is that it’s not repeatable, how can we tell the difference between that and plain ordinary bad-science in the ‘truth’ domains? – because that’s also not-repeatable too. Following the logic of this, we discover quite quickly that there’s no simple ‘truth’-based test that could distinguish between the two, because in both cases doing things the same nominal way may lead to different answers. Beyerstein in this instance would not only not be helpful, but could be actively misleading, always labelling the workings of the Complex domain as ‘wrong’ and therefore ‘pseudoscience’. Which it might be, or might not be, but there’s no way to tell: even the concept of ‘true’ versus ‘false’ doesn’t make much sense in that kind of context. Which is a problem.

But instead of trying to cling on to a notion of ‘true’ versus ‘false’ in a context where it won’t and can’t work, what does make sense is to use some concept of value. In other words, the test-criterion we need in the two ‘value’-domains Complex and Chaotic is usefulness, not ‘truth’.

Next question: what determines ‘usefulness’? By definition this is always going to be somewhat subjective and context-dependent – but that doesn’t mean that it’s a random free-for-all. Feyerabend’s anarchic dictum “anything goes” does indeed need to hold sway here, but it’s a disciplined ‘anything goes’ – a considered, functional form of anarchy, if you like (or even if you don’t). In turn, this brings us into the well-understood (if, by its nature, not necessarily well-defined) realm of quality-management. Which brings us to all those tools that Dave has so happily despised, such as Six Sigma and the like.

The problem – and again for some impenetrable reason Dave doesn’t seem to like this fact – is that each of these tools is context-dependent. Six Sigma, for example, is all about managing quality in terms of defects per million events: so it only makes sense to use Six Sigma if we have millions of exactly-identical events, which in practice places us in Cynefin’s Simple domain. If we’re not in the Simple domain, don’t use Six Sigma: simple, really. No need to make a song-and-dance about it and denigrate it as ‘Sick Stigma’, because it’s perfectly fine where it does work. Same with every other tool and technique: we switch between them according to context.

Within any given context, I’ve also found it useful to compare against a relatively simple yardstick of effectiveness. In my own practice, for the past decade or so, I’ve used a frame which describes effectiveness in terms of five distinct dimensions:

• efficient: makes the best use of available resources – typically the least wasteful use
• reliable: can be relied upon to deliver the required results, optimised over the required timescale
• elegant: aligns best with simplicity, clarity, ergonomics and other ‘human factors’
• appropriate: ensures that the delivered results are ‘on purpose’
• integrated: assists in bringing everything to work together as a unified whole

All of these need valid metrics: and in general, any appropriate metric will do – even if sometimes it’s just a 1-5 subjective scale, such as I use, for example, in my SEMPER organisational-capability diagnostic. Once again, in effect ‘anything goes’ here: the selection-criteria for metrics revolve around effectiveness, not ‘truth’.

And ‘truth’ approaches – such as Dave has so aggressively promoted in the comments to the previous post and elsewhere – really aren’t much help in deciding metrics and models here, because ‘truth’ only applies to part of the context, as we’ve seen above. True/false logic can’t lift itself by its own bootstraps: it can work within a set of assumptions and postulates, but it can’t be used to define or validate them. (Attempting to do so is known as ‘induction’, otherwise known as ‘cheating’ – or ‘pseudoscience’, of course.) So to make it work we have to jump up a step to a kind of ‘meta-level’, which, as I said in the previous post, might be called ‘nonrational’ or ‘arational’ or ‘metarational’, but I prefer to use the good old classic term ‘magical’. Which Dave doesn’t like, but that’s too bad, bluntly. (He also doesn’t like the alternate term ‘technology’, so he’ll just have to lump it, really.)

To help in deciding metrics and models and the like, we need to run the whole thing reflexively and recursively. (I’ve described in some depth how to do this in whole-of-enterprise architecture in my book Real Enterprise Architecture, if you’re interested.) The Cynefin frame is useful for this: we run it backwards, so to speak, to help us identify what needs to be handled in an appropriate manner for Simple, Complicated, Complex or Chaotic.

Even more useful than Cynefin for this, as mentioned in the previous post, is the frame that we developed for Disciplines of Dowsing. And as you’ll see from the two-page reference-sheet, the reason why it’s even more useful is that not only does it describes characteristic to help us identify which mode or domain we’re in, but also how to recognise when we’re losing discipline within that domain, and reasons and tactics to move from one domain to another. For example, if we’re in the ‘Scientist’ domain (i.e. Cynefin ‘Complicated’ domain), and we start getting emotional and defensive or aggressive about it, that warns us straight away that we’ve allowed ourselves to drift towards the ‘Priest’ domain (Cynefin ‘Simple’ domain), and either need to get the emotion out of it to return to the Scentist, or else intentionally switch to the Priest, or one of the other domains, as appropriate. The result is that we maintain discipline throughout the whole space – not solely in the ‘truth’ domains, as with Beyerstein and the like.

I’m well aware that dowsing and suchlike may feel a bit uncomfortable for some folks here, but unfortunately it’s the only example I have available right now. (There’s another variant in the Berg Time & Mind article, showing how to balance subjective disciplines in archaeological research with the more conventional ‘objective’ disciplines, but it’s essentially the same as in the reference-sheet.) Likewise the examples in the useful set of ‘seven sins of dubious discipline’ in the Disciplines book mostly relate to dowsing and archaeography. So if you’re working in knowledge-management or enterprise-architecture, for example, you’ll probably need to do some significant translation to make it work in your own work-context. But I assure that it is worth the effort: the result makes it a heck of a lot easier to work out what’s going on in a context –  especially the kind of dysfunctional, chaotic, blame-filled business-contexts that we so often have to deal with these days – because it helps to ensure that discipline of an appropriate kind is kept in play at all times.

So, to come back to the original question, is Cynefin a pseudoscience, a cult? Short answer, as we’ve seen above, is “probably not” – but you’ll probably need a little bit of magic to help you prove it!

Constructive comments and suggestions welcomed, of course – and many thanks for sticking with me this far on this.

(This has turned out to be an enormously long post – I’d better put a ‘Read more…’ link in here before continuing.)

This time the Tweet was from Cynefin creator Dave Snowden:

• snowded: NLP as Cargo-Cult psychology. Great paper http://jarhe.research.glam.ac.uk/media/files/documents/2009-07-17/JARHE_V1.2_Jul09_Web_pp57-63.pdf

The link points to a 7-page academic paper [PDF] by Gareth Roderique-Davies of University of Glamorgan, which purports to indicate that NLP (‘Neuro-Linguistic Programming‘ – a kind of self-hypnosis psychological tool) has no scientific basis, and is therefore ‘cargo-cult psychology’. I do take his point that there are some worrying flaws in NLP itself, and even more worrying flaws in many of the ways in which NLP is promoted and used these days. But I’ve seen this kind of ‘scientific’ review before, and I said so in my re-Tweet of Dave’s first message:

• tetradian: @snowded: “NLP as Cargo-Cult psychology. Great paper http://tr.im/IjbF ” <disagree: NLP has serious flaws but this is just a hatchet-job

The problem is that the reviewer is trying to assess NLP in conventional scientific terms – which makes no sense right from the start, though his world-frame would itself make it impossible to see why it makes no sense. (For enterprise-architects, by the way, this is the same underlying reason why IT-centrism or organisation-centrism is such a problem: the frame itself makes it impossible to see beyond the frame.) The title of Bandler and Grinder’s original book that defined NLP way back in the 1970s gives the reason why the scientific frame won’t work: it’s called The Structure of Magic.

Yup, that’s right: magic.

Most self-styled ‘scientists’ treat that word in the same way as IT-centric ‘enterprise’-architects treat business-architecture and beyond: namely a randomised, undifferentiated grab-bag of all the bits of reality (or business-reality, in IT-EAs’ case) that they don’t understand. And then complain that it’s a mess, and doesn’t make sense in their own chosen terms, and therefore doesn’t exist. Which is not exactly honest – and it’s certainly not helpful in practice, because magical-thinking is often the only way out of many everyday scientific, technological and business dilemmas and problems.

A small tale here. Everyone ‘knows’ that Isaac Newton was one of the world’s greatest scientists, yes? (Which he was, of course.) But not many people know that he was also interested in a great many other subjects, including religion, alchemy, astrology and much else besides: in fact he wrote more on alchemy, for example, than on all of his scientific studies put together. Edmond Halley, the then Astronomer Royal, was berating Newton for the latter’s studies of astrology: it was all nonsense, he said, ridiculous, utterly unscientific – or words to that effect, anyway. Newton’s short, sharp retort: “I have studied the subject, sir, and you have not!” End of conversation…

Which brings us back to NLP, and the structure of magic. As it happens, I have indeed “studied the subject, sir” – for more than forty years, in fact – and I guess most people reading this blog probably haven’t, so it might be useful if we do a quick tutorial here on the role and limitations of the scientific frame and mindset, and the contrasting role of magical-thinking. To do this I’ll pick up on another of today’s Tweets, from knowledge-management (KM) guru David Gurteen:

• DavidGurteen: Is KM a Pseudoscience? #KM http://www.greenchameleon.com/gc/blog_detail/is_km_a_pseudoscience/

This link points to an article by another key figure in KM, Patrick Lambe – much better thought-through and much more considered than the previous piece. Using a checklist from an article by Barry Beyerstein, he scores KM overall as having a score of only 5.4 out of 10 as a ‘rational endeavour’, and concludes that it is too close to a pseudoscience: “must do better”, he says.  But what that article misses, yet again, is the bald fact that trying to assess most of KM in scientific terms makes no sense. The only way we can make sense of it is via a magical approach.

(Yes, I know I still haven’t explained yet what I mean by “a magical approach” – give me a chance, I’m getting to that in a moment! )

Before we can look at magic, we need to understand science – as much for what it isn’t as for what it is. What it isn’t – as any competent scientist would admit – is “the answer to Life, The Universe, Everything”. Instead, it’s a particular body of knowledge, developed in terms of a specific set of methods and assumptions, and which can only make sense – or be useful and valid, rather – within a very specific set of constraints. Science has been extremely successful within those constraints - so successful, in fact, that many people fail to realise that by its own definitions it is not and cannot be successful outside of them. Therein lie many huge problems for KM, for enterprise-architecture and for many other disciplines – including magic.

This is perhaps best described in one of my all-time-favourite books, WIB Beveridge’s The Art of Scientific Investigation. First published in 1950, it’s been continually in print ever since, and remains one of the great classics of scientific research. I’ll have to quote from memory, as my copy is back in Australia, but his introduction starts like this:

Complex equipment plays a central role in the science of today, but it should never be forgotten that the most important instrument in research must always be the mind of the researcher.

Beveridge expresses concern that “perhaps not enough attention is paid to making the best use of it”. To this end he focusses on the actual practice of science, rather than solely on the end-products of that practice. Hence his book includes detailed descriptions and examples on strategy, hypothesis, the use of chance and intuition, and “the hazards and limitations of reason”. (Most of his examples come from his own field of biology and biochemistry, but they’re just as applicable to every other branch of science.) The summary in his chapter on reason is particularly important, though forgive me if I again have to quote from memory:

The origin of discoveries is beyond the reach of reason. The role of reason in science is to come afterwards, to review and reassess and to build a general theoretical scheme. … Most biological ‘facts’ are so uncertain that at best we can only reason on probabilities and possibilities.

And that last sentence remains just as true as ever, despite the advances of molecular biology and the like over the past half-century: the only certainty in science is that many things will always remain uncertain. But it’s all too easy to forget that fact: that’s where the problem starts.

It’s also all too easy to forget that ‘the scientific method’ depends entirely on its base-assumptions: it cannot be relied upon outside of their remit. For our purposes, the most important of these assumptions include:

• causality – all events are connected via cause/effect chains in a linear ‘arrow of time’
• repeatability – given the same conditions, all experiments and results must be repeatable by others
• falsifiability – every hypothesis must be framed in such a way as to enable its negation by experiment
• consistency – the results and hypotheses in each domain of science cannot contradict those of other domains of science

Within those constraints, science works extremely well – and likewise, usually, any technology based on that science. But it’s essential to realise that it only works within those constraints – and there are plenty of conditions where those assumptions break down. Repeatability and falsifiability will seem to make sense whilst we’re dealing with the mid-range of scales, but in fact they break down as we move more towards  the very small – down into quantum levels, as per Heisenberg’s Principle - or to the very large – where experimentation and repeatability are often inherently impossible (at least on the kind of time-scales that we live in!). The same applies as we move more towards unique events: chaos-mathematics makes the level of unpredictability more predictable, but does not reduce the unpredictability itself. Consistency also frequently breaks down between domains: last I heard, for example, the most likely theory of star-formation requires a universe much older than ‘permitted’ by the most likely theory of cosmology. And out at the fringes of science – particularly in nuclear physics – there are plenty of examples where any linear concept of causality will break down, and at times looks remarkably like traditional magic. For example, the old magical notions of ‘action at a distance‘, teleportation and telepathy are all ‘permissible’ in current quantum-entanglement physics, and in some cases have even been demonstrated in laboratory-experiment – even if only at quantum scales.

And there are plenty of real-world, everyday examples of where those assumptions will break down – especially in KM and the like, where we’re often dealing with contexts which, by definition, are either unique or near-unique. So complaining that KM might be considered by some to be a ‘pseudo-science’ is to miss the point, because there’s no way that it can be a ‘science’ in those formal terms above. Instead, to make sense of what’s going on, we may well need to turn to other approaches: science is one approach that we might use, but it’s not the only one.

Which, by a round-about route, brings us back to where we started, with Dave Snowden and the Cynefin framework. Starting from the unknown – what Dave describes as the domain of ‘Disorder’ – we have four distinct methods to ‘make sense’ of what’s going on:

• the Simple domain: apply rules to ‘categorise – sense – respond’
• the Complicated domain: apply algorithms and logic to ‘sense – analyse – respond’
• the Complex domain: apply guidelines and heuristics to ‘probe – sense – respond’
• the Chaotic domain: force change through action, to ‘act – sense – respond’

I know Dave can get ‘curmudgeonly‘ when we place these Cynefin domains in a simple two-axis frame, but in this case there’s one frame that aligns extremely well, and does add quite a lot to our understanding of Cynefin itself. These two axes are value versus truth, and inner (personal) versus outer (collective), which gives us four domains: inner truth, outer truth, outer value, inner value. These domains map almost exactly to those four main Cynefin domains and their sense-making tactics:

• ‘inner truth’: Simple domain – rules or supposed ‘universal truths’ that purport to apply to everyone, everything, everywhere
• ‘outer truth’: Complicated domain – algorithms and the like, often with multiple factors and complicated interactions and delays, but always amenable to causal analysis
• ‘outer value’: Complex domain –  use ‘seeds’ and experiments to probe into the context, to allow meaning to emerge
• ‘inner value’: Chaotic domain – any meaning that may be derived is context-dependent and probably personal only

(The chapter ‘Can’t we explain this scientifically?‘ in my 1990 book “Inventing Reality” likens each of these modes with a means to survive within a swamp: run too fast to sink; climb up a pole; weave a platform between a group of poles; or spread your weight on swamp-shoes. The advantages and disadvantages of each mode are summarised in some detail there: might be worthwhile to read that chapter now and then come back here.)

In practice we would – or should – usually switch between each of these modes, much as Beveridge implies in The Art of Scientific Investigation. But the key point here is that a ‘scientific’ approach – which depends on causality and logic – can only make sense in the two ‘truth’ domains. Trying to use ‘truth’ tactics in the ‘value’ domains is not a good move: we risk ending up with what Dave Snowden calls ‘pattern entrainment’, such that in effect we use a quasi-religious belief as a substitute for true science or sense – which is not a good idea. (For more on this, see, for example, Amory Lovins’ video on “How the practice and instruction of engineering must change“.). Which means that we need to use entirely different approaches in the two ‘value’ domains. We could use terms such as ‘non-rational’, ‘arational’ or ‘meta-rational’ for this, but we might as well use the term that already exists for this: magical.

Magical-thinking isn’t a mistake: it’s what we need to use in the two ‘value’-domains – or, in Cynefin terms, the Chaotic domain and, especially, the Complex domain.

This post has rambled long enough already, so I’d better not go into too much detail. But one of the key tactics here is to deliberately use beliefs as tools, especially in the Complex domain, using them as if they are true whilst still recognising that they may not necessarily be ‘true’ in absolute sense. In classic scientific terms, another name for this tactic is hypothesis, as contrasted with idea (Chaotic domain), theory (Complicated domain) and law (Simple domain). It’s what we do in most technology-development: for example, we might use ideas from science, but we might also use analogy, metaphor, serendipity or even images from a tarot-deck – what works is whatever happens to work. And the fundamental question here is not science’s ‘How does it work?’, but ‘How can it be worked?’ – not how do we make it more ‘true’, but how do we make it more effective, more efficient, reliable, elegant, appropriate, integrated.

(Incidentally, this is one of several reasons why using the term ‘applied science’ as a synonym for ‘technology’ is misleading and even dangerous, because we end up applying the wrong criteria to measure that technology’s value – assuming ‘technology’ in the original sense of ‘tekne‘, a body of knowledge and related practices rather the rather incomplete sense as ‘machines and stuff’. Another concern is that by purporting to be ‘science’, a usage of technology can also attempt to claim science’s status as ‘value-free’ – and hence supposedly not subject to the ethical and other value-constraints that, by definition, are actually the core of every technology. And magic too, for that matter . In this sense, technology and science are fundamentally different from each other, whereas technology and magic are fundamentally the same. In fact the only real difference between the latter is that magicians tend to be a bit more ‘way out’ in their choice of beliefs, especially when the technology is more about mind than matter.)

Whichever mode we use at any given time, the key to all of this is discipline. (This applies in magic as much as in any other technology: as the pseudonymous author of the influential SSOTBME put it, “all those boring meditation books are just the magical equivalent of a school chemistry primer”. But that’s another story… ) Which, finally brings us to why I wrote this post in the first place, because we need a disciplined approach not only to the use of each domain, but also to how not work work within each domain, and how instead to switch between the domains in an effective, intentional manner.

Most readers of this blog would know me as a specialist in whole-of-enterprise architecture. But my real interest, and real work, is in methodology and meta-methodology – the design of methodologies to suit each specific context and need. Behind that, what really concerns me is the process of developing skills as true skills capable of dealing with the complexities and chaos of the real world – rather than as glorified ‘trainings’ that are only usable in the safe, easy purported-predictability of the ‘truth’ domains. I’ve been engaged in this work for well over forty years: for example, one of the tools I developed that you may have seen is the Skills Labyrinth, a live-metaphor for the skills-learning process.

But one of my primary test-cases for this – mainly because it’s almost the closest I can find to a ‘pure’ interpretive-skill, with very little manual-skill and technical-knowledge required to get started – is what’s known in Britain as dowsing, the generic for ‘water-divining’ and the like. (Each country has their own term for this: Americans would know this as ‘water-witching’, for example, whilst Dutch might call it ‘wichelen’.) It’s a classic ‘magical’ skill, sufering – as so many do – from an overdose of idiots, and much-derided by self-styled ‘skeptics’ who rely only on ‘scientific’ theory rather than technological practice and hence don’t have any real grasp of what they so obsessively dismiss. (As it happens, we know a great deal about the physics, physiology and psychology of the skill: one key point we now know for certain is that there is no single mechanism involved, but rather a complex ‘weighted-sum’ merge of multiple mechanisms. Hence most of the classic means of scientific enquiry – “how does it work?” – make little sense, whereas technological enquiry – “how can it be worked – does indeed work well here.)

Worldwide, I’m actually better known as a writer on dowsing and related subjects than on IT or enterprise-architecture: my first book on this – nowadays known as The Diviner’s Handbook – was first published in 1976, translated into some dozen languages, has been in print continuously ever since, and is regarded as one of the standard reference-works on the subject (or learning-guide, rather, because that’s its real purpose). And I apply exactly the same rigour to my work in that field as I do to anything else: I insist on keeping myself, and others, strictly to the correct discipline in the appropriate domain. Which at times is not ‘scientific’, of course – but so what? If the ‘scientific’ mode is not appropriate in that part of the technology, don’t use it! Which is exactly the same principle as we need to apply in KM, or enterprise-architecture, or anything else that is inherently complex and in any way inherently unique, and hence where the usual constraints of ‘rational repeatability’ and the like do not and cannot always apply.

Hence yet another book of mine, co-authored with the archaeographer Liz Poraj-Wilczynska, and published late last year, called Disciplines of Dowsing. (You can download the e-book version for free from the website, though please consider buying the print version if you’re going to use it in practice!) Parts of this work have also been published in the Berg peer-reviewed academic journal on archaeology, Time & Mind. In it we explore the application to dowsing practice of the same four approaches to sense-making and action, linked to Cynefin as above, and cross-linked to standard quality-improvement tactics such as kaizen, the Deming/Shewhart PDCA cycle, ISO-9000:2000 and reflective methods such as After Action Review. It’s the same principles, applied in a slightly different area to what most KMs and EAs might know, but otherwise no different at all. What is different – and which we haven’t seen anywhere else – is an explicit emphasis on how and when and why to switch between each of the disciplines. Which, in turn, we could – and, I would argue, we should – apply in turn to our other everyday work-domains such as KM and EA and the like.

There’s also a strong emphasis in the book on how to identify and avoid some all-too-common pitfalls, the ‘seven sins of dubious discipline’ such as the Hype Hubris, the Newage Nuisance and the Meaning Mistake. (‘Newage’ is perhaps a more accurate term for much of what purports to be ‘new age’: it rhymes with ‘sewage’, ‘the discarded remnant of what was once nutritious’… yup, I can be a cynic too! ). But the point here is that, again, there are exact equivalent of the ‘seven sins’ in every other kind of skill, including those in the sciences: for example, Roderique-Davies’ paper on NLP includes several all-too-obvious examples of the Meaning Mistake. If we don’t understand the limitations of science, and worry too much about seeming ‘unscientific’ or ‘pseudoscience’, we’re likely to end up damaging the quality of our skill and our results rather than improving it. In that specific sense at least, magic is real – and as Cynefin shows us, it matters just as much as science and the like to the quality and validity of our practice.

In addition to the e-book of Disciplines of Dowsing, there’s also a two-page reference-sheet that summarises the four sets of disciplines, and that’s perhaps more immediately usable in practice. (The material on the ‘seven sins’ is only in the book, though.) It’s written for dowsers, of course, but it doesn’t take much translation to apply it direct to KM, EA, software development or any other complex-domain skill. Download it, perhaps, and let me know how it works for you? And thence it might be worthwhile writing another version specifically for KM or whatever. Something different to play with, anyway.

Being an ‘alternative’ field, dowsing does suffer from more than its fair share of kooks and flakey ‘New Age’ types, but at present there’s a much stronger emphasis on practicality, professionalism and discipline – hence my book on Disciplines of Dowsing that I co-authored last year with archaeographer Liz Poraj-Wilczynska, and a set of related articles (see summary [PDF]) that we wrote for the society’s journal, which was the reason why I was at the conference. An interesting bunch.

So for me it was no surprise to find some innovative ideas there – some of which were definitely relevant to other fields, including business-architecture and enterprise-architecture.

One which bridged the gap between dowsing and technical world was a lovely Google Earth ‘mashup’ by Hugo Jenks, linking traditional dowsing techniques to current GIS (geographical information systems) with a purpose-built embedded-controller and an ingenious software hack. One of the standard dowsing techniques uses a single horizontal rod with a vertical handle as a mechanical amplifier to highlight small hand-movements. Hugo had made up a version of this with twin sensors to record the deviation either side of straight-ahead (the dowsing ‘signal’); he then fed this in real-time into a laptop which also had a GPS card to record position. A button on the dowsing-rod handle could also be used to trigger a GPS ‘waypoint’ marker to record specific key points of interest. With this array, he was then able to map the signal – again in real-time, if required – onto Google Earth, as a direct trace of response. A simple grey-scale indicated response-intensity, using a mid-grey as neutral, with white and black as the two extremes. The demonstrator video showed a clear mapping of below-surface structures on an archaeological site. Given the increasing use of dowsing in archaeology as a rapid non-destructive survey technique, this looks to be a really useful addendum to that toolkit – especially as this approach enables us to do away with the cumbersome stick-and-string survey-grid typical of many site-surveys, and also allows arbitrary granularity of search. Interesting.

Somewhat earlier I’d had a lengthy conversation with an engineer (whose name I forgot to record, much to my chagrin) about Stafford Beer’s Viable System Model – one of the cornerstones of systems-theory in organisations, that I reworked into a whole-of-enterprise ‘viable services model’ for my book The Service-Oriented Enterprise. This guy had done his Masters degree with Raul Espejo – Stafford Beer’s right-hand man on the Cybersyn whole-of-nation information-system in Chile in the 1970s – so was able to tell me a lot more about that ground-breaking work on organisational complexity.

Finally, an excellent conversation with an architect (Elizabeth Phillips or Catharine Fortlage, I think?) about physical architecture supporting organisational architecture, and the need to link the organisational silos or ‘tribes’:

Design the floor-plan to be like a wandering path through the jungle; each tribe has its own patch, its own personal space, yet there are shared ‘watering-holes’ – neutral spaces owned by everyone and no-one – where anyone from any tribe may meet any other.

This reminded me of some work we did a few years ago with state-police in Australia, where our brief from the executive was to create a metaphoric ‘totem pole’ to “unify the tribes” within the police-force itself. That conversation pointed me to the burolandschaft (literally ‘office-landscape’) movement of the 1950s; then to a really useful 1993 article – “A Vision of the New Workplace” – on the impact of management-theories such as Business Process Reengineering on office-design; and thence to ‘Origins of the Office’, another useful resource on working environments, office paradigms and interplay between management-theory and workspace, embedded in a website by architects Caruso St John for the Arts Council of Britain.

The moral of this story? Innovation and ideas can arise from anywhere, and the most useful ones often arise from unexpected places. As Louis Pasteur once put it, “in the field of research, chance favours the prepared mind”; if we only allow ideas to come from the expected places, we’re limiting our chances!

As David puts it, “WOW!!!” – very impressive indeed, and definitely reminiscent of the system shown in the sci-fi film Minority Report. What worries me, though, is that there’s a significant risk of a serious term-hijack here. As a “wearable gestural interface” to contextual information available via the net, ‘SixthSense’ is certainly an innovative form of augmented reality; but that’s all it is – it’s just clever technology, not ‘sixth sense’ in the traditional meaning of the term.

Probably the closest definition of ‘sixth sense’ would be “access to information which is not available directly via touch, taste, sight, sound or scent”. So any form of indirect sensing – such as plain old telephone or television, just as much as internet data-sources – is technically a kind of ‘sixth sense’. Another often-cited component is synaesthesia, any kind of cross-merging of the senses – so that aspect of the definition would apply to SixthSense too, because it cross-maps the indirect net-derived information with that arising from the immediate physical world. But not only is there a real danger of IT-centrism – where the technology becomes the sole centre of attention, ignoring the purpose for that merging of information – but we also risk assuming that we should constrain the meaning of ‘sixth sense’ to the available information solely to that which already exists in accessible form on the net. If we do the latter, without full awareness of doing so – in other words, if we fall for the implied term-hijack – we could entrap ourselves within three potentially lethal problems:

• we may shut out other information-sources, including possibly our own senses – “lost in cyberspace” etc
• we may limit ourselves only to what is already known – risking loss of insight or innovation
• we may be unable to test or verify the reliability or trustworthiness of the ‘augmented’ information-sources

From a human perspective, it’s essential not to limit our sources of information, because each can both provide unique information of its own, and also provide cross-checks against the sources, This is a key theme in enforcing transparency via the ‘social web’, for example. But it also brings us to the more traditional meaning of ‘sixth sense’, via the often strange concepts – or experiences, rather – such as psychometry, remote-viewing, telepathy, dowsing and the like. Generically these are often classified as ‘inituive skills’ – where the word ‘inituion’ literally translates as ‘teaching from within’. I’m well aware that self-styled Skeptics and other followers of the fundamentalist religion of ‘scientism‘ may have difficulty with any such notions, but as it happens, I’ve studied dowsing or ‘water-witching’ for several decades now: my first book, a kind of ‘teach-yourself guide’ nowadays known as The Diviner’s Handbook, was first published way back in 1976, and has been continuously in print ever since. This perhaps seem a bit of a surprise if you’ve only only known me as an enterprise-architect, but as far as dowsing is concerned, I’m generally regarded as one of the world experts in the field – particularly in its intersection of theory and practice as methodology. I do know what I’m talking about here: most self-styled Skeptics don’t. (At which point I’m reminded of Isaac Newton’s retort to astronomer Edmond Halley when the latter mocked his extensive writings on astrology: “I have studied the subject, sir, and you have not!” )

The point there is that in all of these intuitive-skills there’s a clear gradation from straightforward physical synaesthesia (one that for some people does quite literally resemble IT-based augmented-reality) all the way through to what we might describe as ‘good question…’; most people seem to make a big fuss about the ‘good question’ end of the scale, but in practice it’s the more ordinary world that is more important in most dowsing work, and, crucially, it is a learnable skill, dependent on much the same disciplines as for any other skill-based technology. (More info on that in my book Disciplines of Dowsing, co-authored with archaeologist/archaeographer Liz Poraj-Wilczynska.) Because this is technology, not science, it’s not ‘fraud’ for such intuitive information to come from any mixture of sources: it’s just information. (Though it’s often important to be able to identify which source the information arises from, so as to be able to verify the information-value – a theme we’ll return with the third point above.)

If we only limit ourselves to known sources of information, we’ll be unable to discover anything new. Often, for example, we’ll come across instances of a tactic I describe as “In order to remember something you never knew, first set out to forget it”. The mathematician Henri Poincaré provides one famous anecdote of this kind:

The circumstances of the journey made me forget my mathematical work; arrived at Coutances we boarded an omnibus … At the moment when I put my foot on the step the idea came to me, without anything in my former thoughts seeming to have paved the way for it, that the transformation that I had used to define the Fuchsian functions were identical with those of non-euclidean geometry. I did not verify this, I did not have the time for it, since scarcely had I sat down in the bus than I resumed the conversation already begun, but I was entirely certain at once.

This is a key theme in one of my favourite books, William Beveridge’s The Art of Scientific Investigation, which explores the use of chance, the use of intuition, the hazards and limitations of reason, and suchlike concerns in the process of scientific research. (Another example quoted in Beveridge’s book is Kekulé’s well-known story about how he discovered the ring-like structure of benzene: at the end, he urges his fellow-scientists, “Gentlemen, we must learn to dream!”) So the science of science itself is still something of a mystery: a century or more later, we still don’t know much about how these processes work, but we do have a much clearer understanding of how they can be worked – in other words, the technology and methodology, rather than the science. To quote Louis Pasteur, “In the field of scientific endeavour, chance favours the prepared mind”; yet if we arbitrarily constrain our sources of information, we’re limiting our chances. An open mind matters here – and ‘open’ in every sense, too.

Finally, by what means can we test and trust the information from these ‘augmented’ sources? Much of the self-styled ‘New Age’ teachings, for example, might perhaps be described not so much as ‘channelling’ as an open drain: no cross-checks of any kind, and far too often just ‘received truth’ for the gullible and self-deluded. But is much of what’s on the internet really any better? Google Maps’ interpretation of British post-codes is notoriously variable in its accuracy: I’ve sometimes found it to be half a mile or more off-target, especially in the smaller towns and villages. As a desmonstration of the technology’s potential, the SixthSense presentation was brilliant – but I really do have serious doubts as to how well it would work in practice. As with cloud-computing, Enterprise 2.0 and the rest of the current hype-wagons, there are some really serious questions about security and data-quality and the like that will need to be addressed before it could be trusted for use in any non-trivial real-world application. And as with other IT-hype term-hijacks, that’s exactly what usually doesn’t happen, because the hype is itself used to block out any visibility of those broader issues.

So yes, SixthSense is an excellent demonstration of net-based augmented-reality’s potential: but it’s important that we don’t let the hype and excitement block out the broader, richer, traditional meaning of ‘sixth sense’.

A couple of years ago it was Mike Mepham, who worked with me for some years in the Wordsmiths days, back in the mid-1980s, and went on to fame amongst puzzle-fans as the person who brought the Sudoku craze to Britain. This time it’s a perhaps more famous friend, John Michell (see the obituary in the London newspaper The Independent).

The rather gushing obituary concentrates on his writings, and indeed it was his The View Over Atlantis – the ‘rather peculiar book’ that my parents brought home from a Bristol bookshop in 1969 – that really started me on my own earth-mysteries researches, building on previous schooldays-experiments with Tom Lethbridge’s work on dowsing. I’ll admit, though, that I found almost all his later work impenetrable to the point of incredulity – with the exception of a brilliantly acerbic little poem written in the aftermath of the unprovoked assault by police (the Battle of the Beanfield) at Stonehenge in 1985:

…but here’s the subtle dodge:
Stonehenge has now been proved to be / an old Masonic Lodge
…[so] they’re not just simple coppers / spoiling other people’s fun
they’re members of the Brotherhood / out worshipping the sun

But to me it wasn’t the writings that that meant so much: it was the man. One who saw the world through rose-tinted glasses – literally so. A cultured Etonian voice; a sculptured, elf-like face; a bird-like manner, quick, sharp, like a heron; an intense scholar’s intelligence balanced by bright wit and a warm, genuine inclusiveness – I was stunned when, at a book-launch of mine a few years back, he told me that he regarded me as one of his peers, because to me he had no real equal either then or now. An eccentric in the best sense of that term: one who stands aside from the usual centre, and applies that leverage to change the world.

I last met him a year ago, at the Megalithomania gathering in Glastonbury. (Reading the Megalithomania site, I’ve just realised I’m a bit late in this – John died almost a month ago, 24th April. His obit was in The Independent only yesterday, though, and that was the first I’d heard of it.) He’d always looked older than his age – back in the 60s and 70s he looked to be in his sixties at least, though I now realise he must then only have been in his mid-forties – but he was definitely looking old by then, yet still active, engaging, aware, alert to all the subtle nuances of ideas.

Yes, and a real ‘character’ too. The obit coyly states that he “joined the civil service as a Russian interpreter”, but it was more likely the intelligence-service, either MI5 or MI6: in other words, he was, bluntly, a spy – part of the same Cambridge clique that produced the double-agent Kim Philby. Yet though he may have come from the Establishment, he was certainly not of it: there is a happily apocryphal tale of him in one of his post-Cold War visits to Moscow, chatting to the security-guards at Vnukovno airport whilst rolling up a joint literally under their noses, lighting up and waving to them as he wandered out of the door surrounded by a cloud of that so-characteristic aroma. It undoubtedly never occurred to him to be concerned about its extreme illegality, and they probably never had a chance to notice: like the best of anarchists, he harmed no-one, yet he made up his own rules everywhere he went.

Oddly, I know almost nothing about his earlier life beyond his writings and research. The Independent obituary mentions his time at university and in the Royal Navy, but no mention of parents or childhood. In a very literal sense, he seems to have come from nowhere: it certainly felt like that when, as an awed, angst-ridden eighteen-year-old, I first met him in Glastonbury almost forty years ago.

Yet there’s a quote from him in the Independent obit that seems to sum up almost perfectly his life and his work:

The important discoveries about the past have been made not so much through the present refined techniques of treasure-hunting and grave-robbery, but through the intuition of those whose faith in poetry led them to scientific truth.

Life as poetry: that was John Michell. Like so many others, my own life has been enriched by his gifts and his presence: so my thanks, and fare you well.

Aim is to give a variant of the presentation I did for the Megalithomania conference in Glastonbury last year, but this time with much more of an emphasis on the underlying disciplines that make it possible to get useful results in working with ‘alternate realities’ and suchlike – in other words, to bring it into line with the book Disciplines of Dowsing: the quest for quality that I co-wrote last year with Liz Poraj-Wilzynska, and which we’re currently adapting for archaeography and archaeology.

Looking forward to being at the conference, especially as some old friends such as Paul Devereux will be there. See you there too, perhaps?

Probably the key idea there is a systematic methodoology for subjective investigation – mapping feelings, sensing and so on. Most of the illustrations we’ve used for this have been either in dowsing – as in Disciplines of Dowsing, which, like the Time & Mind article, I co-authored with Liz Poraj-Wilczynska – or ‘perceptual mapping’ for archaeography, which we described in Time & Mind. But it’s actually generic: with a few tweaks to customise to each context, it could be used for any type of subjective investigation.

In essence, we split the context across two axes – inner/subjective <-> outer/objective, and ‘value’ <-> ‘truth’ – to give four distinct modes or dimensions, which we label ‘Artist’ (inner value), ‘Mystic’ (inner truth), ‘Scientist’ (outer truth) and ‘Magician’ (outer value). The point is that the rules and tactics we need to use in each dimension can be inherently incompatible with those of the others; but we need all of them to make sense of the whole. The methodology describes how to handle this conceptual juggling-act.

There’s a two-page summary (somewhat dowsing-oriented) at http://tetradianbooks.com/2008/09/disciplines-ref/ , and a lot more detail (but even more dowsing-oriented) in Disciplines of Dowsing, at http://tetradianbooks.com/2008/09/disciplines/ .

But I’d be very keen to adapt this to other fields of subjective research, such as we’ve already done for archaeology and archaeography. Could apply it in futures, for example, or marketing, or knowledge-management, or any part of the sciences in general wherever feelings or sensings or subjective impressions play any active part.  If that’s likely to be of interest to you, perhaps get in touch?

Still, I am managing to take some time to play tourist. Or sort-of. Yesterday I took about a hundred photos of a megalithic site at Portela de Meizo, near the northern border with Spain; will attempt to upload one or two in the next few days. And today in Braganza, up in the north-east corner of the country, some drawings, including one of an Iron Age stone sculpture of a boar that’s literally been skewered by a ‘pelourinho’ crucifix – it’s up in the citadel, if anyone wants to go hunting for it. (There’s a larger boar-sculpture, still almost intact, in the small town of Murca, about halfway between here and Vila Real, straight to the west. Took some photos of that one on my last trip here a couple of years ago.)

Tomorrow a dowsing-related workshop in the small town of Vila Nova de Foz Coa – don’t yet know what I’m supposed to be doing, as they only told me about this afternoon, and it starts at 9am tomorrow! Watch This Space again, I guess?

More later, anyways – this pilgrim must head bedwards to rest his tired self and soul for an early start in the morning…