There had been a radical shift in the Australian industrial relations system – after a century of centralised determination of standardised wages and conditions via a third party, the enterprise became the focus. Professor Bill Ford, originally my university lecturer and subsequently a colleague in consulting assignments, had for some time been regarded as a maverick and a disruptive influence.. ..and this shift in the legislative framework provided an ideal opportunity for a radical re think of the process of agreeing workplace arrangements.

A cornerstone of the approach was setting up learning teams, to explore issues of shared interest such as work arrangements, customer service, quality and salary systems. They were, in effect, our early version of Social network Stimulation (SNS)… even though we did not know it! An example of different disciplines coming to a similar place from different start points.

Like SNS, learning teams had ‘rules’ about membership, designed to reduce the impact of experts, and increase communication and connections across silos and different levels of the organisation. The issues that teams explored had loose boundaries ( eg find out anything that is relevant to developing excellence in customer experience), short time frames, the requirement to visit organisations in different industries and so on.

For management, there were concept teams – the group responsible for exploring new ideas and concepts to determine applicability in their own organisation. In some organisations we were able to include union representatives, and occasionally customers or suppliers.

The documentation of the agreements – required to be registered within the industrial legal system – were non legal and used ‘plain english’ – a kind of reversed disruption. . They contain purpose and intent, commitments and obligations, diagrams, and explanations of the philosophies and concepts underpinning the agreement – the intent and purpose. They were totally unlike anything that have ever been registered as a legal industrial instrument.

I have strong recollections of the beginning of the process in a number of organisations, where complaints about our insistence on using different language and concepts were loud and sometimes bordering on offensive. Standing firm on this was pivotal to the outcome being different from the industrial relations practices of the past – as soon as an organisation used the language of their past it was inevitable that the outcome departed little from the past. I remember being contacted by one CEO who had been to a well publicised presentation by a number of prominent companies on their experience with Enterprise Development Agreements.. “ I don’t know what they are but I want one”. The response being more about the CEO’s ego than an understanding of, and commitment to the process of innovation.

Which leads me to the parallels with using Cognitive Edge. There are reasonably constant complaints about the ‘use of jargon’, or ‘need for plain English’., particularly from accreditation participants. There is a real tension in making something accessible , because if it sounds too much like something we already know and we do not have to work at finding the differences – our understanding and capacities will be limited by our existing knowledge. With acknowledgement and apologies to Zen Buddhism - – ‘change only happens at the edge’ … and ‘the centre must be emptied for new learning to happen’. And from another perspective, seeing and attempting to recreate the outcomes ( such as the visuals from Sensemaker™ or the registered Enterprise Development Agreements) without the struggle of new language results in being somewhere between poor and effective imitation and ‘this stuff does not work’. Or maybe this is a polarity about disruption – with the ideal state being the capacity to embrace new language and concepts, with the excess state represented by ‘dense and impenetrable jargon’ , and the absence ‘ more of the same;’
The health warning is of course that the new language needs to really represent a shift in perspective and understanding – not the reinvention and re - badging of what is essentially the same old approach.

Necessary – but not sufficient. Some of the other ‘necessary but not sufficients’ I will comment on in subsequent blogs,

The annex was nearing completion, and the move in date was set. One of the builders said “ I thought you would be settling in the new dog today”. Me “What new dog”. He: “ The chihuahua that Bella is bringing”. Given that I had already said yes to a ferret, a bird and a fish tank and have extreme prejudice against very small dogs – and had not been asked before she collected it, I was absolutely seething.

The fast response from Bella and the ensuing conversation resulted, I believed, in a shared understanding, clarity and about expectations. I left home for 5 days away feeling reasonably self satisfied that I had dealt with a potentially challenging situation well. This morning the email from Bella ‘cancelled our arrangement’, and let me know that her furniture had been moved out. The keys were on the kitchen bench.

As I am in Brisbane on Day 3 of the accreditation course- welcome to a shallow dive into chaos! A quick flurry of phone calls to move it into complex. Dogs to be fed, and put inside. Mobilising the network to find an alternate tenant. More options to be explored in the next few weeks. A Cynefin dynamic in action …but certainly not one carefully planned – or even anticipated.

Which brings me to the world of change management – and the plethora of books, articles and experts available that all purport to provide the answers of how to do it and be successful. The implied assumptions of order and control contained in the advocated change management plans and models have always contrasted with my experience.

Aspirations are dressed up as ‘ways to do it’ – it seems to me from an approach of – “lets crate an ideal approach to achieving something, write it up and see if anyone can make it work. If they do, the case studies and conference circuit appearances- and further books will flow.’ This contrasts sharply with a ‘lets try something – and if it works, write it up’ approach- or as an ex boss of mine would say – ‘Policy will only be developed in the light of experience .’ There are always unintended consequences, and being responsive and adaptive is fundamental to not being overwhelmed and paralysed by the unexpected.

Being disruptive and being disrupted….two parts of the same process. On reflection there were of course weak signals about the situation above – even before the Chihuahua . I DID see the gorilla – just ignored it to my mini -peril.

Over the years I have tried a variety of ways to provide an answer – while ‘free range feral’ appealed to me at one time, it probably would not have engendered confidence in potential employers. Charles Handy used the term ‘portfolio worker’ to describe people whose life was a mix of activities, paid and unpaid. While this provided a veneer of respectability for the somewhat unemployable, it still did not answer the question. I finally reverted to’ I do stuff’ – some of which I get paid for’.

So it was with a great sense of relief when I first encountered Dave, and the Cynefin framework in 2003 and discovered a way of describing and revelling in being disruptive – not for its own sake, but with purpose and intent. Disruption is a life long theme for me… something which came naturally and was unable to be tamed. Now I had a way of describing it.

Embracing all aspects of disruption, the impact and consequences, both planned and unplanned seems to me to be an important part of being a Cognitive Edge practitioner. The tools and methods – and underlying philosophies - are disruptive to those who use it and those who it is used upon. As a practitioner I am constantly engaged in selecting which tools and processes to use, the level of disruption that might be tolerated, and when to ‘back off’. It is some of these issues that will form the basis of my reflections over the next 2 weeks.

The tensions of implementation were explored recently with a group of practitioners in Melbourne including…

* What are fundamental philosophies and values embedded in Cognitive Edge tools that cannot be compromised – without compromising the outcome?

* What are the core capabilities needed by facilitators and participants to effectively engage in disruption?

* When does the facilitator walk away from a process or assignment?

* How much resistance is too much resistance?

More on this in a day or so.

Jigsaw puzzles are not all born equal, and it’s about much more than size. A large puzzle just requires more patience than a smaller one, but need not be harder to figure out. One of the strangest ones I ever saw, and which I regret not buying to this day, had the same picture printed on both sides, in portrait orientation on one side and in landscape on the other, and you had to figure out which side up the pieces had to go. In the round puzzle I mentioned earlier, it was not even possible to identify all the edge pieces from the word go, as many of them did not have obviously straight edges.

But then there are the ones no amount of rationality can budge. This summer I came up against one that defied all logic – the woodland picture, with a stone bridge over a rushing brook, was somewhat blurred; elements like branches or stones were interrupted by leaves or foaming water and did not often carry over from one piece to the next, large pieces fitted next to small ones without compassion for the puzzler. Apart from building the frame, my analytical mind was of no use whatsoever. Sometimes, my hand went to a particular piece of its own volition, without me being able to explain why this piece would fit. Other times a piece almost called to me, saying that it fit the pattern of what I was doing then, while I was not even looking for it. The whole time I felt like I was grappling with an invisible foe, as if I needed ninja skills to intuit what my next move should be. Great was my satisfaction when I could finally stand back and admire the finished puzzle, all 500 pieces of it!

So I wondered – has anyone ever developed a taxonomy of jigsaw puzzles? Or constructed a Cynefin framework for jigsaws? That woodland puzzle would surely be a candidate for unordered space!

So the Foundation I work for set out to generate evidence to support solutions in all our programmes. That turned out to be easier said than done in something like a bursary programme. The sample sizes required to achieve acceptable power and discrimination using traditional statistical methods were simply prohibitive in terms of cost. All the ethical issues familiar in social research presented themselves; for example, how can we not provide the support we believe can make a difference to the bursars’ success just for the sake of having a control group in the experiment? And if we see something is not working, how can we not intervene just to get good data?

Then we get to the philosophical aspects of what constitutes convincing evidence for policy purposes. When I refer to evidence-based policy making, I often get a most cynical response. Case studies in the medical world show that a strong emphasis on data can lead to over-diagnosis and cause more problems than it solves.

So to get beyond implementing education policies just because they have worked elsewhere or seem like good ideas is not a simple problem; anyone who has experience with it or has an interest in grappling with it is most welcome to help us think about how to do it.

* Think of something that happened that day
* Start with “One day, a long, long time ago there was a …”
* Personalize the thing or animal you thought of into a character she could sympathize with
* Create a problem for the character and explore the consequences
* Find a way to solve the problem
* End with a description of how the thing or animal lived after the problem was solved.

This made it much easier to construct an impromptu story. One evening I even ended up with a pink flannel sheep social network. It started with the pink sheep on her green flannel pyjama suit. Of course the sheep was lonely; he had no other sheep within reach to talk to. Until one day (a key phrase when constructing the story), when he realized that where the pyjama top covers the pants, he could get close enough to another sheep on the pant half, and they had a lovely gossip. Then they both found other sheep they could reach across a fold of the fabric, or where the sleeve rests on the pants, and soon all the pink sheep were sharing news by passing messages up and down the pyjama suit, telephone-style.

Then she became a teen-ager, and suddenly my stories were too childish. So I threw out the story generator and started anew, thinking up more complex, darker stories that did not always have happing endings. After a few nights, we mutually decided that this did not work – it did not have the same comforting, ritual effect, for one, and it was hard work to think up original stories. For a few weeks, we stopped the stories altogether, but that also was not satisfactory: bed-time wasn’t as much fun anymore. So eventually I went back to the old recipe, choosing more grown-up characters and giving them more typical teen-age problems. This strategy lasted until she went to boarding school at the beginning of the year. When she was scared and alone that first night, I sent her a text message starting with “One day, long long ago, there was a laundry basket, which went to boarding school for the first time”, inviting her to complete the rest of the story. And that was the end of the story-telling ritual – I miss it often!

I wonder though, while the story generating algorithm started life as an effort-saving device for mom, it does represent an archetypal story plot. Will she somewhere in her subconscious, when she grows up, have a programme that says “every day brings a new problem, but never fear, every problem has a solution”?

When I started out as a statistician, there were no personal computers; we made very strong assumptions just to be able to calculate the results; non-parametric methods with fewer assumptions took all-night runs on the university mainframe for a simple hypothesis test. Then came the PC; suddenly exploratory statistics became possible – not that it was considered rigorous enough to be proper statistics back then. But I loved it – it was like being a detective, looking for structure in a mass of data, using dimension-reduction techniques to squash the information down into two or three dimensions that could be visualized and interpreted, looking for patterns in graphs and finally, when the data set gave up its secrets, finding out what the patterns I saw could actually correspond to in the real world! Unfortunately, in the first stage of analysis, the pattern often corresponded to a management decision nobody bothered to tell the poor statistician about, but that’s another story.

Sounds familiar? When I first saw the scatter plot matrix in Explorer, I felt like I’d come home – even better, I could now do the same kind of analysis on “soft” data too!

To my statistical mind, fitting linear (e.g. polynomial) regression models to data is an admission that you don’t know anything about the underlying mechanism, otherwise you would have used a more explanatory model. Linear models only represent correlations and no causality can be inferred from them; they only apply to the range covered by your experiments and cannot be extrapolated to different conditions, but they can indicate promising directions in which to search for better solutions – so again, isn’t this what one does in the chaotic domain?

So I have to acknowledge, statistical methods are applicable in the chaotic domain, especially the empirical type of methods (functional models and many other techniques fit better in the complicated domain). But I’ve never ever simply discarded an outlier, they are the most interesting species of data point!

That's how I ended up careening through the Surrey Hills, in the summer of 2003, being yelled at by a cabbie for not planning ahead, looking for a tiny little village that was a 40minute walk to the nearest bus stop. It wasn't my fault: all I had was a sketchy email telling me to show up at a 700 year old tavern called the Parrot Inn in a village called Forest Green that wasn't even on most maps.

In Forest Green, they were all characters. It didn't help that I was hallucinating from jetlag and Dave kept sending me off on mysterious nighttime errands. The material might as well have been magic (at least in the Arthur C. Clarke sense). For a week we worked our way through the theories, exercises such as anecdote circles and two-stage emergence (which remain largely unchanged today), and approaches to complex facilitation. We'd had a few Cynefin meetings by then and played with the methods, but this was the first time I'd really seen how powerful they could be with a large group.

Flash forward

For the first time in San Diego I was really able to enjoy the workshop, because I wasn't flailing wildly during the day and curling into a fetal position at night. I could sit back and watch the body language as Craig and Michael explain the theories leading to the model. It's fun to watch people struggle to grasp the concepts and then see their eyes widen when they see the implications. Others cross their arms in discomfort, confusion or outright refusal.

A quarter to a third of the participants may not be able to accept these ideas. I remember one woman, many years ago, trying to obliterate the Chaotic domain with repeated crosses of her pen, saying, "No, no, that's not good."

"Organizations are very resistant to big changes," Michael said during day one. But the same is true about individuals, and accepting, cold turkey, the implications of a world that is simultaneously simple, complicated complex and chaotic is a very big change.

It isn't an easy journey. It isn't easy to learn these ideas or to practice the methods based on them. This stuff is riskier because it is different, difficult, participatory and honest. To resist the urge to reduce problems and work on small pieces—to reject the common "idealism" that analysis will reveal right answers and best practices for every situation. "It depends" isn't a satisfactory answer, even when it is the only answer.

"When you facilitate with emergent methods, you cannot control outcomes," Michael says.

While academics were largely involved with the first two or three levels, most practitioners are still applying the ideas at the metaphor level with only passing references to mechanisms or models. More likely, they are reaching back to myths not mathematics (eg, misapplying the "butterfly effect").

My question then—and now—was: as conversations about complexity shift from describing existing behaviors to developing new approaches, how do we better integrate these levels?

That conversation led to our involvement with a project that became Emergence: Complexity & Organization: An International Transdisciplinary Journal of Complex Social Systems (E:CO). Ultimately, the editors' introduction to the inaugural issue framed the dilemma this way:

Academic discussions about complexity are often biased towards quantitative research and mathematical models that are inappropriately prescribed for systems comprised of actors endowed with free will, who are simultaneously part of and aware of the system. The metaphors of complexity have a usefulness of their own, but too often they are applied without adequate reference to the mechanisms, models and mathematics behind them.

What's most interesting to me about the Cynefin model is that it marries four ways of looking at the world that are usually thought to be incompatible. (Per Ron's comment, I'm not ignoring Disorder, just treating it separately.) With their biases for perception and action, people are likely to have blind spots for the others that cause them to misinterpret, not just miss the signals.

Take Haiti, which most people consider to be a chaotic place. This was how people saw it before the earthquake because government and international aid agencies were unable to render assistance and alleviate suufering. In fact, criminal gangs had most neighborhoods under their control—at least as far as being the dominant constraints on emergent social patterns. The distinction becomes clear when the earthquake wipes out almost all structures (in both the social and literal senses) regardless of whose control they were under and genuine Chaos takes over.

I use this example with painful misgivings. After a trip to Port au Prince last May to research formal and informal knowledge sharing in the UN Peacekeeping Mission there (MINUSTAH), I demonstrated and explained the Cynefin model to the KM team and best practice officers from peacekeeping missions all over the world.

"Think of an embolism," I said, as an example of the kind of random event that throws a system into chaos. "Or an earthquake."

Eight of those I interviewed in Haiti were lost January 12th.

"This explains everything!" is the typical reaction I get when demonstrating. Last summer, I watched this happen again when I set up a contextualization exercise for UN Peacekeepers in an ancient square in the Italian town of Otranto. For Peacekeepers, the fallacy of Order from Chaos is built into their Security Council mandates, when in fact almost every aspect of their missions straddle the boundaries of complex and complicated.

I generally introduce the model in one of two ways. Sometimes I use client anecdotes in a contextualization exercise and gradually explain more about the differences while watching participants adjust their positions. Other times, I let the model unpack from the assumption of Order and Chaos.

The Cynefin Framework fundamentally rejects the binary paradigm of Order and Chaos. But to explain the model, I think it's really important to acknowledge how much of the world sees that world as either one or the other—and how much of the world will resist seeing four domains instead of two instead of one.

It takes less effort to force every situation into the contexts you expect—and to dismiss the failures—than to juggle multiple models and multiply our options and interpretations.

In other words, most people prefer to see the world as either fundamentally ordered (mechanical) or fundamentally unordered (organic). Either way, they tend to be biased against the alternative perspective as either dangerously chaotic or oppressively regimented.

Moreover, I assume that more people have a bias for Order than Chaos—or think that they should—regardless of what their local philosophers tell them.

Oversimplification isn't just fundamental to human nature—it's fundamental to nature. Learning takes more effort than knowledge. (Biologist Dan Brooks helped me to understand this in conversations at a 2004 complexity conference in Havana.) It's not that we living creatures are lazy, but because our resources are already over-extended. Sensing our environment is information. Reacting to our environment is learning. Repeating the reaction is called knowledge. Knowledge is more efficient than learning. However, adapting to changes in the environment requires learning.

Harking back to earlier versions of the model, the horizontal dimension represented learning and training or tacit and explicit, while today the two sides signify Unorder and Order.

I know that Dave doesn't agree with me, but I actually think that they should signify "learning" and "knowledge" in a way that makes the two terms directional poles—in a way that gives them somewhat opposite meanings.

Simple and complicated (called "known" and "knowable" for a while) emphasize what we already know—or at least believe to be true—and further investigations and analysis must either accept or falsify these premises. We assume that our assumptions are correct. On the other hand, learning is largely about what we don't know. That is, we must assume that our assumptions could be wrong, which is the predominant mode in complex and chaotic domains.

The model could be seen to progress from maximum objectivity to maximum subjectivity running counter-clockwise from Simple around to Chaotic. The transitions across domain borders are gradual except between Simple and Chaotic, which may account for the catastrophic movement noted there.

To be more philosophical about it, in the ordered domains, we live by faith. In the unordered domains, we thrive by doubt.

I’ve been grappling with the Cynefin/Cognitive Edge ideas since 1999 and my sense of interpretations, implications and applications continues to evolve in a stick-slip way as the friction of old beliefs break loose under pressure. I find that a useful understanding of the foundational model depends on making it my own, by adding personal examples and baroque embellishments—most of which are likely to abrade away under scrutiny. Last week’s San Diego course helped to bring together some fragmented thoughts. Although they remain incomplete, I’m eager for feedback . Abrade away, me hearties…

So I'm curious what you think about the framework I'm sketching out.

In fact, these things aren'ty just considered inappropriate for workplace and management conversations (emotions, beliefs, ego). In some cases, it’s actually illegal to engage on this level.

I've started to work on a framework for how I see these deeply held beliefs and behaviors working their way out from that spiritual place into our personal lives, professional lives and social interactions.

So from the inside out, these successive layers look something like this:

Identity—Who are you? Where do you come from?

Faith—What do you believe about how the world works?

Values—What rules and priorities do you derive from your beliefs?

Integrity—How much do you comport to these values?

Civics—How do you balance integrity to personal beliefs/values with the beliefs/values of others in the community in order to collaborate on common or collective goals?