Since my last post, life has been a little frantic, moving with little rest between three continents and a schedule that left me no time to keep up with email, let alone write blog posts or get started on one overdue article on alternatives to scenario planning. That builds on the recent 3As paper, which is getting a lot of traction on social media. But I wouldn’t have it any different; meeting and engaging with new people from various backgrounds keeps me alive and thinking. I have a few weeks before doing six days on the Portuguese Camino. If anyone wants to join in, let me know. It is 6-12 October, and the package includes bed, breakfast, dinner and luggage transport. A chance to spend six days walking and talking with Portuguese food and wine will not be missed. After that, I will be in Brazil and the US at what will be, shall we say, an ‘interesting’ time, which will take out more or less the whole of November and will include a complete masterclass on the West Coast for the first time in years. That and Paris in early December are the last chances to get up to date on the latest thinking if you want to hear it from the horse’s mouth.
But I now have a couple of weeks to catch up on a series of blog posts. I plan to return to the narrative theme next, but for the moment, I wanted to update an earlier post on the characteristics of intervention in a complex system. This is an update, so there will be some cutting and pasting of material, and I will also link that post to this. That earlier post was a bit of a brainstorming session, and eight characteristics of how you intervene in a complex system were identified. I also summarised Paul Cilliers seminal list of the characteristics of a complex system. Over time, I’ve been trying to make the list easier to remember and also to get it focused. Getting things to the point where you can create a name-mnemonic form takes time and experimentation, but I think I am there with PAGODA. I kept playing with the names but could not fit in an F for fractal, then ChatGPT (which is helpful for this sort of thing) threw out pagoda when I let it miss the odd letter, and as a Pagoda can be considered a type of fractal representation it all worked, And yes I do know its not a strict fractal in the mathematical sense of the word but it does illustrate the idea of fractality over aggregation. The process is not complete, as I need the dark mnemonic of things you should not do, but that will take some time to assemble.
To summarise the changes and why they were made. I removed Sensors as they are not a characteristic; they are something you need to set up. Patterns came out as monitoring for their emergence is again an activity, not a characteristic. I added in Proximity, which was a significant omission last time. So it was close last time, but I am much happier with it now.
Emergence happens in a complex system when many rich local interactions between actants exist. The local and rich words are critical here. If we go back to COVID-19, in most nations, there was an excellent response to the proximate threat of COVID-19, and people accepted the sacrifices, but Climate Change, which requires tremendous sacrifice, does not get attention as it is distant (although coming closer daily). In order to allow the national and international changes, you need (in a short election cycle) to change the dispositional state, which requires a focus on creating micro-sacrifices at a local level; you make it proximate in both time and space. When the number of such changes reaches critical mass, the dispositional state will undergo a phase shift that will permit larger-scale changes. I’ve illustrated this through the central issue for our time, but it applies to any organisation of any nature.. Closenge by and personal , is essential to sustainable change; change is bottom-up, although it may be stimulated top-down. From the leadership perspective, you need to see what the system can sustain rather than assuming you can work that out in advance. All of this has implications for virtual and physical working as we don’t get the same sensory input in a virtual environment as we do in a physical one, but measuring when people are in the office or mandating presence is not the solution; that type of draconian, context-free action will just distance you from those who work for you.
These are critical to engaging people in thinking about a problem. If you walk down a street, you don’t pay attention until you stumble, and then you start to actively think about the placement of your feet and the conditions. 83% of radiologists do not see the picture of the Gorilla, but if it were animated, they would. Methods to create descriptive self-awareness re critical to the Cynefin eco-system, and there is a wide range of methods to trigger what we have long known as descriptive self-awareness, not telling people or guilt-tripping them through facilitation but taking them through parallel processes. Hence, they become aware of differences by seeing varying patterns generated through a common process rather than being lectured or guilt-tripped; consequently, they can take contextually appropriate action.
Granularity matters and requires a Goldilocks solution. Too finely grained, and things get random; too coarsely grained, and novel interactions that would give rise to new emergent properties are suppressed. At the right level of granularity, things can combine and be recombined in different ways. The best way to date (and there will be more) to achieve this is the Estuarine Mapping instruction, which keeps breaking things down until you agree. Some aspects of object orientation in software development, including polymorphism and inheritance, are relevant here. In terms of Assemblage Theory, changing the granularity is a deterritorialisation method that can change the affordances for distributed action within a system. Constructors, an essential aspect of Estuarine, are also important here and omitting them from the Estuarine process while possibly making things more accessible (I think that is an excuse by facilitators who don’t understand the concept, so they can’t explain it) in the short term misses critical aspects of managing in complexity as they provide points of stability.
A critical concept with a hat-tip to the book of the same name by John Kay is a powerful strategy in problem-solving. As anyone with teenage children already knows, the most effective way to solve issues is rarely to tackle them head-on other than when they are trivial or as a refuge of last resort. Kay’s book contains examples of how complex and intractable problems were solved by working on a related issue. Working obliquely also means less public commitment to solving a particular problem and more time to watch for unintended consequences. It also gives more space for solutions to emerge rather than be manufactured or imposed. In general, anything explicit will be gamed, so making your objectives explicit, or God help us, your North Star, tells people what sort of things you want to hear; consequently, you can’t trust the result. Also, obliquity allows for the emergence of novelty that you could not anticipate or predict but may be more helpful. We handle that using SenseMaker® for serendipitous search and exaptive innovation, which will be formalised in future posts, but there is already material in the EU Field Guide.
Removes interpretative layers between the decision maker and the raw or finely-grained data on which a decision is based. The more layers of interpretation there are, the more that gets filtered out, and the easier it is to manipulate the decision-maker based on what is presented to them. Our work on cultural mapping takes people directly from a statistical pattern to the stories of the water cooler without interpretation. The new body of work I signalled last year on distributed decision-making goes further in removing bureaucracy, which is progressing, looking at nondirected search mechanisms that are common in nature. New work here includes ways to distribute scarce resources without bureaucratic control. I’m not releasing that into the public domain yet, so if you’re interested, get in touch.
Abstraction enables abductive insight and reasoning. At its simplest, this can be a metaphor to get people to think about things differently. We have also used metaphor-based games to break entrained thinking patterns, and archetypes (situational and persona) can achieve similar results. SenseMaker® also has an application here; in exaptive innovation and design, we bring together needs and capabilities through high abstraction metadata, using SenseMaker® to suggest connections that might not otherwise occur to people. It can also be used in decision-support applications to identify novel patterns. And then, there is the range of aporetic methods developed to handle the central domain of Cynefin; I wrote about all of this recently for those who want more details. Humans hallucinate (which includes the use of imagination), and that allows us to manage novelty without the inductive-orientated training data sets of AI, which at its heart, bullshits.
Decision-making and initiation of action are critical. You don’t want homogenised context-free interventions; every situation or aspect of a system has a different starting place. A principle here is never to aggregate an aggregate but always use the same, finely-grained source data assembled at the level of people’s competence to act. A fractal is a geometric shape in which each aspect has the same statistical characteristics as the whole. This is pretty easy to understand in mathematics, but the word is often abused in social systems and theory. It is essential to our narrative work and vector theory of change: more stories like these, fewer like those.
The opening picture of a Pagoda is by Tom Vining, and the banner picture is cropped from an original by Kristin Snippe, both from Unsplash.
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I inherited The Little World of Don Camillo from my mother and still have it in ...