“We shall not cease from exploration, and the end of all our exploring will be to arrive where we started and know the place for the first time.”
— TS Eliot
Our Beyond the Basics team is about to host our last gathering of the current cycle of offers, back in North America. Over the past five Beyond the Basics offerings I have learned more than I feel like I’ve shared. I can feel that my practice has changed as a result of doing this work, and I’ve become interested in the way our team’s ideas and lessons from working at scale have begun to outline a form and practice of leadership that is needed in much of our work now.
Dave is working on a theory of change, which I think is a good thing. In this latest post he has a nice summation of the way to move to action in complex situations (like cultures):
So where we are looking at culture change (to take an example), we first map the narrative landscape to see what the current dispositional state is. That allows us to look at where we have the potential to change, and where change would be near impossible to achieve. In those problematic cases we look more to stimulating alternative attractors rather that attempting to deal with the problem directly. Our method is the look at the narrative landscape and then ask the questions What can I (we) do tomorrow to create more stories like these and fewer like those? The question engages people in action without analysis and it allows us to take an approach that measures vectors (speed and direction) rather than outcome. The question also allows widespread engagement in small actions in the present, which reduces the unexpected (and potentially negative) consequences of large scale interventions.
In sum, complexity work is about understanding the context to understand where the potential for evolution might lie. From there you try experiements to see what you can learn, and support what works while removing support for what doesn’t
It’s an old saw, but it’s actually a simple thing. And I keep writing about it because it seems TOO simple for most folks. Shouldn’t strategy be more ordered, laid out and thought through than this.
As always the answer depends, but with complex situations the answer is no. Save your discipline and rigour for understanding things as they evolve rather than trying to get it all right from the start.
via Change through small actions in the present – Cognitive Edge.
Thanks to a rich conversation with artistic researcher Julien Thomas this morning I found this video of Olafur Eliasson at TED in 2009. In this presentation he talks about the responsibility of a person in a physical space, and discusses how his art elicits a reaction beyond simply gazing at a scene. It address one of the fundamental problems in our society for me: that of the distinction between participation and consumption. So much that happens in physical spaces and in our day to day lives has been geared towards gazing and consuming and away from participation and responsibility.
I’m prepping for a small gig with a non-profit moving to a shared leadership model, and also reading a bit more on Cynefin strategy, and so there are a lot of tabs open in my browser this afternoon. instead of saving them all to an Evernote folder, I thought I’d share the best ones with you.
I have been teaching the Cynefin framework for a number of years now. Like Dave Snowden i learn as much or more from needing to share it than I do from actually deploying it. I find myself sharing the framework for three applications: strategy and decision making, leadership and basic understanding of complexity. Because the framework is both simple to describe and supported by a deep set of theory and practice, it is always a challenge to make my description simple enough to be understood, but full enough to be appreciated.
So I thought I would put out some step-by-step guides based on how I explain Cynefin to clients and in teaching situations. This is the first one, on using Cynefin to introduce complexity and it’s implications for strategy and decision making. I would love feedback in the comments, especially if I have used terms that are defined poorly or hard to understand, and also if I have made any leaps in logic that are too large to understand in one bound. The goal is simplicity and clarity in description.
Cynefin, complexity and decision making.
1. There are two kinds of systems and problems: ordered and unordered.
2. Ordered problems are predictable and knowable, unordered problems are unpredictable and unknowable. It is important to understand this point deeply, because this is a fundamental distinction that has massive implications.
3. Ordered systems have a reliable causality, that is, causes and effects can be known, and usually display a clear finish line. Sometimes this causality is obvious to everyone, such as turning a tap to control a flow of water. Sometimes this causality is only obvious to experts, such as knowing what causes your car engine to start making strange noises.
4. Unordered systems throw up complex problems and chaos. Complex problems such as poverty and racism, have causality that that only be understood retrospectively, that is by looking back in time, and they have no discernible finish line. We do a reasonably good job of seeing where it came from, but we can’t look at the current state of a system and predict what will happen next.
5. Chaotic problems are essentially crises in which the causality is so wild, that it doesn’t really matter. For example, in the middle of a riot, it does you no good to understand causes until you can get to safety.
6. Because ordered systems display predictable outcomes, we can more or less design solutions that have a good chance of working. We just need to understand the system well enough and enlist the right experts if it’s unclear what to do. Once we have a solution, it will be transferable from one context to another. Designing and building a car, for example.
7. Because unordered systems are unpredictable we need to design solutions that are coherent with the context. For example, addressing the role of stigma in the health care system requires a solution to emerge from the system itself.
8. Complex problems can be addressed by creating many small probes: experiments that tell us about what works and what doesn’t. When a probe has a good result, we amplify it. When it has a poor result, we dampen it. Strategies for amplification and dampening depend on the context, and the problem.
9. In ordered systems, linear solutions with well managed resources and outcomes will produce desired effects. We can evaluation our results against our intentions and address gaps.
10. In complex systems, we manage attractors and boundaries and see what happens. An attractor is something that draws the system towards it. A boundary is something that contains the work. For example addressing the effects of poverty by creating a micro-enterprise loan program that makes money available for small projects (attractor) and requires that it be paid back by a certain time and in a certain way (boundaries). Then you allow action to unfold and see what happens.
11. When you have a solution in an ordered system that works, you can evaluate it, create a process and a training program around it and export it to different contexts.
12. When you have a solution that works in a complex system, you continue monitor it, adjust it as necessary and extract the heuristics of how it works. Heuristics are basic experience based, operating principles that can be observed and applied across contexts. For example, “provide access to capital for women” provides a heuristic for addressing poverty based on experience. Heuristics must be continually refined or dropped depending on the context.
1 2