One has to be very careful attributing causes to things, or even attributing causality to things. in complex systems, causality is a trap. We can be, as Dave Snowden says “retrospectively coherent” but you can not know which causes will produce which effects going forward. That is the essence of emergent phenomena in the complex world.
But even in complicated problems, where causality should be straightforward, our thinking and view can confuse the situation. Consider this example.
Imagine someone, a man, who has never seen a cat. I know, highly implausible, but this is a hypothetical from Alan Watts’ book, On the Taboo Against Knowing Who You Are, which was written in the sixties; pre-YouTube. Watts uses this fictional fella to illustrate the unfelt influence of perspective and the dangers inherent in our strong inclination to seek cause-and-effect relationships.
“He is looking through a narrow slit in a fence, and, on the other side a cat walks by. [The man] sees first the head, then the less distinctly shaped furry trunk, and then the tail. Extraordinary! The cat turns round and walks back, and again he sees the head and a little later the tail. The sequence begins to look like something regular and reliable. Yet again the cat turns round and he witnesses the same regular sequence: first the head and later the tail. Thereupon he reasons that the event head is the invariable and necessary cause of the event tail which is the head’s effect. This absurd and confusing gobbledygook comes from his failure to see the head and tail go together; they are all one cat.”
We often create and embed the wrong patterns because we are looking through a slit. As Watts says, by paying very close attention to something, we are ignoring everything else. We try and infer simple cause-and-effect relationships much, much more often than is likely in a complex world. For example, making everyone in an organisation focus on hitting a few key performance indicators isn’t gong to mean that the organisation is going to get better at anything other than hitting those key performance indicators. All too often this will lead to damaging unintended consequences; absurd and confusing gobbledygook.
via abc ltd.
Our traditional Boxing Day movie this year was The Imitation Game, the new film about Alan Turing and his team’s efforts to break the Enigma code used by the German Navy in the Second World War. While the film itself was good it was full of fictional scenes that were intended to point at some of the interesting things that happened at Bletchley Park during that war. Having done a bit of reading on the subject, it’s clear that the film simplified many things, took liberties with others and glossed over what is a really interesting story, but the movie itself still holds up, even if Cumberbatch basically turns Turing into his Sherlock Holmes.
At any rate there were a few things in the fils that provided interesting reflections on some of the ideas I have working with a learning about both through my study of Cynefin dynamics (the way problems and solutions move through the Cynefin domains) and with the two loop theory of change which I am using a lot. So here are a few examples.
Solving problems obliquely. Complex problems can’t be solved by taking a head-on, brute force approach to the solution. The film is basically about this writ large, but one vignette stands out as interesting. When Turing needs new staff he devises a way to find them by running a crossword contest in a newspaper. Anyone who solves the problem in under ten minutes gets contacted by MI6 and invited to come and write a test. Although this is not how Joan Clarke joined the project, it was a good way of sorting out the talent from the confirmation biases that riddled the intelligence establishment (in this case gender bias).
Disintermediated sensemaking. The idea of letting everyone have the data and find patterns there is an important aspect of working with complexity. While the problems that the team were solving were indeed complicated, they needed to exploit complex human behaviours in order to have a chance to solve them. A complex problem is solvable with enough expertise, and indeed making a code HAS to be solvable if it is to work. If you don’t want others to solve it you simply make the encryption keys so elaborate that there isn’t enough time in the history of the universe to solve the problem. So while in theory, code breaking is a merely technical problem, in order to solve it, you have to narrow down the permutations to make it possible for the technical solutions to be applied. At Bletchley Park, this came down to reading human factors, which is something only the human operators could do. But they could only do that by having access to the raw data and by creating safe-to-fail probes of the system (by using these factors to solve the codes). When they worked, they were exploited.
There are some incredible stories about the way which the women who were intercepting messages came to know their counterparts in Germany. Each German communications officer had his own style, his own signature. And human error in creating predictable procedures meant that people could use these patterns as weak signal detection in order to break some messages, in the case of the Polish codebreakers that did much of the early work on cracking Enigma, even discern the wiring of the machines themselves. This is a classic pattern of what Dave Snowden calls Cynefin dynamics, specifically how we move from safe-to-fail probes in the complex domain to exploiting findings using complicated and in some cases obvious solutions.
This is a really interesting story, and I’ve ordered a couple of books to read in further. I’m very interested to see how the human factors were sensed, discerned, exploited. Combining that capacity with the incredible engineering talents of Turing and his crew provides some excellent stories and examples of Cynefin dynamics at work.
Hmmm…maybe I should have let the group do this…
When I popped off to London last week to take a deep dive into Cognitive Edge’s work with complexity, one of the questions I held was about working with evaluation in the complex domain.
The context for this question stems from a couple of realities. First, evaluation of social programs, social innovation and other interventions in the human services is a huge industry and it holds great sway. And it is dominated by a world view of linear rationalism that says that we can learn something by determining whether or not you achieved the goals that you set out to achieve. Second, evaluation is an incredibly privileged part of many projects and initiatives and itself becomes a strange attractor for project planning and funding approval. In order for funders to show others that their funding is making a difference, they need a “merit and worth” evaluation of their funds. The only way to do that is to gauge progress against expected results. And no non-profit in its right mind will say “we failed to achieve the goals we set out to address” even though everyone knows that “creating safe communities” for example is an aspiration out of the control of any social institution and is subject to global economic trends as much as it is subject to discrete interventions undertaken by specific projects. The fact that folks working in human services are working in a complex domain means that we can all engage in a conspiracy of false causality in order to keep the money flowing (an observation Van Jones inspired in me a while ago.) Lots of folks are making change, because they know intuitively how to do this, but they way we learn about that change is so tied to an inappropriate knowledge system, that I’m not convinced we have much of an idea what works and what doesn’t. And I’m not talking about articulating “best practices.”
The evaluation methods that are used are great in the complicated domain, where causes and effects are easy to determine and where understanding critical pathways to solutions can have a positive influence on process. in other words, where you have replicable results, linear, summative evaluation works great. Where you have a system that is complex, where there are many dynamics working at many different scales to produce the problems you are facing, an entirely different way of knowing is needed. As Dave Snowden says, there is an intimate connection between ontology, epistemology and phenomenology. In plain terms, the kind of system we are in is connected to the ways of knowing about it and the ways of interpreting that knowledge.
I’m going to make this overly simplistic: If you are working with a machine, or a mechanistic process, that unfolds along a linear trajectory, than mechanistic knowledge (problems solving) and interpretive stratgies are fantastic. For complex systems, we need knowledge that is produced FROM the system and interpreted within the system. Evaluation that is done by people “outside” of the system and that reports finding filtered through “expert” or “disinterested” lenses is not useful for a system to understand itself.
Going into the Cynefin course I was interested to learn about how developmental evaluation fit into the complex domain. What I learned was the term “disintermediated sensemaking” which is actually the radical shift I was looking for. Here is an example of what it looks like in leadership practice.
Most evaluation uses processes employing a specialized evaluator undertaking the work. The problem with this is that it places a person between the data and experience and the use of the knowledge. And it also increases the time between an experience and the meaning making of that experience, which can be a fatal lag with strategy in emergent systems. The answer to this problem is to let people in the system have direct experience of the data, and make sense of it themselves.
There are many many ways to do this, depending on what you are doing. For example:
- When clustering ideas, have the group do it. When only a few people come forward, let them start and then break them up and let others continue. Avoid premature convergence.
- When people are creating data, let them tag what it means, for example, in the decision making process we used last weekend, participants tagged their thoughts with numbers, and tagged their numbers with thoughts, which meant that they ordered their own data.
- Produce knowledge at a scale you can do something about. A system needs to be able to produce knowledge at a scale that is usable, and only the system can determine this scale. I see many strategic plans for organizations that state things like “In order to create safe communities for children we must create a system of safe and nurturing foster homes.” The job of creating safe foster homes falls into the scope of the plan, but tying that to any bigger dynamics gets us into the problem of trying to focus our work on making an impact we have no ability to influence.
- Be really clear about the data you want people to produce and have a strategy for how they will make sense of it. World Cafe processes for example, often produce scads of data on table cloths at the centre of the table, but there is often so little context for this information that it is hard to make use of. My practice these days is to invite people to use the table cloths as scratch pads, and to collect important data on post it notes or forms that the group can work with. AND to do that in a way that allows people to be tagging and coding the data themselves, so that we don’t have to have someone else figure out what they meant.
- Have leaders and teams pour over the raw data and the signification frameworks that people have used and translate it into strategy.
These just begin to scratch the surface of this inquiry in practice. Over the next little while I’m going to be giving this approach a lot of thought and try it out in practice as often as I can, and where the context warrants it.
If you would like to try an exercise to see why this matters try this. the next time you are facilitating a brainstorm session, have the group record dozens of insights on post its and place them randomly on a wall. Take a break and look over the post its. Without touching the post its, start categorizing them and record your categorization scheme. Then invite the group to have a go at it. Make sure everyone gets a chance to participate. Compare your two categorization schemes and discuss the differences. Discuss what might happen if the group were to follow the strategy implicit in your scheme vs. the strategy implicit in their scheme.
My mate Geoff Brown has a great post on complexity in practice as he aimed to get well after an injury. This is a fantastic story.
After a couple of session of observations, conversations about pain sites, work habits and past physical/medical history, my Osteopath discovered a complex pattern of underlying, causal factors that contributed to my injury. Together, these factors like tight hamstrings and assymetrical posture interact with each other to create an emerging pattern of dysfunction. Translated to English = the many little problems with my body mechanics create weaknesses that make me more vulnerable to injury. So, like in all complex systems watch the Wolf in Yellowstone National Park video below the underlying cause of my sudden injury is not that clearcut. The remediation of these multiple factors is even more complex.
Hope you’re feeling better Geoff!
via How to work with a complex system – lessons from an Osteopath | Tangent Consulting.
This afternoon I’m coming home after a morning running a short process for a church in Victoria, BC. The brief was pretty straightforward: help us decide between four possible scenarios about our future. Lucky for me, it gave me an instant application for some of the stuff I was learning in London last week.
The scenarios themselves were designed through a series of meetings with people over a number of months and were intended to capture the church’s profile for its future, as a way of advertising themselves for new staff. What was smart about this exercise was the fact that the scenarios were left in very draft form so there was no way they could be confused for a “vision” of the future. It is quite common in the church world for people to engage in “visioning exercises” to deal with the complex problems that they face, but such visions are doomed evermore to failure as the bigger organization is beginning to enter into a period of massive transformation and churches are suffering from all kinds of influences over which they have no control.
Visioning therefore is not as useful as selecting a lens through which the organization can make some decisions.
Each scenario contained some possible activities and challenges that the church would be facing, and the committee overseeing the work was charged with refining these down to a report that would, to use my own terms, be a collection of heuristics for the way the organization would act as it addressed future challenges.
Our process was very informed by some thinking I have been doing with Dave Snowden’s “Simple rules for dealing with complexity.” Notably principles about avoiding premature convergence, distributing cognition and disrupting pattern entrainment. Furthermore, the follow up work will be informed by the heuristic of “disintermediation” meaning that the team working on the project will all be working with the raw data. There is no consultants report here. The meaning making is still very much located with the participants.
So here was our process.
- At small tables of four, participants were given 5 minutes to read over the scenarios silently.
- We then entered a period of three 15 minute small group conversations on the topic of “what do you think about these scenarios?” Cafe style, each conversation happened with three different groups of people. I was surprised how much introduction was going on as people met new folks. The question was deliberately chosen not to be too deep or powerful because with a simple question, the participants will provide their own depth and power. When you have a powerful need, you don’t need to contrive anything more powerful than what people are already up for.
- Following the cafe conversations, a round of silent reflection in which people were given the following direction. “Express your preference for each of the scenarios on a scale of 1-7. Seven means “Let’s do it” and one means “No Way.” For each scenario write your preference on your post it and write a short sentence about the one concrete thing that would make your vote one point higher.” So there is lots in this little exercise. First it’s a way of registering all of the objections to the scenarios without personalizing them. Secondly it gets at concrete things that the team can do to improve scenarios and third it harvest preferences and not simple yes/no decisions which are not appropriate for this kind of work.
- At each table someone gathered all the posts its of the same colour and by colour folks came to the front and placed them on the scale. Doing it this way meant that no one was sure whose preference was going where and it also meant that people couldn’t revise their post its once they saw how the preferences were being expressed.
The whole thing took about 75 minutes.
The result of this sense making was the chart you see above. Two hundred pieces of finely grained information ordered by the people themselves. The project team now has at least three things they can do with this material.
- They can recreate the scale, as each post it is colour and preference coded. That way they have a rough idea of the scenario with the greatest support, and they can show anyone who wants to see metrics where we stand on the proposals.
- They can cluster post its for each scenario according to “work that will make it better” which means they don’t have to pay attention to the scale. The scale is completely subjective, but each of these post-its contains one piece of concrete information to make the scenario better, so in some ways the numbers don’t really matter. They can cluster these ideas by each scenario AND they can re-cluster them by each topic to give an idea of overall issues that are happening within the organization.
- If we wanted to go a step further, we could use these post it notes to do a number of Cognitive Edge exercises including a Cynefin contextualization (which would tell us which things were Obvious, Complicated and Complex (and maybe Chaotic) and we could also do some archetype extraction which might be very useful indeed for constructing the final report, which would stand as an invitation to thier new personal and an invitation to the congregation.