Design principles for managing complexity

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Current version

  1. Obliquity, a 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.
  2. Granularity matters and this is 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.
  3. Sensors are critical, and they need requisite diversity and, as far as possible, provide real-time feedback so that the weak signals of emergent patterns become visible early enough so that the energy costs of amplification or disruption are low. SenseMaker® was designed for this and has various techniques to identify where there is sufficient consensus of action. It also critically aims to find the 17% who have seen the picture of a gorilla before they talk to the 83% who didn’t. This used to be called distributed cognition, which is another way of seeing it.
  4. Abstraction enables abductive insight and reasoning. At its simplest, this can be the use of 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 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.
  5. Patterns are fundamental to human sense-making. Our work on cultural mapping shows narrative patterns rather than spider diagrams and the like, which assume causality and privilege the interpreter (which may be why some consultants like them). Humans are highly sensitive to patterns in other people’s reactions, the landscape around us, etc. We have strong peripheral vision and can quickly sense that something doesn’t seem right if, and that is an important qualification, our attention is drawn to something through some form of anomaly. Visualisation is one way to achieve this, and it’s an important aspect of SenseMaker®, which has the added advantage of the explanatory stories that sit behind the patterns.
  6. Disintermediation 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 in nature. Expect some major announcements over the next few weeks.
  7. Fractal, 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. If in doubt, remember: never aggregate an aggregate.
  8. Anomalies are critical to engaging people in thinking about a problem. If you walk down a street, then 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 was animated they would. Methods to create divergent outcomes are key 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 so they become aware of differences in such a way they can take action.

These are not a list of the characteristics of a complex system (Cillier’s list remains a good summary, but the sufficient but not necessary qualities necessary for intervention in complex systems. Cillier’s list remains a good summary

Things that you should be wary of:'

  1. Inattentional Blindness - We simply do not see the things we do not expect to see.
  2. Premature convergence
  3. Pattern entrainment - Our perception, what we physically perceive, is influenced by what we expect to see and is filtered by our existing concepts and world view. It is a first fit, not best fit, pattern recognition and privileges our most recent experience.
  4. Path dependency - Our predisposition on how to act is based on our accumulated knowledge and previous experiences, these influence the path we are likely to choose in a situation.
  5. Retrospective coherence

Things that you ask:

  1. What can I change?
  2. (out of that set) Where can I monitor the impact of change?
  3. (out of that set) Where can I readily amplify success or dampen failure?

You scale a complex adaptive system by decomposition (to the lowest level of coherent granularity) and rapid recombination Things you manage

Commentary

The scaling principle also applies to the way you resolve conflict

The common (and often not properly attributed) What, So What, Now What question sequence really needs to interweave with the above rather than apply to the situation as a whole. For more on that phrase, its origin and issues this post has some thoughts

Historic principles anthro-complexity:

  1. Work at a coherent level of granularity, which generally means to work at a lower, or more finely grained, level of detail.
  2. Distribute the cognition, when orientating a problem, issue or situation within a wider context.
  3. Disintermediate the decision-maker and the activity.

There really are only three things we can manage in a complex adaptive system:

  1. Connections
  2. Constraints and
  3. Energy allocation

Everything else is for the birds.

Things you do

  1. Identify which aspects of the system are complex.
  2. Identify, from what is in play, the things available to manage.
  3. You only need to understand enough, in order to act.
  4. From what’s in play, consider what can be modified (or modulated).
  5. From what can be modified, what can be monitored.
  6. From what can be monitored, what can be rapidly amplified or dampened.
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