One concept I like when I’m thinking of complexity is the Cynefin framework developed by Dave Snowden (see the picture on the right). I mentioned the framework already in one of my answers to the comments of the last post on ‘What is complexity?’.
The beauty of the framework is that it helps you to categorize problems in simple, complicated, complex and chaotic. Furthermore, it gives you a strategy for each of these domains how to design your problem solution. For example for complicated problems the strategy would be ‘sense – analyze – respond’, meaning that first you have to sense the problem, analyze the system (or call in experts who know the system) and respond based on the analysis.
I do think that it makes sense to differentiate between the four domains. The problem really is that in the past we treated many problems that are actually complex as only complicated or even simple problems. Also in international development. In order to categorize these problems as actually being complex, we need this sort of frameworks and guidance how to approach them.
I realize that I use the word categories here. Now if you listen to the video on YouTube where Dave Snowden introduces the Cynefin framework, he makes it quite clear that this is not a categorization model, but a sense-making model. A categorization model, in his explanation, is model where the framework precedes the data. That means that the data can be filled in quickly into the existing model – with the risk to lose out on the subtleties. A sense-making model on the other hand is one where the data precede the framework. Here, “the pattern of the framework emerges from the data in a social process”, as Dave Snowden puts it.
But I think it is easiest if I let Dave Snowden introduce the framework himself. Have a look here at the YouTube movie.
For more information, there is also a Wikipedia page on the Cynefin Framework.
I had the privilege to participate in a part of an event organized by USAID on embracing complexity and what this means for the agency. I participated by webinar, which unfortunately only covered the first half of the day. However, Ben Ramalingam, one of the speakers at the event, posted a summary of the day on his blog. I highly recommend to read his post here.
At the moment, I am reading and thinking a lot about complexity and how it could be applied to development and enrich the Systems Dynamics Analysis I am using in my work. Today, I read an article by David J. Snowden and Mary E. Boone titled “A Leader’s Framework for Decision Making” and published in the Harvard Business Review back in November 2007. Snowden and Boone added a box to their article in which they describe the main characteristics of complex systems. I found this to be a very comprehensive and yet understandable description an that’s why I want to share it here.
Here you go:
It [a complex system] involves large numbers of interacting elements.
The interactions are nonlinear, and minor changes can produce disproportionately major consequences.
The system is dynamic, the whole is greater than the sum of its parts, and solutions can’t be imposed; rather, they arise from the circumstances. This is frequently referred to as emergence.
The system has a history, and the past is integrated with the present; the elements evolve with one another and with the environment; and evolution is irreversible.
Though a complex system may, in retrospect, appear to be ordered and predictable, hindsight does not lead to foresight because the external conditions and systems constantly change.
Unlike in ordered systems (where the system constrains the agents), or chaotic systems (where there are no constraints), in a complex system the agents and the system constrain one another, especially over time. This means that we cannot forecast or predict what will happen.
Moreover, Snowden and Boon differentiate between two types of complex systems. In the first type, the individual actors or ‘agents’ in the system strictly follow predefined, simple rules, such as birds flying in a flock or ants in an ant colony. In the second type, however, the individual agents are not animals but humans and, hence, follow their own reasoning according to the relevant context and situation.
Consider the following ways in which humans are distinct from other animals:
They have multiple identities and can fluidly switch between them without conscious thought. (For example, a person can be a respected member of the community as well as a terrorist.)
They make decisions based on past patterns of success and failure, rather than on logical, definable rules.
They can, in certain circumstances, purposefully change the systems in which they operate to equilibrium states (think of a Six Sigma project) in order to create predictable outcomes.
So where does this lead us in our everyday work? Snowden and Boone also offer a number of tools to manage complex situation out of which I want to pick two that I find are relevant for the work in development projects:
Open up the discussion. Complex contexts require more interactive communication than any of the other domains. Large group methods (LGMs), for instance, are efficient approaches to initiating democratic, interactive, multidirectional discussion sessions. Here, people generate innovative ideas that help leaders with development and execution of complex decisions and strategies. (…)
Stimulate attractors. Attractors are phenomena that arise when small stimuli and probes (whether from leaders or others) resonate with people. As attractors gain momentum, they provide structure and coherence. (…)
The first point clearly points out that participation still is a very important part of every development project that really wants to make a difference. In the end we have to be aware that it is not us that is changing the system, but we are merely working to enable the system to move itself towards a more favorable state (who defines whether this state is more favorable remains another point to discuss and influences a lot whether the system is actually moving in that direction).
The second point is important to recognize that we always have to look for things that work or try to start small pilots and see whether they work and amplify them. This is essentially the recognition that change to a system happens from within a system.
I will continue blogging about complexity, many things are going on in that field. So stay tuned.