Tag Archives: dave snowden

Of Complexity and Chaos

Cynefin framework

The Cynefin Framework with the newly renamed ‘Obvious’ domain (formerly ‘Simple’). Source: Cognitive Edge

In the Cynefin framework, complex and chaotic are two separate domains. Complexity is defined as the domain where agents and constraints co-evolve, chaos as where there are no constraints. Both are part of the unordered side of Cynefin, i.e. where events are unpredictable and expert knowledge and analysis are not leading to better decisions. Chaos is seen as a domain where you don’t really want to be, so all you have to do there is go act quickly and decisively to get out. To use Dave Snowden’s words: “Chaos is a transitionary domain.  (…)  If you collapse into it without [intention] then the strategy is to move out in a controlled way; you will move out as constraints happen naturally.   Entered deliberately it can create the conditions for radical innovation, used as contained chaos it allows for distributed cognition or Wisdom of Crowds. Nothing resides in Chaos for any period without sustained effort.” Continue reading

Exploring narrative sensemaking

I haven’t been posting for a while. The reason is that our first daughter was born in August and we are still overwhelmed with having a new person in our household. My work has been cut down to the minimum so we can cater to and at the same time hugely enjoy the new person in our lives.

Nevertheless, I have been doing some work. An interesting new avenue I am exploring is that of narrative sensemaking. Narrative inquiry has a long history and there are various branches to it. The branch I am exploring is based on the approach by Dave Snowden and his company Cognitive Edge, which attempts to collect metadata together with stories that can be analyzed statistically. This effectively adds a quantitative component to the otherwise purely qualitative nature of narrative inquiry.

As a first pilot we have added a narrative study to a larger thematic study on Regional Economic Development (RED). This thematic study is implemented by a consortium consisting of Mesopartner and SISTME for the Multilateral Investment Fund (MIF) of the Inter-American Development Bank. The goal of the narrative part of the study is to find factors that promote or hinder Local Economic Development initiatives to reach scale – either through effecting changes on policies or through a copying effect by other regions and actors.

Currently, we are collecting narratives from LED practitioners in Latin America. But we are also adding experiences from practitioners all around the world to get a richer picture and be able to compare the importance of the factors. We are using SurveyGizmo to collect the narratives. Although it does not allow for all the tricks as a specifically developed software like Cognitive Edge’s SenseMaker, we see it as a low-cost alternative to test the approach. We will know more about the suitability of the tool when we are done with the study. In any case we are eager to also use the more powerful SenseMaker Suite in upcoming projects and compare the functionality.

If you have made experiences in local and regional economic development that you would like to share, please fill out the questionnaire and share your story. You will have the chance to win a book voucher worth 75 USD. Here is the link to the three versions of the questionnaire we have: English, Spanish, Portuguese

How to strengthen innovation – good practice vs. emergent practice

The Cynefin FrameworkThe last week of June I had the privilege of attending a three-day training event with Dave Snowden, founder of Cognitive Edge and “mental father” of the Cynefin framework. For me this was a great experience and although I had read a lot of stuff around complexity (also by Dave), there were still many new insights I got. Some things were new, others just became clearer. One thing that I knew but that was becoming more pronounced during the training is the differentiation between best/good practice and emergent practice. Continue reading

Results Measurement and the DCED Standard: a commitment to move forward

We now need to start a constructive discussion on how a truly systemic Monitoring and Results Measurement (MRM) framework could look like (as Evaluation does not play a big role in the current discussions, I am adopting the expression MRM and avoid the M&E). In this post, I will take up the discussions on MRM and the DCED Standard for Results Measurement from the two guest posts by Aly Miehlbradt and Daniel Ticehurst and will add from a discussion that runs in parallel on the very active forum of the Market Facilitation Initiative (MaFI). I will also add my own perspective suggesting that we need to find a new conceptual model to define causality in complex market system. Based on that, in my next post, I will try to outline a possible new conceptual model for MRM. Continue reading

Do we need a goal or is virtue sufficient purpose?

David Snowden has written on his blog about purpose and virtue (more specifically here, here, here and here). I find it a fascinating line of thought, but still cannot  wrap my head around it completely. The basic idea is that in contrast to systems thinking, where an idealized future is identified and interventions aim to close the gap to this future, complexity thinking (or at least the one advocated by Snowden) focuses on managing in the present and with that enabling possible futures to emerge or evolve that could not have been anticipated. Now the latter, the management without a specific goal, of course, asks for a purpose or motivation. Why should we bother, if we don’t have a goal? Continue reading

What is complexity? II

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.

What is complexity?

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.