Complex adaptive systems – first exposure

Cynefin framework By Snowded (Own work) [CC BY-SA 3.0 (, via Wikimedia Commons

It was suggested that I might find Complexity Theory relevant to my proposed area of study, so over the last couple of weeks, I’ve been attempting to familiarise myself with the concepts it proposes (more of that in a later post). During that research, I came across this lecture (seminar?) by Dave Snowden – “Combining Complexity Theory with Narrative Research,” in which he introduces  research approaches which deal with complex adaptive systems. He argues that traditional research techniques evolved to deal with ordered, rather than complex systems and new tools and techniques need to be brought to bear.

It’s an interesting talk, spanning a range of topics and Dave is a most engaging speaker. He discusses the rationale behind the techniques he’s used to make sense of these systems, from diabetes in aboriginal peoples to how ‘the West’ is viewed in Iran. He terms the methodology he brings to bear ‘distributed ethnography,’ in which research respondents not only provide the raw data, but also index (code?) the data. Thousands of micro-narratives from respondents are captured and indexed using an app which feeds masses of categorised data back to the researchers in real time. The assertion is that person who tells the story also ‘owns the interpretation,’ thus resulting in  the final analysis being more objective and ethical. The enormous data sets produced enable statistical interpretation, but with embedded stories to provide secondary explanatory power, rather than constituting the primary source for interpretation.

The app referred to is SenseMaker, which is free for respondents. The infrastructure which delivers the context-specific content, supports the data collection and analysis and provides all the supplementary resources is delivered by Dave’s company, Cognitive Edge. Perhaps unsurprising then that Dave is such a champion for the techniques he advocates. That said, I find the notion of building the capacity for research respondents to categorise their own data worthy of further thought. A possible technique for addressing researcher bias perhaps? However, even if I had the budget and resources to use SenseMaker, would I? To answer that I’d need to explore more deeply the extent to which this methodology aligns with my research questions, aims and objectives. Whether I do that or not, I will definitely be thinking more about micro-narratives and respondent coding.


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