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Reflexions II: The Metaphor

February 24, 2010

As part of this reflective exercise, I've been going through a lot of old notes from the early days of the Cynefin Centre, which eventually metamorphosed into Cognitive Edge. When we began, one of the things that I noticed was that different types of people seem to be dealing with complexity science at different levels:

-Mathematics
-Models
-Mechanisms
-Metaphors
-Myths

While academics were largely involved with the first two or three levels, most practitioners are still applying the ideas at the metaphor level with only passing references to mechanisms or models. More likely, they are reaching back to myths not mathematics (eg, misapplying the "butterfly effect").

My question then—and now—was: as conversations about complexity shift from describing existing behaviors to developing new approaches, how do we better integrate these levels?

That conversation led to our involvement with a project that became Emergence: Complexity & Organization: An International Transdisciplinary Journal of Complex Social Systems (E:CO). Ultimately, the editors' introduction to the inaugural issue framed the dilemma this way:

Academic discussions about complexity are often biased towards quantitative research and mathematical models that are inappropriately prescribed for systems comprised of actors endowed with free will, who are simultaneously part of and aware of the system. The metaphors of complexity have a usefulness of their own, but too often they are applied without adequate reference to the mechanisms, models and mathematics behind them.

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The Cynefin Company (formerly known as Cognitive Edge) was founded in 2005 by Dave Snowden. We believe in praxis and focus on building methods, tools and capability that apply the wisdom from Complex Adaptive Systems theory and other scientific disciplines in social systems. We are the world leader in developing management approaches (in society, government and industry) that empower organisations to absorb uncertainty, detect weak signals to enable sense-making in complex systems, act on the rich data, create resilience and, ultimately, thrive in a complex world.
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