Society for Organisational Learning Australia, The Cynefin Centre
7-9 December 2005, Sydney
Libby Kalucy, PHC RIS
Making sense of complexity was the theme of a very stimulating three day workshop held in Sydney in December 2005, run by the Society for Organisational Learning Australia for the Cynefin Centre. The Cynefin Centre is an international network that focuses on the application of complexity science to management and organisational practice. The Centre spun off from IBM in July 2004. At the heart of the Cynefin Centre is a distinction between ordered and unordered systems, and the consequent recognition that systems with fundamentally different qualities require the application of contextually differentiated methods for both diagnosis and intervention.
As humans we try to make sense of the world we live in, usually by understanding the relationship between causes and effects. Some aspects of systems in the world of primary health care are more ordered than others, as cause is related to effect in ways that are known to us (for example, in immunisation), or at least are knowable with sufficient fact finding and analysis (diagnosis and treatment of specific conditions). Other aspects, of health system organisation for example, are more complex. There are visible relationships between cause and effect, and we can perceive the patterns that emerge through the interaction of many agents with retrospective coherence. However we are not able to predict which pattern will emerge in future. Sometimes the world is turbulent and chaotic, as during a natural disaster or epidemic of unknown cause, when there is no time to investigate change and wait for patterns to emerge.
We can make better sense of things if we understand what type of system we are dealing with, and use appropriate methods and tools. This is one of the main application areas of the Cynefin Centre.
In a simple system where cause and effect are related in a known manner, the people in an organisation can sense incoming data, categorise the data and respond according to predetermined practice recorded in manuals and operational procedures. Structured techniques are both desirable and mandatory. Best practice is possible.
In a more complicated system, incoming data must be analysed before appropriate responses can be determined, as relationships between cause and effect may be separated in time or space, and difficult to fully understand. Experiment, expert opinion, fact finding and scenario planning are appropriate. Learning organisations come into their own, together with systems thinking and methodology to identify cause-effect relationships. Good practice is a feature of this type of system.
To make sense of complex systems we need to probe the situation to make the patterns more visible, then stabilise the patterns we want and create conditions where the patterns we want are more likely to emerge. Multiple perspectives are necessary to make the patterns visible to a decision maker. Narrative techniques are powerful in providing multiple perspectives. Emergent practice is a feature of complex systems.
In chaotic situations there is a need to act quickly and decisively to reduce the turbulence. Chaos, a favourite state of anarchists, can however create conditions for innovation, resulting in novel practice.
The Cynefin Framework illustrates these ideas.
 
References
Web: http://www.cynefin.net/
Web: http://www.solaustralia.org/
Kurtz, C.F., Snowden, D.J. (2003). The new dynamics of strategy: Sense-making in a complex and complicated world. IBM Systems Journal, 42(3): 462-483. Retrieved from http://www.research.ibm.com/journal/sj/423/kurtz.html
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