Cognitive Edge Making sense of complexity

Transcription

1 Cognitive Edge Making sense of complexity Accreditation programme June 2006 AGENDA Tuesday Wednesday Thursday Overview of sense making Understanding communities Practitioner Day Harvesting narrative Interpreting narrative Narrative projects Application to strategy Social network analysis +/- Social network stimulus Generic mapping applied to KM Advanced use of models Practitioner Day Practitioner Day Practitioner Day

2 The landscape of management Complex Output Simple Output Computational Complexity a simulation Process Engineering a machine Naturalistic Sense making an ecology Systems Dynamics an organism Simple Input Complex Input Mission SENSE MAKING FOR COGNITIVE EDGE The development and application of new scientific thinking in the context of organisations and their environment OPEN SOURCE METHODS Creation of an open source movement for consultancy practice and theory based on complexity principles DISTRIBUTED (EMERGENT) RESEARCH Development of trans-disciplinary research based on emergence, participation and co-evolution

3 A full copy of the CCLicence is available at - Knowledgebase. Traditional scientific method has always been at the very best hindsight. It s good for seeing where you ve been. It s good for testing the truth of what you think you know, but it can t tell you where you ought to go Robert M. Pirsig. Zen and the Art of Motorcycle Maintenance (1974)

4 Joining up the dots... Boisot Omnipedia issue 6 Sept/Oct 2004 Dots Number of dots Number of possible links Number of possible patterns L= N(N-1)/2 P=2L Links N=4 L=6 P=64 N=10 L=45 P=3.5 trillion Patterns N=12 L=66 P=4,700 quadrillion Sense making framework Naturalistic evolutionary Technofabulists Art- Luddites Nature of the system Ordered Complex Chaotic How we perceive Information processors Pattern processing Ideology & power The way we know Explicit Narrative Experiential

5 Three key phrases Identities form around attractors within barriers Humans evolved as pattern based, not information based intelligence We always know more than we can tell, we will always tell more than we will write The Cynefin Model un-ordered systems Complex P-S-R Emergent Practice Chaotic A-S-R Novel Practice Complicated S-A-R Good Practice Simple S-C-R Best Practice ordered systems

6 Cynefin is a sense making framework not a categorisation model Think of a situation where the problem was managed as ordered, but the situation was complex. What were the consequences?

7 Structures Complex Chaotic Complicated Simple Exercise and the butterfly stamped

8 Some key contrasts efficiency V effectiveness stability V resilience rules V habits reductionist V emergent outcome based V patterns Thinking differently Un-order Order landscape management manage emergence resilience Archetypes as lenses onto reality Heuristics & habits effectiveness event prediction anticipate futures stability Archetypes as repeating structures Rules & regulation efficiency

9 Popular errors (Klein) Sense making is basically connecting the dots and fitting the pieces of the puzzle together Sense making builds up from data to produce a story People should avoid premature consideration of a hypothesis More data leads to better sense making Limitations of concepts Interactions: agents & context Process Systems Sense making Effectiveness

10 The name Cynefin is a Welsh word whose literal translation into English as habitat or place fails to do it justice. It is more properly understood as the place of our multiple belongings; the sense that we all, individually and collectively, have many roots: cultural, religious, geographic, tribal etc. We can never be fully aware of the nature of those belongings, but they profoundly influence what we are. The name seeks to remind us that all human interactions are strongly influenced and frequently determined by the patterns of our multiple experiences, both through the direct influence of personal experience and through collective experience expressed as stories