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Cynefin, statistics and decision analysis

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Journal of the Operational Research Society

Abstract

David Snowden's Cynefin framework, introduced to articulate discussions of sense-making, knowledge management and organisational learning, has much to offer discussion of statistical inference and decision analysis. I explore its value, particularly in its ability to help recognise which analytic and modelling methodologies are most likely to offer appropriate support in a given context. The framework also offers a further perspective on the relationship between scenario thinking and decision analysis in supporting decision makers.

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Acknowledgements

I have gained much from discussions with Tim Bedford, Emma Carter, Angela Dale, John Maule, Alec Morton, Nadia Papamichail, Jesus Rios, David Snowden, Theo Stewart and Doug White, and Carmen Niculae, who helped me see the subtleties that the Cynefin model can articulate. Although these ideas have developed over many years, three recent projects gave them impetus: Sustainability Assessment of Nuclear Power: An Integrated Approach, a research collaboration funded jointly by the UK Engineering and Physical Sciences Research Council and the Economic and Social Research Council; Algorithmic Decision Theory, a programme funded by the European Co-operation in Science and Technology; and Investing in an Uncertain Future, a programme of seminars and workshops funded by the Scottish Institute for Advanced Studies. I am grateful to all.

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French, S. Cynefin, statistics and decision analysis. J Oper Res Soc 64, 547–561 (2013). https://doi.org/10.1057/jors.2012.23

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