Cynefin and Research Planning

1. Cynefin and Research Planning Simon French simon.french@mbs.ac.uk

2. Bringing together • Statistical Inference • Decision Analysis • Knowledge Management • Sense-making • Problem structuring methods We do not pay enough attention to sense-making in research planning

3. Knowledge Management and Nonaka’s SECI Sense-making and articulation is as important to Science and research The practice of Science and research

4. Cynefin: a Welsh habitat D. Snowden (2002). "Complex acts of knowing - paradox and descriptive self-awareness." Journal of Knowledge Management6 pp. 100-11.

5. Complexity vs Complicated • Confusingly complexity science is not primarily about the complex space! • It is about computationally intensive models: i.e. complicated models • Models  understanding cause and effect • So complexity science applies to the knowable space much more than the complex space.

6. Cynefin and decision making probe,sense,respond Sense, analyseandrespond actsenserespond categorise and respond

7. Cynefin and solutions Judgementcollaborationknowledge mgmt Evaluation andvalidationjudgement based Information systemsdata assimilation and fitting then optimisation Explore and seek insight Evaluation andvalidationdata driven Databases expert systems, neural nets, deterministic optimisation

8. Cynefin and statistics Uniqueevents exploratoryanalyses Repeatable events Events? Estimation andconfirmatoryanalysis

9. Cynefin and data collection Case studies, interviews, and surveys Experimentsand trials

10. So ... ... why do we see so many articles in social science and management journals dealing with issues that are clearly in the complex space but using confirmatory methods: • Analysis of variance/covariance • Structural equation modelling • Precisep-values • ...

11. For complex issues We need to use exploratory methods to help us make sense of the situation, discern cause and effect, and gradually move the issue into the knowable space where we can use confirmatory methods.

12. Too many research methods books • Begin with a false picture of scientific research that starts with a hypothesis • Yet the creative part of science is developing hypotheses • i.e. in many cases working in the complex space

13. Exploratory methods • Exploratory data analysis • Eyeballing the data • Stem-and-leaf plots, etc. • Tukey (1979) • Multivariate analysis • Factor analysis, cluster analysis, etc. • But take p-values as a guide not a prescription • Confirmatory analyses and a ‘pinch of salt’ • Data mining • Automated EDA and (conditional) pattern searching • Problem structuring methods

14. Check-lists Simply an aide-memoire • Used to prime brainstorming • Used to structure reports

15. External environment: Political Economic Social Technical Environmental Legal/legislative Internal Environment: Strategy Structure Systems Style Shared values Skills Staff PESTEL and 7 S’s

16. Technical, Organizational and Personal PerspectivesMitroff and Linstone

17. Simple two dimensional plots • Easy to draw on paper or flip charts • Even better – use ‘post-its’

18. Uncertainty identification

19. Networks Can show inter-relations

20. Mindmaps

21. Cognitive Mapping

22. Rich Pictures A picture is worth 1000 words ....

23. Rich picture diagram of “hole in the ozone layer” issues as perceived in 1988 From Daellenbach (1994)

24. In summary • We need to recognise that confirmatory statistical analyses need a lot of prior understanding before they can be applied. • We need to recognise the role of sense-making explicitly and spend time on it. • There are tools to help ...

25. Questions?