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Types of Decision Problem and Applications of Decision Support and Analysis

Types of Decision Problem and Applications of Decision Support and Analysis. Simon French simon.french@mbs.ac.uk. Types of Decisions. Science. Values. Experts. Stakeholders. Accountabilities and responsibilities. Forecasts of what might happen. Process expertise. Analysts. Players.

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Types of Decision Problem and Applications of Decision Support and Analysis

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  1. Types of Decision Problem and Applications of Decision Support and Analysis Simon French simon.french@mbs.ac.uk

  2. Types of Decisions

  3. Science Values Experts Stakeholders Accountabilitiesand responsibilities Forecasts of what might happen Processexpertise Analysts Players Decision Makers

  4. Strategy Pyramid (1) • Strategic • Tactical • Operational

  5. unstructured, long time spans of discretion • Strategic • Tactical • Operational • Instinctive(recognition primed) very structured, short time spans of discretion Strategy Pyramid (2)

  6. Strategic thinking ….. Tactical thinking …. Implementation Strategic, unstructured decision making Operational, structured decision making Planned, Orderly Activities

  7. Responsive Activities & Emergent Strategy Immediate response …… regain of control Strategic, unstructured decision making Instinctive, (rehearsed?) decision making

  8. Rationalistic decision making brings coherence to parts of the strategy The interplay between rationalistic and emergent strategy Savage’s ‘small world’ So decision analysis is usually made against background of some inconsistency and in recognition that this will continue

  9. Organisational Levels • Strategic  Corporate Strategic • Tactical  General • Operational  Operational • Instinctive  Hands-on Work (recognition primed)

  10. Levels of Decision Support Level 0:Acquisition, checking and presentation of data, directly or with minimal analysis, to DMs Level 1:Analysis and forecasting of the current and future environment. Level 2:Simulation and analysis of the consequences of potential strategies; determination of their feasibility and quantification of their benefits and disadvantages. Level 3:Evaluation and ranking of alternative strategies in the face of uncertainty by balancing their respective benefits and disadvantages.

  11. DSS by levels and domains Level 3 ORmodels AI/ExpertSystems DecisionAnalysis Level of Support Level 2 Softmodelling Forecasting Level 1 Business IntelligenceData Mining EIS Level 0 Hands-on work Operational General Corporate Strategic Domain of Activity

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

  13. Cynefin and decision making probe,sense,respond Senseandrespond actsenserespond categorise and respond

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

  15. Cynefin and statistics Uniqueevents exploratorystatistics Repeatable events Events? Estimation andconfirmatorystatistics

  16. Cynefin and investigation Case studies and surveys Experimentsand trials

  17. Do preferences exist? • DeFinetti famously said • “Probabilities do not exist” • Do preferences exist? • or better • When do preferences come into existence?

  18. Cynefin and Values Uniqueevents Values/preferencesnot fully understood Repeatable events Events? Values/preferencesunderstood & rehearsed

  19. Applications:Simpler than you think! Simon French

  20. Decision support means • Helping the decision makers and the other players understand • Working at their cognitive level • Need simple models usually to convey ideas • Analysts may need complex models • but more likely they need diagnostics for simple models • Paradoxically decision support and analysis drives to simplicity • Requisite modelling • Start simple and build in necessary complexity until there is sufficient understanding to ‘make the decision’

  21. Chernobyl • The world’s worst nuclear accident • Complex event at a complex time in Soviet Union’s history • Many people affected • Vast swathes of land contaminated

  22. Hierarchy used in 5th Conference

  23. Decisions based on Intervention Levels Measure of Dose Above this level, relocation would be advised and offered In between these levels, many countermeasures would be implemented to clean up the area and protect the population Below this level, there would be little need to do anything except reassure the population

  24. Details of the Countermeasure Strategies

  25. Framing Issues Imagine that you are a public health official and that an influenza epidemic is expected. Without any action it is expected to lead to 600 deaths. However, there are two vaccination programmes that you may implement: • Programme A would use an established vaccine which would save 200 of the population. • Programme B would use a new vaccine which might be effective. There is a 1/3rd chance of saving 600 and 2/3rds chance of saving none.

  26. Framing Issues Imagine that you are a public health official and that an influenza epidemic is expected. Without any action it is expected to lead to 600 deaths. However, there are two vaccination programmes that you may implement: • Programme A would use an established vaccine which would lead to 400 of the population dying. • Programme B would use a new vaccine which might be effective. There is a 1/3rd chance of no deaths and 2/3rds chance of 600 deaths.

  27. Pareto Plots

  28. Sensitivity analysis

  29. Chernobyl • The ‘world’ was a complex as it comes • The analysis and presentation was really rather simple • And hugely effective.

  30. Fast and Frugal aids • Simple heuristics have been shown to help substantially reduce psychological biases • For instance, Gigerenzer has shown that ‘frequency’ presentations can reduce the issue of ‘forgotten base rates’

  31. Probabilities as frequencies

  32. Other fast and frugal ideas • Consider the opposite • Challenge your thinking • Calibrate yourself against past decisions • Over-define some parts of the model • Beware of framing effects

  33. Other fast and frugal ideas • Consider the opposite • Challenge your thinking • Calibrate yourself against past decisions • Over-define some parts of the model • Beware of framing effects • Positive emotions encourage divergent thinking • Brainstorm and formulate issues when you are happy!

  34. Applications of decision support and analysis is usually about bringing together various simple ideas to help decision makers evolve their understanding, preferences and beliefs.

  35. The process of decision analysis Formulate Evaluate Review No Requisite? Yes Decide

  36. DSS by levels and domains Level 3 ORmodels AI/ExpertSystems DecisionAnalysis Level of Support Level 2 Softmodelling Forecasting Level 1 Business IntelligenceData Mining EIS Level 0 Hands-on work Operational General Corporate Strategic Domain of Activity

  37. Linear programming models • Huge and complex • But actually rather simple with respect to the world • Algorithms are complex (though idea is easy) • But models are simple to explain in principle

  38. Business Intelligence and Analytics • Is data mining based on simple or complex models • Algorithms are complex • But representation to managers is usually simple • Flags and warnings saying ‘check this!’

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