Types of Decision Problem and Applications of Decision

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

Types of Decisions 2

Players Science Values Experts Stakeholders Accountabilities and responsibilities Forecasts of what might happen Decision Makers Process expertise Analysts 3

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

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

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

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

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

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

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. 10

DSS by levels and domains Level 3 Level of Support Level 2 AI/Expert OR Systems models Decision Analysis Forecasting Soft modelling Level 1 Business Intelligence EIS Data Mining Level 0 Hands-on work Operational General Domain of Activity Corporate Strategic 11

Cynefin: a Welsh habitat D. Snowden (2002). "Complex acts of knowing - paradox and descriptive self-awareness. " Journal of Knowledge Management 6 pp. 100 -11. 12

Cynefin and decision making probe, sense, respond Sense and respond act sense respond categorise and respond 13

Cynefin and solutions Judgement d n a collaboration knowledge mgmttion on i a a t u a l id t b a l n v a E v e m e g Explore and d ju seek insight d e s data assimilation and fitting then optimisation d n a n io ion n t la ua idat rive l Ev va a d t a d Databases expert systems, neural nets, deterministic optimisation 14

Events? Re Unique events ry o at ics r lo ist p ex tat s pe ev atab en le ts Cynefin and statistics d n a y n it o tor a a s m i firm tic t Es on atis c st 15

Cynefin and investigation s e i ud eys t s rv e s su a C nd a ts n e ls m i ia r e tr p Ex and 16

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

Cynefin and Values s d e c rse n e ea r fe eh e r r p / & s d e o u l to a V rs e d un 18 pe ev atab en le ts Re Unique eventsces d n o e r sto e f r e r de p / un s la ue ully V tf Events? no

Applications: Simpler than you think! Simon French

Decision support means • Þ 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’ 20

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 21

Hierarchy used in 5 th Conference 22

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 23

Details of the Countermeasure Strategies 24

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 1/3 rd chance of saving 600 and 2/3 rds chance of saving none. 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 lead to 400 of the population dying. • Programme B would use a new vaccine which might be effective. There is a 1/3 rd chance of no deaths and 2/3 rds chance of 600 deaths. 26

Pareto Plots 27

Sensitivity analysis 28

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

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’ 30

Probabilities as frequencies 31

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 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 • Positive emotions encourage divergent thinking – Brainstorm and formulate issues when you are happy! 33

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

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

DSS by levels and domains Level 3 Level of Support Level 2 AI/Expert OR Systems models Decision Analysis Forecasting Soft modelling Level 1 Business Intelligence EIS Data Mining Level 0 Hands-on work Operational General Domain of Activity Corporate Strategic 36

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 37

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!’ 38