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Types of Decisions
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Players
Decision Makers
Experts
Science
Forecasts of what might happen
Stakeholders
Values
Accountabilitiesand responsibilities
Analysts
Processexpertise
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Strategy Pyramid (1)
• Strategic
• Tactical
• Operational
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Strategy Pyramid (2)
• Strategic
• Tactical
• Operational
• Instinctive(recognition primed)
unstructured, long time spans of discretion
very structured, short time spans of discretion
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Planned, Orderly Activities
Strategic thinking ….. Tactical thinking …. Implementation
Operational, structured decision making
Strategic, unstructured decision making
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Responsive Activities & Emergent Strategy
Immediate response …… regain of control
Instinctive, (rehearsed?) decision making
Strategic, unstructured decision making
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The interplay between rationalistic and emergent strategy
Rationalistic decision making
brings coherence to parts of
the strategy
So decision analysis is usually made against background of some inconsistency and in recognition that this will continue
Savage’s ‘small world’
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Organisational Levels
• Strategic Corporate
Strategic
• Tactical General
• Operational Operational
• Instinctive Hands-on Work
(recognition primed)
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Levels of Decision SupportLevel 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.
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Business IntelligenceData Mining
DSS by levels and domains
Domain of Activity
Level of Support
Hands-on work
Operational General Corporate Strategic
Level 3
Level 2
Level 1
Level 0 EIS
AI/ExpertSystems
ORmodels
Forecasting
DecisionAnalysis
Softmodelling
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Cynefin: a Welsh habitat
Cause and effect can be determined with
sufficient data
K nowable The realm of
Scientific Inquiry
Complex The realm of Social Systems
Cause and effect may be determined after the event
Chaotic Cause and effect not discernable
K nown The realm of Scientific
Knowledge Cause and effect understood
and predicable
D. Snowden (2002). "Complex acts of knowing - paradox and descriptive self-awareness." Journal of Knowledge Management 6 pp. 100-11.
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Cynefin and decision making
K nowable The realm of
Scientific Inquiry
Complex The realm of Social Systems
Chaotic
K nown The realm of Scientific
Knowledge
categorise and
respond
Senseand
respond
probe,sense,
respond
actsense
respond
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Cynefin and solutions
K nowable The realm of
Scientific Inquiry
Complex The realm of Social Systems
Chaotic
K nown The realm of Scientific
Knowledge
Databasesexpert systems, neural
nets, deterministic optimisation
data assimilation and fitting
then optimisation
Judgementcollaboration
knowledge mgmt
Explore and seek insight
Eval
uatio
n an
d
valid
atio
n
data
driv
en
Eval
uatio
n an
d
valid
atio
n
judg
emen
t bas
ed
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Cynefin and statistics
K nowable The realm of
Scientific Inquiry
Complex The realm of Social Systems
Chaotic
K nown The realm of Scientific
Knowledge
Repea
tabl
e
even
ts
Uniqueevents
Events?
Estim
atio
n an
d
confi
rmat
ory
stat
istics
expl
orat
ory
stat
istics
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Cynefin and investigation
K nowable The realm of
Scientific Inquiry
Complex The realm of Social Systems
Chaotic
K nown The realm of Scientific
Knowledge
Expe
rimen
ts
and
trial
sCase
stud
ies
and
surv
eys
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Do preferences exist?
• DeFinetti famously said – “Probabilities do not exist”
• Do preferences exist?
• or better
– When do preferences come into existence?
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Cynefin and Values
K nowable The realm of
Scientific Inquiry
Complex The realm of Social Systems
Chaotic
K nown The realm of Scientific
Knowledge
Repea
tabl
e
even
ts
Uniqueevents
Events?
Value
s/pr
efer
ence
s
unde
rsto
od &
rehe
arse
dValue
s/pr
efer
ence
s
not f
ully u
nder
stoo
d
Applications:Simpler than you think!
Simon French
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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’
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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
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Hierarchy used in 5th Conference
Normal Living
Effects
Resources
Radiation
Stress
PublicAcceptability
Affected Region Rest ofUSSR
FatalCancers
Hereditary
Related
Related
Health
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Decisions based on Intervention Levels
Measure of Dose
Above this level, relocation would be advised and offered
Below this level, there would be little need to do anything except reassure the population
In between these levels, many countermeasures would be implemented to clean up the area and protect the population
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Details of the Countermeasure Strategies
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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.
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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.
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Pareto Plots
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Sensitivity analysis
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Chernobyl
• The ‘world’ was a complex as it comes
• The analysis and presentation was really rather simple– And hugely effective.
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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’
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Probabilities as frequencies
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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
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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!
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Applications of decision support and analysis is usually about bringing together various simple ideas to help decision makers evolve their understanding, preferences and beliefs.
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The process of decision analysis
Formulate
Evaluate
Review
Requisite?
Decide
Yes
No
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Business IntelligenceData Mining
DSS by levels and domains
Domain of Activity
Level of Support
Hands-on work
Operational General Corporate Strategic
Level 3
Level 2
Level 1
Level 0 EIS
AI/ExpertSystems
ORmodels
Forecasting
DecisionAnalysis
Softmodelling
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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
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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!’
