Transcript LGA conference presentation

Core Council Business Under
Radical Uncertainty
Dr. Geoff Wells
Academic Director, Sustainable Business
International Graduate School of Business
University of South Australia
Uncertainties in climate science
• Early stage of development
• Role of climate factors; cascading uncertainty
• Feedback effects
• Prediction of ecosystem risks
• Adaptive and technological responses; fertilisation of
crops
• IPCC process
• Rebuttal
Uncertainties of human impacts
• More dramatic IPCC scenarios
• Human impacts: first level effects
• Human impacts: second level effects
• Distributional effects
• Mass movements of people
Uncertainties of economic analysis
• Time horizon
• Averaging and assumptions
• Range of business-as-usual estimates
• Mitigation cost estimates
• Critique
– Other scenarios
– Overstating costs of climate change
– Understating costs of mitigation
– Uniquely low interest rates
• Overall judgement of Stern Review
Council Business Under
Climate Change Uncertainties
Relevant management frameworks
• Local Government Act 1999
– Strategic management plans
– Annual business plans and budgets
• Australian Accounting Standard #27
– Component functions and activities of local
government
– Depreciation of non-current assets
Climate impacts & risks
• Increased erosion, landslides, sinking of ground
surface, disruption and damage to buildings and
public utilities or other infrastructure caused by global
warming impacts.
• Increasing incidences of respiratory illness, heat mortality,
and other public health impacts associated with
climate change.
• Impacts to private lands or resources that detract from
commercial uses such as recreation, e.g. loss of use of
property used for skiing, tourism based on coral reefs,
or terrestrial wildlife.
• Impacts to agriculture, including decrease in agricultural
water supplies, lower water quality, increase in agricultural
operational costs (fuel, pesticides, fertilisers), and
increase in food prices.
( Ross, C, Mills, E & Hecht, S 2007, Limiting liability in the greenhouse: insurance risk-management
strategies in the context of global climate change, Public Law & Legal Theory Research Paper Series,
Research Paper No. 07-18, UCLA School of Law.)
Climate impacts & risks
• Impacts to lands or resources that detract from resource
consumptive uses (e.g. timber production).
• Mobilisation of chemical wastes, sewage, petroleum products
by natural disasters. Post-event mould after flood events.
• Poor financial performance or other consequences
of businesses' failure to reduce carbon emissions or to reduce
risks attributable to climate change.
• Interruptions to operations, communications, transportation, or
supply chains due to failure to prepare for extreme weather
events.
Climate impacts & risks
• Economic losses to businesses due to failure to prepare for
weather-related disruptions of energy, water, or other utility
services.
• Weather extremes involving changes in precipitation,
ice, temperature, or visibility have impacts on
vehicle accident incidence, which, in turn, includes a
component of liability insurance losses.
• Cross-border economic damages arising from new
regulations or taxes, policy on carbon markets.
• Risks associated with supply-side energy measures to
reduce greenhouse-gas emissions, e.g. from use of nuclear
power, hydrogen, or carbon capture and storage.
Climate impacts & risks
• Impacts on ecosystems: degradation of habitats, increased
threats to species, changes in geographical distribution,
changes in locations of parks and reserves.
• Impacts on demographics:
– Significant population movements, away from higher
temperatures and water deficit, towards lower temperatures
and water availability.
– Demographic cascades from relocation of industry.
– Potential for significant numbers of climate change refugees
from Pacific nations.
Financial Analysis
Handling Uncertainty
Four Levels of Uncertainty
Courtney, H 2001, 20|20 foresight: crafting strategy in an uncertain world, Harvard Business School
Press, Boston, MA.
Level 1: A clear enough future
• Business strategists face opportunities where the range of
possible future outcomes is narrow enough that this
uncertainty doesn’t matter to the decision.
• Point forecasts can be developed that are precise enough
for strategy development.
• Future path of main drivers relatively clear.
• Market not prone to external shocks or internal upheaval.
.
Level 1 tools
SITUATIONAL
ANALYSIS TOOLS
Traditional tools:
Business diagnostics
Porter’s Five Forces.
SWOT analysis.
Discounted Cash
Flow/NPV valuation
models.
END PRODUCTS
Forecasts of key
value drivers under
different strategic
assumptions.
DCF valuation of
alternative models.
DECISION-MAKING
MODEL
Choose the strategy
that maximizes the
organisation’s
objective.
Level 2: Alternate futures
• Set of possible future outcomes that are mutually
exclusive & collectively exhaustive (MECE), one of which
will occur (cf. multiple choice).
• Analysis can help establish relative probabilities but can’t
tell you which one will occur.
• Most common business strategy challenge.
Level 2 tools
END PRODUCTS
SITUATIONAL
ANALYSIS
TOOLS

Traditional tools,
plus:

Decision-tree
analysis.

Scenarioplanning.

Game theory.


Complete description
of a MECE set of
scenarios:
--industry structure,
conduct, performance
in each scenario
--dynamic path to each
scenario, including
trigger events or
variables
--relative probabilities
of each scenario
--valuation model for
each scenario
Analysis of
probabilities and
payoffs.
DECISIONMAKING
MODEL

Decision
analysis.
Level 3: A range of futures
• A range of possible future outcomes can be identified, but
no obvious point forecast emerges.
• Strategists can only define a representative set of
outcomes within the range of possible outcomes (set is not
MECE).
• Unstable macroeconomic conditions—unpredictable GDP
growth, inflation and interest rates, currency fluctuations,
etc.
Level 3 tools
END PRODUCTS
DECISION-MAKING
MODEL

Complete
description of
representative set
of scenarios.

SITUATIONAL
ANALYSIS TOOLS

Traditional tools,
plus:

Scenario-planning.

Game Theory.


Latent demand
research
techniques.
Analysis of
probabilities and
payoffs.

Analysis of strategy
impacts on
probabilities within
the range of
outcomes.

System dynamics
models.

Techniques based
on option-pricing
models.
Qualitative decision
analysis.
Level 4: True ambiguity
• Uncertainties are unknown and unknowable.
• Analysis cannot identify the range of potential future
outcomes or scenarios within that range.
• Not possible to identify all the relevant variables that will
define the future.
• Limitless range of future outcomes.
• Typical of new political, scientific, technological
developments and environments.
Level 4 tools
END PRODUCTS
SITUATIONAL
ANALYSIS TOOLS

Fore-sighting.

Analogies and
reference cases.

Simulation.

Complete set of
what you would
have to believe
statements to
support different
strategies.

Supporting
analogies and
reference cases.

Key market
indicators.
DECISION-MAKING
MODEL

Getting
comfortable with
what you would
have to believe.
Handling Uncertainty in BCA
BCA benefits categories
Benefits
Use
Direct
Non-use
Indirect
Option
Existence
Scenario analysis
Issue of concern
Horizon year
Related elements
incl stakeholders
Location in
structuring space:
Clusters
Focus on high
impact/low
probability
segment
Underlying forces
Events
Priorities 2-3
Combinations of
extremes
3-4 scenarios
Ranges &
extremes of forces
Locate elements
of other quadrants
in scenarios
Scenario events,
timelines,
causalities
Review high
impact/ low prob
segement for
scenario coverage
To Scenario/Decision
Decision analysis
From ‘Scenarios’
Scenarios
Business idea
Matrix evaluation
Lower-level
strategies or
decisions
Current strategy
Contemplated
strategy
Range of
alternative
strategies
Business
strategies
Strategy/scenario
payoffs
Rank Str/Scen
combinations
SA Water Risk
Assessment
Guide
Filter Str/Scen
combinations
Swing weighting of
Str/Scen
combinations
Weighted
aggregate scores
of Str/Scen
combinations
Matrix of
aggregate scores
to evaluate
robustness
Sensitivity
analysis
To Simulation
Probabilistic risk analysis
Priority business
strategies/actions
Modelling of
factors/ Influence
diagram
From ‘Scenarios/Decision’
Preliminary
sensitivity analysis
on factors
Tornado diagrams
ROI Factors
Key factors
affecting
outcomes
Elicit probability
distributions
Factor/Years
Perform the
simulation
NPV calculations
Sensitivity
analysis on results
of simulation
Compare
alternative
courses of actions
Investment
options
Modelling
dependence
relationships
Plot distributions
of alternatives
Stochastic
dominance
analysis
Mean-standard
deviation
Utility functions
Investment
Decision
Modelling uncertainty
removals
Annual catch
Loss rate
Threshold
Mechanics
removal rate
Current
population
size
Population
size
Total Animals
Prob Bands
Mechanics
Rmax
K
z
rate of
increase
Distribution
Variations
Uncertainty & decision-making
• The precautionary principle
• Radical uncertainty and irreversibility
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Converting radical uncertainty to subjective risk
The conservative maximin decision rule
Keeping options open
Increasing the resilience of the system
• Integrating and aggregating
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The strengths and limitations of modelling
Deliberative decision-making
Approaches to coordination
Emergent decision-making