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Delivering Client Value through Uncertainty
Management
Tim Wells
Halcrow Group Ltd
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Introduction
PM for Halcrow Group Ltd
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Our Markets
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Selection of Projects
Seoul International Airport
Clyde Arc Bridge
Egyptian National Railways
Chendu Ecological Park China
Thames Barrier
Rhudbar Dam Iran
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Adding Client Value through management of uncertainty
What is Client Value
Robust Decision Making
Tour through hierarchy of case studies (coastal planning)
Take Home Messages & Barriers
Scope
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Innovation Predicting their needs Compliance Technically rigorous solutions Sustainable solutions Social / Ethical / Environmental Responsibility (SEE) Manage project risks (cost and programme) Robust decisions
What adds value to clients
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Robust Decisions:
Decisions that are not sensitive to uncertainty
Stand the test of time / ‘Future Proofed’ / ‘No Regrets’
Survival Strategies
o Organisational level
o Capital investment decisions
o Business Strategies / Mergers & Acquisitions
o Product development
o Flood Risk Management Options Appraisal
Robust Decision Making
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Robust Solutions – Top Down
Implement solutions that cope well with uncertainty
Resistant, Resilient, Reliable, Adaptability, Flexibility
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Robust Solutions – Bottom Up
Understand and Formalise Uncertainty
Identify Uncertainties / Assumptions, Model Building, Defining Parameters, Uncertainty / Probabilistic Analysis, Sensitivity
Testing, Supporting Decision Making
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Hierarchy of Case Studies
• Technical - Flood defences ; Rock Sizing
• Project - Project Risk Management
• Strategic – Long Term Investment
ProjectRisk Register
R
Mon
itor
Mitigate Ass
ess
Identify
Context
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5.00
5.50
6.00
6.50
7.00
7.50
m (
AO
D)
50%
99%
95%
Flood Defence Freeboard
Traditional Design
Design for Standard of Protection - 1:200 (0.5%AP)
Safety margin added on to represent uncertainty
Defence crest elevation (design water level)
Uncertainty in modelling
Uncertainty in future SLR
Waves
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Added Value
• Better understanding of existing performance
• Understand dominant parameters
• Provides scientific rigor - robust
• Better evidence for decision making
• Transparent (share)
• Potential cost savings
Regression Sensitivity for DefenceWL/D14
Std b Coefficients
Wave Height/D12 .279
Uncertainty on Transformat.../D10 .558
Extreme Water level at Sou.../D6 .778
-1 -0.75 -0.5 -0.25 0 0.25 0.5 0.75 1
Traditional Design
Design for Standard of Protection - 1:200 (0.5%APF)
Safety margin added on to represent uncertainty
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Rock Sizing
Armouring for coastal structuresDesign based on empirical formulation (Van der Meer/Hudson)Many uncertain parameters / lots of correlations / expert
choice
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Rock Sizing
Armouring for coastal structuresDesign based on empirical formulation (Van der Meer/Hudson)Many uncertain parameters / lots of correlations / expert
choice
Wn50 5.5T
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1 3 5 7 9
5% 90% 5% 2.0688 6.2991
Mean=3.909881
Distribution for Rocksize/C60
0.000
0.050
0.100
0.150
0.200
0.250
0.300
0.350
Mean=3.909881
1 3 5 7 9
Added Value
• Understanding of performance envelope
• Making informed choices
• Trade-off [cost/safety & confidence in performance]
• Support traditional methods
Deterministic
Rock size needed to
Prevent failure for
Given range in
Forcing events
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Project Risk Management
The Environment Agency is the leading public body for protecting and improving the
environment in England and Wales
NCPMS – National Capital Programme Management Services = Delivery of the
nations flood defence projects
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Drivers
“The Environment Agency has accepted the culture of risk management. It is considered to
be best practice and is mandatory.”
£200M annual capital investment needs effective management (>500 live projects)
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Dedicated Extranet Website
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Facilitated workshopsKey team members
Focus on programme / activitiesID Causes /Consequences
OwnershipConsensus
Risk Register
Prioritise (qualitative)ID Mitigation
Residual probabilityQuantitative (3 point)
Assumptions@Risk simulations
ConsensusActions become programmed tasks
Named ownership
Review cycleManage actions
Update risk registerShare knowledge
ContinuousIntegrated into PMCapture Lessons
ProjectRisk Register
R
Mon
itor
Mitigate Ass
ess
Identify
Context
Understand Objectives
RM Process
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Sources of Uncertainty
Project Objectives
Poor Decision Making
Unrealistic Expectations
Insufficient Planning
Changes to Team
Weakly defined outputs
Unfamiliarity
Unexpected Findings
Poor Weather
Complexity
Errors
Time and Resource Constraints
Equipment Failure
Supplier / client Performance
Delays to Approvals
Access Problems
Consultation process
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Risk Model – Risk Register
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Risk Model – Risk Register
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Risk Model
-0.2 0.15 0.5 0.85 1.2
5% 90% 5% 0 1
Mean=0.69
Distribution for Binomial/S16
0
2
4
6
8
10
12
Mean=0.69
-0.2 0.15 0.5 0.85 1.2
1 2 3 4 5
5% 90% 5% 1.3209 3.6198
Mean=2350.197
Distribution for PERT/M5
Val
ues
in 1
0^ -
4
Values in Thousands
0
1
2
3
4
5
6
Mean=2350.197
1 2 3 4 5 0 0.25 0.5 0.75 1
90% 5% 0 .7698
Mean=383.6671
Distribution for single Risk/U7
Val
ues
in 1
0^ -
3
Values in Thousands
0
1
2
3
4
5
6
7
Mean=383.6671
0 0.25 0.5 0.75 1
x =
Single Risk
0 4 8 12 16
5% 90% 5% 2.9696 9.0819
Mean=5928.328
Distribution for BS Risks/T16
Val
ues
in 1
0^ -
4
Values in Thousands
0.000
0.500
1.000
1.500
2.000
2.500
Mean=5928.328
0 4 8 12 16
∑
Multiple risks
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Risk Model – sensitivity analysis
Provide a means of prioritising management effort
Regression Sensitivity for All ProjectRisks inc' Big 5/...
Std b Coefficients
Risk ID9/AA19 .028
Risk ID15/AA25 .031
Risk ID18/AA28 .031
Risk ID2/AA12 .04
Risk ID12/AA22 .043
Risk ID24/AA34 .046
Risk ID7/AA17 .049
Risk ID6/AA16 .054
Risk ID8/AA18 .055
Risk ID3/AA13 .099
Risk ID1/AA11 .105
Risk ID4/AA14 .134
Risk ID20/AA30 .184
-1 -0.75 -0.5 -0.25 0 0.25 0.5 0.75 1
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• Improves the Deliverables (Critical Review)
• Develops team Understanding (Sharing Knowledge)
• Feel more in Control (Understanding Risks)
• Develop targeted Contingencies (Quantify Risks)
• Better Prepared for risk (resilience) (Dry-runs of issues)
• Improves personal / Firm Capability (Thinking Differently)
• Demonstrates Forward Thinking to clients (Proactive not Reactive)
• Saves Money (Less Issues occurring)
Added Value (Project)
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• Balanced view of risk exposure across programme (efficient decision making)
• Understand likelihood of budget delivery
Early release of contingency - build more schemes!
• Schedule certainty (phase procurement input)
Match supply with demand
Added Value (Programme)
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Strategic Level -
Future Investment Requirement
2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 2110
Year
Inve
stm
ent
(£B
)
95 percentile confidence outputs for future scenarios
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Scientific Rigour & Richer understanding of the problem and solutions
Performance certainty, transparency, robust - defendable evidence
Prioritisation of management effort
Effective expenditure – potential to save £
Take Home Messages
How can exploring uncertainty add value
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Barriers
Represents Change (expert & client)
Still faced with tough decisions (confidence level)
In hands of the Analyst
Challenges
Communication of benefits and value
Training of technical staff
Selling value to clients (who get value and ultimately pay)
Barriers / Challenges
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Thank you & Questions
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Decision Making Process
UKCIP decision making framework – a framework for decision making given uncertainty in climate change.