Post on 11-Feb-2016
description
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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 levelo Capital investment decisionso Business Strategies / Mergers & Acquisitionso Product developmento 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 UncertaintyIdentify 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 Assess
Identify
Context
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5.00
5.50
6.00
6.50
7.00
7.50
m (A
OD
)
50%
99%
95%
Flood Defence Freeboard
Traditional DesignDesign 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 DesignDesign 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 forGiven 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 Assess
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
Valu
es in
10^
-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
Valu
es in
10^
-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 MessagesHow 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.