1

Delivering Client Value through Uncertainty

Management

Tim Wells

Halcrow Group Ltd

2

Introduction

PM for Halcrow Group Ltd

3

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

5

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.