project risk analysis - the irm · the most from their investment and expenditure in built assets....

Project Risk Analysis

Neil Dunkerley | 17th May 2012

17th May 2012 |Neil Dunkerley | 2

About EC Harris

■ EC Harris is a leading global Built Asset Consultancy, helping clients makethe most from their investment and expenditure in built assets.

■ We work across a wide range of sectors, and our professional skills includedisciplines from asset and facilities strategy to management informationsystems – quantity surveying, programme, project, risk and constructionmanagement to software development.

■ In 2011 we became part of the ARCADIS Group of companies

■ ARCADIS is an international company providing consultancy, design,engineering and management services in infrastructure, water, environmentand buildings.



■ Quantitative Risk Analysis (QRA)

– Why

– Modelling

– Outputs

– Benefits

■ Range Modelling

■ Railway Possessions

■ Wave AnalysisNationwide

07/Jan/01

04/Feb/01

04/Mar/01

01/Apr/01

29/Apr/01

27/May/01

24/Jun/01

22/Jul/01

19/Aug/01

0% 4% 7% 11%

15%

18%

22%

2 6%

29%

3 3%

37%

40%

44%

48%

51%

55%

59%

62%

66%

70%

73%

77%

81%

84%

88%

92%

95%

99%

Co

mp

leti

on

Dat

eR

ang

e

Sorted by 75% completion date

Distribution for Risk total / Risktotal/CK109

Va

lue

sin

10

^-4

Values in Thousands

0123456789

Mean=1053.606

0 1 2 30 1 2 3

5% 90% 5%.4126 1.7341

Mean=1053.606



■ To enable Clients to gain confidence in estimates andschedules

– should understand the outputs

– appropriate analysis should be undertaken

■ Aids decision making


QRA – Why? Overspend & Overrun

■ Cost

– Deterministic estimation

– Unforeseen events e.g. risks

– Scope uncertainty / change

– Assumptions incorrect

– Exclusions

■ Schedule

– Deterministic estimation

– Unforeseen events e.g. risks

– Scope uncertainty / change

– Assumptions incorrect

– Exclusions

– Sunny-day forecasting

– Human factors (sickness,holidays, etc)

– Key milestone constraints

– Perceived critical path


QRA – Modelling■ Cost

– Review / check estimate

• Scope

• Inflation – base date

• Contingency

• Assumptions / Exclusions

– Modelling

• @Risk

• Uncertainty in quantities & rates

• Risks e.g. ground conditions, approvals, exchange rates,political, etc


Va

lue

sin

10

^-4

Values in Thousands

0123456789

Mean=1053.606

0 1 2 30 1 2 3

5% 90% 5%.4126 1.7341

Mean=1053.606


Values in Thousands

0.000

0.200

0.400

0.600

0.800

1.000Mean=1053.606

0 1 2 30 1 2 3

5% 90% 5%.4126 1.7341

Mean=1053.606


QRA – Modelling■ Schedule

– Review / check schedule

• Scope

• Contingency / Float

• Assumptions / Exclusions

• Logic – Constraints, Missing, Leads & Lags, Types

• Calendars

• Resources (Levelling, Productivity)

– Modelling

• Pertmaster

• Correct logic errors / remove constraints

• Uncertainty in task duration (generic, task / group specific)

• Risks e.g. ground conditions, approvals, weather, political, etc


QRA – Outputs

■ Cost

– Total

– Sections / Elements

– Contingency

– Target costs

– Uncertainty / risk sensitivity

■ Schedule

– Schedule Finish Dates

– Task Start / Finish Dates

– Sectional completions

– Key milestones

– Float / Contingency

– Task Criticality

– Duration / Schedule Sensitivity

– Uncertainty / risk sensitivity


QRA – Benefits?– Independent review of estimate / schedule

– Scope defined (baseline)

– Assumptions & Exclusions defined & agreed

– Unforeseen events (e.g. risks) identified & prioritised formanagement (i.e. risk register)

– Contingency estimated & agreed

– Schedule

• Model key tasks / stage durations & anticipated finish

• Critical path review and task criticality

• Removes double counting of project delay in cost risk register

Range Modelling


Range Modelling – Why?■ Organisations are careful when publishing estimates as failing to reliably

predict the outturn cost can result in a loss of reputation

■ Often the world is not that simple, programmes and projects change

■ A more informative method of presenting estimates, is to present anexpected outturn and express the range of likely outcomes that the outturncost is likely to fall within. This has two advantages:

– Early estimates reflect the range of costs associated with solutions indevelopment

– Estimates for projects nearing construction should be become morecertain


What EC Harris has delivered

■ The Highways Agency post the Nicholls Review 2006 selected EC Harris tosupport range estimating given our industry experience and our flexibility tomobilise to meet demanding timescales.

■ Created a Range Modelling Tool

– that captures estimates based upon a standard WBS; with estimates,risk and uncertainty allowances.

■ Particular innovations of the Range Modelling Tool are:

– Takes into account different modelling distributions, accuracy of data,and dependencies

– Automate the process of uploading project estimates from separateexcel files.

– In built checking mechanisms in triplicate, confirms the accuracy ofresults.


Range Modelling

Railway Possessions

“Overrunning Engineering Works”


Railway Projects

Development /Preparatory Works

EngineeringWorks –

Possession/s


Railway Possessions

WorksTakePoss.

ReturnPoss.

Prep.Works

Reinstatement.Works

OperationalRailway

OperationalRailway

Milestone/s Milestone

Wave Analysis


Wave Analysis

■ A Wave model and chart are a form of time risk modelthat shows the range of completion dates for each ofmany small projects, usually of a similar nature

Nationwide

07/Jan/01

04/Feb/01

04/Mar/01

01/Apr/01

29/Apr/01

27/May/01

24/Jun/01

22/Jul/01

19/Aug/01

0% 4% 7% 11%

15%

18%

22%

26%

29%

33%

37%

40%

44%

48%

51%

55%

59%

62%

66%

70%

73%

77%

81%

84%

88%

92%

95%

99%

Co

mp

leti

on

Dat

eR

ang

e



Wave Analysis■ Each project will have a planned completion date

■ The effect of any opportunities or risks to completion is to spread theplanned completion date over a range:

p la n n e dc o m p le t io nd a te

5 M a r , 2 0 0 1 3 1 M a r , 2 0 0 1

e a r ly c o m p le t io n la te c o m p le t io n

t im e lin e

■ Each date within this rangehas a probability ofoccurrence

■ There is a date in the rangeat which there is a 75%chance the project will becompleted on or before

plannedcom pletiondate

5 M ar, 2001 31 M ar, 2001

early c om pletion late com pletion

P robab ility

5% probability c om pletionon or before

95% probability c om pletionon or before

Probability

75% probability


Wave Analysis

■ This is one project of many.

07/Jan/01

04/Feb/01

04/Mar/01

01/Apr/01

29/Apr/01

27/May/01

24/Jun/01

22/Jul/01

19/Aug/01

0% 3% 7% 10%

13%

17%

20%

23%

27%

30%

33%

37%

40%

43%

46%

50%

53%

56%

60%

63%

66%

70%

73%

76%

80%

83%

86%

89%

93%

96%

99%

Co

mp

leti

on

Dat

eR

ang

e


Nationwide

07/Jan/01

04/Feb/01

04/Mar/01

01/Apr/01

29/Apr/01

27/May/01

24/Jun/01

22/Jul/01

19/Aug/01

0% 4% 7% 11%

15%

18%

22%

26%

29%

33%

37%

40%

44%

48%

51%

55%

59%

62%

66%

70%

73%

77%

81%

84%

88%

92%

95%

99%

Co

mp

leti

on

Dat

eR

ang

e


Wave Analysis

■ The ranges for all the other projects are also plotted.

■ The red line is the desired finish date for all of the projects.



■ Clients should understand the outputs

■ Appropriate analysis should be undertaken

– based upon the available information and within theavailable time

– get out what you put in!

■ Enable Clients to gain confidence in cost estimates andprogrammes

■ Better decision making

■ Successful projects – delivered on time and withinbudget

Thank You!

Neil Dunkerley

[email protected]

project risk analysis - the irm · the most from their investment and expenditure in built assets....

Documents