Risk analysis for project decision-making Presented by Keith Gray Monday 10th October 2016 APM North West branch and Risk SIG conference Alderley Park, Macclesfield

1. Risk analysis for project
decision-making
Keith Gray
APM Risk SIG Committee

2. Agenda
 Research on project failures
 Two questions
 Challenges for project decision-makers
 The project life cycle and decision-
making
 Risk analysis definitions and outputs
 Can risk analysis help?

3. Research on project failures
 1994,World Bank issued the Wapenhans
Report on its overall project portfolio
(Infrastructure for Development). It
identified an increasing number of poorly
performing projects and concluded that
there were two main causes: over-
optimistic estimates of project viability
and inadequate attention to risk and
uncertainty.

4.  2013, National Audit Office identified that
the tendency for over-optimism, whether
unconsciously or deliberately, results in
the underestimation of time, costs and
risks to delivery and the over-estimation
of the benefits.
Research on project failures

5.  2014, PWC report ‘Portfolio and
Programme Global Survey’ summarises
regular themes from previous surveys.
One of the themes is estimating. In 2004
and 2007 the theme was bad estimates
while in 2012 and 2014 the focus was
again on the same issue namely, poor
estimating in the planning phase.
Research on project failures

6.  2015, Calleam study concluded that
there are 101 common causes of project
failure grouped into 13 major categories,
one of which is estimation. Two
examples are i) decisions are made on
singular values of duration and costs
rather than using a range of values that
reflect the risks and uncertainties in the
estimates for the forthcoming project
phase(s) and ii) there is a failure to build
in contingency to handle risks and
uncertainties.
Research on project failures

7. Infrastructure examples
Cost Overruns of High Profile Projects (Source: Megaprojects and
Risk: An Anatomy of Ambition, Flyvbjerg, Bruzelius and
Rothengatter)

8. Two questions for project decision-
makers
 How risky is this project?*
 How do you know?*
 Risk analysis may be able to help
answer these questions
*Acknowledgements to Dr David Hillson, The Risk Doctor

9. Challenges for decision-makers
 Will everything go according to plan?
 What can blow the project off course?
 Is the plan optimistic?
 What are the governance arrangements?
 Who is the sponsor?
 Who are the stakeholders?
 Is the funding secure over the project life cycle?

10.  How good are the estimates?
 Have they been independently verified or
tested as in reference class forecasting?
 Have the assumptions been tested?
 Have lessons learned from previous
projects been reviewed and taken into
account?
 Do we have the resources (in house or
in the supply chain) to meet the
complexity of the project?
Challenges for decision-makers

11.  Do we have the resources (in house or
in the supply chain) to meet the
complexity of the project?
 How experienced are the decision-
makers in relation to the complexity of
the projects they are making judgments
on?
 To what extent do the project promoters
present the project in such a way as to
get the business?
Challenges for decision-makers

12. The project life cycle

13. The risk process (PRAM* Guide)
*PRAM = (Association of Project Management) Project Risk Analysis and Management

14. Risk analysis definitions
 Qualitative – assessment of risk relating to the qualities and
subjective elements of the risk. Useful for understanding the
effect of individual risks and prioritisation
 Quantitative – modeling of numerical outcomes by
combining values and relationships between values. Useful
for determining a range of likely outcomes, risk drivers,
planned effectiveness of risk responses and setting
contingency
Source: PRAM Guide

15. Output of qualitative assessment –
risk matrix

16. Outputs of quantitative analysis –
tornado graph

17. Outputs of quantitative analysis –
histogram and cumulative distribution
graph

18. Outputs of quantitative analysis –
comparison of cumulative distribution
graphs

19. Can risk analysis help?
 Questions of any project:
– How risky is this project?*
– How do you know?*
 Use quantitative analysis to answer first question
 Use qualitative assessment to help answer the second
question
 Risk analysis can help project decision makers by
alerting them to the probabilistic nature of projects
 The ranges of time and cost could be used instead of
using a single value, to set a risk-adjusted baseline
 A defensible contingency could be set based on risks and
uncertainties
*Acknowledgements to Dr David Hillson, The Risk Doctor

20. Thank you
Any questions?
Keith Gray
keith@riskperformance.biz
+44 (0) 7879 423242

21. This presentation was delivered
at an APM event
To find out more about
upcoming events please visit our
website www.apm.org.uk/events