Risk Management
Vignesh Sivadass
2022MANG6143Week7slidesv5.pptMANG 6143
Project Risk Management
Mario Brito
Reading for this week
- Chapman(2019), Chapter 4, page 132-142
- Chapman(2019), Chapter 7, page 343-345
- Chapman(2019), Chapter 7, page 365-378
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Your task this week is to:
- Read Chapman and Ward (2011), page 49-51. Section: The probability-impact grid (PIG) – a tool that needs scrapping.
Write a comment in the discussion board about how the PIG is applied in your subject area and what are the limitations of using this method.
Write a reply to a comment written by one of your colleagues.
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Transcon 3
case study discussion
Discussion starting point
Still use the working assumption that the
objective is maximizing the expected value of
M = B – C,
where M = margin (contribution to profit),
B = bid (price),
C = cost (direct),
but assume we want to understand the
expected value of C in total, and associated risk.
Cost estimate summary sheet example
comp item/option base min max exp choices/assumptions
1 mainframe etc 3.6 3.6 3.6 3.6 no choice
2 Astro 0.3 0.3 0.3 0.3 no choice
Zenith 1.0 1.1 1.3 1.2
total 1.5
3 Zoro 1.0 1.2 1.4 1.3 if no hostile takeover
Astro 0.8 0.7 1.1 0.9 preferred option
4 omitted
5 to avoid making this slide too complex
total direct cost 10.9 14.2 12.5 (£ million)
Interpret this as 13 +/- 2 £ million?
Layered curves can show contributions, including simple linear
curves if discrete outcomes are not portrayed, as shown here
0.5 1 2 3 … 5
0
1.0
Cost (£)
Cumulative
probability
even if precise
non-linear curves
are used, this
portrayal suggests
limited cost
risk
Linking this to common practice
- The value of simple estimating processes.
- The value of more complex estimating processes in their own right and as the basis of simple estimates.
- The key estimating process ideas have been used very successfully by a limited number of organisations.
Some concluding comments
- Many of the key process ideas can be applied to all opportunity, risk and uncertainty management processes.
- Designing processes for contexts is an overarching key idea.
- Seeking simplicity systematically in these processes is another key idea, introducing complexity where it pays being a crucial part of this.
Sensitivity diagrams: Highways Agency example
A basic probability-impact grid (PIG)
Probability
high
low
low medium high
medium
Impact
p1
p2
p0 = 0
p3 = 1
i0 = 0 i1 i2 i3
r2 r3 r4
r1 r2 r3
r3 r4 r5
More powerful portrayal of the information on a PIG
source number 3 – reliable probability
available, but very uncertain impact
impact
0 … complete scale for outcome values from zero to the feasible maximum
probability
1.0
0
source number 2 – very uncertain probability, but predictable impact
source number 1 – uncertain probability and impact
Health Warning
Any source which
has a probability of 1 does not lend itself to this portrayal, so
very important uncertainty is
omitted by any event based
risk management approach using
this framework
complete
scale from
0 to 1.0
Sensitivity diagrams: a high clarity BP example
The structure all uncertainty phase
The need to test the robustness of working assumptions in the search for clarity efficiency is central to this phase, requiring basic modelling skills and a very clear and comprehensive understanding of the range of possible approaches available.
This phase is also coupled to concerns like:
- we need to order sources of uncertainty for several reasons,
- we need to order responses,
- we need to identify general responses,
- we need to understand dependencies,
- we need a comprehensive qualitative analysis prior to quantitative analysis.
Structure phase specific tasks
from the
identify
phase
review other plans and Ws
and associated sources
identify general responses
and order responses
examine links between
sources and responses
develop diagrams and
review associated models
review key plan components
and associated sources
other selective
restructuring
explore
interactions
develop
orderings
refine
classifications
deliverables
fit for purpose?
to the
ownership
phase
yes
no
Portion of a source-response diagram for an
offshore project platform fabrication activity
start-up
problems
yard not
available
productivity
variations
industrial
disputes
mobilize and accept
a short delay
long
delay
find an
alternative yard
none
available
accept a
long delay
Linking this portrayal to some alternatives
- Comparing the three ‘yard not available’ scenarios portrayed by the source-response diagram in the last slide and a common practice probability-impact grid (PIG) equivalent.
- Considering a traditional decision tree equivalent.
- Comparing a traditional fault tree or event tree equivalent.
- Systems dynamics, inference diagrams and other feedback loop portrayals as further examples, illustrated by an example from the rolling stock component of the Channel Tunnel project.
Cognitive mapping portrayal of feedback loops
Lack of system freeze
Tight time scale
Enforced work on
unfrozen items
Increased rework
Increased delay
More limited
resources
Increased cross-relation
between parallel activities
More parallel activities
Increase in
activity durations
More work to do
Design changes
Approved delays
Reproduced by permission of the Operational Research Society
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Systems Dynamics: Human error
Loh, T.Y., Brito, M.P., Bose, N., Xu, J. and Tenekedjiev, K. (2020), Human Error in Autonomous Underwater Vehicle Deployment: A System Dynamics Approach. Risk Analysis, 40: 1258-1278.
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Systems Dynamics: Human error
Next week…
- We will discuss the Ownership phase
- Recommended reading
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- Chapman(2019), Chapter 7, page 345-346
- Chapman and Ward (2011), Chapter 9 page 235-350
