Palisade Conference
Francois Joubert – Transnet Capital Projects
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1
Context and Problem statements
• Transnet Capital Projects currently has approximately 130 projects in its
portfolio:
• Spread across 4 phases of the project life cycle
• Various complexities
• Value from R2 million to R13 billion
• Conveyor belt installations, quay walls, rail rehabilitation, wash bays, new
railway lines, pipe rack installations, fire equipment installations, building
rehabilitation etc.
• We use MS Excel to create the risk registers and then capture it in CURA
where all risk follow-up and reporting is done from.
• Problem Statement 1: Taking costing and uncertainty into consideration,
develop methodology which can be used on data extracts from Primavera to
indicate which of the projects are likely to be completed at higher than Approved
Budget.
• Problem Statement 2: What does Transnet see as an acceptable risk register
model?
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Part 1: Simplified costing report
Cost Item
Approved
Budget
Committed
Spend
Uncommitted
Spend
FFC
Project 1, Item A
R100
R80
R20
R90
Project 1, Item B
R50
0
R50
R50
Project 2, Item C
Etc.
•
Item A: We have a budget for R100 and have placed a contract for R80. We assume that we have a
90% chance of spending between a Low of 85%, an middle of 90% and High of 105% of the outstanding
R20.
•
TotalItem A = Committed Spend + Monte Carlo (Uncommitted Spend)
•
TotalItem A = Committed Spend + RiskLognormalt(0.05,0.85*R20,0.5,0.9*R20,0.95,1.05*R20)
•
TotalItem A = R80 + RiskCompound(RiskBinomial(1,0.9),RiskLognormalt(0.05,R17,0.5,R18,0.95,R21))
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Part 1: Simplified costing report
TotalItem A = R80 + 90% chance of
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Part 1: Simplified costing report
Cost Item
Approved
Budget
Committed
Spend
Uncommitted
Spend
FFC
Project 1, Item A
R100
R80
R20
R90
Project 1, Item B
R50
0
R50
R50
Project 2, Item C
Etc.
•
Item B: We have a budget for R50 and have not placed a contract. We assume that we
contract value will range between 95% chance and 110% of the contract value. The
Budget is used as the middle value.
•
TotalItem B = Monte Carlo (Uncommitted Spend)
•
TotalItem B = RiskLognormalt(0.05,0.95*R50,0.5,R50,0.95,1.10*R50)
•
TotalItem B = RiskLognormalt(0.05,R47.5,0.5,R50,0.95,R55))
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Part 1: Simplified costing report
TotalItem B =
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Part 1: Simplified costing report
Cost Item
Approved
Budget
Committed
Spend
Uncommitted
Spend
Forecast
ed final
cost
Project 1, Item A
100
90
10
95
Project 1, Item B
50
0
50
50
Project 2, Item C
etc
•
TotalProject = ∑ TotalLine – all Contingencies
•
RiskTarget function is used to find position of FFC on generated distribution.
•
The simulation is run on the entire dataset which is exported from Primavera.
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Part 1: Logic
  
Budget /
FFC
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Part 1: Example
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Part 1: Advantages and Improvements
• Advantages:
• Quick and easy to answer management questions such as:
• Which project can we declare saving on?
• Which large projects do we have a risk of going over budget and why?
• Early warning regarding cost overruns.
• Double check on existing processes (costing/estimating and contingencies).
• Can provide business intelligence regarding problems in the estimating
process.
• Improvements
• Go one level deeper.
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Part 2: Logic for Risk Registers
• Scope:
• Multiple and once-off risks.
• Schedule or Cost as inputs.
• Cost can be Rate * Time.
• Must make provision in distribution selection for risks which are more risky.
• Must calculate Specific Contingency.
• Must rank risks (in addition to using Proximity and Tornado graphs).
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Part 2: Logic for Risk Registers – Frequency
•
•
In both cases, the rest of the logic
remains the same.
Typical Poisson:
• Damages to underground
services.
• Inclement weather
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Part 2: Logic for Risk Registers – Impact type
•
Schedule gets
converted to cost
based on weighted
standing time cost.
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Part 2: Logic for Risk Registers – Distribution type and Ranking
•
•
•
Use RiskCompound
together with
RiskLognormalt.
Remove all Zero values
– we don’t want the
model to ‘hide’ high
impact, low probability
risks.
We rank according to
the 80th percentile –
together with Tornado
graphs.
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Part 2: Logic for Risk Registers – Contingency
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Part 2: Example
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Part 2: Advantages and Improvements
• Advantages:
• Flexible.
• Expandable.
• Caters for all our requirements.
• Improvements
• Complex If-statements.
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