Embed Size (px)
Citation preview
Quantitative Risk Analysis – Fallacy of the Single Number
World Tunnel Congress 2015Dubrovnik
Dubrovnik, 27.05.2015
Philip [email protected]
Alfred Mö[email protected]
Technikerstr. 32 6020 Innsbruck Austria www.riskcon.at
Rosengartenstr. 28 Schmerikon Switzerlandwww.moergeli.com
John [email protected]
1101 Worchester RoadFramingham MA 01701USAwww. johnreilly.us
Slide 2www.riskcon.at www.moergeli.comQuantitative Risk Analysis – Fallacy of the Single Number www.johnreilly.us
1. Uncertainty
2. Probabilistic and Deterministic Approach
3. Examples from Real Projects
4. Summary
Overview
Slide 3www.riskcon.at www.moergeli.comQuantitative Risk Analysis – Fallacy of the Single Number www.johnreilly.us
Uncertainty – Distinguish Between Basic Elements and Risk
Will always occur(e.g. elements in a cost estimation)
Exact price or time is uncertain
Uncertaintyin predictions
Basic Elements(Cost, Time, etc.)
Risk
Has a probability of occurrence Consequences (costs, time, etc.)
are uncertain
Slide 4www.riskcon.at www.moergeli.comQuantitative Risk Analysis – Fallacy of the Single Number www.johnreilly.us
Uncertainty in a 14 Day Weather Forecast
Example temperatures (German television):
Exemplary risk:No construction works
below 2°C
Additional probability that risk will occur
Increasing deviation
Date
Munich Temperatures
Slide 5www.riskcon.at www.moergeli.comQuantitative Risk Analysis – Fallacy of the Single Number www.johnreilly.us
Information re Deterministic Versus Probabilistic Method in Project Development
Deterministic approach: – single figure (sharply defined):
Determined (no range) Has high uncertainty Appears accurate but is not!
Probabilistic approach: –bandwidth represents the range of potential values
Uses ranges Degree of certainty changes
according to project progress
Cost Uncertainty
Planning Approval Construction
Goal: Best possible cost estimate during project development over time
large range for large uncertainties
narrower range for smaller uncertainties
Slide 6www.riskcon.at www.moergeli.comQuantitative Risk Analysis – Fallacy of the Single Number www.johnreilly.us
Probabilistic and Deterministic Approach
Slide 7www.riskcon.at www.moergeli.comQuantitative Risk Analysis – Fallacy of the Single Number www.johnreilly.us
Comparisons of Deterministic and Probabilistic Method
InputSingle risk
ResultOverall
risk potential
Single number:probability of occurrence times impact
50 % X 20k USD=
10k USD
Uncertainty not considered
Deterministic Method Probabilistic Method
Distribution: probability of occurrence and several values for the impact (e.g., minimum, most likely, and maximum)
Considers uncertainty
10kUSD
20kUSD
50kUSD
50 % &
A simple mathematical addition to give the aggregated consequence for all risks. This results in an expected consequence for the aggregated risks.
iitotal IpR *
Simulation methods produce a probability distribution based on thousands of realistic scenarios.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0%
1%
2%
3%
4%
5%
6%
7%
1,00
0
2,50
0
5,00
0
7,50
0
10,0
00
Val
ue a
t Ris
k
Rela
tive
Fre
quen
cy
Distribution Function (Impact in kUSD)
Slide 8www.riskcon.at www.moergeli.comQuantitative Risk Analysis – Fallacy of the Single Number www.johnreilly.us
Fallacy of the Deterministic Approach (1)
A deterministic method can give equal weight
to risks that have a low probability of occurrence and high impact
and risks that have a high probability of occurrence and low impact
using a simple multiplication of probability and impact.
This approach is incorrect.
Slide 9www.riskcon.at www.moergeli.comQuantitative Risk Analysis – Fallacy of the Single Number www.johnreilly.us
Fallacy of the Deterministic Approach (2) - Example
Very Likely
Likely
Possible
Unlikely
Very Unlikely
Negligible Minor Moderate Significant Severe
1 2 3 4 5
5
4
3
2
1
5
5
Flat tire
TBM fire
Give equal weight to completely different scenarios.
By multiplying the two elements of probability and impact, these values are no longer independent.
Loosing the probability information
Loosing the scenario impact information
The actual impact will definitely deviate from the deterministic value (i.e., the mean) see following example.
Example deterministic calculation:
TBM fire: (1/500) x 4,000,000 $ = 8,000 $
Tire damage mine dumper: 80% x 10,000 $ = 8,000 $
NPP accident: (1/10,000,000) x 80.000,000,000 $ = 8,000 $
Slide 10www.riskcon.at www.moergeli.comQuantitative Risk Analysis – Fallacy of the Single Number www.johnreilly.us
Examples from Real ProjectsApplying the Probabilistic Method
Slide 11www.riskcon.at www.moergeli.comQuantitative Risk Analysis – Fallacy of the Single Number www.johnreilly.us
Examples from Current Projects
Koralm Base Tunnel (Southern Austria)With a total length of 32.8 km and a maximum cover of 1.250 m the base tunnel will traverse the Koralpe mountain range. The tunnel system is designed with two single-track tubes (approx. 66-71 m² per tube) and cross drifts at intervals of 500 m. Excavation for the Koralm tunnel is executed by two double shield TBM’s for long distances.
Slide 12www.riskcon.at www.moergeli.comQuantitative Risk Analysis – Fallacy of the Single Number www.johnreilly.us
Example 1: Customized Distribution Function – The Scenario
Scenario:
A tunnel with 1,000 m of TBM excavation is designed without a final lining as a result of expected favorable geological conditions.
However, a final lining may become necessary in some sections if geological conditions turn out to be less favorable. If it will be necessary to excavate 700 m or more with a final lining, final lining will be implemented for the full length of 1,000 m.
Slide 13www.riskcon.at www.moergeli.comQuantitative Risk Analysis – Fallacy of the Single Number www.johnreilly.us
Example 1: Individual Distribution Function – Estimation and Result
The quantity is modeled by the individual distribution.
The financial impact is modeled by a deterministic value: 2,000 USD
Slide 14www.riskcon.at www.moergeli.comQuantitative Risk Analysis – Fallacy of the Single Number www.johnreilly.us
Examples from Current Projects
Hydro Electric Power Plant Spullersee (Vorarlberg /Austria)
Planned in 3 scenarios2 surface scenarios1 subsurface scenario
For comparison consider basic costs and risks for each scenario.
Ground risks subsurface scenario
Production outage surface scenario
Slide 15www.riskcon.at www.moergeli.comQuantitative Risk Analysis – Fallacy of the Single Number www.johnreilly.us
Example 2: Event Tree Analysis – Scenario Description
Scenario:Access road to the construction site of the reservoir
Probability of 40% that the access road will not be permitted (nature reserve)
In this case (risk does occur) there will be 2 alternatives:
1. Extension of the existing public road to the reservoir. Estimated probability for permission only 20%
2. No permission for the public road => new cableway for material transport Most expensive scenario (80%)
The whole scenario can be modeled by an event tree.
Slide 16www.riskcon.at www.moergeli.comQuantitative Risk Analysis – Fallacy of the Single Number www.johnreilly.us
Example 2: Event Tree Analysis – The Model
Risk Access Road
Not permitted
Public Road
Cableway for material transport
Permitted
40%
60%
20%
80%
8%
32%
60%
Costs for the access road are estimated to be 1,000,000.If there will be no permission, the costs for the access road are saved in a first step.
Omitted access road
8%-1,000,000 -1,000,000 -1,000,000
Extension of public road 467,500 550,000 880,000
Min Most likely Max
Omitted access road
32%-1,000,000 -1,000,000 -1,000,000
Cableway for material transport 1,912,500 2,250,000 2,925,000
Triangle
Slide 17www.riskcon.at www.moergeli.comQuantitative Risk Analysis – Fallacy of the Single Number www.johnreilly.us
Example 2: Event Tree Analysis – The Result
Cost bandwidth scenario public road
(opportunity)
Cost bandwidth scenario
cableway for material transport
After simulation the result is a probability distribution that displays the overall risk potential.There is a probability of 60% that the risk will not occur (see red distribution function).
8% x (-1,000,000 + 550,000) + 32% x (-1,000,000 + 2,250,000) + 60% x 0= -36,000 + 400,000 + 0
364,000 will not occur in reality
Deterministic Approach:
Slide 18www.riskcon.at www.moergeli.comQuantitative Risk Analysis – Fallacy of the Single Number www.johnreilly.us
Example 2: Event Tree Analysis – Risk Administration and Analysis Tool (RIAAT)
http://riaat.riskcon.at
Slide 19www.riskcon.at www.moergeli.comQuantitative Risk Analysis – Fallacy of the Single Number www.johnreilly.us
Summary
Every cost estimate for future events comes with significant uncertainties.
The probabilistic method delivers comprehensive information • range of probable cost• probability information• specifics of potential risk event
In particular, probabilistic methods support owners and contractors to better understand their risks.
• allowing contractors to price their work knowing those risks• allowing owners to budget accordingly
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0%
1%
2%
3%
4%
5%
6%
7%
1,00
0
2,50
0
5,00
0
7,50
0
10,0
00
Val
ue a
t Ris
k
Rela
tive
Fre
quen
cy
Distribution Function (Impact in kUSD)
e.g. 80%risk potential coverage
