Review of Benchmark Infrastructure Costings
Presenter:
Viraj Abeykoon
24 July 2018
1 Title of Presentation goes here
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Disclaimer
Review of Infrastructure Benchmark Costings
2 Title of Presentation goes here
01 Introduction
02 Overview of Methodology
03 Background Data Processing
04 Monte-Carlo Analysis
05 Standardising Rates
06 Example Results
Topics
Review of Infrastructure Benchmark Costings
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Introduction01
Review of Infrastructure Benchmark Costings
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The project aims to achieve:
> Streamlined delivery of PSPs and ICPs
> Provide accurate Benchmark Cost Estimates with a high
degree of confidence
6 Infrastructure categories were investigated:
> Roads and Intersections
> Bridges
> Culverts
> Sporting Pavilions
> Sports and Recreational Fields
> Community Centers
Introduction01
Review of Infrastructure Benchmark Costings
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Overview of
Methodology
02
Review of Infrastructure Benchmark Costings
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Collate VPA DataExtract Statistical
PropertiesRun Monte-Carlo
Process
Prepare representative drawings and
extract quantities
Obtain Total Project Costs for
Infrastructure Items
Obtain two types of Rates
Overview of Methodology02
Review of Infrastructure Benchmark Costings
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Background Data
Processing
03
Review of Infrastructure Benchmark Costings
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Create a database of previously adopted rates
Split to various infrastructure items
Checked for Regional/ Topographical variations
Estimates with insufficient granularity were discarded
Background Data Processing 03
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Background Data Processing
> Extracting Statistical Properties
Average Rate for each element
Standard Deviation for each element
> Regional Variances and Topographical
Variances were not observed in the
data.
> Extracted costs modeled to follow a
normal distribution
Example
03
50 52.5 55 57.5 60
Item Estimate 1 Estimate 2 Estimate 3 Mean Standard
Deviation
Kerb (per
meter)
55 52 60 55.67 4.041
Drainage Pipe
(per meter)
260 250 300 270 26.458
Review of Infrastructure Benchmark Costings
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Monte-Carlo Analysis04
Review of Infrastructure Benchmark Costings
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> Monte-Carlo analysis is a world-renowned tool used to
simulate a range of possibilities
> In this instance, a range of infrastructure costs
> Results can be used to provide Probabilistic Estimates
> Cardno conducted 200,000 simulations
> Quantities for above simulations were extracted from
representative drawings
Monte-Carlo Analysis04
Review of Infrastructure Benchmark Costings
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Monte-Carlo Analysis04
Item Rate ($/m) Quantity (m) Total ($)
Kerb 56.00 10 560.00
Drainage 265.00 10 2650.00
TOTAL 3210.00
Review of Infrastructure Benchmark Costings
50 52.5 55 57.5 60
%
230 250 270 290 310
%
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Monte-Carlo Analysis
Repeating this process over 200,000
iterations provides a distribution of
possible project costs.
P50 and P90 Totals were selected.
04
0
5000
10000
15000
20000
25000
24
300
00
25
410
00
26
520
00
27
630
00
28
740
00
29
850
00
30
960
00
32
070
00
33
180
00
34
290
00
35
400
00
36
510
00
37
620
00
38
730
00
39
840
00
40
950
00
42
060
00
43
170
00
44
280
00
45
390
00
46
500
00
Fre
qu
en
cy
Project Cost
Cost Frequency Distribution
Review of Infrastructure Benchmark Costings
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Standardising Rates 05
Review of Infrastructure Benchmark Costings
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Standardising Rates
> Obtained 2 sets of rates for each item
producing P90 and P50 Monte-Carlo
totals
> Based on ‘Inversing’ Normal Distribution
of rates
> Example Monte Carlo result is P90 = $3,420
05
Item P90 Rate
($/m)
Quantity (m) Total ($)
Kerb 57.00 10 570.00
Drainage 285.00 10 2850.00
TOTAL 3420.00
Review of Infrastructure Benchmark Costings
50 52.5 55 57.5 60
%
230 250 270 290 310
%
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Example Results06
Review of Infrastructure Benchmark Costings
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Example Results06
Review of Infrastructure Benchmark Costings
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Example Results06
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Example Results06
Review of Infrastructure Benchmark Costings
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Example Results06
Review of Infrastructure Benchmark Costings
Thank you
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