1. Optimisation Modelling for Roads through an Outsourced Service
Greater Shepparton City Council
Case Study

2. Why might a Council outsource its Pavement Management System?
It can be a more affordable option, especially for;
resourcing issue (human resource or cost constraints).
limited ability to attract and retain technical expertise to administer a PMS (primarily regional areas).
PMS software (what to buy and how much to pay).

3. What is a Pavement Management System?
It’s a planning and decision making tool for pavements. It allows you to;
Model pavement deterioration– life cycle analysis
Investment options v Consequences
Activity decisions (treatment matrix)
Optimisation

4. Our Decision It’s more cost effective (at this point in time)
Removes risk (sourcing skills)
To commence optimisation
To introduce objectivity

5. Shepparton Region

6. Our Road Network GSCC Road Network Total Asset Value $1.3B
Total Road Length
2400km
Seal Roads
1143km
Total Road Asset Value
$519M
Sealed Road Asset Value
$421M
Unsealed Road Asset Value
$98M

7. The Forgotten PMS Greater Shepparton had a PMS up to 2010/11
2 staff with administration access
Inaccurate data (PMS was resource hungry)
Considered Risk
Owning and operating software
Recruiting and retaining technically competent people

8. 8’s 9’s and 10’s
2010/11 Condition Survey was done by visual inspection
Data reduced to an asset section condition score (0-10)
Asset Management System Data Dump
AMS our only source of (limited) information
Resorted to “fix worst first”
Making 8’s 9’s and 10’s our priority
Considered Risk
We are not optimising our spend
That our assessment of roads is subjective

9. Keeping the Crew’s Busy
Task
12/13
13/14
14/15
Reseals
$1,955,000
$1,786,000
$1,790,000
Reconstructions
$4,220,000
$3,860,000
$4,000,000
Asphalt/Major Patching
548,000
$634,000
$591,000

10. Indicative Optimised Program over 20 years

11. 2016/17 Works Breakdown

12. Optimisation v Fix Worst First
Where road investment is biased toward predictive maintenance, rather than allowing a road to deteriorate until it needs more extensive reconstruction.
Fix Worst First
An overall score is attributed to the road section based on the overall condition (based on the assessors perceptions) and the worst sections are fixed first.

13. Trigger for Change Trigger was our 2014/15 Tri-annual Condition Survey
Opted for video and laser road surface profiling
Road asset broken down into 20m sections, with each distress identified and measured within that section
No need for 8’s, 9’s and 10’s.

16. Raw data

17. Assetic - Objectives Optimised Treatment Programs
Rolling 3 Year Capex Program
Consequence Modelling
1-25 year condition prediction modelling
Funding Gap Analysis
Ability to use data in GIS

18. Assetic Modelling Road Definitions

19. Asset life cycle profiles

20. Condition v Budget options
The type of outputs we expect to see:
A comparison of different budget scenarios where we can optimise the spend and compare the benefit in overall network condition

21. Backlog calculation at $5M per annum
Calculate the backlog of works and see the impacts of different budget scenarios on the calculated backlog

22. GIS graphical comparison of service levels for different budget scenarios
A visual representation of the of the network under different budget scenarios

23. Capital Plan by asset
A breakdown of the spend required on each asset over the term of the model (i.e. 10 years). We will also get a list of which assets need work, when they require work, and what type of work they need (i.e. slurry seal vs AC overlay vs rehab)

24. Basic Comparative Costs – GSCC Network
In House Cost
Annualised Condition Data
$40,000 (over three years)
Technical/Administrator (0.5FTE)
$50,000 inc oncosts
PMS Software (licensed)
$25,000
$115,000
Outsourced
Annualised Condition Data
$40,000
PMS Service
$25,000
$65,000
“Piece of string” An internal service can be > $200,000p.a depending on staff and software.
Network size is a major contributing factor e.g State Road Authorities

25. Wrap up Outsourcing can be an affordable option
Comes fully resourced, low risk of service delivery problems
Data hosted by third party
PMS builds in objectivity to capex decisions
PMS allows for optimisation/predictive models
Private sector is willing to work with Councils