The challenge
Situated between Geelong and Ballarat and just one hour’s drive west of Melbourne, Golden Plains is a vibrant rural municipality renowned for its food and wine, iconic music festivals and goldfield heritage. With many attracted to the area’s rural lifestyle, affordable housing, and proximity to larger cities, it is considered one of the fastest-growing regional Local Government Areas (LGAs) in Victoria. The current population is 24,249 and is expected to increase to 42,193 people by 2041 (a growth rate of around 2.6% per annum).
As the community grows and expectations increase, there is ongoing pressure for higher quality, always-available assets, from roads and buildings to park furniture and play equipment. For Golden Plains Shire Council, this means finding ways to offer a higher level of service for the same amount of money — doing more with less.
To achieve the best outcomes for the community, including future generations, Golden Plains aims to take a whole-of-life approach to managing its aging infrastructure while meeting agreed levels of service in the most cost-effective manner. There is no one-size-fits-all answer — it must use a mix of approaches, from preventive to predictive maintenance, while minimizing risk for all critical assets.
Looking ahead to the next 10 years, Golden Plains knew it needed to be prudent in its investment decisions. And yet, the greatest upfront challenge was not having a holistic view of the condition of its assets. With information spread across multiple systems — AssetAsyst, Moloney, myData, SynyergySoft, as well as GIS — the council lacked a standardized approach to managing asset data.
When capturing information on road defects, for example, data needed to be entered into two separate systems, resulting in extra work and increasing the risk of human error. Another issue was using a spreadsheet to manage road asset data. Important information could be accidentally deleted by writing over cells, and there was no audit trail. In addition to this, staff needed to learn how to use multiple systems to manage asset data.
Golden Plains urgently needed a single source of truth for its asset data — a central repository across its portfolio for better visibility of the state of all assets. On top of creating a single asset register, it also needed a single solution to help manage the asset lifecycle process — including maintenance, accounting, and predictive modeling — to help improve cost efficiency, maintain performance and minimize risks.
The solution
Golden Plains implemented an enterprise asset management (EAM) solution and chose to partner with Brightly to implement the Assetic platform, in line with their corporate directive to migrate software to cloud solutions. (Brightly is now known as Siemens Asset Management, and Assetic is part of the Siemens portfolio.)
The council had confidence in Brightly (now Siemens) as it knew it was a world-class software provider that was well-used by LGAs in Victoria and throughout Australia. The solution was also strong in GPS support; could be self-implemented, module by module, at the council’s own pace; and had a strong user community with resources and events offering knowledge-building and networking opportunities.
Golden Plains started by implementing the asset register on a class-by-class basis. By migrating to
Assetic, Golden Plains can now manage its asset data in a structured way — preventing data errors and duplication while creating a systematic approach for all asset-related decision-making and accounting. “With the help of Brightly [Siemens] we have consolidated our asset data sources into a single source and streamlined data management process,” says Wendy McAlpine, Coordinator of Asset Management at Golden Plains Shire Council.
Assetic has also been a huge help in improving the council’s maintenance and road defect inspections. Golden Plains started with two asset classes in the maintenance module to understand the capacity of the maintenance system, as at the time they were not using any maintenance system. For the first time, Golden Plains has been able to view target completion dates for each defect. This clearly indicated that the maintenance teams had not been scheduling repairs in accordance to the road hierarchy, providing strong evidence that they should migrate managing maintenance requests into the EAM platform.
More recently, Golden Plains implemented Brightly’s asset lifecycle prediction modeling and capital planning software, Predictor, which is also now a part of the Siemens portfolio.
Golden Plains now has a solid history of planned and reactive maintenance activities across its building portfolio, helping the council understand which areas they needed to focus their attention on. Predictor also highlighted the importance of having fit-for-purpose data for modeling, providing insights on funding deficiencies and improving staff buy-in around renewable requirements.
The results
By consolidating data into one system and creating a standardized approach to data management, Golden Plains better understands the lifecycle of its assets, giving them confidence in making data-driven decisions.
What’s more, buildings maintenance data showed Golden Plains that they were spending considerable time and money on septic issues at its buildings, prompting the team to investigate further.
Looking ahead, the council is exploring how they will migrate roads and drainage maintenance into Assetic for planned and reactive maintenance, with work to date analyzing existing business processes and highlighting the need for additional resources and streamlined workflows.
With new roads condition assessments scheduled to take place next financial year, the council is also keen to use the data in Predictor to help up-manage their renewal works planning.