Information to be provided
- Summary of the project, product, framework
The Department of Transport (DoT) through the Asset Condition Assessment Project (ACAP) is developing a clear understanding of asset condition at an individual asset, system and network level to meet the State’s objective of providing an integrated safe and reliable transport network. ACAP focuses on delivering reliable asset condition data to inform renewal requirements that best balance risk, cost and performance. DoT worked with its Technical Advisor to produce:
- A decision-making framework enabling the balancing of risk, cost and performance
- A data management framework,
- A pilot testing the framework and strategy using a technology solution
- A roadmap for subsequent stages.
- Description of project or framework addressing the assessment criteria
The project delivery was split into three core workstreams:
- Asset Decision Support Framework (ADSF),
- Modelling Tool Assessment and Data Management Framework (DMF)
- Pilot to integrate and test the deliverables developed in the first two workstreams.
The ADSF was developed with the following drivers in mind:
- To inform decision making regarding the future management and funding options for the Victorian public transport network.
- To support the testing and validating of ACAP data to support the project vision and objectives.
By highlighting three core themes of the two drivers, these being future management, funding options and testing and validating the ACAP data, we can see a distinct link back to the three core asset management principles of risk, cost and performance. At its core, the ADSF is an exercise of balancing risk, cost and performance over time to support the DoT in meeting their objectives in providing an integrated, safe and reliable transport network across Victoria.
In addition to these general principles, the ADSF was also designed with consideration to legislative and corporate objectives and the Victorian Government’s Asset Management Accountability Framework (AMAF). The legislative and corporate objectives were incorporated to set the broad direction, to identify requirements and potential define specific inputs for any funding modelling exercises. The AMAF also set overall expectations for the “whole of lifecycle approach”, governance, resourcing and data management.
The ADSF was further bolstered by the development of a DMF and Modelling Tool Assessment. The DMF was developed to provide a data-focussed foundation to support the ADSF as effective asset management fact-based decisions are underpinned by the availability of good quality data. The data itself also needs to be well understood and applied in the appropriate business context to enable sound, fact-based decisions.
The Modelling Tool Assessment then provided a high-level assessment of potential asset renewal modelling tools to support DoT in choosing the correct one for their future asset management decision-making needs. Each of the modelling tools were assessed against the following weighted assessment criteria:
- Functional requirements
- Non-functional requirements
- Architectural requirements
- Preliminaries (which included configuration and set up)
A shortlist of tools was then presented in different tiers to support DoT in selecting the most appropriate modelling tool to pilot to test their asset management decision-making needs.
The ADSF, DMF and Modelling Tool Assessment were then tested in a Pilot. The main objective of the Pilot was to demonstrate to DoT how the asset condition data collected throughout ACAP could be incorporated into an asset renewal model and what insights could be obtained from the model outputs. Once again, the Pilot was, at its core, a demonstration of the balancing of performance (asset condition data), cost (asset renewal model) and risk (insights from model outputs).
The Pilot began with a phase of data processing where data from ACAP Phase 2 and several other data sources were processed and transformed into a suitable format for modelling input into a modelling tool. Data gaps had to be filled and the quality ratings for each data source were scaled as necessary.
While condition data is a key requirement for any renewal modelling exercise, it is not the only data input requirement. Other asset information including but not limited to cost, performance, criticality and risk were considered and combined with condition data to ensure sensible modelling outputs were achieved.
The AECOM Plan$pend platform was selected as the appropriate modelling tool for the Pilot as the platform was able to determine the end of the useful life for each of the assets taking into account all the asset information. Each of the assets were then flagged for a renewal action and then prioritised based on age/condition/performance, criticality/risk, and O&M cost savings.
The modelling outputs were then displayed through a series of dashboards in PowerBI to further enable DoT’s decision-making process. In particular, the dashboard included the following views:
- Executive Overview: The Executive Overview screen allows for a high-level overview of the ACAP dataset and the renewal model outputs.
- Renewal Profile: This view allowed for a more detailed view of renewal projects generated by the model. Renewal forecast information was depicted through the bar chart, per asset level in the table and geospatially on the map.
- Network Planning: This view provided detailed information for asset performance, criticality and risk.
- Forecast Investment Needs: This view provided insights into current and future spend (capital cost) on asset renewal and backlog and how it would affect asset condition over time. This view truly encompassed the balancing of risk, cost and performance over time.
- Scenario Comparison: To further support DoT in their decision-making, this view provided a comparison of multiple scenarios in terms of annual capital cost, backlog cost, condition rating and remaining useful life of the assets through the line graphs across the current and future years.
Data Quality: This view illustrated the confidence level of the datasets and consisted of a weighted average data quality scores for each data type.
All three workstreams were delivered by a joint team from AECOM and WSP through the DoT Technical Advisory Panel over an eleven-week program. The diverse nature of the joint team ensured the solution developed for DoT was specifically suitable for their needs. The project has validated the data collected through the previous stages of ACAP and supported DoT in achieving their overall objective of delivering an integrated safe and reliable transport network in the short, medium and long term
- Opinion as to specific contribution made by the nominated individual/team/organisation
The joint DoT, AECOM and WSP team have been able to validate the ACAP data and support DoT in connecting their overall asset management objectives with the ACAP data through the development of an ADSF and adjoining frameworks and assessments. The ADSF also serves as the vehicle that enables the balancing of cost, risk and performance over time for DoT; ensuring that they are able to make the optimal decisions for their assets.
Additionally, the use of the Plan$pend model was also unique. Through many projects undertaken with US DoTs, historical asset and degradation data was incorporated into the Plan$pend model. This data is the foundation for its degradation model and was utilised by the team to realistically model degradation and renewal triggers and actions for the Victorian transport assets. This increases the accuracy and reliability of the renewal models that were generated for the pilot, further demonstrating the value of the data and the benefits of using the ADSF.
It must also be said that although the degradation models were based on real US data, the overall project still considered the specificity of the Victorian transport network and the unique contractual arrangements. The ADSF, DMF, Modelling Tool Assessment and Pilot all considered the vertically structured agreements between DoT and the asset maintainers (Rail Transport Operators (RTOs)). The deliverables took into account the delineation between responsibilities of all the parties and specifically tailored decision-making points and outcomes for each party.
The works have also formed the foundation for subsequent phases of DoT’s ACAP and strategic asset management works; where more asset classes will be modelled using the methodology outlined through the successful Pilot. The aim of the next phase of modelling will be to model further renewal profiles, thereby equipping DoT with the capability to make better decisions regarding the balancing of risk, cost and performance for more asset classes in their portfolio.
- General comments
The DoT, AECOM and WSP team worked together in a collaborative form, holding several workshops and sessions to develop deliverables hand-in-hand. Each workstream had a single lead and all leads liaised with each other on a weekly basis to ensure that each workstream could incorporate changes or learnings quickly. Team members also worked across different workstreams which also reduced the risk of workstreams becoming siloed and deliverables being developed separately. This also helped with cost control as the team could be as condensed as possible with all team members having the required background knowledge to move between tasks easily.
The team members selected for the project were diverse in background and not only included members from an Asset Management background but from Transport Advisory, Rail Engineering, and Data and Analytics. The chosen skillsets and team members also complemented the DoT project team members. This follows a philosophy that the AECOM Asset Management & Materials (AM&M) team hold dearly whereby we recognise that we are stronger because of our differences and as such, the AM&M team were awarded the AMPeak Diversity Award in 2021.
Together the joint AECOM and WSP team was able to work collaboratively with the DoT team and draw upon their different experiences and lenses of the Victorian Transport Network to develop the most suitable frameworks and assessments for DoT. This collaboration across different disciplines was highlighted mostly through the pilot where the expertise of different team members had to be combined to produce the best outcome for the project. For example, the experience of the Transport Advisory team members was pulled together with the experience of the Data Analytics team and DoT’s team to better understand the different use cases for the final dashboard.
In essence, the project was undertaken in a manner where risk, cost and performance were balanced effectively to demonstrate how the best outcome can be achieved for DoT.