Linking information across different systems enables agencies to quickly answer important questions that might have taken hours of staff time without integrated data. Integrating data opens up access to previously siloed data sets across the organization. It allows an agency to reduce duplicative effort, achieve efficiencies and derive greater value from its data. Some questions that rely on integrated data are:
Investments and Accomplishments
- What have we spent over the past ten years on route X in county Y (across all assets and including both maintenance and rehabilitation)?
- What percentage of deficient pavements will be addressed by our current capital and major maintenance programs?
Work Costing and Scoping
- What does it cost us to restripe a mile of pavement markings in each district?
- What locations identified along the linear referencing system (LRS) are planned for next year?
- Do the costs estimated by our pavement management system match what we are actually seeing in our projects?
- If we upgrade our guardrails whenever we do a paving project, how long will it take, and what will it cost to eliminate the current backlog?
- How can we best plan our projects to address multiple needs that may exist along a corridor?
- How many years does our standard mill and fill pavement treatment last for roads in different traffic volume categories?
Tradeoffs and Prioritization
- How should we prioritize our asset replacement/rehabilitation projects, considering not only life cycle management strategies but also stormwater management, safety, congestion, non-motorized, transit and ADA needs?
- How should we allocate our available funds across multiple asset types?
- What assets were on route X in county Y prior to the storm? What will it cost to replace them?
An integrated approach to asset data collection, management and reporting not only makes it easier to answer these questions; it also can reduce costs. Opportunities for achieving efficiencies include:
- Using a single application to manage information about multiple assets.
- Using Data Warehouse/BI and GIS tools to provide reporting and mapping functions rather than investing effort to develop these capabilities within individual asset management systems.
- Gathering data on multiple assets through the same approach – using mobile technology, video imagery and/or LiDAR (see section 7.2)
- Sharing asset data across the life cycle – for example, automating methods for extracting asset data from design plans to update asset inventories (described further below).
Emerging technologies and new data sources are making an integrated approach to asset data management even more important. For instance, there are increasingly opportunities to use data collected from cell phones and connected vehicles that may cut across many asset categories. Also, there has been and will likely continue to be rapid advancement in machine learning techniques, such as for extracting asset data from video imagery or predicting optimal maintenance interventions given a wide array of data. Using these techniques typically requires establishing large, integrated data sets.
In addition, advances in computer-aided design and engineering software are making it possible to integrate asset data across the life cycle and achieve efficiencies and cost savings in maintaining asset inventories. See the discussion in section 7.1.4 further on.