Collection of asset inventory, condition and performance, treatment and work history, and external decision-maker and public perception in a manner that can be incorporated into DOT TAM programs.
Improvements in this Area are aimed at advancing methods for collecting and assuring the quality of key data supporting TAM analysis, reporting, and decision-making, Improvements may include deployment of innovative technology solutions, as well as improved quality control and assurance techniques and streamlined business processes.Open the full set of Response Templates for Area B
Understanding asset inventory, condition and performance is fundamental to TAM. Data collection activities must be planned to ensure that the right data are gathered – with sufficient quality to support decision making. Data collection is costly so agencies must carefully manage scope and work to achieve efficiencies.Explore Section B.1
Agencies track information about capital projects from planning through construction phases. If properly structured, this information can be leveraged within TAM to update asset inventories and condition projections, and maintain asset-specific work histories that can be used to better understand asset performance.Explore Section B.2
Capture of standard maintenance work order and accomplishment information can provide valuable insights for asset life cycle planning and maintenance budgeting.Explore Section B.3
While many TAM decisions are based on technical factors such as condition indices, it is important to put processes in place to understand both asset user and decision maker values. These values can be used to make appropriate use of the technical information for decision making.Explore Section B.4
This project showcases the value of defining data collection standards and data capture strategies that allow for consistency field data collection. These are foundational to development of mobile field data collection tools and downstream analysis tasks. Also highlighted in this project is the cost benefit analysis that must be made with respect to software customization decisions.
This case study demonstrates how a specific DOT could advance these elements from practice level 3 to practice level 4, by implementing improvements for automated data quality collection audits.Explore Case Study
This project showcases the ability to leverage Federal requirements as an impetus to addressing a larger and more complex issue. Additionally, this project reveals the importance of change management and careful attention to understanding in entirety:
- the business process,
- what will change, and
- how it will affect the stakeholders.
The training and certification aspects of the case study illustrate a method to support sustained change.
This case study demonstrates how a specific DOT could advance these elements from practice level 1 to practice level 2 or 3, by implementing improvements for data quality collection plan.Explore Case Study
This project demonstrates establishing enterprise standards and driving consistency so that statewide inventory can be collected uniformly. This project also illustrates the careful analysis of determine data value to guide investment decisions on how much data to collect and when dealing with large data sets the importance of automating processing steps to create efficiencies.
This case study demonstrates how a specific DOT could advance these elements from practice level 2 to practice level 3, by implementing improvements for manual data collection automation and collection tools and methods consolidation.Explore Case Study