Area B – Collect Data

Area B – Collect Data

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
Inventory, Condition, and Performance Collection

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.

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Response Templates
Project Information

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.

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Response Templates
Maintenance Information

Capture of standard maintenance work order and accomplishment information can provide valuable insights for asset life cycle planning and maintenance budgeting.

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Response Templates
Priority Criteria and Values

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.  

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Response Templates
Case Studies
Mobile Field Data Collection Implementation
Virginia DOT

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.

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Data Collection Quality Management Plan Implementation
Colorado DOT

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.

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Statewide Vehicle-Based Data Collection
Utah DOT

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.

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