Component D
Data Usability and Analysis
Data Usability and Analysis is the existence of useful and valuable data sets and analysis capabilities available in accessible, convenient forms to support transportation performance management. While many agencies have a wealth of data, they are often disorganized, or cannot be analyzed effectively to produce useful information to support target setting, decision-making, monitoring or other TPM practices. Read more…
Implementation Steps
Data usability and analysis is broken down into three interrelated subcomponents:
- Data Exploration and Visualization: Availability and value of data, tools, and reports for understanding performance results and trends.
- Performance Diagnostics: Availability and value of data, tools, and reports that allow an agency to understand how influencing factors affected performance results both at the system and project levels.
- Predictive Capabilities: availability and value of analytical capabilities to predict future performance and emerging trends.
Making the Connection
Data Usability and Analysis (Component D) supports all TPM practices undertaken at an agency. Without data that is fully understood and utilized, an agency is wasting resources collecting and storing data that is not being used. Analysis of data provides the insight necessary for the agency to adjust strategies to improve performance.
Learn More
The Data Usability and Analysis chapter contains three sections:
Keep reading the complete Component D: Data Usability and Analysis…
What it Takes
A proactive approach to data usability can ensure that available data are put to good use for TPM. Agencies should examine not only the data and tools that are available for performance monitoring and reporting but also the backgrounds and capabilities of the staff that will be analyzing and using the data. Build staff capacity through recruiting, training, and mentoring
External collaboration can be pursued to help provide the necessary capabilities when partner agencies share common performance monitoring and reporting needs. In this situation, available staff resources can be pooled to take advantage of complementary skill sets across agencies. Staff roles and responsibilities can be negotiated as part of data sharing agreements.
It is important to keep in mind that most agencies already have capabilities for data analysis in place. The processes defined in this guidebook can be viewed as a way to build on existing capabilities in order to strengthen the value of data for transportation performance management.