Data Practices Chapter 7 – Key Themes

  • Date: February 18, 2022

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Key Themes

When it comes to making decisions, data is one of the most important tools that agencies have to ensure that their decisions are beneficial to their customers and the agency. Obtaining data is the first part of the process, whether it comes from traditional pen and paper or automated technology that exports data directly into the hands of analysts. By following data standards, agencies create efficiencies in data sharing and analysis both within their organization and when sharing with outside entities. Increasingly, stakeholders of transit agencies expect agencies to publish open data, and most agencies already make use of open data sources to facilitate both day-to-day operations and planning.

How data is used is just as important as how it is collected, stored, and disseminated. Planning and performance monitoring are two of the biggest uses of transit data. Both internal agency data, open data, and other external datasets allow agency staff to make data-driven planning decisions. Partnerships can also provide novel datasets, and in turn be strengthened when an agency shares its own data effectively. Besides creating more efficient services, data is also critical in ensuring that transit service is accessible and equitable in the agency’s service area and that the service provided is useful for different population groups to make different types of trips.

The following are key themes among the data practices summarized in this Guidebook.

The adoption of new technology can not only improve data collection and analysis, but also improve customer access to data.

The adoption of most new technologies not only enables agencies to collect data passively but also to provide that data to customers to help with their trip planning. Technologies like AVL systems provide agencies with large samples of runtime, speed, and on-time performance data, and greatly reduce the need for manual ridechecks that provide only small samples of data. At the same time, these systems enable real-time vehicle location information to be disseminated to customers through mobile apps or on agency websites, thereby improving their ability to plan their trips. Similarly, APC systems provide agencies with large samples of ridership data and, at the same time, can in some cases disseminate real- time passenger load data to customers.

Adopting industry data standards let agencies easily use tools that consume common datasets

The adoption of standards such as GTFS opens up new tools for agencies to provide information to customers and conduct different types of analysis. GTFS allows riders to use free trip planning tools such as Google Maps or an agency-branded mobile app. The schedule and spatial data included in a GTFS feed, such as route alignments and stop locations, also allows agencies to more easily conduct Title VI service equity analyses and accessibility analyses using GIS software.

The more data an agency has available, the better it can monitor performance and make planning decisions

Making good planning decisions is dependent on having good data to back those decisions up. Similarly, effective performance monitoring provides an early signal of problems that need an agency’s attention— issues that can then be solved through good planning decisions. The more data are available to an agency, the better decisions it can make. For example, when adjusting service levels, agencies can review performance monitoring statistics based on APC or ridecheck data to see if any of their current routes are experiencing overcrowding. Similarly, data showing declining ridership on a specific route or service would allow an agency to make the decision to reallocate its resources away from that service and into areas of greater need.

Agencies can make better decisions using external data, and partnerships can be key to accessing this data

Data collected or created by other entities can be useful to transit agencies when planning new routes or making service modifications. While datasets created by entities like the Census Bureau are open and available online, many datasets maintained by other entities may not be publicly available. For example, regional or statewide travel demand models can provide valuable information on the demand for certain trip connections in a region. Unless an agency forms a partnership with these entities, it may be difficult to access and use this data regularly, let alone interpret it. Similarly, partnerships with major employers or colleges and universities can open up new datasets for agencies, including where workers or students live. This allows agencies to better tailor services to the needs of these unique groups.

Additional Considerations for Decision-Making

Despite the usefulness of data, it should not be the only source of decision-making when it comes to transit planning. Certain datasets, particularly when in aggregate form, can smooth over signs of poor performance that many riders encounter on their day-to-day journeys. For example, on-time performance may be fine when averaged over the course of an entire peak period; however, there may be one or two trips that are consistently late. Those trips hide in the data yet frustrate riders nonetheless. Therefore, things like public outreach, feedback loops, and stakeholder outreach can be just as important as data collection and analysis.