Best Practices: How to Effectively Use Data to Drive Meaningful Decision Making in Public Transit

What does data-driven decision making look like in public transit? In an era where public transit networks must be more efficient, sustainable and responsive, a culture of evidence-based continuous improvement is crucial for success. Despite the growing availability of data, many agencies struggle to use it effectively to drive meaningful change. The key to unlocking data’s full potential is transforming it into actionable insights that enhance operations, improve rider experiences and support sustainability goals.  

The data challenge: Fragmentation and inaccuracy  

Public transit agencies collect vast amounts of data daily, from ticketing and vehicle location to rider counts and environmental metrics. However, much of this data remains fragmented across multiple systems, making it difficult to create a unified view of operations. In some cases, data is incomplete or locked in proprietary systems, requiring specialized skills to access and interpret it. As a result, insights are delayed, inaccurate or unactionable, hindering timely, informed decision making.  

Best practices for data-driven decision making  

To overcome these challenges, public transit agencies must adopt a structured and comprehensive approach that moves beyond siloed data streams. Below are several best practices for transforming raw data into actionable insights, which can make a difference.  

1. Acquire, clean and format transit data   

Effective decision making starts with collecting data from sources like vehicle location, rider feedback and operational metrics. This data needs to be cleaned, removing errors and anomalies, and formatted consistently for easier processing. While it may not always be possible to collect all data from the outset, a consistent approach enables the use of data from incompatible sources in the future. An intelligent data platform can help transit agencies consolidate and prepare disparate data sources for information processing.   

2. Convert data into rich information: Understanding what happened and when  

Once data is clean and consistently formatted, patterns emerge, such as service performance—like whether the right vehicle was in the right place at the right time. This processed data forms a repository of valuable information for deeper analysis.    

3. Transform data to knowledge: How experience enhances understanding of impact in transit  

Once a set of rich information exists, analysis can uncover trends, performance and real-world impacts. With time and experience, trained transit professionals can conduct cost-benefit assessments and prioritize targeted improvements.   

4. Identifying the cause: How transit agencies can take corrective action  

Identifying root causes is the domain of transit professionals such as planners, schedulers and depot managers. Best practices enable them to assess the network from different angles, such as on-time performance, stop details or running times using their expertise to uncover insights, collaborate on solutions and prepare for change.  

5. Improve and measure: Implementing action plans to optimize operations  

The goal of data-driven decision-making is to improve the rider experience. By analyzing operational performance and metrics like rider feedback, transit agencies can make targeted evidence-based changes that improve performance and make network savings. Once these changes are made, the cycle can iterate continuously. The service modifications generate new data that is ingested, transformed, analyzed and understood. These can be compared to prior performance and incremental improvements to the network can continue, driven by this systemic feedback loop.  

Embracing a data-driven future  

Data-driven decision making is essential for transit agencies to meet the growing demands of urban mobility, sustainability and operational efficiency. As public transit evolves, data will unlock new performance levels. Agencies investing in integrated data platforms and analytics tools will improve service delivery and build a sustainable future.  

As we enter 2025, reflect on how your agency uses data and which goals to prioritize. Now is the time to set a vision for how data can shape future success.