Making data matter : the role of information design and process in applying automated data to improve transit service

Abstract

As public transit agencies install new technology systems they are gaining increasing amounts of data. This data has the potential to change how they operate by generating better information for decision-making. Deriving value from this data and applying it to improve service requires changing the institutional processes that developed when agencies had little reliable information about their systems and customers. With automated systems producing large quantities of high quality data, it becomes the impetus for, rather than simply the input to, measurement. Capturing more value from automated data thus involves rethinking what agencies can know about service. This research uses the Massachusetts Bay Transportation Authority (MBTA) as a case study. It first assesses how the MBTA currently uses real-time and historical data. Based on this assessment, it redesigns and advances the agency's daily performance reports for rapid transit through a collaborative and iterative process with the Operations Control Center. These reports are then used to identify poor performance, implement pilot projects to address its causes, and evaluate the effects of these pilots. Through this case study, this research finds that service controllers' trust and interpretation of performance information determines its impact on operations. It concludes that new data will be most effective in producing service improvements if measurements accurately reflect human experience and are developed in conjunction with their eventual users. It also finds that developing pilot projects during this collaborative process enables new performance information to result in service improvements. Based on these findings, this work produces a set of recommendations for generating useful performance information from transit data, as well as a specific set of recommendations for expanding the use of data at the MBTA.