Getting around Boston can be tricky. For many people, hopping onto one of the Massachusetts Bay Transportation Authority (MBTA) buses that crisscross the metro area is often the easiest way to get from point A to point B. For the MBTA, effectively forecasting revenue is not quite so simple.
A team of students in the computational science and engineering master’s program offered by the Institute for Applied Computational Science (IACS) at the Harvard John A. Paulson School of Engineering and Applied Sciences used data analytics to help the MBTA generate a more granular model of passenger transactions.
“Because of the complexity of the fare system and the large number of monthly pass holders, precisely assigning revenue to, say, a specific hour on a specific bus route is much more complicated than just counting passengers,” said Nathaniel Burbank, S.M. ’17. “To conduct that kind of analysis, you have to drill down much further.” Read more.