Business

Fixing the T: Technology can help balance cost equation

The T could collect a premium for riding buses and trains during high congestion periods to move ridership off peak and improve service, argues John Macomber.
Dina Rudick/Globe Staff/file
The T could collect a premium for riding buses and trains during high congestion periods to move ridership off peak and improve service, argues John Macomber.
Kayana Szymczak for the Boston Globe
John Macomber is a senior lecturer at Harvard Business School.

The MBTA faces the same problems that confront every transit system in the world: Riders want to pay less in fares and taxpayers want to contribute less in subsidies. In exchange, everyone wants to receive more safety, more reliability, more frequency, longer routes, and later hours.

These opposing financial forces never add up. But new technologies and modern business models, many invented in Massachusetts, could vastly improve the balance of this age-old equation. Let’s enhance the T’s tool kit using technologies that involve sensors and tracking to make the most of resources; use big data and transparency to assure money is spent well; and encourage dynamic pricing that charges more during peak periods to balance loads and match customer preferences.

Consider passenger miles. In 2015, the MBTA will carry us about 1.8 billion passenger-miles. (The annual budget of the T is also about $1.9 billion – about a dollar per passenger-mile. Only one-third of this money comes from fares). Passenger-miles are an archaic way to measure transit, stemming from the old days when accountants could only look back and add up the totals in hindsight.

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But not all miles have the same cost — and not all passengers have the same preferences. Today, in the era of smart cars, smart thermostats, smartphones, and even smart refrigerators, we have another generation of tools to deploy in the cost/revenue equation.

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Sensors and tracking can address the cost side and how to best use equipment the T already has. How about dispatching buses and trains when they are needed, based on who is approaching the platforms, and using an app that anticipates passenger needs, such as Waze or Google Transit? Or measuring, tracking, anticipating, and fixing high problem routes, equipment, and mechanics using statistically proven schedules, parts, and training? This is how we already track and rate industries in the rest of our lives.

Big data and transparency help us to think about revenues and who gets how much value from their use of the T. Or the inverse — who loses value from bad transit? During recent storms, businesses, schools, and hospitals complained loudly about revenue lost and costs incurred because personnel (and customers) could not get in. Employees lost pay.

These organizations should invest in public transit to mitigate future disruptions. In the old accounting days, we’d worry this money would be wasted. In the new era of smart investment tracking (pioneered by local mutual fund companies such as Fidelity and State Street) we can verify that designated assessments go where they are intended. In Bogota, Colombia, for example, businesses directly contribute to the construction of rapid transit routes because they benefit directly.

Dynamic pricing is made possible by the marriage of sensors, tracking, big data, and transparency. We all are accustomed to car services and sports teams varying prices based on demand — just look at Uber rates or StubHub markups. The T could collect a premium for riding buses and trains during high congestion periods to move ridership off peak.

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Similarly, it’s conceivable to charge a premium for late night riding, reflecting the much higher cost per passenger when trains and buses are partially full. The billing technology is available and ubiquitous; your mobile phone already has it.

But do we want to price transit out of reach of lower income people, many of whom need reliable public transit to survive? Of course not. Do we want to tax residents into oblivion to subsidize public transit? Of course not. Cities such as Singapore charge close to the full cost for a ride but also subsidize individuals who need help. This is a more enduring way to allocate the cost of transit — as a function of the relative value the rider is willing to pay.

We can expect the customary gnashing of teeth over state subsidies for the T and the same old management fights. But we can also arm the T with modern data, sensor, and tracking tools to better serve us all.

John Macomber is a senior lecturer at Harvard Business School.