How Uber could make MTA better

Since it entered the market in 2011, Uber has been a behemoth presence in New York City. Everywhere you go, you could point out an Uber experience happening on the streets in real-time. Uber fits perfectly with the NYC persona of efficiency and individualism: seamlessly requesting a car on your phone and being picked up and dropped off exactly where you want to be. It digitized the marketplace of customers who needed rides with drivers with cars. The magic was in the algorithm to match the most optimal car to the closest customer. It inspired copycats like Lyft and Via to join the fray and utterly decimated the yellow cab industry. By 2019, over 80,000 drivers were working for Uber and getting millions of people to where they wanted to go.

Surprisingly, the NYC City Council has a fair amount of regulatory control over Uber and other transportation network companies that want to do business in the 5 boroughs. For instance, in 2018, the City passed several bills to regulate the number of drivers and increase the minimum wage of these contractors. It has also managed to get Uber to share ride data such as location data, trip mileage, route, and how much the driver was paid. This data has been utilized to match with traffic cameras to ensure public safety.

Uber and their cohort have given up this data warily, citing IP and user privacy concerns. In the case of IP, it is interesting to think about what competitors could glean from how Uber directs its drivers to pick up and drop off. And by competitors, I specifically mean the MTA.

I think about this quote from Enrique Peñalosa, a former mayor of Bogota a lot - "An advanced city is not one where even the poor use cars, but rather one where even the rich use public transport." In most regards, New York City met that criteria with around 56% of New Yorkers using public transport according to NYPTA.

Then came Covid. Overnight, the city was shut down, thousands were dying every day. MTA reported a free fall in usage and more importantly, fares that kept the service financially afloat. As the city slowly came back to life by early 2021, the MTA usage was still low. Folks were afraid of not only germs but a perceived sense of increased violence. Lack of users begets service cuts and many worry about the potential downward spiral of the MTA’s service and economic prospects. Even in 2023, transit ridership in New York City remains significantly below 2019 levels. 

To address this downward trend, I believe that the MTA needs to enhance its relevance significantly by analyzing Uber’s ride-share data, revealing what destinations are not currently served by public transport routes. This straightforward strategy would illuminate critical aspects of transportation needs.

1. Where: Most immediately, where do people need to go? To make this data more digestible, I would recommend a quarter-mile radius of all pick-ups and drop-offs to see the most common arcs. Is it mostly across boroughs or is the travel between boroughs? How much is it east to west vs north to south?
2. When: Another key question is when do folks use Uber? This is likely similar to overall trends in driving but how does that change with specific routes? This can help dictate when higher levels of service are needed vs leaning on traditional ideas of business.
3. How long: How fast on average does Uber get passengers to their location?
4. How often: What larger capital projects are actually worth funding based on usage?

By digesting and analyzing this data, the MTA could pilot-test several new bus routes and see how popular they are. They could decide to add more local or express routes. For example, if they had a specific A train that went from JFK directly to Jay Street MetroTech, West 4th, and 34th Street to address the airport travel need. They could also decide to market certain underutilized routes to highlight how fast they could get to where they are going.

It can’t be understated how powerful this data and its applications could be. Uber itself knows the value of it and has created a consulting arm of their business, Uber Movement, to help cities better plan their transportation strategy. Should the City Council legislate that Uber provide these key datasets to improve MTA and in short the city as part of being licensed to work in the city?

The integration of Uber's comprehensive ride-share data with the MTA's operational framework presents an opportunity to revolutionize New York City's public transportation system. By analyzing patterns in Uber's data, the MTA can test, adapt, and ultimately innovate its public service to ultimately enhance connectivity in the city.