A Katz School student team's proposal to reform the New York City subway system is a finalist in a business case competition sponsored by the Zicklin School of Business at Baruch College.
Their proposal, 鈥淎 Data-Driven Approach to Urban Mobility,鈥 leverages advancements in artificial intelligence, data analytics and Internet of Things (IoT) technologies to revitalize the Metropolitan Transit Authority (MTA).
It was chosen by an expert panel of judges, including Carson Au, manager of properties and infrastructure development at JetBlue Airways; Henry Chen, deputy director of planning and policy at the MTA; Helaine Korn, executive director of graduate programs at Baruch College; and Danny Park, senior manager of products and development at PwC.
鈥淲e delivered data-backed solutions in digital transformation for the MTA before a panel of judges, including an MTA representative,鈥 said Mapalo Lukashi, a student in the Katz School鈥檚 M.S. in Data Analytics and Visualization. 鈥淚鈥檓 so glad and grateful to God to have been part of this. Kudos to my team for sparing no sleep to present a memorable pitch.鈥
Despite being one of the world鈥檚 largest and oldest public transportation systems, the MTA is grappling with significant challenges, including service delays, aging infrastructure and a strained financial model. Recent events like the global pandemic and evolving commuter patterns have further exacerbated these issues, leading to a sharp decline in ridership and fare revenue. In response, the MTA is seeking solutions to ensure its long-term sustainability and resilience.
Recognizing the potential of digital technologies to address pressing issues rapidly and cost-effectively, the MTA called for proposals to develop a comprehensive digital transformation strategy. The goals are reducing operational inefficiencies, boosting revenue and enhancing the overall customer experience. Participating teams were asked to predict the impact of their digital initiatives on the MTA鈥檚 operations and revenue by 2028, with a focus on feasibility, innovation and alignment with the MTA鈥檚 objectives.
The Katz School team, which included Lukashi, Loretta Ching'andu (M.S. in Digital Marketing and Media), Abdulla Mamun (M.S. in Data Analytics and Visualization) and Rachael Ojopagogo (M.S. in Data Analytics and Visualization), proposed the use of AI and IoT sensors for predictive maintenance. By optimizing asset lifespan and creating dynamic service schedules based on real-time ridership data, the MTA, they said, can improve service efficiency and resource allocation. The team suggested deploying autonomous vibration sensors on train cars and tracks to detect wear or damage, using image recognition technologies for infrastructure inspections and applying data analytics to predict potential failures.
To address the MTA鈥檚 financial challenges, the team recommended dynamic pricing models that adjust fares based on demand, time of day and specific routes. In addition, they proposed exploring innovative funding mechanisms, such as municipal bonds, federal grants and public-private partnerships, to finance capital projects without straining the operating budget.
Team Thunders, as they called themselves, estimated the cost for implementing these technologies at $220 million, covering the initial setup and deployment. The team鈥檚 proposal outlined a detailed roadmap for the integration of these solutions, including timelines, budget allocations and resource requirements. Their proposal is expected to significantly reduce unexpected equipment failures by 20% and annual maintenance costs by 15%, based on benchmarks from other transit systems like Tokyo鈥檚.
鈥淭he digital transformation strategy aims to make public transit the preferred mode of transportation in New York, fostering economic growth and social equity,鈥 said Mamun. 鈥淥ur vision for a data-driven, efficient and financially sustainable MTA could pave the way for a brighter future for New York City鈥檚 transit system and its millions of daily riders.鈥
