Real-Time Analytics Improve Airport Operations


London’s Heathrow airport is responsible for carrying over 80 million passengers annually, making it the busiest European airport and among the world’s most highly trafficked. Adding to the complexity and scale of the operation, Heathrow offers flights to over 200 destinations across the globe. Through all of this, Heathrow airport’s staff is committed to ensuring “happy passengers, traveling on time, with their bags.”

To accomplish this feat, Heathrow staff rely on something known as an airport operations center (APOC). APOCs work by gathering representatives from the main airport stakeholder groups into a single room, which then becomes a decision-making nerve center. In its initial iteration, several technologies including video surveillance were used to monitor Heathrow’s operations and relay information back to staff in the APOC.

Despite improvements in Heathrow’s operations resulting from the early-stage implementation of the airport operations center, it became clear that additional real-time data collection and analytics capabilities would be necessary to provide the highest level of service to all passengers. Because the airport offers flights to so many locations, nearly one third of passengers land in Heathrow before departing on a connecting flight. Due to the volume of transfer passengers and the increased operational complexities involved with ensuring a seamless experience for these passengers (relative to non-transfer passengers), the Heathrow team decided to focus efforts on enabling activities related to the processing of transfer passengers.

After framing the problem and collecting preliminary data, it became clear that Heathrow’s APOC would be vastly better equipped to handle transfer passengers if it had access to accurate forecasts of when and where passengers would arrive at different points in the airport. In situations where the system indicated that passengers were likely to miss connecting flights, this data would allow staff to mitigate issues by offloading passengers in advance, expediting passengers through the airport, altering departure times, or modifying staffing levels in advance.

When the new advanced analytics and machine learning system was deployed, Heathrow stated that they expect reduced misconnect rates yielding estimated savings of $100 per passenger, as well as reduced headcount in transfer security, and a boost to the overall transfer experience. Heathrow believes that this could lead to increased overall demand over time, yielding even greater benefits to both the airport and airlines.  Fittingly, word of the project’s success has traveled, with other airports in Europe, Asia, and North America implementing or expressing interest in their own version of the system. It was for these revolutionary contributions to airport operations that Heathrow airport was nominated as a finalist for the 2019 Wagner Prize.