Airline Weather Disruptions Management – Incorporating Machine Learning

The 2022-2023 winter holiday travel period was extremely tough for airline customers. Airlines dominated the news following adverse weather events accompanied by large technology and process failures. These failures led to multi-day cancellations and thousands of stranded customers long after the weather had passed. The flying public and regulators demand that airlines take action to resolve their enduring technology deficiencies.

There is, however, a silver lining in this renewed airline tech focus – an opportunity to take a closer look at machine learning when implementing new airline disruption management and recovery tools.

Background of Airline Operations Control

Very few airline passengers (and even airline employees) fully comprehend the complexities and logistics involved to get a flight from A to B.

Once airline revenue managers and network planners publish a flight schedule and make seats available for sale, there is massive work to ensure every airline’s flight is positioned for safety, success, and an on-time departure.

To execute that schedule, every airline has an Operations Control Center (OCC or IOC) to coordinate every flight component, including maintenance control, crew scheduling, aircraft routing, flight planning, customer service, and meteorology. Leading these OCCs are airline managers tasked with directing an airline’s network response…