corporate travellers provide data airlines can use

In 2019, we calculated that analytics represents an up to $40 billion opportunity for global aviation, in retail alone. The reality for aviation has changed completely since then, but the importance of analytics has not: it has enabled the industry to react and manage networks and commercial functions in a way that is more agile than ever.

At many airlines, commercial functions have embraced new data and ways of operating, and the next challenge is to do so at scale. With COVID-19, the unprecedented extent of network breakdown means historical commercial data have become less relevant. Network teams are looking for pointers on where they should deploy capacity. Marketing teams would likely benefit from new data to steer promotions and improve marketing-spend effectiveness. And sales teams are struggling to get ahead of competitors’ sales initiatives.

Forecasting returning traveler demand will be vital to solving some of these issues and getting ahead in the new reality. Decision makers should ask themselves where analytics can add value, what they need from their data platform, and how their standard ways of working will need to change.

Responding to the crisis

As of September 2020, our models indicated the airline industry was operating at only around 55 percent of precrisis capacity and was mostly limited to domestic routes. The industry’s total revenue may fall by more than $400 billion for 2020 as a whole,1 and some geographies may not see a return to prepandemic levels of available-seat-kilometers until 2023

Revenue managers have been at the center of managing this crisis. Some have proved agile and resourceful in their adoption of new data, and this has also led to new ways of working.

Revenue and network managers have worked closely to understand unconventional demand signals and to make route, capacity, and pricing decisions accordingly. Some airlines have formalized this collaboration into commercial “nerve centers,” with the aim of increasing the precision of demand forecasting.

In our experience, the solutions to these and other issues lie in new, unconventional data sources.

Read rest of the article at McKinsey