What COVID did to our forecasting models (and what we built to handle the next shock)

By: Harrison Katz How Airbnb built forecasting models resilient enough to survive a global pandemic and whatever shock comes next. The week everything broke In March 2020, the forecasting models that had served us well in stable times faced a new challenge: predicting outcomes in a world that had suddenly changed. At Airbnb, many of the financial metrics we forecast depend on two separate events: when guests book, and when they actually travel. A booking made today might correspond to a trip three days from now or three months from now. The distribution of that gap, what we call the lead-time composition, drives how we translate today’s bookings into future revenue (see Figure 1). The pandemic reshaped what was being booked and where. Hosts shifted their inventory toward longer stays and remote-friendly properties, while guests pivoted from urban centers to rural and suburban destinations. These supply and demand shifts interacted with each other over time, as hosts adapted listings to