Hotel Revenue Glossary · Forecasting
Forecast Accuracy
A measure of how closely the forecast matched actual results, typically expressed as a percentage. A forecast accuracy of 95% means the prediction was within 5% of the actual outcome. Measured for rooms sold, ADR, and total revenue.
Why it matters: Forecast accuracy is a measure of the revenue manager's analytical credibility. Consistently accurate forecasts build trust with ownership and operations teams. Poor accuracy undermines confidence in pricing decisions and can lead to staffing misalignments.
Worked example: You forecast 118 rooms for a Thursday and sell 124: absolute error 6 rooms, 6 / 124 = 4.8%. Over 30 days the daily errors run +6, -9, +4, -2 and so on. What matters is the mean absolute error - say 5.1% - and whether the signed errors sum to near zero. If they sum to +140 rooms across the month you are not inaccurate, you are biased low, and housekeeping has been under-rostered every week.
Common mistake: Measuring accuracy on the month total, where a run of over-forecasts cancels a run of under-forecasts and the headline looks excellent. Operations feels the daily error, not the monthly one. Report mean absolute error by day alongside the signed total, so bias and noise show up as two separate problems.