Forecast Accuracy measures how closely a hotel’s forecasted results match the actual results. Revenue managers use it to assess the reliability of forecasts for room demand, occupancy, room revenue, or other performance measures and to improve future planning.
How It Works
Forecast accuracy is evaluated by comparing forecast values with actual outcomes for the same dates and metric. The appropriate calculation depends on the measure being forecast and the method used by the hotel. Forecast error should be reviewed consistently over time to identify systematic overestimation or underestimation.
Practical Example
Suppose a hotel forecasts 180 room sales for a particular night but actually sells 170 rooms.
Forecast Error = Actual Rooms Sold − Forecast Rooms Sold
Forecast Error = 170 − 180 = −10 rooms
The hotel sold 10 fewer rooms than forecast, meaning the forecast overestimated demand by 10 rooms.
How to Interpret Forecast Accuracy
A forecast that consistently differs from actual results may lead to poor pricing, staffing, and inventory decisions. Reviewing forecast errors helps revenue managers identify whether assumptions, booking patterns, cancellations, or market conditions need to be reconsidered.
There is no single universal accuracy formula for every hotel metric. Methods such as absolute error, percentage error, and weighted error measures have different uses, and percentage-based measures can be problematic when actual values are zero or very small.
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