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Revenue Management Glossary

Mean Absolute Percentage Error (MAPE)


The Mean Absolute Percentage Error (MAPE) is a formula used to determine the accuracy of hotel revenue management forecasts, compared to actual outcomes.

How to use it

Forecasting plays a crucial role in predicting occupancy rates, revenue and other key performance indicators, and is a basis for establishing more accurate revenue management strategies and planning and allocating resources efficiently in hotel management. MAPE provides a clear, intuitive percentage-based result that indicates the average error magnitude in forecasts, making it easy for hoteliers to understand and communicate the accuracy of their forecasting.

Important note: MAPE can be skewed by data points where the actual values are very low, leading to disproportionately high percentage errors. When issues like these arise, it is best to use other metrics, either alone or in combination with MAPE, to accurately calculate the errors.


MAPE is calculated in two steps:
1 – Subtract the forecasted value for the given date (or the sum total of all forecasted values over a date range) from the actual value on the same date.
2 – Take this number and divide it by the actual value to determine the MAPE.

Related Terms

Revenue Management, RMS, Forecasting, ADR, RevPAR, Occupancy, Travel Demand, Yield Management
MAPE is particularly useful in evaluating the accuracy of my property’s forecasting related to our revenue, occupancy, performance evalutions and budgeting and planning, compared to the actual bookings and revenue earned. By monitoring my hotel’s MAPE, I can better understand the errors in our forecasting models and improve them for future calculations, which will help us make better, data-based decisions on revenue management strategies and operational issues.

Gustavo Peña

Gustavo Pena