Skip to main content
Advanced Technical IVT

MAPE

Pronunciation: MAY-pee

Also written as: MAPE — Mean Absolute Percentage Error

Mean Absolute Percentage Error; a statistical metric used to measure the accuracy of a demand or sales forecast by expressing the average error as a percentage of actual values.

Full Definition

MAPE (Mean Absolute Percentage Error) is one of the most commonly reported forecast accuracy metrics in retail analytics. It is calculated by taking the absolute difference between forecast and actual values, dividing by the actual value for each period, averaging the results, and expressing the outcome as a percentage. Lower MAPE values indicate greater forecast accuracy. Editors should note that MAPE has a known limitation: it can produce skewed results when actual values are close to zero (as can occur for new product launches or very slow-moving SKUs). In such cases, documents may reference alternative metrics such as WMAPE (Weighted MAPE) or RMSE (Root Mean Square Error), and editors should ensure these acronyms are all expanded on first use.

Usage

Usage note: Always expand on first use. When WMAPE or RMSE also appear, expand each acronym individually. Do not use 'MAPE score'—the term is already a metric; 'MAPE value' or simply 'MAPE' is preferred.

In Context

  • "The new forecasting engine reduced MAPE from 18.4% to 11.2% across the fresh produce category, significantly improving replenishment efficiency." — Supply chain analytics report
  • "The editor expanded 'MAPE' to 'Mean Absolute Percentage Error' on first occurrence and added a footnote noting the WMAPE methodology used for zero-sales SKUs." — Technical editing note

Also known as

mean absolute percentage error forecast error rate

Don't confuse with

RMSE MAE WMAPE forecast bias

Editors from these organisations have used our services since 1998

Reuters BBC Oxford University Press Penguin Random House Springer Microsoft Suncor Energy United Nations Fisher Investments IBM The Home Depot KODAK CHEVRON