Demand Forecast Accuracy Calculator
Calculate accuracy of demand predictions
About this calculator
The Demand Forecast Accuracy Calculator measures how precisely your demand predictions match actual sales results. This essential business tool calculates key accuracy metrics like Mean Absolute Percentage Error (MAPE) and forecast bias to help supply chain managers, inventory planners, and business analysts optimize their forecasting processes. By quantifying prediction accuracy, businesses can improve inventory management, reduce stockouts, minimize excess inventory costs, and make more informed strategic decisions based on reliable demand forecasting performance.
How to use
Enter your actual demand values and corresponding forecasted demand values for the same time periods. The calculator will automatically compute accuracy metrics including MAPE, Mean Absolute Deviation (MAD), and bias percentage. Review the results to identify forecasting strengths and areas for improvement in your demand planning process.
Frequently asked questions
What is a good forecast accuracy percentage?
Generally, 85-95% accuracy is considered good, though this varies by industry, product type, and market volatility.
What's the difference between MAPE and MAD?
MAPE shows percentage error relative to actual demand, while MAD shows absolute average deviation in original units.
How often should I measure forecast accuracy?
Monitor forecast accuracy monthly or quarterly to track performance trends and make timely adjustments to forecasting methods.