The primary advantage of Mean Absolute Percentage Error (MAPE) is its interpretability as a percentage, making it easily understandable across different domains and to individuals without a strong statistical background.
Here's a breakdown of the benefits:
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Ease of Understanding: MAPE expresses the error as a percentage, which is intuitively grasped by most people. For instance, saying "the forecast is off by 5%" is more easily understood than saying "the forecast has a Mean Absolute Error of 2.5 units."
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Scale-Independent: Because it's a percentage, MAPE allows for comparing forecast accuracy across different datasets with varying scales. You can compare the accuracy of sales forecasts for different product lines, even if the sales volumes are significantly different. For example, you can directly compare a MAPE of 10% for predicting sales of $100,000 worth of Product A with a MAPE of 10% for predicting sales of $1,000,000 worth of Product B.
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Broad Applicability: MAPE can be applied in a wide variety of industries and situations, including sales forecasting, demand planning, financial modeling, and supply chain management. Its simple interpretation makes it a versatile metric.
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Communication Tool: It's a useful tool for communicating forecast accuracy to stakeholders who may not be familiar with more technical error metrics. This is particularly helpful when presenting forecast results to management or clients.
However, it's important to acknowledge MAPE's limitations. It can be unstable near zero values and undefined when actual values are zero. Despite these limitations, the ease of understanding it provides makes it a widely used and valuable metric.
