CPIM Practice Exam

What does 'bias' refer to in forecasting?

1. A random deviation from the mean

2. A consistent deviation from the mean in one direction

3. A deviation that averages out to zero

4. The accuracy of the forecast

The correct answer is: A consistent deviation from the mean in one direction

Bias in forecasting specifically refers to a persistent deviation from the mean in one direction. This means that if a forecasting method consistently overestimates or underestimates future values, it is said to have a bias. Identifying bias is crucial because it helps forecasters understand the systematic error in their predictions and make necessary adjustments. For example, if a forecasting model consistently predicts sales that are 10% higher than the actual sales over a period, this indicates a positive bias. On the other hand, if it consistently predicts 10% lower than actual sales, this suggests a negative bias. Recognizing this deviation helps organizations refine their forecasting methods, leading to improved accuracy over time. In contrast, random deviations, deviations that average out to zero, or the overall accuracy of the forecast do not capture the concept of bias as it is understood in forecasting terminology. Random deviations may happen due to unpredictable fluctuations, while deviations that average out to zero indicate that there are no systematic errors, and accuracy refers more broadly to how close forecasts come to actual outcomes without specifically addressing the directional consistency of errors.