Certified Supply Chain Professional (CSCP) Practice Exam

When does bias occur in forecasting?

1. When actual demand equals forecast

2. When cumulative actual demand differs from cumulative forecast

3. When data is not available

4. When forecasts are consistently high

The correct answer is: When cumulative actual demand differs from cumulative forecast

Bias in forecasting refers to a systematic error that occurs when the forecast consistently deviates in one direction from the actual demand. This means that the forecasts are not accurate over time and tend to be skewed either too high or too low. The correct response indicates that bias occurs when the cumulative actual demand differs from the cumulative forecast. This difference shows a consistent pattern of either overestimating or underestimating demand over a period. If the cumulative forecasts consistently exceed the actual demand, it signals a tendency to predict larger needs than what materializes, indicating a positive bias. Conversely, if cumulative actual demand consistently surpasses forecasts, this reflects a negative bias. In scenarios where actual demand aligns perfectly with the forecast, as noted in one of the options, there wouldn't be a bias because the forecast would be accurate. Similarly, while the absence of data may lead to inaccurate forecasts, it does not inherently create a bias since bias specifically concerns the consistency of forecast errors rather than the absence of data itself. Additionally, forecasts being high on their own does not necessarily indicate bias unless this is a persistent, systematic tendency. Recognizing cumulative discrepancies between actual demand and forecast results is vital in identifying and correcting biases that can impact supply chain decision-making and strategy.