What do tracking signals primarily identify?

Tracking signals are a critical tool in the management of forecasts, as they provide insight into the biases within forecasting processes. Specifically, they assess the accuracy of forecasts relative to actual demand over time. The tracking signal calculates a ratio of cumulative forecast errors to the mean absolute deviation, which helps to identify whether there is a consistent underestimation or overestimation of future demand.

When the tracking signal indicates a bias, it can serve as an early warning system for planners. A positive tracking signal suggests that actual demand is consistently higher than forecasted, while a negative signal indicates the opposite. Recognizing forecast bias can lead to necessary adjustments in forecasting techniques, methodologies, and assumptions, ultimately improving the overall accuracy of supply chain planning.

In this context, it becomes clear why tracking signals are crucial for identifying forecast bias as they directly relate to how forecasts align with actual outcomes. This allows organizations to adapt their strategies accordingly, enhancing overall operational performance.