Tracking signals are used to detect forecast bias.

• A. Forecast Bias
• B. The Bullwhip Effect
• C. A Tracking Signal
• D. Forecast Error Sum

Answer: (C)

Tracking signals are used to detect forecast bias by examining how forecast errors accumulate over time relative to the typical size of those errors. It’s calculated as the cumulative forecast error (CFE) divided by a measure of forecast error variability, usually the mean absolute deviation (MAD). When the tracking signal stays within predefined limits, errors look like random variation; if it crosses a limit, it signals persistent bias—meaning forecasts are consistently too high or too low and the method may need adjustment. This is why the concept described is the tracking signal itself. The other ideas describe either the bias itself, a different supply-chain phenomenon, or a simple sum of errors that doesn’t account for error magnitude, so they don’t capture the monitoring mechanism that tracking signals provide.