In the absence of any other information or visibility, individual supply chain participants can begin second-guessing what is happening with ordering patterns, and potentially start over-reacting. This is known as?

• A. Forecast Bias
• B. A Tracking Signal
• C. The Bullwhip Effect
• D. The Running Sum of Forecast Errors

Answer: (C)

The bullwhip effect explains this well. When supply-chain participants lack visibility into real consumer demand, they infer changes from their own ordering and forecasts and react more aggressively than warranted. Each stage amplifies those guesses, so small shifts at the consumer level become larger and larger swings upstream as orders are adjusted, inventory is piled up or reduced, and lead times stretch. The result is overreactions and more volatile ordering patterns higher in the chain, even though actual demand hasn’t swung as much.

Forecast bias isn’t about this amplification pattern; it’s a systematic over- or under-forecast over time. A tracking signal is a diagnostic that checks whether forecast errors show bias, not the dynamic amplification itself. The running sum of forecast errors is a metric used to detect cumulative bias, again not the phenomenon of information gaps triggering amplified ordering.