The Bullwhip Effect, the magnification of demand variability throughout the supply chain, poses a challenge to firms. Inaccurate forecasts increase it, with forecast errors translating into higher inventory costs at a local level and impacting other members of the supply chain, as their decisions are based on mis-estimated incoming orders. The conventional measure for the Bullwhip Effect does not reflect how forecast uncertainty evolves in the supply chain. A new metric is proposed that overcomes many of the limitations of the Bullwhip Ratio: the Ratio of Forecast Uncertainty. It benchmarks the upstream forecast errors to the downstream's. An inventory simulation is deployed to study the properties and usefulness of this measure. It connects to inventory costs at the upstream level and holds more explanatory power than the standard Bullwhip Ratio and the complementary Net Stock Amplification. Managers can use it to better understand the upstream impact of the forecasting process. Highlights A key factor of the Bullwhip Effect (BE) is how the demand signal is modelled. The uncertainty of demand is the determinant of the quality of the forecasts. Existing BE metrics conflate the uncertainty and variability of demand. Propose the Ratio of Forecast Uncertainty (RFU) to overcome this. RFU relates more strongly to inventory costs than standard BE metrics.