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In this forecasting method, $\alpha$ is the smoothing constant that determines the weight assigned to the most recent actual demand. The term $(1-\alpha)$ is the complementary weight applied to the previous forecast.

Conditions: $\alpha$ is fixed at 0.4 in the worked example.; $(1-\alpha)$ is calculated as 0.6.; The weights must sum to 1 for the formula to represent a valid weighted average.

In this forecasting method, $\alpha$ is the smoothing constant that determines the weight assigned to the most recent actual demand. The term $(1-\alpha)$ is the complementary weight applied to the previous forecast.

Conditions: $\alpha$ is fixed at 0.4 in the worked example.; $(1-\alpha)$ is calculated as 0.6.; The weights must sum to 1 for the formula to represent a valid weighted average.