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What is exponential smoothing and why is it popular for business forecasts?

Exponential smoothing forecasts using a weighted average of past observations where recent data gets the most weight and older data fades away. Extensions add trend and seasonality, such as Holt-Winters. It is popular because it is fast, robust, needs little data, handles many series and is easy to explain.

The smoothing parameter controls how quickly the forecast reacts: a high value follows recent changes, a low one is stable. Software usually fits this automatically.

Variants:

Its limits are that it cannot easily use outside drivers such as price or promotions, so a regression or machine-learning approach may be better when those matter. It remains a strong baseline.

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Published by Zansa · Last updated 2026-11-06 · Category: Forecasting and data science