Holt-Winters forecasting

Holt-Winters forecasting is a statistical method used to predict future data points by analyzing and modeling patterns in past data. It considers three key components: the overall level (average), the trend (direction of movement), and seasonality (regular repeating patterns). By adjusting these components as new data comes in, Holt-Winters can produce more accurate forecasts, especially for data with consistent seasonal fluctuations, like sales that peak during holidays or seasons. This approach helps businesses plan better by anticipating future demand, inventory needs, or other time-based trends.