A method of forecasting where time series data are separated into up to three components: trend, seasonal, and cyclical, where trend includes the general horizontal upward or downward movement over time, seasonal includes a recurring demand pattern such as day of the week, weekly, monthly, or quarterly, and cyclical includes any repeating, non-seasonal pattern. A fourth component is random, that is, data with no pattern. The new forecast is made by projecting the patterns individually determined and then combining them.