Historic data sets often exhibit the effects of one-time events that cause outliers. The event that causes the outlier may be known or unknown. Although exponential smoothing is a remarkably robust procedure, these outliers may decrease the quality of the forecasts and (especially) the confidence limits.

You can eliminate the effect of an outlier by coding it as a special event that occurs only once. If you have several outliers, each must be coded as a distinct event type. Forecast Pro will “explain” each outlier as the result of its associated event.

The impact of outliers on the forecasts and the confidence limits will be greatly reduced. Beware however: if outliers continue to occur in the forecast period, then the confidence limits are likely to be unrealistically narrow.