forecasting technique that uses a weighted moving average of past data as the basis for a forecast. The procedure gives heaviest weight to more recent information and smaller weight to observations in the more distant past. The reason for this is that the future may be more dependent upon the recent past than on the distant past. The method is effective when there is random demand and no seasonal fluctuations in the data. It is a popular technique for shortrun forecasting by business forecasters. Each new fore-cast is based on the previous forecast plus a percentage of the difference between that forecast and the actual value of the time series at that point.