Weighted Average/Exponential Smoothing Forecasting

The simple moving average method gives equal weight to each of the historic usage figures. The figure for January contributed equally to the forecast for July as the usage figure for June.  This does not account for the fact that older figures are less reliable than more recent figures. The weighted average, or exponential smoothing method of forecasting takes into account gradual trends in item usage to provide more accurate forecasting. The method gives greater weight to usage figures recorded in recent months. Table 3 shows weighted average forecasting compared to simple average forecasting. Whilst the total values are the similar, the weighted forecast smooths the forecast major peaks and troughs in the period. A weighted average forecast can be calculated using a formula in excel or a reliable MRP system is capable of performing the calculation.

Table 3: Weighted Average/Exponential Smoothing Forecasting

The video below provides a short tutorial on how to calculate weighted average/exponential smoothing forecasting in Excel.