Simple moving average forecasting method gives less sensitivity for the increase in length of average period with a lagging trend. It smooths out short-term fluctuations, resulting in less volatility, but makes it difficult to detect changes or trends in shorter periods. In this method, past data is used for calculating moving average for constant period of time. The fresh average is computed at the end of each period by adding the actual demand data for the most recent period and deleting the older data. Weighted moving average and exponential smoothing methods assign unequal weight to observations and give more weight to recent data.
