Forecasting is concerned along with estimating future demand for products. For the reasons of making decisions along with respect to planning workforce, production and inventories levels and economic lot sizes, this is essential to know the products requirements. A number of modelling approaches have been planned for demand forecasting and are discussed in detail in a number of books in the region of production forecasting and management. In this section, an extensively utilization short-term forecasting approach is demonstrated, named Moving Average approach. The moving-average approach is easy to implement and thus is generally accepted. An average of n past observation is determined in order to eliminate the random variations. All the time a new observation is existing, the oldest one is discarded to calculate the new average. This will be clear along with following illustration.
Within the last 7 days, the demand for a product A was n1 = 20, n2 = 26, n3 = 19, n4 = 24, n5 = 23, n6 = 21, n7 = 28. Enhance a forecast for the eighth day.
The 7-day moving average is =
M7 = (20 + 26 + 19 + 24 + 23 + 21 + 28)/ 7
The forecast for the after that day is 23.
Now, assume the actual demand for the eighth day is 34; after that n1 is dropped and n8 is added to acquire the new moving average that is:
M1 = (26 + 19 + 24 + 23 + 21 + 28 + 34)/7
Hence, the forecast for the after that day is 25.