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A procedure of demand forecasting using data mining techniques is proposed to forecast the sales amount of new short life-cycle products for an actual food processing enterprise. The enterprise annually produces 100∼150 kinds of new items with short life-cycle between one week and three months to supply 260 convenience stores in the region of jurisdiction. Based on the previous delivery data in the first selling week, sales amount in the second, and the third selling weeks can be forecasted for their new products. Especially, some effective association rules about hot items and cold items are obtained by using data mining technologies for new short life-cycle products.

Demand forecasting procedure for short life-cycle products with an actual food processing enterprise