Supply Chain Collaborative Forecasting Methods Based On Factors

This paper proposes that sales and demands information are equally important in the supply chain. It discusses the role of factors in chorological forecasting and puts forth the supply chain collaborative forecasting methods based on factors and presents the relevant empirical studies. In the light of the historical actual sales data, factors of Spring Festival transportation, shutting down for examinations, and repairs and minor repairs are extracted and quantified in different hierarchies and domains. At the same time, they are reverted in the corporate sales forecasting. The empirical studies indicate that factors play an important role in supply chain sales forecasting. Their application can greatly improve the specific and general forecasting accuracy and represents the thought of collaborative forecasting. They can contribute to the supply chain implication and prominent information application; they can contribute to positively employing the potential negative constraints of supply chain enterprises; and they can also contribute to the management of supply chain as the information whole. All these can be considered as an extension of the economic information filter in different hierarchies and modules.