Improving supply-chain performance by sharing advance demand information
In this paper, we analyze how sharing advance demand information (ADI) can improve supply-chain performance. We consider two types of ADI, aggregated ADI (A-ADI) and detailed ADI (D-ADI). With A-ADI, customers share with manufacturers information about whether they will place an order for some product in the next time period, but do not share information about which product they will order and which of several potential manufacturers will receive the order. With D-ADI, customers additionally share information about which product they will order, but which manufacturer will receive the order remains uncertain. We develop and solve mathematical models of supply chains where ADI is shared. We derive exact expressions and closed-form approximations for expected costs, expected base-stock levels, and variations of the production quantities. We show that both the manufacturer and the customers benefit from sharing ADI, but that sharing ADI increases the bullwhip effect. We also show that under certain conditions it is optimal to collect ADI from either none or all of the customers. We study two supply chains in detail: a supply chain with an arbitrary number of products that have identical demand rates, and a supply chain with two products that have arbitrary demand rates. For these two supply chains, we analyze how the values of A-ADI and D-ADI depend on the characteristics of the supply chain and on the quality of the shared information, and we identify conditions under which sharing A-ADI and D-ADI can significantly reduce cost. Our results can be used by decision makers to analyze the cost savings that can be achieved by sharing ADI and help them to determine if sharing ADI is beneficial for their supply chains.
manufacturing supply chain management forecasting information sharing