The relative significance of forecast errors in multistage manufacturing
通过多因素制造仿真，研究了预测误差的两个组成部分（偏差和变异性）、产品组合、批量策略和缓冲策略对库存和客户服务的影响，发现减少预测偏差比减少变异性更有效，且偏差管理对按时交付比降低库存更重要。
Abstract It is intuitive that controlling forecast errors should result in better customer service and lower inventories. But forecast errors come from various sources. Multistage manufacturing experiences supply and lead‐time uncertainties as well as demand uncertainties, and manufacturing has more than one lever to pull when addressing these uncertainties. The relationship of forecast errors to manufacturing performance is not clear. Furthermore, the pursuit of forecast accuracy may not be the best use of managerial resources. In this study, using a many‐factored manufacturing simulation, we examine two components of forecast errors, the mix of special and standard products, lot‐sizing, and buffering policies as they affect inventories and customer service. Although most conclusions are situation dependent, reducing forecast bias is shown to be much preferred to reducing forecast variability, bias management is more important to on‐time delivery than to inventory reduction, and the value of such reductions is particularly important in situations where there are large lot‐sizes and small buffers.