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.