A draft of the paper is available for download
We investigate the dynamic behavior of service-oriented supply chains by developing a two-stage
serial capacity management model. Reflecting the reality of many service (and custom manufacturing) supply chains, each stage holds no finished goods inventory, but rather only backlogs that can be managed solely by adjusting capacity. Using control theory, we develop an optimal policy that trades off backlog costs against capacity adjustment costs when information is shared. We then establish the potential for an increase in demand variability along an optimally managed supply chain. Contrary to conventional wisdom, we also show that, while lead-time reduction does generally reduce backlog variance, it also increases capacity variance, resulting in a trade-off between service quality and personnel costs at each stage. Furthermore, such lead-time reductions increase backlog variances at subsequent stages resulting in a service quality trade-off between stages. Finally, we show that sharing backlog information will not materially improve overall supply chain performance if the target lead- and capacity adjustment times of the stage closest to end-customer demand are much smaller than subsequent stages’.