Global Dual Sourcing and Order Smoothing: The Impact of Capacity and Lead Times

Abstract

A fter decades of offshoring production across the world, companies are rethinking their global networks.Local sourcing is receiving more attention, but it remains challenging to balance the offshore sourcing cost advantage against the increased inventories, because of its longer lead time, and against the cost and (volume) flexibility of each source's capacity. To guide strategic allocation in this global network decision, this paper establishes reasonably simple prescriptions that capture the key drivers. We adopt a conventional discrete-time inventory model with a linear control rule that smoothes orders and allows an exact and analytically tractable analysis of single-and dual-sourcing policies under normal demand. Distinguishing features of our model are that it captures each source's lead time, capacity cost, and flexibility to work overtime. We use Lagrange's inversion theorem to provide exact and simple square-root bound formulae for the strategic sourcing allocations and the value of dual sourcing. The formulae provide structural insight on the impact of financial, operational, and demand parameters, and a starting point for quantitative decision making. We investigate the robustness of our results by comparing the smoothing policy with existing single-and dual-sourcing models in a simulation study that relaxes model assumptions.

Inventory management for stochastic lead times with order crossovers

“…showing that the POUT policy generates orders that are a convex combination of the stochastic component of the demand and the previous order (Balakrishnan et al 2004, Boute & Van Mieghem 2014. The term T in (5) is the target net stock-the safety stock-the average inventory level.…”

Robust Dual Sourcing Inventory Management: Optimality of Capped Dual Index Policies and Smoothing

“…Hua et al (2015) extends the vector base-stock policy to the best weighted bounds (BWB) policy. Boute and Van Mieghem (2015) analyze dual sourcing systems that feature suppliers' capacity cost and flexibility, and propose an analytically tractable dual sourcing smoothing policy, which is a linear control rule that smooths orders. For continuous review models, Moinzadeh and Nahmias (1988) extend the standard (Q, R) policy to dual sourcing with deterministic lead times and fixed costs.…”

“…i.e., when supplier capacity and flexibility costs are added to the traditional ordering cost and inventory holding and backlogging cost: Allon and Van Mieghem (2010) propose the tailored basesurge (TBS) sourcing policy, which orders at a constant rate from the slow source and follows a base-stock policy for the fast source. The dual-sourcing smoothing (DSS) policy proposed by Boute and Van Mieghem (2015) determines the fast and slow order quantities by smoothing out the observed series of demands. Given that we do not consider supplier capacity considerations, we leave out DSS but we do include TBS as a benchmark because Xin and Goldberg (2017) have proved that the TBS policy is asymptotically optimal (for the uncapacitated dual sourcing system) as the lead time difference grows large.…”

The Impact of Lead Time Uncertainty on Supply Chain Performance Considering Carbon Cost

“…The lead time is also called replenishment delay, which is the time gap between sending an order and receiving it. Existing studies demonstrate that lead time is a key factor that affects supply chain performance [4]. If the lead time is uncertain, the situation is complex from both the cost and service perspectives.…”