Investigation Into Sources of Volatility in Sortation Center Processes to Improve Productivity and On-Time Delivery

Abstract

Target Corporation has expanded its Last Mile Delivery (TLMD) capabilities through an omni-channel, "stores-as-hubs" strategy, using stores as fulfillment centers for online orders. The Target Sortation Centers was developed to receive packages from stores in the region, sort, route and dispatch these packages each day to accomplish faster delivery for online orders. Designed to never hold inventory, the goal is to have every package received delivered that same day. This presents new operational challenges common for brick-and-mortar retailers that develop an omni-channel strategy. This thesis investigates core processes in Sortation Centers to identify sources of volatility and propose improvements that enhance productivity and on-time delivery while minimizing labor costs and incomplete volume. Many of the current processes in Target’s Sortation Centers are manual and unstandardized. Moreover, improving operations and piloting changes is challenging, especially during peak seasons. To address these challenges, this study employs discrete event simulation (DES) using SimPy, informed by current operational data and in-person observations, to model and analyze current processes. Key findings reveal that pre-sorting TLMD volume from other national carrier volume at the stores prior to linehaul pick up for same day packages decrease the overall completion times for the day’s volume by 5.8% and lowers incomplete volume probability by up to 85% under excess volume scenarios. These process changes enhance site resilience to demand volatility without significant capital investment. The research underscores the value of DES for testing process improvements virtually and highlights the need for network-level optimization across Target’s omnichannel supply chain. Recommendations include piloting floor loading and pre-sorting in select markets, alongside future exploration of performance standards, automation, and standardized processes to further mitigate volatility impacts.