Cost-optimized warehouse storage type allocations

Abstract

Amazon's phenomenal sales growth and desire to maintain "Earth's Biggest Selection" have led to an increase in the diversity of product offerings that has resulted in a corresponding increase in complexity of Amazon's warehouse storage management. There is currently limited insight into the trade offs between the capital, fixed and variable costs of Amazon's storage related operational decisions, leading to inefficient warehouse storage type allocations and higher operational costs. The focus of this six-month LGO internship was to develop a cost model that takes into account all relevant costs to develop recommendations on warehouse storage type allocations for both existing and new fulfillment centers in Amazon's North America Fulfillment Center network. This thesis begins with an overview of Amazon and a description of their fulfillment center network. The overview is followed by a literature review of current warehouse design frameworks and storage optimization research. The following chapter analyzes the current inbound warehouse processes to identify what the relevant storage decisions are, where they are being made, and the current decision making process. Finally, through the development and implementation of a cost model and an analysis of key findings, the thesis provides recommendations for cost-optimized warehouse storage type allocations. The major recommendations are to replace floor pallet storage within existing fulfillment centers, increasing Non-Sortable product mix in select existing Sortable fulfillment centers, and optimized storage type allocations for new fulfillment centers. The expected scaled annual cost savings associated with these cost optimized warehouse storage type allocations within the existing fulfillment centers is 34% across the entire network and 62% for the select Sortable fulfillment center. The expected scaled annual cost savings associated with the optimized storage type allocations for the new fulfillment centers is 24% per new Sortable building and 11% per new Non-Sortable building. The methodology utilized within the cost model to compare fixed, variable and capital costs can be applied more broadly to assess the cost impact of different storage types in any warehousing design framework.