Case Study: Greenfield Warehouse Design for a Growing Ecommerce Apparel Company

Background and Challenges

An ecommerce women’s clothing company had one centralized warehouse supporting all brick-and-mortar and ecommerce fulfillment operations nationwide and was experiencing significant growth. Given the sizeable growth of the business, they signed a lease for a new warehouse space that was double the size of their existing facility. The additional capacity was essential to support the forecasted volumes, however, the existing warehouse processes were very manual and required significant labor to achieve the current demand levels. Some of the key operational challenges were:

• Poor Inventory Visibility: Scannable inventory locations did not exist, and locations were not systematically supported. Inventory was organized in alphabetical order and separated into sections; returns, main apparel area, and bulkier apparel area/overflow.

• Segregated Storage Areas: The warehouse had three separate storage areas that were picked from to fulfill orders. Operators would travel through the main apparel storage area first and then locate any missing inventory in the returns or overflow area if not stocked in the main area. The excessive travel due to the segregated areas and lack of inventory visibility caused long fulfillment times.

• Lack of Inventory Flexibility: Items were stored in alphabetical order in fixed locations. Locations were essentially the supplier’s name, item name, and other attributes. The location identifiers were manually created which added labor hours to support this inventory storage methodology.

• A Fluctuating Cycle of New Trends: New items were introduced on a weekly/bi-weekly basis while older styles and off-season items were donated or sold off at the end of its lifecycle. The constant cycle of new items resulted in extra labor to modify the alphabetical, fixed inventory locations.

• Batched Fulfillment: Groups of orders were batched and picked together into a large, one-bin cart and separated prior to shipping. While batching orders offers improved productivity in terms of pick times, the sortation of orders after picking added labor hours to an already laborious fulfillment operation.

The existing warehouse operation was very manual and could pose risks to productivity if replicated in the new larger facility with increased demand. Establish’s goal was to determine how these processes can be improved while also creating a warehouse design that enables the growth.

The Evaluation and Analysis

Establish evaluated the receiving, storage, and fulfillment processes in order to identify the gaps and challenges in the operation. In parallel, warehouse data was gathered, analyzed, and profiled to understand the operational volumes and identify opportunities for improvements. After the analysis, the following findings were determined:

• Non-seasonal items and promoted seasonal items accounted for a large portion of sales each week.

• The top-selling items required replenishment one or more times per day.

• 4% of the items were non-movers and were essentially end-of-life-cycle items.

• Jewelry and accessories product groups were the slowest moving inventory.

• 50% of all orders consisted of 1 item.

The Recommendations

Design a Layout with Optimal Flow

The warehouse was designed to accommodate pallet racking for overstock, shelving for picking activities, hanging racks for returns, fulfillment/shipping stations, and inbound and outbound processing areas near the docks. Overflow inventory, shoes, and end-of-lifecycle items were stored in the pallet racking while all other clothing items were stored in accessible shelving. The hanging racks for returns were positioned next to the main shelving area and close to the inbound doors where returns are received. Fulfillment/shipping stations were stationed next to the main picking area and followed an assembly-line design that was directed towards the outbound dock doors.

Implement Velocity Slotting

Fast-moving, non-seasonal items and promoted seasonal items were stored closest to the fulfillment stations in case flow rack while all other items were stored in standard shelving. The case flow rack allowed for automatic replenishment of the pick location with three additional cases of each item. Slower-moving product groups were positioned further away from the fulfillment stations.

Update the Picking Methodology

Batched orders were picked to multi-bin carts to segregate the orders prior to the shipping process. This removed the manual sorting process before shipping. Single-item orders were batched together and maintained batch picking to a single-bin cart. Since these orders all consisted of one unit, no sorting was required, and a single-bin cart can fit more orders than a multi-bin cart.

System Limitations

It was determined their current system did not support scannable inventory locations or other system functionalities that could alleviate some of the key challenge areas highlighted above, therefore, the slow-moving inventory was still slotted in alphabetical order in the short-term. Exploring a new WMS was a long-term recommendation. It was important to complete the move and allow the operation to settle before any drastic system changes. Implementing a new WMS would allow for flexible storage, logical slotting, improved inventory visibility, and other inventory management capabilities that were nonexistent in their current system.

The Results

Given the system limitations, prioritizing the storage methodology, layout, short-term velocity slotting, and fulfillment strategies were the main focus areas. After fulfilling these short-term recommendations, the overall fulfillment time was reduced by 25%. The new layout and strategy also decreased daily operator travel and decreased the number of first shift replenishments.