SUCCESS STORIES
When a leading footwear & apparel distributor with over 2,600 stores in various countries across North America, Asia, Australia, and New Zealand faced issues with labor costs, they knew it was time to act. With over 100,000 SKUs and over 300,000 locations across three distribution centers (DCs) in the United States, they were looking to increase picking effi ciency and reduce labor costs.
One key challenge that this company faced is that all three DCs had pick locations that were not slotted to reduce picker travel time. Also, case pick effi ciency was low due to long travel paths which increased overall labor costs. Finally, the current put-away-logic was not defi ned to reduce travel time for replenishment of the pick areas. For the ‘eaches’ pick areas within all DCs, Alpine performed at least four slotting scenarios based on different sets of goals, rules and constraints. By pick area, Alpine developed comparative reports to evaluate and compare all scenarios using real time peak week orders. Next, the team finalized the scenario that could be implemented by comparing the improvements from baseline using metrics such as lines picked per man hour, units picked per man hour, total distance traveled, total travel time and total replenishments required.
The company partnered with Alpine Supply Chain Solutions for slotting support. Alpine started by analyzing the outbound shipment records, item master, and location master. The team visited all three DCs, developed digital twins in the OptiSlot slotting software and validated inputs with the customer. Also, with the input from the client, Alpine fi nalized the list of constraints to be used for the slotting scenarios such as no heavy cases (greater than 25 pounds) on the top/bottom level of the each pick area, allowing only two orientations of case dimensions, using like item separation, placing footwear vs. apparel in diff erent zones, and separating footwear zones based on the manufacturer.
In the end, Alpine Supply Chain Solutions achieved the metrics that were agreed to during the kick-off call with the customer. The company is expected to save $198,000 per month which is going to be an expected $2.37M savings per year. This translates to a 53 headcount reduction, assuming $45K annual costs per employee.The footwear & apparel company was very data oriented and embraced Alpine’s methodology. They also had high quality data which aided Alpine throughout the entire project. Overall, it was a successful project for both parties and the customer was very happy with the results.
