Case Study：
Background: Belle is a major player in the Chinese footwear industry, ranking first in Chinese women's shoe sales for 12 consecutive years. As the leading women's shoe brand in China, its retail network covers approximately 300 cities in China, with close to 20,000 direct-operated stores for shoes and sportswear. Previously, Belle relied mainly on traditional manual picking in the process of distributing footwear and apparel products, but encountered the following key problems in actual operation:
Seasonal Fluctuation Challenges: The footwear and apparel industry is significantly influenced by seasonal and fashion trends, resulting in significant cyclical fluctuations in order volume. This puts enormous pressure on warehouses during peak periods, while resources remain idle during off-peak periods. The manual picking mode cannot flexibly cope with this dynamic change.
Management Challenge of Numerous SKUs: Footwear and apparel products come in a wide variety of styles, sizes, and colors, resulting in numerous SKUs. The manual process of finding and picking is time-consuming and labor-intensive, with a high error rate, affecting delivery speed and customer satisfaction.
Inventory Accuracy Issue: Due to the complexity of product attributes, traditional inventory counting and management methods are prone to errors, making it difficult to achieve real-time and accurate updates of inventory data, thus affecting supply chain decisions and business operations.
Rising Costs: With the annual increase in labor costs, especially the demand for skilled pickers, the cost burden of warehousing logistics has increased, squeezing enterprise profit margins.
Solution:
After thorough site surveys and needs analysis, our company recommended the adoption of split tray sorting machines as the solution for Belle.
Project Scale: 480 trolleys, 300 destinations, 10 input stations.
Implementation Time: From August 12, 2018, for planning and design to project completion on September 21, 2018, it took 39 days.
Effect Display: After the introduction of split tray sorting machines, Belle achieved significant results:
Substantial Increase in Picking Efficiency: Compared to traditional manual picking methods, picking efficiency improved by over 70%, significantly reducing delivery time and providing customers with faster service.
Sharp Reduction in Labor Input: A 40% reduction in labor demand reduced reliance on manual labor and greatly reduced employee workload.
Improved Picking Accuracy: Accuracy increased to 99.9%, ensuring accurate delivery of every piece of footwear and apparel to consumers, greatly reducing customer complaints and disputes.
Significant Increase in Customer Satisfaction: Due to the improvement in picking efficiency and accuracy, customer satisfaction increased by 30%, further consolidating Belle's market position.
In terms of color, size, and seasonal items, clothing logistics is recognized as a multi-frequency small-batch logistics model closest to single-item management. This multi-frequency small-batch model demands greater precision in footwear and apparel order picking. The increasingly personalized demands of footwear and apparel industry consumers have led to an increase in multi-batch small-batch and rapid-response requirements, forcing a substantial improvement in both inbound and outbound efficiency.
The return rate in the footwear and apparel industry is relatively high compared to other industries. The penetration of e-commerce has further increased the return rate and the number of returns, causing a surge in the handling pressure of reverse logistics. This is likely to affect the efficiency of reclassification, shelving, and inventory turnover, leading to warehouse backlog, increased costs, or forced clearance sales in stores.
The footwear and apparel industry experiences large fluctuations in order flow, resulting in significant changes in picking operations. Small promotion operations are generally about 5 times the daily average workload, while major promotion operations are typically 20 to 40 times the daily average workload. During peak periods such as promotional seasons and new season launches, the surge in shipments and returns, coupled with unstable order inflow and outflow, brings many uncertainties. Different shipment volumes require a more flexible picking mode, which demands that the footwear and apparel warehousing picking-sorting system can respond efficiently. Currently, manual picking not only has low sorting efficiency and high error rates but also incurs high labor costs, with significant staff turnover making management difficult, thus making it difficult to cope with this situation calmly.
The omnichannel sales of the footwear and apparel industry include various types, such as multi-level distribution models, direct-operated stores, online sales models, online group buying models, offline outlet models, and customer customization models, among others. Different sales models have different order structures and types, requiring flexible sorting solutions to adapt to different types of order picking.
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Automatic sorting equipment, through advanced recognition and classification technology, can quickly and accurately categorize and summarize footwear and apparel products. Compared to traditional manual picking, automatic sorting is faster and more accurate, greatly improving picking efficiency.
Automatic sorting equipment can achieve rapid automation from inbound to outbound, avoiding errors and delays caused by human factors, thus improving outbound efficiency. In addition, due to the high efficiency and accuracy of automatic sorting equipment, it can also reduce error rates and loss rates, further improving outbound efficiency.
Traditional picking requires a large amount of manpower, is time-consuming and labor-intensive, and prone to picking errors. Automatic sorting equipment can effectively reduce the number of picking personnel, reduce labor costs, and ensure picking accuracy and efficiency.
The high efficiency and accuracy of automatic sorting equipment can quickly process orders and deliver the required goods to customers promptly. This not only improves customer satisfaction but also increases sales and responds quickly to market demands, optimizing supply chain management.
