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.
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.