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Cloud Warehouse Distribution

Cloud Warehouse Distribution

2025-03-20

latest company case about [#aname#]

Case Study:

Background: Cainiao is part of the Alibaba Group, the world's largest cross-border e-commerce logistics company, with one of the largest logistics networks globally. At that time, Cainiao relied mainly on manual operations for picking in its cloud warehouse distribution business. With the continuous growth of business volume and the increasing complexity of order structures, traditional manual picking methods exposed several pain points:

Efficiency Bottleneck: Manual picking speed is limited by the proficiency and physical condition of employees. Especially when faced with a large number of SKUs, the time cost of finding product locations is high, directly impacting order processing speed and overall logistics efficiency.

Accuracy Issues: Long periods of high-intensity work can lead to frequent human errors, such as picking the wrong goods or missing picks. This not only affects customer satisfaction but also brings subsequent service pressures such as returns and exchanges, as well as potential economic losses.

Rising Costs: With the annual increase in labor costs and the need for a large number of temporary workers during peak periods, warehousing operating costs are difficult to control.

Lack of Flexibility: For situations with large fluctuations in orders and changing demands, the manual picking system responds slowly and cannot quickly adapt to changes in order structures and quantities.

Solution:

After in-depth site surveys and needs analysis, we recommended the adoption of cross-belt sorters as the solution for Cainiao.

Project Scale: 156 trolleys, 160 destinations, 6 induction stations.

Implementation Time: From August 6, 2019, for planning and design to project completion on September 21, 2019, it took 45 days.

Effect Display: After the introduction of cross-belt sorters, Cainiao's cloud warehouse distribution achieved significant results.

Efficiency Improvement: Compared to traditional manual picking methods, picking efficiency improved by over 60%, greatly reducing the delivery time of parcels.

Accuracy Improvement: Sorting accuracy reached over 99.9%, significantly improving the accuracy of parcel delivery, reducing customer complaints and disputes.

Increase in Customer Satisfaction: Due to the improvement in picking efficiency and accuracy, customer satisfaction increased by 15%, winning Cainiao more trust and praise.

Significant Reduction in Labor Costs: A 30% reduction in labor input reduced labor and operating costs, bringing higher economic benefits to Cainiao.


Latest company case about
Solutions Details
Created with Pixso. Home Created with Pixso. solutions Created with Pixso.

Cloud Warehouse Distribution

Cloud Warehouse Distribution

2025-03-20

latest company case about [#aname#]

Case Study:

Background: Cainiao is part of the Alibaba Group, the world's largest cross-border e-commerce logistics company, with one of the largest logistics networks globally. At that time, Cainiao relied mainly on manual operations for picking in its cloud warehouse distribution business. With the continuous growth of business volume and the increasing complexity of order structures, traditional manual picking methods exposed several pain points:

Efficiency Bottleneck: Manual picking speed is limited by the proficiency and physical condition of employees. Especially when faced with a large number of SKUs, the time cost of finding product locations is high, directly impacting order processing speed and overall logistics efficiency.

Accuracy Issues: Long periods of high-intensity work can lead to frequent human errors, such as picking the wrong goods or missing picks. This not only affects customer satisfaction but also brings subsequent service pressures such as returns and exchanges, as well as potential economic losses.

Rising Costs: With the annual increase in labor costs and the need for a large number of temporary workers during peak periods, warehousing operating costs are difficult to control.

Lack of Flexibility: For situations with large fluctuations in orders and changing demands, the manual picking system responds slowly and cannot quickly adapt to changes in order structures and quantities.

Solution:

After in-depth site surveys and needs analysis, we recommended the adoption of cross-belt sorters as the solution for Cainiao.

Project Scale: 156 trolleys, 160 destinations, 6 induction stations.

Implementation Time: From August 6, 2019, for planning and design to project completion on September 21, 2019, it took 45 days.

Effect Display: After the introduction of cross-belt sorters, Cainiao's cloud warehouse distribution achieved significant results.

Efficiency Improvement: Compared to traditional manual picking methods, picking efficiency improved by over 60%, greatly reducing the delivery time of parcels.

Accuracy Improvement: Sorting accuracy reached over 99.9%, significantly improving the accuracy of parcel delivery, reducing customer complaints and disputes.

Increase in Customer Satisfaction: Due to the improvement in picking efficiency and accuracy, customer satisfaction increased by 15%, winning Cainiao more trust and praise.

Significant Reduction in Labor Costs: A 30% reduction in labor input reduced labor and operating costs, bringing higher economic benefits to Cainiao.