How is AI greasing the gears at GigaCloud? CTO gives insight

HIGH POINT — The dizzying pace with which artificial intelligence (AI) is developing can make it difficult to gauge where, and how, these new technologies are having an impact on the furniture business.

For a relatively new player in the industry like GigaCloud Technologies, which is deploying AI and related capabilities at multiple points in a novel business model, the nature and extent of their impact can be harder still to gauge.

GigaCloud CTO Xin Wan recently provided Furniture Today with insight into the role that AI is playing for the B2B large-parcel logistics and technology solutions provider.

He explained that GigaCloud is bringing together disparate parts of a “fragmented data landscape” in the large-parcel logistics sector.

Xin claims that, for traditional logistics providers, there are “inherent limitations to the way (they) operate. They often lack the data visibility in the end-to-end supply chain, from the manufacturer to the end customer, and struggle to compare and optimize fulfillment processes across different sales channels. This fragmented data landscape hinders AI’s ability to fully streamline large parcel fulfillment.”

New fulfillment options

GigaCloud aims to address these blind spots that arise because of “incomplete information (in the) end-to-end supply chain, from the manufacturer to the end customer” and to help companies  “compare and optimize fulfillment processes across different sales channels.”

“With our end-to-end fulfillment capabilities for large parcel merchandise … we leverage the power of AI to provide participants across the supply chain with new fulfillment options,” he said.

Xin noted that even before a purchaser places an order on GigaCloud’s B2B marketplace, AI-powered algorithms are humming in the background.

“We leverage AI from the moment the products are ready for shipment in the factories of overseas suppliers. We proactively use it to forecast warehouse capacity and predict shipping times, ensuring we have the storage and transportation resources needed. Additionally, AI helps us maintain an optimal inventory distribution across our warehouses.”

AI also plays a key role at the order dispatch stage, according to Xin.

“Once the products reach their designated warehouses and customer orders are received, our AI and machine-learning-supported systems then dispatch these orders to customers across the country efficiently.

Planning effective shipping schedules requires the consideration of various factors such as anticipated warehouse usage, transportation capacity and predicted ocean shipping times. The complexity arises from the sheer number of variables and uncertainties. Here, AI plays a crucial role by analyzing these factors to create optimized fulfillment plans.

Optimized load balancing

These technologies also play a central role in optimized load balancing, Xin noted.

“AI adjusts load balancing based on real-time sales data and fulfillment choices, ensuring optimal balance,” he said. “When a fulfillment center receives an order with particularly large volumes, AI can identify the large volume and redistribute some of the workload to other centers with available capacity. This approach optimizes resource allocation throughout the fulfillment network, ensuring streamlined operations.”

Providing a specific delivery window to end-consumers is one notable limitation of these technologies at present, he added.

“Despite AI’s capabilities, providing specific delivery windows to end customers remains challenging due to factors beyond its control,” Xin noted. “For example, some customers may use a shipping location other than one of our fulfillment centers, and some third-party carriers may have less advanced information systems. While AI cannot yet provide specific delivery windows to end customers, it can help us find a balance between speed and cost in large parcel logistics.”

Balancing speed and cost

Xin elaborated that this balancing act between speed of fulfillment and cost to the purchaser is really the linchpin for GigaCloud’s customers.

“Given our B2B nature, our customers are the sellers (manufacturers/suppliers) and buyers (retailers/resellers) in our marketplace,” he said. “For them, finding a balance between speed and cost is often more important than just being fast. When an item is ready to be shipped, we offer our B2B buyers the flexibility to choose between GigaCloud-managed fulfillment or self-managed fulfillment, where AI comes into play for either option.”

While its clear that AI’s impact changes in nature across different areas of the ordering and fulfillment chain in GigaCloud’s model, it still underlies “the entire transaction lifestyle,” Xin explained.

“AI-powered decision-making can optimize the flow of goods, inventory positioning and transportation routing, leading to reduced waste and lower overall transaction costs for our customers.”

See also:

  • Opportunity Impact: How AI can streamline warehouse operations
  • AI-powered solutions create value, a few challenges, for retail

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