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EnglishA company with 100,000 employees often faces the challenge that finding the right person to solve a problem is more troublesome than solving the problem itself—especially in an industry like express delivery, which features numerous service points, a complex structure, and an extreme focus on efficiency.
STO Express has solved this problem with a DingTalk AI table. By combining the AI table with an AI assistant, janitors can generate maintenance work orders simply through voice conversations, increasing reporting efficiency by 90%.
Having been deeply involved in the express delivery industry for more than 30 years, STO has continuously invested in digital infrastructure development. In September 2023, STO fully migrated its organization and business to DingTalk, achieving digital management of 13 billion parcels. With the launch of tools like the DingTalk AI table, more than 100,000 employees—from headquarters to local service points—now enjoy the efficient support brought by intelligent technologies.
The following is a case study from STO Express.
STO Express: A Pioneer in China's Private Express Delivery Industry
Founded in 1993, STO is China's first private express delivery company. It pioneered the franchise model and is now a national 5A-level logistics enterprise, a Fortune China 500 company, and an A-share listed company. The company operates 5,000 independent service points, more than 55,000 service stations and retail outlets, and nearly 6,000 owned trunk-line vehicles, with an average daily throughput of about 60 million packages.
Pain Point: Difficult to Find the Right Person, Slow Response
Zhao Daqing, a branch manager in Nanjing, says that in the past, there were many different systems, and it was unclear who was responsible for specific issues, leaving him unsure whom to turn to for help. Even when issues were reported, the fragmented processes made it hard to track down the person in charge.
Zeng Zhe from the Operations Support Department at headquarters had to "scroll through" numerous group chats to find pending inquiries, making it easy to miss messages, difficult to follow up on progress, and resulting in high communication costs.
Solution: An AI Table–Driven Automated Inquiry System
At the end of 2024, the Business Decision Support Department launched the "STO Process Assistant"—an automated inquiry service system built on a DingTalk AI table. The system integrates issue feedback, operations and maintenance handling, status updates, and real-time notifications, and is embedded in the Employee Service Window and functional pages, enabling users to submit requests anytime and track progress throughout the entire process.
Dramatic Results: Improved Efficiency, Faster Closed Loop
Now, Branch Manager Zhao simply submits a form in the DingTalk Employee Service Window, and the issue automatically enters the AI table, triggering a notification. Progress updates are pushed in real time to individual accounts, significantly reducing information delays.
The system delivers the following benefits:
For frontline employees: Standardized issue reporting, transparent progress tracking, and no need to scroll through chat histories.
For the operations and maintenance team: Full-process automation—seamlessly connecting order acceptance, task assignment, and feedback—shortens the processing cycle.
STO believes that both the "timeliness" and "quality" of service are critical. Through the AI table, the "Process Issue Resolution Initiative" has successfully cracked the dilemma that "finding the right person is harder than solving the problem itself."
Administrative Innovation: AI Assistant Makes Maintenance Requests "Done in One Sentence"
In addition to business systems, administrative work order management at headquarters had long been inefficient. The original OA system had limited functionality, cumbersome processes, and manual notifications that were prone to delays.
Fang Jun from the Administration Department explains that previous attempts to implement various solutions failed, as they were costly and inflexible. At one point, the team even reverted to using Excel—but data was scattered, prone to errors, and hard to manage.
A free AI table built in just 2 hours completely solved this "year-long" problem.
The new system restructures the maintenance process into four key modules: the requester, the maintenance personnel, progress tracking, and feedback evaluation, forming a visual closed loop.
The core features include:
An AI assistant automatically generates work orders: Employees can describe issues via group chat or by scanning a QR code and speaking into the device, and the AI automatically recognizes the issue and creates a work order.
Smart form filling and instant notifications: After submission, administrative staff receive detailed information in real time and can quickly claim or assign tasks.
Automatic classification and assignment: The system determines the type of issue based on the content and precisely notifies the responsible person.
Full-process management on mobile devices: Work order status can be viewed and handled directly in the DingTalk message feed.
A closed-loop feedback mechanism: Once a work order is completed, the results are automatically sent back, and the requester can provide online feedback, ensuring that every request receives a response.
To make the system easier to use, the team has posted QR codes for the "STO Maintenance Assistant" near air conditioners, restrooms, and other locations, allowing even janitors unfamiliar with digital tools to easily submit maintenance requests.
In the first month after the system went live, nearly 100 work orders were processed, with the average response time dropping to 10 hours, and 74.6% of cases closed on the same day.
Conclusion: From Efficiency Gains to Service Evolution
In the express delivery industry, which handles tens of millions of packages daily, every work order is a critical factor affecting the customer experience. The flexible systems powered by DingTalk AI tables not only improve internal efficiency but also drive an upgrade in service philosophy—every request can be quickly captured and precisely addressed, helping companies move toward more refined operations.
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