How DingTalk's AI Spreadsheet Became STO Express Employees' "Process GPS" by Identifying Problem-Solvers Among 100,000 in One Second

At a 100,000-employee company, finding the right person to solve a problem is often more difficult than solving the problem itself—especially in industries like express delivery, where there are numerous outlets, complex organizational structures, and an extreme focus on efficiency.

STO Express solved this challenge with a single AI-powered table on DingTalk. By integrating AI tables with an AI assistant, janitors can now generate maintenance work orders simply through voice conversations, improving reporting efficiency by 90%.

With over 30 years of experience in the express delivery industry, STO has consistently invested in digital infrastructure. In September 2023, STO migrated its entire organization and operations onto DingTalk, achieving digital management for over 130 million packages. With tools like DingTalk's AI tables, more than 100,000 employees—from headquarters to local outlets—now benefit from intelligent, efficient support.

Below is a case study from STO Express.

STO Express: Pioneer of China’s Private Express Delivery Industry

Founded in 1993, STO Express was China’s first private express delivery company and pioneered the franchise model. It is now a national 5A-rated logistics enterprise, ranked among the Fortune China 500, and listed on the A-share market. The company operates 5,000 independent outlets and over 55,000 service stations and stores, owns nearly 6,000 long-haul vehicles, and handles an average daily volume of around 60 million parcels.

Pain Point: Difficulty Finding Responsible Personnel and Slow Response

Zhao Daqing, station manager at an STO outlet in Nanjing, said that in the past, due to multiple systems and unclear responsibility assignments, it was often unclear whom to turn to for help. Even when issues were reported, tracking down responsible parties was difficult because processes were scattered across different channels.

Zeng Zhe from the headquarters’ operations support team had to manually scroll through countless group chats to find pending inquiries—leading to missed messages, difficulty tracking progress, and high communication costs.

Solution: An AI Table-Powered Automated Inquiry System

By the end of 2024, the Business Decision Support Department launched the "STO Process Assistant"—an automated inquiry service system built on DingTalk’s AI table. The system integrates issue reporting, operations maintenance, status updates, and real-time notifications, embedded directly into employee service portals and functional pages, enabling instant submission and full visibility throughout the process.

Significant Results: Improved Efficiency and Faster Closure

Today, Manager Zhao only needs to submit a form via the DingTalk employee service portal. The issue automatically enters the AI table and triggers notifications, with real-time progress updates pushed directly to his account—greatly reducing information delays.

The system delivers the following benefits:

For frontline staff: Standardized issue reporting and transparent, trackable progress—no need to search through chat histories.

For maintenance teams: End-to-end automation from order receipt, assignment, to feedback ensures seamless coordination and shorter resolution cycles.

STO believes that service timeliness and quality are critical. With AI tables, the "Process Issue Resolution Initiative" successfully resolved the long-standing problem where "finding someone to help was harder than solving the issue itself."

Administrative Innovation: AI Assistant Makes Repairs “One Sentence Away”

Beyond business systems, administrative work order management at headquarters had also long been inefficient. The previous OA system had limited functionality, cumbersome processes, and manual notifications often caused delays.

Fang Jun from the Administration Department explained that earlier attempts to fix the issue failed due to high costs and lack of flexibility—even reverting temporarily to Excel, which led to fragmented data and frequent errors.

A free AI table, set up in just two hours, completely solved this “unsolvable-for-a-year” problem.

The new system restructured the repair request process into four modules: requester, technician, tracking progress, and feedback evaluation—forming a visible closed-loop workflow.

Key features include:

AI Assistant Automatically Generates Work Orders: Employees can describe issues via voice in group chats or by scanning QR codes; the AI automatically recognizes the content and creates a work order.

Smart Form Filling and Instant Notifications: Once submitted, administrators receive details instantly and can quickly claim or assign tasks.

Automatic Categorization and Assignment: The system identifies the issue type based on content and notifies the appropriate responsible party accurately.

Full Process Management on Mobile: Work order statuses can be viewed and managed directly from the DingTalk message inbox.

Closed-Loop Feedback Mechanism: Upon completion, results are automatically sent to the requester, who can provide online ratings—ensuring every request receives a response.

To improve accessibility, the team posted QR codes for the "STO Repair Assistant" near air conditioners, restrooms, and other common areas, allowing even janitors unfamiliar with digital tools to easily report issues.

In its first month, the system handled nearly 100 work orders, reduced average response time to 10 hours, and achieved same-day closure for 74.6% of cases.

Conclusion: From Efficiency Gains to Service Evolution

In an industry handling tens of millions of packages daily, every work order impacts customer experience. The flexible system powered by DingTalk’s AI tables not only boosts internal efficiency but also elevates service philosophy—ensuring every request is quickly captured and precisely responded to, helping the company move toward精细化 operation (fine-grained, precise operations).

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