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English"On DingTalk, a company no longer needs to be a physical space but rather a system of relationships. In the future, employees may not even need to come to the office in person,"
— Chen Kai, President of Lidar Technology Group
In 1986, Chen Kai's parents founded an electronic components business in Wenzhou, Zhejiang. With a keen business sense, they gradually expanded the company from chip distribution to chip manufacturing and the IoT field. Today, Lidar has grown into a high-tech enterprise focused on IoT product R&D, technology application, and service implementation. It has earned the title "Zhejiang Province's Technology Little Giant" and has been continuously ranked among the "Global Top 500 IoT Companies," holding the position of the world's second-largest supplier of NB-IoT modules.
In 2012, Chen Kai returned from studying abroad and joined the company. In April 2020, he took over as General Manager, leading the company's entry into the 5G sector, marking Lidar's transition into the "second-generation Wenzhou entrepreneur" era. Compared to his parents, Chen Kai is more proactive in embracing digital transformation. As early as 2017, he proposed introducing DingTalk to improve collaboration efficiency. Although the idea was initially rejected, after trying multiple tools, the company ultimately returned to the DingTalk platform in 2024.
Performance Management Goes Digital: Evaluation Cycle Reduced from One and a Half Months to Three Weeks
As a leading IoT company, Lidar once faced management challenges such as inefficient strategic goal decomposition and lengthy performance evaluation processes. Previously, OKR was filled out manually in spreadsheets, while peer reviews were conducted in a separate system, resulting in fragmented processes and severe data silos.
Frontline employees reported, "Listing goals, having them verified by superiors, and filling out evaluations—these steps are cumbersome and disconnected." Managers also faced immense pressure: during each evaluation period, they had to handle thousands of forms, and HR had to manually follow up and write 3–6 Q&A documents to guide operations, leading to high management costs.
In August 2024, Lidar launched DingTalk Agoal Pro Polar Star Edition, enabling a fully digital workflow for goal management and performance evaluation. Employees can fill out forms in the system and update their progress and completion rates monthly. DingTalk AI also provides intelligent support for setting goals, recommending peer reviewers, and automatically driving the process forward through task reminders, completely eliminating the need for manual follow-ups.
The previously fragmented evaluation, peer review, and calibration stages are now integrated into a unified platform with interconnected data. Sun Yao, Vice President of Operations, said, "After switching to DingTalk Agoal, we've moved away from the hybrid online-offline model, and performance evaluations have become efficient, streamlined, and seamless." The evaluation cycle has been dramatically shortened from one and a half months to just three weeks.
Chen Kai shares his experience using DingTalk Agoal
Sales Empowered by AI: Voice Conversations Generate Visit Reports
Writing reports after sales visits used to be a heavy burden. Previously, salespeople had to log into the CRM system and fill out complex forms, which was time-consuming and often led to delayed reporting and inconsistent report quality.
To address this, Lidar built an AI assistant on DingTalk. After a sales visit, salespeople can use voice to talk with the AI at any time, naturally describing the details of the visit. The AI instantly parses the conversation and generates a structured visit report.
A salesperson said, "I can dictate the report while waiting for my car, and if I don't finish, I can add more later. It's all done through conversation, so there's no more procrastination."
The generated reports are automatically split and filed, supporting quick search and statistics. They integrate with Yida to generate multi-dimensional data reports, such as sales views and product views, helping with behavioral analysis and decision optimization.
The visit report assistant built by Lidar
Legal AI Boosts Efficiency Tenfold: Smart Contract Risk Identification and Follow-Up
Lidar reviews about 2,000 contracts annually, placing tremendous pressure on its three legal staff members. Each contract requires a thorough review, taking an average of three days per contract, making it hard to improve efficiency.
Legal counsel Qi admitted, "Even though we use standard templates, we often can't stick to them when clients are demanding."
With the help of DingTalk AI, Lidar created a legal AI assistant. After a contract is uploaded, the AI automatically identifies potential risk clauses and sends them to the responsible party for confirmation, while triggering an automated follow-up process to ensure timely feedback.
Qi said, "Now, most contracts can be reviewed within a day, increasing overall efficiency by more than ten times."
Teambition Breaks Down R&D Silos: Resource Scheduling Accurate to the Day
Lidar's business spans semiconductor chips, IoT modules, and multi-industry application products, making projects highly complex. Departmental silos have long made it difficult to allocate R&D resources across teams.
After introducing DingTalk Teambition, project stage management, task assignment, and resource control can be implemented with simple configuration. Tools like project Kanban boards and Gantt charts make R&D resources highly visible, greatly reducing maintenance costs and allowing resource scheduling down to the day level.
Lidar's digital transformation exemplifies a typical path for second-generation successors in manufacturing leading change: leveraging DingTalk to reconstruct management processes, break down departmental silos, and enhance collaboration efficiency. While preserving the family business's legacy, the company injects new digital momentum. This shift from experience-driven to data-driven operations provides a replicable transformation model for traditional manufacturing enterprises facing complex market environments.
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