Employer Profile

Danone is a leading multinational food and beverage company focused on three dynamic sectors: specialized nutrition, dairy and plant-based products, and water and beverages. Operating in more than 120 markets worldwide, Danone entered the Chinese market in the late 1980s. After more than thirty years of sustained development, China has become Danone’s second-largest market globally, with 10 factories, over 8,000 employees, and contributing approximately 11% of the company’s global sales in 2023.

Industry: Food & Beverage

Employees: 96,000

Challenge

Every campus recruitment season, Danone faces a surge in hiring demands within a short period across a vast geographic range. The large number of student applicants generates management and assessment pressures, compounded by inconsistent interview standards that risk unconscious bias. In addition, there are potential risks of cheating during interviews:

• Interview Management Pressure: During campus recruitment, tens of thousands of candidates apply, while the number of live interviewers—scattered across multiple regions—is insufficient to thoroughly cover every candidate. Relying solely on manual screening would consume substantial time and effort, resulting in low efficiency and high costs.
• Assessment Standard Disparity: Interviewers from different regions may interpret sales aptitude and motivation differently, and when tasked with rapidly evaluating a large pool of candidates, their judgments can easily become skewed. This makes it difficult to maintain consistent national standards, resulting in fluctuating candidate quality and an unfair selection process.
• Cheating Vulnerabilities: Online interviews create opportunities for candidates to cheat, sometimes using tools to evade system monitoring and compromising the integrity of the recruitment.

Solution

MoSeeker partnered with Danone to develop an AI interview system seamlessly integrated with Danone’s own ATS, enabling full automation of the interview process, building a comprehensive and professional interview assessment system, and implementing dynamic regional ranking with visualized results:

• System Integration: The AI interview system and Danone’s ATS are fully integrated in terms of workflow and data. HR professionals can initiate interviews, monitor progress, and view results directly within the existing platform, without the need to switch systems;
• Process Automation: The interview process is fully automated, allowing candidates to schedule interviews 24/7. Through an intelligent scheduling system, tasks are automatically assigned without manual intervention;
• Professional Assessment System: To ensure the recruitment of candidates who precisely match the company’s requirements, MoSeeker developed a customized competency assessment model based on Danone’s historical interview data. This enables AI interviews to demonstrate specialized talent evaluation capabilities. The model covers five competency dimensions, with each question scored from three aspects to provide in-depth assessment of candidates, summarizing their strengths and areas for improvement. The consistency between AI and human evaluations exceeds 80%;
• Dynamic Regional Ranking: All regions use the same evaluation algorithm but carry out dynamic ranking separately, automatically generating performance ranking reports for candidates in different offices with visualized presentation.

Impact

MoSeeker rapidly completed the private deployment and rollout of the AI interview system, significantly improving campus recruitment efficiency and reducing HR workload. For targeted positions, the system allows interviewers to set their own questions, while providing automated and personalized candidate assessment: 

• The AI interview pass rate is set at 35%, meaning that the system can help Danone eliminate 65% of applicants, allowing HR to further shortlist candidates. This enabled Danone to carry out large-scale initial screening via AI interviews and greatly narrow the talent pool;
• The customized private AI assessment model performed excellently, with its evaluation closely matching human judgment. Comparing interviewer manual assessments with AI results showed: for candidate elimination, consistency between AI and human evaluation exceeded 90%; for selecting top candidates, consistency exceeded 85%.
• The AI interview system demonstrated strong consistency in applying evaluation standards. In contrast, different interviewers often interpret criteria differently, and even the same interviewer may unconsciously adjust standards for different candidates. The AI algorithm strictly adheres to a single set of standards and evaluates all candidates equally. By implementing unified standards and conducting semantic text analysis, the AI interview system can provide clear evaluation rationale, making it easier for HR and interviewers to understand the reasoning behind each decision. The AI interview system also delivered an excellent user experience for candidates: 60% provided positive feedback, and 20% said they strongly recommend it.

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