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(Yicai) Feb. 27 -- Mercedes-Benz Group today confirmed to Yicai that it will reduce its headcount in China and increase its operational efficiency through new technologies after the German luxury car brand's local sales dropped last year amid fierce competition.
Facing a challenging market environment, Mercedes-Benz has been actively adjusting its business, including optimizing and streamlining its business processes and organizational structure, and the consolidation or reduction of its business will inevitably influence some employees' work arrangements, the Stuttgart-based owner of Mercedes-Maybach and Mercedes-AMG brands told Yicai.
Next, Mercedes-Benz China will deeply apply new digital technologies to improve operational efficiency, simplify business processes, adjust job settings according to business needs, and integrate or reduce redundant and parallel positions, it added.
Automotive news outlet AutoPix reported yesterday that Mercedes-Benz China has launched layoffs affecting 15 percent of the local workforce, mainly in sales, finance, and parts departments. The marque would give N+11 severance packages, referring to the number of years served plus 11 months of pay, per the report.
Despite global headwinds, Mercedes-Benz retained its position as China's top luxury car seller last year. It delivered more than 714,000 vehicles, down 7 percent year-over-year. The German company's global net profit slumped 28 percent to EUR10.4 billion (USD11.3 billion) in 2024 while revenue fell 4 percent to EUR145.6 billion (USD158 billion), according to its annual report.
The rise of Chinese smart car brands such as Li Auto and Nio has prompted Mercedes-Benz to increase its local research and development investment to accelerate electrification and intelligence.
Last September, Mercedes-Benz announced that it would invest CNY14 billion (USD1.9 billion) with Chinese partners to expand the regional product lineup. More specifically, it would revamp the popular sport utility vehicle model GLE, becoming the first China-exclusive model to be developed by a local R&D team.
Editors: Dou Shicong, Emmi Laine