Customer Stories / Automotive
The BMW Group Streamlines Multilingual Business Processes Using Amazon Translate
Opportunity | Industry Challenge
The BMW Group, like many global automobile manufacturers, must manage operations in many different languages. Headquartered in Germany, the company oversees 120,000 employees and assembles cars and motorcycles in 31 manufacturing plants across 15 countries. “With suppliers and production all over the world, we have to provide our documents in numerous languages,” says Fabian Schrickel, group leader of technical translation, standardization, and product conformity at the BMW Group. For the company to effectively communicate with customers, retailers, suppliers, partners, and employees, it needed accurate, high-quality machine translations.
With the support of AWS, we were able to reduce our translation time by over 75%.”
Group Leader of Technical Translation, Standardization, and Product Conformity, The BMW Group
The BMW Group uses Amazon Translate, a neural machine translation service, to automatically translate documents from German into 30 different languages. Using this solution, global suppliers and production employees can comprehend key information quickly and efficiently, such as repair instructions. “Without this translation service, the worldwide production of BMW cars and motorcycles, as well as Mini and Rolls-Royce, would not be possible,” says Schrickel.
To enhance translation quality, the BMW Group also uses Active Custom Translation (ACT), a feature of Amazon Translate that gives developers more control over machine translation output. “Amazon Translate provides not only the translation but also the [ability] to customize the translation with our own data,” says Kathrin Berkel, emerging technologies and artificial intelligence specialist at the BMW Group. The BMW Group can customize the translation to reflect its style, tone, and specific terminology, improving the overall quality of its translation outputs. Through ACT, the BMW Group uses parallel data to refine and configure translations to fit its business needs as well as to customize the entire translation process.
Outcome | Benefits of Using AWS
By performing machine translations using Amazon Translate, the BMW Group has vastly improved the speed and quality of its multilingual communications. “With the support of Amazon Web Services (AWS), we were able to reduce our translation time by over 75 percent,” says Schrickel. In addition to advancing speed and quality, the company also reduced its translation costs on AWS.
The BMW Group also enjoys the scalability, reliability, and robustness of AWS-powered infrastructure. Because it can scale on demand to support new use cases, the company sees key opportunities for future advancement. “Amazon Translate will give us an opportunity to expand our service portfolio due to the fact that it can translate quickly and simply,” says Veith Koerner, language and translation manager at the BMW Group. “We’ll get translations much faster at a lower cost.” For example, the company plans to use Amazon Translate to deliver synchronous translation across all of its business processes. This solution will provide its employees with the ability to translate communications in real time throughout the workday, enhancing productivity.
The BMW Group has facilitated the production of millions of vehicles by using Amazon Translate and will continue to use AWS services to advance its global operations. “With the support of AWS, we want to bring translation at the BMW Group to the next level,” says Schrickel.
About BMW Group
The BMW Group is a multinational manufacturer of luxury vehicles and motorcycles. Headquartered in Munich, Germany, its brands include BMW, Mini, Rolls-Royce, and BMW Motorrad.
AWS Services Used
Amazon Translate is a neural machine translation service that delivers fast, high-quality, affordable, and customizable language translation. Neural machine translation is a form of language translation automation that uses deep learning models to deliver more accurate and more natural sounding translation than traditional statistical and rule-based translation algorithms.
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