Beiersdorf’s team of more than 900 scientists have been researching innovative, cutting-edge skin care solutions for decades. By centralizing its immense data library and leveraging AI-powered knowledge mining with Microsoft Azure Cognitive Search, its researchers can find the information they need quickly. Features such as document summarization, semantic search, document tagging, and optical character recognition allow researchers to extract key information fast, enabling them to spend less time searching and more time on industry-leading product development.
“Our in-house Azure-based search engine is equipped with AI and semantic capabilities to index terabytes of data across various heterogeneous data sources—thereby democratizing Beiersdorf’s R&D knowledge among our research scientists.”
Stephan Abend, Head of the Data Science Hub, Beiersdorf
Decades of research and skin care innovation
Beiersdorf has produced superior skin care products since 1882. The maker of leading brands such as NIVEA, Eucerin, La Prairie, Labello, and Hansa last has been testing, analyzing, and evaluating Beiersdorf’s products to ensure their continued excellence for decades, and the organization’s research efforts have led to the creation of a robust library of institutional knowledge.
Beiersdorf’s team of 900 scientists leverage this library to build on and innovate from previous research, and to expedite their current work. But first, they need to be able to find what they’re looking for.
With data stored across diverse sources, including more than 800 SharePoint sites and Beiersdorf’s Data Lake, researchers had struggled to find the relevant research they needed quickly. Beiersdorf decided to augment its inhouse R&D search engine with Microsoft Azure Cognitive Search and the document summarization feature in Azure Cognitive Services for Language.
Building a centralized, searchable digital library
To ensure the company’s digital transformation efforts deliver the centralization, organization, and accessibility its researchers require, Beiersdorf built a cross-functional team of data engineers, data scientists, machine learning engineers, and full-stack developers. This team focused on unifying Beiersdorf’s resources and creating tools to enable R&D teams to continue to deliver cutting-edge research and skin care innovations.
Stephan Abend, the head of the Data Science Hub at Beiersdorf, is a mathematician with experience in building data-driven solutions for various industries including banking, media, and FMCG. He helped begin an era of data transformation efforts at Beiersdorf. “Tech is the infrastructure, the vehicle, which allows us to get real-world products into a digital world where we can process them accurately and algorithmically,” says Abend. “If you really want to make data-driven decisions, you need digital solutions.”
To create a searchable, centralized database, Beiersdorf adopted Azure Cognitive Search, which enables researchers to derive direct, accurate answers from across multiple data sources. Using semantic search and document summarization, researchers get AI-powered results that contextualize, summarize, and highlight the most relevant information. “Our inhouse Azure-based search engine is equipped with AI and semantic capabilities to index terabytes of data across various heterogeneous data sources—thereby democratizing Beiersdorf’s R&D knowledge among our research scientists,” explains Abend.
Concise, condensed access to institutional knowledge
Beiersdorf has created an advanced, AI-powered platform that harnesses Beiersdorf’s resources through seamless, user-friendly features and custom-built solutions. Document summarization and key phrase extraction, features offered by the Azure Cognitive Service for Language, find and excerpt relevant information from lengthy documents while also providing context and condensing the essential knowledge.
With document summarization, paragraphs become sentences; pages of irrelevant information are transformed into simple outlines. This reduces the amount of time researchers need to spend scanning text and helps users navigate immense amounts of data. Even scanned documents and hard-to-read PDFs can be quickly accessed with optical character recognition (OCR), which extracts printed or handwritten words into text.
Looking ahead, Beiersdorf plans to build similar search and data capabilities for departments across the organization. By applying AI data mining technology, employees will be able to gain more customer insights, analyze customer feedback, and better understand consumer perception.
Custom solutions for industry-leading innovation
Several custom features tailor Beiersdorf’s solutions to the skin care industry. For example, a custom-built document tagging feature allows researchers to quickly categorize research by topic or product area. Using the semantic search feature of Cognitive Search, Beiersdorf has leveraged machine learning to categorize words and phrases that are specific to the skin care industry.
For example, a search of “ascorbic acid” will also return results for studies on vitamin C (which is another name for the component). This helps researchers find all relevant information, without having to waste time searching for different phrases or variations on their query.
Less searching, more science
For over 140 years Beiersdorf’s research has helped the organization create products that support people's daily self-care–an impressive history that deserves to be unlocked even more. Azure AI allows R&D teams to focus their time and energy on what they’re best at—research.
“Beiersdorf aims to hire the smartest brains in biochemistry,” says Abend. “We’re able to free our researchers from interacting with dozens of different interfaces, which means more quality time spent on research and innovation.”
The technology infrastructure also ensures that new research will be archived, tagged, and summarized dynamically, ensuring access to information for future research teams. With these powerful capabilities, Beiersdorf can leverage its own research in more strategic and impactful ways, ensuring that it continues to be a leader of superior skin care solutions.
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“We’re able to free our researchers from interacting with dozens of different interfaces, which means more quality time spent on research and innovation.”
Stephan Abend, Head of the Data Science Hub, Beiersdorf
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