Problem Statement
The client’s R&D knowledge was fragmented across spreadsheets, lab notebooks, documents, repositories, and individual experts, making it difficult for scientists to discover and reuse historical research. This led to duplicated experimentation, slower product development, limited cross-functional visibility, and knowledge gaps when experienced researchers transitioned out. The enterprise needed an R&D Knowledge Management approach that could connect fragmented scientific and regulatory knowledge and make institutional intelligence easily discoverable across the R&D lifecycle.
Impact
- Knowledge graph connecting 90+ entities across 15+ entity types, linked through 130+ explicit relationships
- Addressed a segment where ~50% of professionals lose 1-5 hours a day searching for information, with data-heavy roles losing even more
- Targeted the ~60% of CPG R&D spend that typically went to renovation, maintenance, and rework rather than genuine innovation
- Discovery time for prior experiments collapsed from days to seconds via natural-language search
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