A Fortune-ranked consumer packaged goods company faced mounting competitive pressure and tightening time-to-market windows. They knew accelerating their Research & Development (R&D) analytics capabilities would give them an edge. But despite their legacy of product innovation, the team struggled to translate advanced analytics theory into rapid solutions that truly delivered value in complex, domain-specific settings.
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Big Challenge
Without fast, practical methods to leverage data science, the company’s R&D teams struggled to maintain their accelerating pace of discovery. Feedback cycles were slow, and project momentum faltered. Upskilling opportunities tailored to research and engineering contexts were not readily available. Off-the-shelf training missed the subtleties of R&D workflows, causing knowledge gaps and stalling tool adoption.
The Solution
Elder Research created and delivered a condensed, eight-week R&D engineering data science upskilling program to jumpstart efforts to innovate through targeted training.
We focused on real-world examples most relevant to R&D—feature engineering, anomaly detection, foundation models, and experimental design. And we sized modules to fit leader participants’ schedules. Live, in-person launches fostered camaraderie, while hands-on projects let pragmatic application drive the learning. These concise sessions enabled busy engineers and researchers to immediately use new skills to achieve tangible business success.
The Results
Participation led teams to adopt new methods for both formulation and manufacturing, unlocking faster product iteration and smarter experiment design. Early cohorts reported a reduction in time-to-insight for key initiatives, and feedback praised the custom fit between curriculum and daily R&D needs.
As one participant noted, “For the first time, I saw how advanced analytics fits with our actual problems.”