One of the world's most recognized management consulting firms employs more than 50,000 professionals across every major industry and region. Its entire value proposition rests on a single premise: that its people see patterns faster, reason more rigorously, and synthesize complexity better than anyone else in the room. That reputation is built insight by insight, engagement by engagement, across thousands of projects every year.

What's less visible is the research that happens inside the firm itself, into how its own people work, what tools and platforms they need, and how the organization can run more effectively at scale. A lean team of researchers, designers, and knowledge practitioners drives that effort. Their remit spans the internal products and platforms that hundreds of thousands of professionals depend on daily.

For years, the firm had Dovetail. But the real shift came when that small research group decided to treat internal adoption as a product problem. They built templates, established naming conventions, trained hundreds of practitioners, and built a community around shared standards. The result is an intelligence system that grows more valuable with every study added to it. Consultants, product managers, and designers across the organization now draw from research that researchers completed years earlier, surfacing insights they never would have found working alone.

That's not just tool adoption. That's customer intelligence compounding at scale.

The research team treated the workspace like a product they were shipping to internal users. They built a shared template library, each project pre-populated with the firm's standard research plan structure, so any researcher could begin a study with the right scaffolding already in place. Naming conventions, folder hierarchies, and firm-specific tag taxonomies followed. They embedded the firm's internal vocabulary directly into the workspace's custom context, so that Chat would understand the organization's language the moment someone opened a query.

The reuse effect became the most compelling proof of what they'd built. A set of foundational interviews, uploaded by one researcher years earlier, had been accessed and built upon by at least five other researchers working on related problems. Each brought different questions and different synthesis goals. Each walked away having saved hours they would otherwise have spent going back to the source.

"People would come to me and say, 'You saved me so many hours of research. I was able to just use your videos and add my own tags.'"

— Research Operations Lead

That kind of compound return only happens when the workspace is structured well enough to be discoverable. Training became the mechanism for spreading that standard. Quarterly sessions brought together researchers, designers, and other practitioners — sometimes hands-on, sometimes a broader demonstration of new capabilities. A session in late 2025 drew more than 75 registrants. The goal was never just feature literacy. It was shifting the culture from "I have research" to "we have research."