Where the money actually goes

When a research study ends, the artifacts scatter.

The Zoom recordings sit in a folder that requires a login that most people don't have. The notes live in a shared doc that hasn't been opened since the project closed. The synthesis is in a Miro board that made complete sense during the workshop and now reads like an ancient map with no legend. The findings are in a slide deck that was emailed to a distribution list on a Friday afternoon.

Six months later, someone has a new research question. They check the obvious places. They don't find anything definitive. So they start over.

This is the hidden cost — not just the money spent re-running studies, but everything that comes with it:

Time. A new study takes weeks from kick-off to readout. That's weeks of researchers', stakeholders', and participants' time. All of it spent to arrive somewhere the team has already been.

Momentum. The question that needed answering didn't get answered — it got deferred. Whatever decision was waiting on that research waited longer than it had to.

Credibility. Nothing erodes confidence in a research function faster than a stakeholder who discovers, mid-debrief, that this exact question was answered two quarters ago. The implicit message is devastating: we're not learning, we're just running studies.

Institutional knowledge. Every time research is re-run instead of retrieved, a team misses the chance to build on what it already knows. Insights that should compound are starting from zero instead.

This isn't a research problem

The teams running repeated research aren't failing at research. They're often running excellent studies — rigorous, well-recruited, carefully synthesized.

They're failing at infrastructure. And in most organizations, no one is explicitly hired to fix it.

Research discoverability is a systems problem that gets misdiagnosed as a rigor problem. Teams respond by asking for better documentation, more consistent tagging, and more thorough readouts. All reasonable requests. None of them address the core issue: research artifacts are stored in disconnected tools with no shared taxonomy, no cross-project search, and no clear path from a research question to the work already done to answer it.

The question "didn't we already research this?" shouldn't require institutional memory to answer. It shouldn't require tracking down the researcher who ran the original study. It shouldn't require digging through three different project management tools and a shared drive.

It should have an answer that anyone on the team can find in under two minutes.