Building the machinery that makes research scale
Research only scales on the infrastructure most people never see — panels, recruiting, consent, incentives. Building it is as much a program-management job as a research one, and I've built it from the ground up in two very different organizations.
Insight doesn't scale. Infrastructure does.
A single study is a craft project. A research practice — one a whole organization can rely on, again and again, without reinventing recruiting every time — is an operations problem. Someone has to build the panels, the screeners, the consent and incentive systems, the tooling and the vendor relationships that sit beneath the work. Do it well and it disappears into the background; skip it and every team quietly pays the tax, one slow, expensive study at a time.
Two organizations, two operations built from zero
The same discipline, in two very different settings — one enterprise, one public-sector — each starting from nothing.
An in-house panel, on tools I built
Rather than pay to re-recruit the same kinds of people study after study, I built two custom in-house tools — one for recruiting, one for managing the panel — behind an in-house research panel drawn from a mix of sources. It gave product teams a reusable pipeline instead of starting cold every time, and cut recruiting time from first contact to accept by 50%.
A state research practice from scratch
At the Office of Data & Innovation there was no research-operations function at all. I built one: an 8,000-participant panel with screeners, consent, and incentive systems across UserTesting, Qualtrics, and Ethnio — designed to reach residents a public service can't afford to miss, and to feed the state's AI evaluation program at scale.
Researcher and operator, in one seat
This is the part of the job that rarely makes the highlight reel: the tooling, contracts, and systems beneath the insight. It's also where a researcher who can run a program earns their keep — turning research from a string of one-offs into a capability an organization can count on. Having built it twice, in an enterprise and a government, is the clearest evidence I can offer that I operate as much as I research.
Insight is the visible half of research. The other half is operations — and it's the half that decides whether the insight ever arrives. — how I think about research ops