Implementing SaaSGrid to reclaim 15 hours a week of reporting

The situation before

Pearl is a dental AI company. Kevin was the first operations hire there and stayed through five years of scaling, so this is a system he knows from the inside.

By the time the company had real scale, RevOps, finance, sales, and customer success were each answering the same questions with different numbers. Every internal and external reporting request meant somebody rebuilding a view by hand. It’s the most common problem in this job and it’s almost never a dashboard problem.

Why SaaSGrid, and what got built

SaaSGrid was the right tool for this because it handles the messy part well: pulling from the systems that already hold the data and turning it into metrics finance will actually sign off on. Buying it was the easy decision. Implementing it properly was the work.

A single source of truth rather than another dashboard. That means agreeing the definitions first, cleaning the data underneath them, and only then building the reporting layer on top. Do it in that order and the dashboard is a short job. Do it out of order and you rebuild it every quarter.

Once that was in place, 95% of the complex pipeline reporting ran without anyone touching it. That’s where the 15 hours a week came from. Not from working faster, from deleting the work.