I spent more than twenty years working inside a major international company. Every week ran the same routine: the same metrics, the same monitoring, the same meetings, going over the same numbers — and almost all of it was done by hand.
My team was nineteen people. Each of us spent about four hours a week pulling data together and filling in spreadsheets, just to get the numbers ready for that week's reporting. Then a manager spent roughly another hour stitching it all into something presentable. Every single week, that's close to two full working weeks of effort spent moving numbers around, before anyone actually got to look at them.
So I went looking for a way to automate it. There wasn't one clean answer. Every vendor we spoke to could do part of the job, never the whole thing. One company handled data and tables, pulling automated sources together. A different company built the pipelines to make that usable in business intelligence tools. A third built the actual visual reports, interfaces and applications. Wanting AI in the mix meant yet another vendor again, and yet more cost.
Nobody offered the whole job in one place. On top of the fragmented work itself, my team spent hours going back and forth between companies and project managers just to get access provisioned, give feedback, and relay information between people who weren't talking to each other. And that was only to get it set up — running and maintaining it afterwards turned into its own ongoing job. One dataset crash, one changed column name, and someone had to drop everything to go and look at it. Turnaround was too slow for weekly reporting, and the cost ran into the thousands, again and again.
So I decided to fix it myself: one system, fully automated, that we managed ourselves end to end. I built it internally, and it worked. Then other departments heard about it and wanted the same thing. Demand kept growing faster than I had hours in the week — and I wasn't being paid to build software on the side. It was simply expected, on top of the actual job.
That gap is the reason Goodfield Studio exists: real automation and reporting, built and maintained by people who actually understand the problem, without needing three or four different vendors to get there.
Goodfield Studio is the studio I kept wishing existed: fast software delivery, data engineering, hands-on testing and fault diagnosis, and security-first AI, under one roof — not spread across a handful of vendors and a queue of change requests.
None of that matters if the people using what I build don't actually benefit from it. I'd rather ship one thing that genuinely works well than ten that are merely finished. That's not a slogan — it's the standard everything here gets held to before it ships, our own apps included.
Built by people who had to live with the broken versions.
— Field Lead, Goodfield Studio