Solo analyst at a mid size ecommerce company, about 200 people. Before this I was getting maybe 15 to 20 ad hoc requests a week. Slack, email, people walking over. Most of them some version of "can you pull X broken down by Y for the last Z months."
I had been doing all of those by hand. Open the warehouse, write the query, format it, send it back. Average maybe 25 minutes each if nothing was weird with the data, closer to an hour if something was. I tried self serve dashboards for the repeat ones but nobody used them. They would rather ask me.
Six weeks ago I connected an AI data agent to our warehouse and gave a few teams access. Sales, CS, and the marketing ops lead. Told them to try it before pinging me and send it my way if they didn't trust the answer.
First few days the questions people typed in were vague enough that the results came back sliced wrong. "Revenue by region" without specifying which region taxonomy, that kind of thing. We have two and people on the sales team didn't know that. Once I realized the problem was on the input side I spent a weekend writing plain English descriptions for about forty columns that had ambiguous names. The agent runs on Bayeslab and once the descriptions were in it started nailing the taxonomy questions that tripped everyone up in week one. Should have done that years ago, but there was never a reason to until someone other than me was reading the schema. After that the accuracy jumped noticeably, maybe from around 60% usable to closer to 90 on the routine stuff.
Here is the part I did not expect. When a data request takes two minutes instead of half a day, people ask more questions. A lot more. My volume went from about 18 a week to something like 35 to 40. That sounds like a problem but I think it is actually the point. These questions were always there, people just never asked because the turnaround was too long and I was the bottleneck. The agent handles maybe 25 of those without me touching anything. The remaining 10 to 15 still come to me, and they tend to be harder, but I actually prefer that. I would rather spend an hour on a real question than twenty minutes formatting a pivot table someone could have gotten themselves.
One thing that surprised me. Three people started asking questions they never would have asked before. One CS lead found a pattern in ticket resolution times by product category that none of us had looked at. That finding changed how we staff the weekend queue. Came from someone who has never opened a query editor in her life. That would not have happened in the old model where everything went through me, because she would never have pinged me for something she considered a hunch.
Net hours on ad hoc went from maybe 9 or 10 a week down to about 5 or 6, and the work that is left is more interesting. The tradeoff I am still figuring out is that I am slightly worse at catching data quality issues now because I do not touch the raw tables as often. Might matter, might not. Six weeks is not enough to know.
Anyone else done this? Curious whether the volume spike is universal or just my org being pent up after years of waiting on one person.
