There's a Gartner paper titled "How to Determine the Right Team Size in Data and Analytics". I did some simple maths on its ranges and wanted to check with data leaders out there: are the numbers realistic?
My personal take: not quite a surprise for large organisations, but I find it almost inconceivable for a company with $50 million in annual revenue (the upper limit of Gartner's "small" range) to have a data team of fifteen people.
One acquaintance said they work for an Australian retailer clocking nearly $1 billion (AUD) in revenue with twenty people in the data team. I found the latter more realistic. What are your thoughts?
The original post carried the working as an image. The paper itself is licensed, so no copy here; the title is enough to find it.
Postscript, September 2026. Gartner's own 2026 data and analytics predictions now argue for smaller, multidisciplinary teams of broad-skilled people working alongside AI agents, and hold up AI-first start-ups with "fewer employees with significant ownership" as the model. That is closer to the twenty-people-for-a-billion-dollars end of the range than to fifteen-for-fifty-million. The arithmetic aged well; the team-of-fifteen didn't.
First posted on LinkedIn. This is the canonical copy, lightly tidied.