At the INMA Product and Data for Media Summit we just wrapped up, one of the modules dealt with “the way we work.” In particular, we heard from José Meroño, the former head of data at Prisa Noticias of Spain, the publisher of El Pais.
I have mentioned José before when we originally connected a few months ago because he had a very interesting story to share about how Prisa spun up its data team. The headline is this: Prisa created a mature, “full-powered” team — including the architecting, the engineering, and hiring work — in 18 months.
This is … very speedy — more speedy than I would have imagined possible in the context of a reorganisation.
But there were some particularly useful insights in what José shared with us. And so, for the folks who didn’t join us at the summit — or maybe who want a handy blog post to share with their boss as they try to negotiate the budget of the data team next year (I’ve been there) — here’s what we learned:
Build a team with a specific mission, even when the team isn’t there yet
José was hired as a seasoned data exec with an early mission that wasn’t so much “build the data team” as “build the data team to support our new foray into paid subscription.”
I think when we spin teams, those that find their footing faster are those that are built in response to a specific goal or task to accomplish. Even as many publishers think, “Hey, I know data is important, we need a bigger team to accomplish our goals,” I would ask that big boss: What is the key mission of data in the next year?
And mission isn’t: “Make us more customer centric.” That’s a company value — not the mission. But Prisa actually gave José a proper mission, which could underpin pretty much every decision in terms of what type of folks to hire or what architecture to develop for the data platform.
It also gave some time horizon to the enterprise. The subscription push was underway, so what were ways that the data team — even as it was being spun — could begin to make contributions to the mission.
Find ways to bring value as early as possible
I speak here as someone with extensive product management experience in heavy-duty technology (analytics tools, CMS) — the kind of product that rarely is a light lil’ MVP. So I am particularly sympathetic to the travails of imagining the earliest version of what you have and how you’ll work with your earliest users.
Usually, that’s a pretty dismal affair. The products don’t do much, the users are living in some kind of super crude system, and the output of all this is usually pretty basic. Which is why I was quite impressed when José told us he went from 20 early testing users in the second quarter of their buildout to a 100 in the third quarter.
Reader, I wanted to reach across the screen and say, “Oh my god, don’t do that!” (It was like when you know where the killer is and you want to tell the blonde on screen, “No, don’t lock yourself into that closet!”)
In any event, goes to show that I was too conservative because José’s team made it work. And what they got was, of course, more customer feedback early — which is invaluable to course-correct before you’re overly invested but also something that every young data team eventually stumbles on, which is that somewhere, you’re going to run worse costs than you think. We will look at this in our next post.
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