Even if your data team is just getting started, never forget money.
We analysed some organisational insights that José Meroño, the former head of data at Prisa Noticias of Spain, the publisher of El Pais, shared with us at the recent INMA Product and Data for Media Summit.
José built the team at Prisa from scratch in record time, and whether you’re planning a blitz of your own, there are some takeaways that all could use.
An earlier blog post explained the importance of having a strong mission and bringing value early on. In this post, we’re going to focus specifically on the money takeaways — how to stop wasting it and where costs are worth it.
Figure out where you’ll be bleeding money, as quickly as you can
One of the things José and his team learned in that first phase of scaling is just where their data machine was going to eat them out of their house.
Now, in a previous job, I remember being on a very uncomfortable hot seat during an emergency meeting because my team’s data budget had unexpectedly exploded in the span of a month as we had onboarded some new customers.
The number by the way was astounding. But the mistake was very much mine: We had had a slower Alpha, and then, having established that all was ship shape, deeply accelerated for a Beta.
The problem is, of course, that data costs tend to be pretty linear with usage when you’re running a lot of uncached, custom queries, and other “rich” pulls. It’s the thing we often forget about because we’re focused on data availability, cleanliness, the experience of our users who interact with our data … and costs feels like a thing we can always get ahold of.
And we can get ahold of our costs. José killed a bunch of expensive reports and only gave certain power users the ability to pull the more expensive dashboards. But there is a real disruption to having to re-engineer potentially significant parts of your systems because you built them out without an early feedback loop into their true costs at scale.
So José had to take on the burden of more customers early, when his team was only six or seven people. But, on the other hand, the build was still early, and they could identify where they’d need to stop the bleeding — before they had fully committed to that bit.
Bring in contractors to speed up your time to market while you build the forever team
I am not going to tell you anything you don’t know when I say that even in the context of recessionary times, hiring for data is a contact sport. So is there such a thing as efficient time-to-market when hiring is going to be either badly rushed, or, well, will get in the way of your timeline?
José had no qualms about hiring contractors to support the team in the build-out, but doing this gave him something else as well. Since he was hiring for well-defined needs, he didn’t have to overthink whether this person was the right mix of skills and experience for the team as it would evolve over time.
One reason early data team hires are often difficult is that you need a few key folks who are jacks-of-all-trades: data engineer, data architect, data scientist … and often a product manager and an executive whisperer. These people exist, but it will take interviewing to find them.
Meanwhile, finding folks who can build some of your early data pipes in your cloud of choice — and not really worry about whether this is someone who will be able to evolve into a different role in six months — that’s significantly easier.
And time is money, which is why time-to-market is a real thing even for a trade, like data, that usually has trouble assigning ROI to many parts of our daily contribution.
Since Prisa had articulated the mission as supporting the subscription effort, there was a way to articulate the value of bringing the data team online earlier rather than take more time to get there.
We come full circle, really, to the point that the transformative approach when it came to this team was that it always had a specific mission.
If you’re a publisher who is assessing how or where or how much to grow your data team, first find a core mission for this team. Not soft n’ squishy aspirations but an actual mission that will orient their choice and help choose way stations to start delivering value early and consistently.
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