Dr. Mario's 2nd 🧠

🗞️ Growing Data Teams from Reactive to Influential

2 min read

It describes an evolution that reminded me to 🗞️ Data as a Product vs. Data as a Service.

Reactive stage

You start here:

… the company’s data expertise is heavily centralized on the data team, while decisions about business priorities are not. As the experts on how to best leverage data, it falls on the data team to change the culture, but starting from a position with very little agency to make that change. The data practitioners continue to try to provide their stakeholders with what they ask for in the hopes that company-wide data literacy will someday come. So the requests pile up, and the team works reactively on data questions that may or may not be best-framed for real business impact.

Ojo! Measuring a data team impact

It should never be the data team’s job (or the data team manager’s job) to prioritize all of the incoming requests by themselves. In an ROI equation, the data team only knows the “I” with certainty, and can only speculate what the “R” might be if they don’t know what the higher level goals of their business partners are.

Proactive stage

To switch to proactive, not only prioritize based on ROI, but also on “culture-changing” tasks:

where the goal is to improve data literacy through learning opportunities for the stakeholders. The work may be the same, but the intention and definition of success changes.

Over a few quarters, the number of impact-driving requests should increase, because the stakeholders have been given the opportunity to gain better intuition for the kinds of analyses that drive real business outcomes.

Influence stage

Yep…

Data teams tend to be a fairly scrappy bunch, and often default to rolling up their sleeves and building what they need in order to get unblocked.

The next obvious step is to build longer-term foundational work into the team’s capacity.

And she suggests to do this by trying to influence other teams roadmaps.

Graph View