Let Them Play: Rethinking Process for Data Teams That Need to Move

By Thais Cooke

The World Cup is in full swing, and soccer is everywhere right now. A friend of mine invited me to watch her kid’s game, and when I looked at the schedule and saw who they were going up against, it made me cringe.

Here is why: last year, I went to watch them play on a cold Saturday morning (who scheduled a game this early, anyway?). Despite that, I usually enjoy these games. However, this time was different: the coach on the other team insisted on stopping the game every minute to reposition his players and give them a quick speech on how to keep their positions. That lasted the entire hour. Soccer is a dynamic game, and that’s why I enjoy it. However, that approach made the game boring, slow, and nothing was done. Parents were left frustrated, and honestly, so was I. Everyone showed up to watch kids play soccer, not to watch them stand around waiting for instructions.

What does this have to do with data? Well, quite a few things.

When Process Gets in the Way of Progress

Every industry is different. I have my reservations with “move fast and break things”, especially because I come from healthcare. Highly regulated industries have much bigger consequences when things “break”, and that’s understandable. However, the coach stopping play every minute mirrors organizations that require approval for every data query, model deployment, or dashboard. All those excessive checkpoints create analysis paralysis, missed opportunities, and demoralized teams. The game stops. The analysts stand around waiting. The business stakeholders check their watches, frustrated that they woke up early (or allocated budget) for... nothing.

Just like that soccer coach, these organizations aren’t wrong about the fundamentals. Yes, data needs proper oversight, security controls, and compliance measures. There must be investment in those areas: building frameworks, implementing the right tools, and training people to navigate complex decisions. And with AI in the mix, the stakes are higher than they used to be. The speed at which teams can now build and deploy means consequences arrive faster, too. But that investment should enable movement, not freeze it. The problem isn’t the “what,” it’s the “how” and the “when.”

Strong fundamentals are built during practice. The best soccer teams drill positioning until it becomes second nature. When game day comes, the coach doesn’t need to stop play every minute because the foundation is already there.

The same principle applies to data teams. Make it clear which situations need escalation and which don’t. A junior analyst pulling a standard customer report shouldn’t need three sign-offs. A data scientist wanting to train a model on medical records and deploy it externally? Yes, that should involve more people. When you reserve your interventions for situations that actually warrant them, people respect the process instead of routing around it.

So what’s the alternative?

Process Should Enable the Game, Not Stop It

Here’s what that over-controlling coach missed: the whole point of positioning and strategy is to enable dynamic play, not replace it. The rules of soccer exist to create the conditions for an exciting, competitive game, not to prevent the game from happening.

Process and compliance aren’t the enemy of getting things done; they’re supposed to be the foundation that makes sustainable progress possible.

When you get the balance right, governance becomes invisible infrastructure. Your teams move fast because they’re confident they’re operating within safe boundaries. Your organization innovates because people aren’t afraid to experiment. And yes, you manage your risks better, because you’ve designed systems that prevent problems rather than just documenting them.

The organizations that get this balance right are recognizing that moving fast and staying safe are both necessary to play the game. They understand that excessive process creates its own risks, and ironically, worse security outcomes because people start routing around the controls. Instead of looking for complexity, they are saving their energy for when complexity inevitably catches up with them.

Saving Your Energy for What Matters

The best soccer coaches I’ve watched set clear expectations before the game, position players strategically at kickoff, and then let them play. They intervene when something is genuinely wrong, make adjustments when needed, and review what happened afterward. The kids learn, they make mistakes, they get better. The game flows.

Building effective data teams works the same way. Start by establishing clear frameworks upfront: here’s what sensitive data looks like, here are the security requirements, here’s how we think about privacy and compliance. Build guardrails into your systems so it’s hard to make risky actions by accident. Train your teams so they understand not just the rules but the reasoning behind them. Then step back.

The key is knowing when to step in. Review and adjust at regular intervals. Learn and improve together, but don’t stop the game every minute. Reserve your interventions for the situations that need human judgment: the edge cases, the novel risks, the complex decisions. Everything else should flow.

Fall Training Starts Soon

I’m hoping that the coach learned something in the off-season. Maybe he watched his team’s frustration, or saw other teams playing, and realized there’s a better way. Maybe he’ll come back this Fall with a new approach: clear positioning, trust in his players, the confidence to let the game flow, and save his interventions for when they really matter.

If your data team’s workflow feels like that soccer game, maybe it’s time for some off-season reflection, too. Ask yourself: are we positioning our teams for success, or are we just stopping play? Are we building capability, or are we building bureaucracy? Are we managing risk, or are we just managing to prevent anything from happening at all?

Because eventually, people stop showing up to games where nothing happens. And in the data world, that means your best talent finds somewhere else to play.

Author Bio

Thais Cooke moved from clinical healthcare into data analytics and now works as a Senior BI & Data Analyst. She writes and speaks on data, AI, and the human layer in between.