If you’ve stayed with this series so far, you’ve likely already crossed an important threshold.

You’re no longer debating whether product data matters.

You’re no longer questioning whether bad data has real cost.

And you’re probably no longer convinced that a new tool or one-time cleanup effort is going to solve this for good.

At this point, most leaders I speak with feel aligned on the why.

Where things become harder—and more personal—is in figuring out what to actually do with that belief.

This is where leadership starts to feel the weight of the decision.

Almost inevitably, the discussion turns to ownership.

Not ownership in the abstract, but ownership in the practical sense:

Where does responsibility for product data actually live inside the organization?

Over time, this question tends to funnel into two realistic options.

Either product data ownership sits closer to the commercial side of the business—product, category, merchandising, marketing—or it sits closer to the technical side—IT, data, systems, or engineering.

Many organizations try to avoid choosing by saying that data “lives in between,” or by carving out a separate data group intended to bridge the gap. In theory, this sounds reasonable. In practice, teams that live in the middle often struggle to influence either side in a meaningful way.

Eventually, leadership has to choose.

And that’s where hesitation sets in.

There’s a quiet concern that comes up again and again in these conversations, even if it’s rarely stated directly.

It usually sounds something like this:

“My product team understands our products deeply.They understand customers, applications, and the market.But they don’t understand data management.If I give them ownership, am I setting them up to fail?”

That concern is not a lack of confidence in your team.

It’s a recognition of reality.

And it deserves to be addressed honestly, not brushed aside with optimism.

When product data ownership sits on the commercial side, it does something important: it keeps data close to strategy, revenue, and customer experience. It reinforces the idea that data exists to serve the business, not the other way around.

But this choice quietly changes what leadership is responsible for enabling.

It is no longer enough for business teams to know what they want. They have to learn how to express that intent in ways that systems, processes, and downstream teams can reliably act on.

That doesn’t mean turning product managers into technologists.

It does mean giving them support in learning how data behaves once it leaves their hands.

Without that support, frustration tends to build on both sides. Technical teams feel like they’re being asked to interpret intent instead of implement clarity. Business teams feel like systems are limiting progress instead of enabling it.

Leadership plays a critical role here—not by solving the problem personally, but by creating space, expectations, and shared language so that translation can actually happen.

At its core, this isn’t a debate about who is more qualified.

It’s about deciding where learning should happen first—and where leadership is willing to invest time, patience, and support.

Do you want the business to grow into data ownership with guidance and guardrails?

Or do you want technical teams to lead initially while building deeper empathy for how data drives growth, efficiency, and customer experience?

Neither choice is wrong.

Both choices require leadership to stay engaged.

What doesn’t work is assigning ownership and hoping maturity will emerge on its own.

One of the most common mistakes I see is leaders waiting for the “right” moment to decide—when teams are more mature, when systems are cleaner, when the organization feels ready.

In reality, readiness follows structure far more often than it precedes it.

Progress usually begins when leadership:

• Acknowledges the tradeoffs openly
• Sets clear expectations without demanding perfection
• Allows teams to learn without fear of getting it wrong
• And treats data not as a side responsibility, but as an asset that deserves care

This isn’t about moving fast.

It’s about moving deliberately.

Product data sits at the intersection of business intent and technical execution. Wherever ownership lives, leadership is ultimately responsible for making that intersection workable, humane, and productive.

The goal is not to choose perfectly.

The goal is to choose consciously—and then support the organization as it grows into that decision.

That’s how progress actually happens.

If this resonated, the next step is not to make a public declaration or reorganize your teams.

It’s to give yourself the space to think clearly about the decision in front of you—what you’re really deciding, what risks you’re willing to accept early, and what your organization needs from you before ownership is assigned.

We’ve put together a short leadership working guide designed for exactly this moment. It’s not a framework or a maturity model. It’s a private lens to help you clarify how to begin, what to ask for, and how to move forward without overcommitting.

If you’re ready to take the next step, start here.