Delivering Data Products That Actually Lands
- Dave Findlay
- Jul 3
- 3 min read
We’ve talked about how to define data opportunities, align the work, and co-design the solution.
But now comes the part that gets all the attention (and often all the pressure): delivery.
In theory, this is where the
hard work pays off. In practice, it’s where good ideas can still fall flat if we’re not intentional.
Let’s talk about how to deliver in a way that doesn’t just meet the spec but actually sticks.
Start small, finish strong
You don’t need to ship the entire vision in version 1. In fact, trying to do that is what delays delivery and creates complexity. Instead, aim for something focused, useful, and easy to explain.
Think:
what’s the version we could release in 30 to 60 days that would make someone’s job noticeably easier?
That’s your starting point.
When the business sees something work in the real world, even if it’s simple, their confidence goes up, their engagement deepens, and your next iteration becomes easier to define.
Keep meeting with the business
Co-creation doesn’t end at design. It continues all the way through delivery and into adoption.
We recommend meeting with your business stakeholders twice a week for 30 minutes. That might sound like a lot (“woah, really?”), but it makes all the difference.
If you’re solving a real problem, your business partner will want to stay engaged. And these regular check-ins pay off in three big ways:
Visibility and momentum. They keep the project top of mind for your stakeholders (who already have more on their plate than time allows).
Clarity and speed. Developers get a predictable space to ask clarifying questions instead of taking a guess and building the wrong thing.
Shared understanding. These meetings bridge the classic gap: business learns more about tech, and tech learns more about the business.
Two quick meetings a week. That’s it. Enough to stay connected, remove blockers, and strengthen the relationship.
Support adoption like it matters (because it does)
Data teams often treat delivery as the last step. But for the business, it’s the first time they interact with what you’ve built.
We recommend supporting delivery with:
• Live walkthroughs and recorded demos
• Clear, written guidance (ideally contextual, not generic)
• Slack/email support channels for quick help
• Champions embedded in the team who can answer questions and model usage
Your job isn’t done when the feature goes live. It’s done when people start using it confidently.
Measure what matters
We’re big believers in defining what success looks like before you build, not retrofitting metrics after the fact.
In most cases, the business impact won’t be direct attribution to revenue. And that’s okay.
What you can measure is:
• Time saved
• Data confidence
• Frequency of use
• Workflow improvements
• Fewer ad hoc requests or manual workarounds
These are all strong signals that what you delivered is making someone’s life easier, and that’s what good looks like.
Make learning part of the process
Every delivery cycle should end with a short debrief: what worked, what didn’t, and what should we do differently next time?
This is where your delivery model becomes dynamic and responsive. You’re not just releasing features. You’re improving how your team delivers over time.
Final Thought
Delivery is more than launch day. It’s the beginning of real-world impact.
If you’ve defined the right opportunity, aligned the team, and co-designed with the business, you’re already 80% of the way there.
Now all that’s left is to land it.
At Fuse, we believe a great data strategy only matters if it leads to action.
If you’re ready to move from planning to execution — and build solutions your team will actually use — let’s talk.
