Data Projects to Data Products, Part 2: Making the Shift
- Dave Findlay
- Oct 21
- 2 min read
In Part 1, we talked about why the traditional data project model is failing and how a shift toward data products offers a better path forward.
But that shift doesn’t happen overnight.
Most data teams today are caught in a cycle of intake, delivery, and support.
Even if they want to work differently, the gravitational pull of “just get it done” is strong. So how do you change that?
Here are five practical steps to help your team move from project delivery to product thinking.
1. Start with Problems and Possibilities
If you're drowning in intake requests, your first step isn’t to stop everything and start building products. It's to understand the business landscape.
Use a framework like RICE (Reach, Impact, Confidence, Effort) to score the highest priority problems that you're handling today. Then have proactive conversations with your business counterparts about where data could create leverage to refine your prioritization assumptions.
Don’t just wait for intake. Run Vision Workshops to explore the “art of the possible” and uncover opportunities that aren't yet on the roadmap.
This helps shift the narrative from “data team as service desk” to “data team as strategic enabler.”
2. Shift Allocation Toward Products
As you identify product opportunities, start shifting team members to support them.
This doesn't mean killing all projects. But it does mean setting aside explicit capacity to build and grow data products.
One approach is to set an initial ratio like 75% project-based service delivery, 25% product development and adjust it over time. As more durable products take hold, your need for reactive service work should shrink.
Be transparent with the business. Let them know that the goal is better outcomes, not less support.
3. Create New Operating Rhythms
You can't deliver data products using the same rhythms as project work.
Move from rigid project timelines to product backlogs. From milestone-driven gantt charts to agile sprints. From ad hoc status updates to regular demo sessions with users.
Create space for iteration and feedback. Treat adoption and value creation as success metrics, not just delivery.
4. Rewire Incentives and Mindsets
If you want your team to act like a product team, you need to reward them like product team.
That means giving them time to go deep on a problem space. Encouraging experimentation. Recognizing progress based on user outcomes, not task completion.
It also means helping your stakeholders adapt. Product thinking requires shared ownership. That can feel uncomfortable at first, but it’s what unlocks trust and traction.
5. Define and Launch Your First Product
Don’t wait for perfect structure. Start small.
Pick a real user need. Define a thin slice of a data product that could meet it. Assemble a cross-functional team. Build it. Test it. Launch it. Improve it.
Make the benefits visible. Show the before and after. Tell the story in a way that resonates with the business.
Then do it again.
At Fuse, we believe a great data strategy only matters if it leads to action.
