Delivering Data Products That Actually Lands

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.

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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.

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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:

1. Visibility and momentum. They keep the project top of mind for your stakeholders (who already have more on their plate than time allows).

2. Clarity and speed. Developers get a predictable space to ask clarifying questions instead of taking a guess and building the wrong thing.

3. 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.

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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.

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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.

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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.

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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.

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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.

👉 Book a strategy call

👉 Read more on the Fuse blog

👉 Follow Fuse Data on LinkedIn

👉 Follow Dave on LinkedIn

How to Design Data Solutions That Actually Get Used

Design isn’t just what it looks like.

It’s how it works for the people who need it and how they feel when they use it.

In our previous posts, we walked through how to:

1. Define initiatives from discovery conversations

2. Align those initiatives around business priorities and engagement capacity

   
   

Now it’s time to design. But that doesn’t mean just drawing pretty charts or dreaming up a slick UI.

It means shaping a solution with the business — one that solves a real need and is simple enough to actually use.

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Co-create, don’t just gather requirements

The business doesn’t want to “hand off” the problem and get a surprise in return. They want to be part of building the thing that will make their work easier.

That’s why we use collaborative design sessions to:

1. Explore what a good solution might look and feel like

2. Walk through real use cases and day-in-the-life stories

3. Sketch out low-fidelity prototypes together

You’re not promising perfection. You’re building shared clarity.

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Don’t confuse features with needs

Stakeholders often describe a solution in terms of features, but your job is to uncover the underlying need. One way to do that is to channel your inner 3-year-old and keep asking, “Why?”

Example:

Stakeholder: "We need to download to Excel" ← that’s a feature.

You: “Why?"

Stakeholder: "We need to share our dataset with colleagues"

You: “Why?"

Stakeholder: “They need to provide updates based on the next steps for each deal record"

You: “Why?"

Stakeholder: "So we can make sure deals are progressing"

You: “Why?"

Stakeholder: "Because if deals don’t progress, we’re at a high-likelihood of losing to a competitor"

You: “So you and your team need to be aware of deal stage progression and be able to identify stalled deals early, so you can mitigate risks that could prevent you from winning the business.” ← that’s a need.

Now we’re getting somewhere.

The real need isn’t Excel. It’s visibility into deal progression to reduce risk and increase win rates.

There are multiple ways to meet that need and now you can work with your stakeholder to design the features that will meet their core need.

Good design doesn’t just deliver the requested feature. It solves the real problem, in the best way for the context.

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Use MosCoW to prioritize feature ideas

During design, you’ll uncover far more ideas than you can realistically build, and that’s a good thing. But you need a way to focus.

We use the MosCoW framework:

1. Must have – Critical to delivering on the core need

2. Should have – High value, but not absolutely essential

3. Could have – Nice-to-haves if time allows

4. Won’t have (for now) – Useful ideas that won’t be in this cycle

Once you’ve categorized the features together, the data team can provide an early estimate of how far down the list they can reasonably go during your current delivery window.

That becomes your target for version 1.

Everything else gets parked on the roadmap, ready for a future iteration if and when the governance committee decides to move it forward.

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Collaborative design sets you up for success when you move into delivery.

You’ve clarified the needs.

You’ve designed with the business.

You’ve aligned on what version 1 includes.

Design is where the solution takes shape. But it only works if it stays grounded.

Start with needs, not features.

Involve your users early.

Prioritize together.

That’s how you design something the business will actually want to use.

Now you're ready to build.

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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.

👉 Book a strategy call

👉 Read more on the Fuse blog

👉 Follow Fuse Data on LinkedIn

👉 Follow Dave on LinkedIn

How to Build Alignment Around Your Data Initiatives (Before You Start Building)

Good decisions made poorly are bad decisions.

That’s why alignment isn’t just a formality — it’s the difference between forward motion and friction.

In our last post, we covered how to define a data initiative: taking raw input from discovery and shaping it into a focused, meaningful opportunity.

But once you have a list of potential initiatives, what happens next?

This is where alignment matters.

Because without it, even the best ideas can stall out.

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1. Start with a business-led committee

At Fuse Data, we recommend forming a small working group of business leaders who all have a stake in data-driven decision-making. This becomes your committee — the team that helps shape and sequence the work.

It’s not about getting consensus on every detail. It’s about:

• Reviewing proposed initiatives together

• Creating space for tradeoff discussions

• Ensuring no single voice dominates the process

A clear, shared process gives everyone a seat at the table and reduces the risk of politics, posturing, or priority whiplash.

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2. Use objective prioritization

To keep things fair and focused, we use a simple scoring framework, RICE:

• Reach: How many people or decisions will this affect?

• Impact: How much could this improve trust, efficiency, or insight?

• Confidence: How well understood is the need?

• Effort: How much work will it take to deliver something meaningful?

This isn’t about chasing the highest score, it’s about framing a thoughtful, shared conversation. Your committee can discuss where initiatives land and why. That transparency helps get buy-in before anything is built.

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3. Be realistic about engagement

Prioritization isn’t just about value, it’s also about readiness.

Once you’ve surfaced a top initiative, ask:

Who on the business side has the capacity to engage in their initiative right now?

Be clear and up-front that this will require their time and energy because successful data work is co-created. If the business can’t partner with you during design and delivery, it’s probably not the right time, even if the idea is good.

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4. Align on your delivery model

We recommend working in 3-month delivery cycles.

Each quarter, you:

1. Choose one initiative to focus on

2. Partner with the business to design and build something useful

3. Report back to your committee with what was delivered and what you learned

That learning then informs your next round of prioritization.

This cycle keeps the work visible, energy high, lets your business partners see real progress, and ensures your roadmap stays dynamic, not dogmatic.

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Final Thought

Alignment isn’t a meeting. It’s a mechanism.

It keeps you honest. It keeps the work connected. And it makes sure that what gets built actually matters.

Because good ideas only create value when they’re delivered well and that starts with getting everyone aligned from the beginning.

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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.

👉 Book a strategy call

👉 Read more on the Fuse blog

👉 Follow Fuse Data on LinkedIn

👉 Follow Dave on LinkedIn