How to measure success in your data and analytics programs.

In data and analytics, it’s common to hear things like:

"Will this sell more donuts?"

“This project will increase sales.”

“This dashboard will reduce churn.”

“This platform will drive efficiency.”

Maybe. But maybe not.

We don’t control market timing.

We don’t control competitor behaviour.

We don’t control what someone posts online.

Trying to directly tie a data initiative to a business KPI is tempting, but often misleading. You can support outcomes. You can influence them. But you can’t control them.

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So what can you measure?

At Fuse, we take a different approach.

We don’t try to own the outcome.

We try to own the conditions that make outcomes possible.

That means asking:

Can we make it easier for people to get the data they need?

Can we increase their confidence in what they see?

Can we reduce the time and effort it takes to act?

If the people using the tools are more effective, the business results will follow.

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What That Looks Like in Practice

In a recent engagement, we built a new sales analytics data product on Snowflake that focused on usability, trust, and speed.

Here’s what we measured:

• A 60% improvement in ease of accessing data

• A 23% increase in confidence in data quality

• A 16% increase in usefulness of insights

• 3 to 5 hours saved per person, per week

Those are real, tangible gains. And they’re a direct reflection of how we made life better for the people doing the work.

And what happened as a result?

Because the data was easier to access, more trusted, and made insights easier to discover, the client identified a major enterprise customer who was significantly underpaying compared to the market average.

That insight led to early negotiations — and an 85% increase in contract value on renewal.

Did the data project drive revenue? No.

It gave professionals the information they needed, to use their skills, to drive revenue.

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The Real Job of a Data Team

"Let figure out what you need and get we'll get it done!"

You don’t move the KPI.

You help the people who do.

Success doesn’t come from tools. It comes from what people do with them — and whether they’re set up to succeed.

So instead of asking, “Will this initiative drive revenue?”

Try asking, “Will this make someone’s job easier, faster, or more effective?”

Because that’s where the real impact lives.

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At Fuse, we believe in making data strategies real.

If you're ready to build for real impact, let’s talk.

👉 Book a strategy call

👉 Read more on the Fuse blog

Everyone Wants Self-Serve Analytics. Few Get It Right.

... but can you export to Excel?

Self-serve analytics is one of those goals that sounds universally good.

“Let’s give business users access to their own insights.”

“Let’s reduce the backlog for the data team.”

“Let’s unlock speed and scale.”

And on paper, it makes total sense.

So the company launches a shiny new dashboard.

There’s a rollout plan. Some training. A few cheers in the kickoff call.

And then… things get quiet.

The numbers don’t quite match what the execs expected.

The filters are confusing.

No one’s quite sure what “active customer” means.

A few weeks later, someone asks, “Can I export this to Excel?”

That’s usually when you know adoption isn’t going as planned.

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The problem isn’t the platform

We’ve got great tools. BI platforms have never been more polished or powerful.

But even the best tool won’t help if no one trusts the data or knows how to get what they need from it.

Here’s what we see all the time:

• If people don’t trust the numbers, they won’t use the tool.

• If it doesn’t answer real business questions, it’s just decoration.

• If it feels like work, they’ll find a workaround. (Spoiler: it’s usually Excel.)

And here’s the real issue:

Most self-serve tools are designed around the data, not the people who need to use it.

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What works instead

Start small. Pick a real problem, not a dashboard.

Work with the team that owns it.

Build something fast.

Make sure it actually gets used.

Then build from there.

Self-serve doesn’t fail because people don’t want it.

It fails because the design assumes too much and listens too little.

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At Fuse, we believe in making data strategy real.

If your self-serve effort has stalled or never quite landed, let’s talk.

👉 Book a strategy call

👉 Read more on the Fuse blog

Why Most Data Strategies Fail (And What To Do Instead)

You’ve Probably Seen This Before: The Challenges of Data Strategies

A company often spends months developing a data strategy. There’s a dedicated task force, numerous stakeholder interviews, and a detailed roadmap filled with hexagons and horizons. Some even create extensive presentations, leading you to wonder whether they aim to win a tender or block out sunlight.

Yet, despite all this effort, nothing changes.

Business users still struggle to get answers without constantly reaching out to a data analyst. The advanced BI tools are often reduced to glorified PDF exporters. As a result, everyone quietly returns to Excel.

Why does this happen?

1. The Strategy is Too Abstract

Most data strategies focus on future-state diagrams, maturity models, and so-called best practices. These elements can look impressive on paper, but they don’t address how users experience data challenges daily.

Your users don’t want a data lake; they simply want to stop waiting two weeks for a basic sales report.

If your strategy doesn’t address those pressing pain points, it will likely go unused.

2. It’s All Planning, No Doing

Many data strategies end up being deliverables disguised as plans. The focus shifts to “finishing the strategy” instead of genuinely “solving the problem.”

If your plan doesn’t empower anyone to improve their work within 30 days, interest will wane quickly.

3. Nobody Owns the Outcomes

Who is accountable for bringing the strategy to life? Often, the answer is nobody. Conversely, it might be everyone, which leads to a lack of accountability. Consequently, the strategy quietly fades into obscurity as other priorities take precedence.

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What to Do Instead

At Fuse Data, we take a different approach:

• Start with Pain. Identify what annoys your team right now.

  
  

• Solve Something Quickly. Focus on delivering a solution that shows immediate improvement.

  
  

• Build Momentum from Success. Leverage these wins to gain buy-in and encourage the team.

  
  

By following this method, your strategy transforms from a static document into a series of real, measurable wins that accumulate over time.

Stop the Cycle of Ineffective Strategies

Many companies fall into the trap of creating comprehensive plans without execution. This can lead to frustration within teams and ultimately hinder business growth. It's crucial to ensure that strategies are not only well-crafted but also actionable.

Engage Your Team

Encourage team collaboration throughout the strategy development process. When employees feel involved and heard, they are more likely to embrace the strategy and work towards its goals.

The Importance of Accountability

Establish clear roles and responsibilities. When someone is accountable for outcomes, the strategy is more likely to be executed effectively. This fosters a sense of ownership and commitment among team members.

Conclusion

If you find this resonates with you or if you have a strategy gathering dust on the shelf, let's talk. I offer a free 30-minute call to help get things unstuck.

Book a call to explore how we can get your data strategy back on track.

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