A Guide For Business Leads to Win in Data and Analytics

By Fiona Gordon & Sarah Burnett  | Co-Founders, Dub Dub Data

There’s a quiet gap in many organisations - a disconnect between the people leading the business and the ones unpacking its data.

Data teams often feel like they’re working in the shadows, translating ambiguity into insight, while simultaneously navigating unrealistic expectations, shifting priorities, and the eternal quest for “just one dashboard that does it all.” Meanwhile, executives are frustrated by what feels like slow delivery, unclear outputs, or insights that don’t match their gut instincts, not to mention that the data teams speak a foreign language!

This blog is for management, senior leaders or the c-suite, who want to bridge that gap.

It’s a candid look behind the scenes of how data teams actually work - and what they wish more leaders understood. From uncomfortable truths to governance woes, from design trade-offs to team chemistry, we’re pulling back the organisation's curtain.

Because when leaders and data teams develop in partnership - not opposition - that’s when real magic happens. Insight lands. Strategies evolve. And the business gets faster, sharper, and smarter.

Let’s demystify the data world, one truth at a time.

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We’ve dedicated an episode of our unDUBBED podcast to What Data Teams Wish Non-Tech Leaders Knew. Skip the scroll and view here. 

The Myth of the Unicorn Data and Analytics Resource

While working in organisations we often heard: “Just find a great data person - they can do it all.”

Spoiler: they can’t. And they shouldn’t (unless you’re prepared for things to take longer or you're paying unicorn rates).

Modern data work spans engineers, analysts, architects, visual designers, storytellers - each with a distinct role to play. Expecting one person to do all of it isn’t heroic. It’s a recipe for burnout and mediocre outcomes, or it's time to up your budget and find someone who has spent the time to hone their skills across data specialties. 

We’ve seen technically brilliant teams completely miss the mark - purely because they didn’t have someone to make the work land. Then, with the addition of a design-savvy analyst or a compelling storyteller, suddenly they could advance when message finally cut through. The insight hadn’t changed - the delivery had.

Build data ecosystems, not unicorns.

It’s the interplay of complementary skills that brings data to life and drives adoption.

Data Governance: An Unsexy Tool for Sanity

If there’s one piece of a data project that feels like overkill - but saves your bacon later - it’s data governance.

Things like naming conventions, documentation, standards, even how we capture our data… they don’t feel urgent. So leaders say, “Can’t we just ship it now and tidy it later?”

Here’s the reality: activities you call overhead today becomes tech debt tomorrow. And not the manageable kind. We’ve inherited dashboards so chaotic - fields named calc_abc_test123_vFinal - that no one wanted to touch. They were fragile beasts, riddled with risk, and weeks were wasted trying to untangle what could’ve been prevented with 30 minutes of planning.

Data Governance isn’t glamourous but it's a non-negotiable.

Like insurance, it feels optional - until it’s not. Bake in some time to your program delivery that includes governance measures and use it to your advantage. Don't skip the stuff that will save you later.

Leadership Demanding Fast Now, will be Slow Forever

Everyone loves a quick fix. Until it costs you three times as much later.

We’ve seen bandaid or MVP solutions duct-taped together to hit a deadline, without time to go back and make them fully robust. They often run ok at first, but since they haven't been optimise they get slower and slower. Time goes by, the responsible analyst to moves on, leaving behind a mysterious black box that no one dares open, but the product is running like a dog. No testing. No documentation. Just fear.

These kinds of shortcuts might save an hour today, but they’ll rob you of weeks later. The smarter path? Build it right. Even if it takes a touch longer.

Abandon the Band-Aid Fixes

Every leader or manager requires teams to work efficiently, but the challenge in data, fast now often means slow forever. By being strategic and spending a little extra time up front, can save a whole lot of headaches in the future.

Hiring Talent is not Just About Skills

“Just get competent data people,” some say. “We just need someone now!”

Hiring for technical capability is great, but every hire has the opportunity to undermine your culture.

Data work isn’t just about the technical chops - it’s about how people think, communicate, adapt, and collaborate. It’s messy. It’s ambiguous. It changes weekly. And when things get murky (which they inevitably do), you want a team that feels like partners, not just people ticking boxes.

We’ve walked into environments with high IQs but zero EQ - friction, fiefdoms, awkward silences. Smart work that never landed. By contrast, when we’re brought in as collaborators - not vendors - the vibe changes. Trust flows. Ideas bounce. Progress speeds up.

Hiring for Culture Fit

Skills are baseline. Culture is the multiplier. And delivery? That’s where the two collide. Whether you’re hiring consultants or building your internal teams, the importance of fit becomes crucial. If someone doesn’t vibe with your culture, even the smartest operators can derail the momentum. That’s when wheels start wobbling - and eventually fall off.

Data Teams Aren't The Enemy. They're Your Debugging Buddy.

This one gets to the heart of it: the belief that when the metrics look wrong, someone must have stuffed up.

But more often than not, anomalies stem from upstream quirks - timing delays, input errors, misaligned definitions. It’s rarely sabotage. Usually it’s just... complexity.

Data teams have analytics initiatives thrown back at them like grenades, "THE DATA IS WRONG!!" only to discover the issue was a typo on data entry, or a misunderstanding in terminology. A conversation could’ve solved it. Instead, it causes defensiveness and delay.

What do Data Teams Want?

So here’s what data teams are saying: "Please don’t lob grenades. Start a dialogue with us."

You're the principal customer, adjust your approach. Tell them what seems off. What you expected. Debug the truth together.

Because they're not opponents. They're partners in clarity.

Embracing the Iterative Nature of Data

One of the biggest misconceptions is that data work is linear - that if you plan it right, it’ll succeed on the first go.

Reality check: data is iterative by nature. Priorities shift. New requirements emerge. Assumptions get tested (and broken).

Good teams embrace that. They launch earlier, iterate faster, and improve continuously for effective results.

Scope in Time for Change

Data isn’t “one and done.” It’s “test, learn and refine.” It's essential for you to budget for that - mentally and financially.

Clarity Isn’t An Accidental Technique

Simplicity is often mistaken for speed. But crafting a dashboard that’s clear, meaningful, and impactful? That takes time, skill, and a heap of hard trade-offs.

Expert data teams aren't just throwing some charts on a canvas. They're thinking deeply about your audience, your decisions, your context.

Avoid Dashboards That Resemble a Jackson Pollock Painting

Simplicity is a discipline. And clarity doesn’t happen by chance - it’s a design choice.

One Dashboard to Rule Them All? Nope.

Another common trap: thinking one dashboard can serve every stakeholder.

Catch-all dashboards become bloated, slow, and vague. No one loves them. No one uses them.

Targeted Information Improves Adoption

A better approach? Break dashboards into persona-specific tiers. Align each to a clear decision or action. Make it obvious who it’s for and what it’s for, and simplify the dashboard.

Less really is more. That’s how you drive usage - and trust.

Invisible Wins Deserve the Company Spotlight

Here’s the paradox: when data systems don’t break, no one notices.

But when they fail? Cue the fire drill.

Celebrations Fuel Motivation

The quiet success of a seamless system often goes uncelebrated. But it’s those invisible wins that power the business. So spotlight them. Encourage your teams to track and communicate ROI, even when everything’s humming along.

Recognition fuels motivation. Don’t wait for a breakdown to say thanks.

Training Isn’t a Perk. It’s a Power Move.

Too many leaders see training as optional - a luxury.

But the stats tell a different story. We’ve seen data teams with strong training cultures show dramatically lower attrition. One of our clients clocked just 7.8% attrition in a year - compared to an industry norm of 35%.

Reducing Attrition

How can you dramatically reduce attrition? Invest in your people.

Training isn’t BS. It’s the foundation of speed, quality, and retention. Treat it like the strategy it is.

Communication Isn’t Just Style - It’s Survival

Let’s be real: data professionals and business leaders often speak different languages.

One side loves nuance and detail. The other wants clarity and action - now.

Misunderstandings happen. Expectations misfire. And momentum suffers.

Solution for Communication Between Leaders & Data Teams

Mutual adaptation. Data teams need to summarise more effectively. Leaders need to get curious about the tech side. AI might just become the translator we’ve all been craving - if it stops hallucinating.

Find the middle ground. That’s where the magic happens.

Data Leadership when you're a Business Lead

If this all sounds familiar, you’re not alone. Data isn’t just a technical game - it’s a cultural one. And when we stop treating it like a war of truths and start seeing it as a shared pursuit of clarity, there's a spark that creates the best data relationships.

Want a team that brings the whole picture, not just pretty charts? We might just be your people.

Let’s roll up our sleeves and debug the truth - together.  Email us - [email protected] 

 - Fi & Sarah
Co-Founders, Dub Dub Data

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Episode Summary

In this episode of unDUBBED, Sarah and Fi discuss the essential insights that non-data leaders should understand about data teams. They explore the evolving nature of data projects, the importance of clarity in dashboards, the misconception of dashboards as a comprehensive solution, the often invisible success of data teams, and the critical role of training in retaining talent and enhancing performance.

Takeaways 

• Data projects require ongoing iteration and adaptation.
• Clarity in dashboards is a result of thoughtful design.
• Leaders should share the impact of data products with the teams who delivered them
• Give time to teams to analyse the ROI of data products 
• If something looks off, set up a call to discuss the data miss, it may be a source system error
• Dashboards should serve specific strategies, not be catch-alls.
• Data teams often work invisibly, yet their efforts are crucial.
• Training is a strategic investment that enhances team performance.

Chapters

 00:00 Welcome to unDUBBED

04:04 Data Projects Are Hardly Ever One and Done

07:41 The Simplest Requests are Sometimes the Hardest to Deliver

10:21 The Invisible Success of Data Teams

11:24 One Product To Rule Them All = A Disaster Waiting to Happen

14:30 Recognising when there aren't any issues

18:10 The Role of Communication Between Data and Business

20:59 Training Helps You to Retain People and Keep IP

25:44 Data People and Business Leaders Speak Different Languages

29:59 Unscheduled Interruption and Podcast Wrap-Up

30:27 Building Bridges Between Data Teams and Leaders

31:55 Closing Thoughts and Future Engagement