Even highly capable BI professionals often struggle to be seen as strategic partners rather than task-takers. Building technically sound dashboards isn't enough — credibility is about aligning with business goals, communicating clearly, and owning outcomes.

Here are five common behaviors that erode trust — and what to do instead to elevate your role and influence.

🚫 #1: Taking Orders Instead of Solving Problems

When you fulfill BI requests without understanding the underlying business question, you risk building something irrelevant—or worse, missing a chance to drive impact.

If a stakeholder asks, "Can you just give me the data?", there's a high chance they plan to build their own spreadsheet, dashboard, or logic on top of it. And that's a red flag. If they're going to build something anyway—why shouldn't it be you?

I had a marketing manager request "all campaign data from the last six months." Instead of delivering a CSV file, I asked what she was trying to figure out. She needed to identify which campaigns drove the most qualified leads, not just clicks. We built a campaign performance dashboard that became her primary tool for budget planning. If I'd just provided raw data, she would have spent hours in Excel, and I would have missed creating something useful.

✅ Fix it: Ask Better Questions

• "What decision are you trying to make with this?"

• "What would success look like if we solved this?"

• "What are you going to do based on the numbers you get?"

These questions transform you from a data provider into a strategic partner.

🚫 #2: Reporting Everything, Highlighting Nothing

Too many dashboards are cluttered, filter-heavy, and directionless. When everything is shown, nothing stands out—and that means your insights are invisible.

I've seen dashboards with 47 different filters and no indication of what users should focus on. Sales managers had to click through dozens of combinations just to determine if they were hitting quarterly targets.

✅ Fix it: Design for Decision-Making

• Start with the takeaway: What's the one thing they need to know?

• Use clear layout, bold labels, and visual hierarchy to guide the eye

• Use color intentionally — not decoratively

  • Highlight what's important (change, exceptions, targets missed)

  • Avoid rainbow palettes that hide meaning

• Don't bury insights in tabs or tooltips. Make them obvious and actionable

Your dashboard should have a clear focal point.

🚫 #3: Ignoring Data Quality

Nothing undermines your work faster than a stakeholder asking: "Are these numbers even right?" If your dashboards are powered by incomplete, inconsistent, or stale data, people stop trusting you—not just the data.

Many BI teams fix quality issues reactively, long after damage is done. Picture a quarterly business review where the CEO examines your dashboard and the CFO says, "These revenue numbers don't match our ERP system." The awkward silence that follows means they'll question your dashboards for important decisions.

✅ Fix it: Own Data Quality Like a Product

• Proactively monitor critical tables and metrics (freshness, completeness, volume, schema changes)

• Set up alerts and validation checks

• Show the last updated date clearly in your dashboard to set expectations

• Build a "known issues" banner or notes section in dashboards. Transparency builds trust

• If data is broken, communicate it early. Taking accountability earns credibility

Data quality isn't "someone else's job." If it affects trust in your output, it's yours.

You can at least add a "data freshness" indicator to every dashboard—green for current, red for stale. This simple addition prevents "are these numbers current?" conversations.

🚫 #4: Hiding Behind Tools and Technicalities

Common conversation:

Stakeholder: "Can we create a waterfall chart to show how we went from last quarter's revenue to this quarter's?"

BI Developer: "Well, Tableau doesn't have native waterfall functionality, and we'd need to create calculated fields for running sums with table calculations, but our data structure has multiple dimension hierarchies that complicate the development..."

Stakeholder: [confused] "So... is that a no?"

✅ Fix it: Lead with Possibilities, Not Barriers

• Instead of “We can’t do that,” try: “Here’s what we can do and what trade-offs look like.”

• Do the research. Sometimes “not possible” just means “we haven’t tried yet.”

• Focus on problem-solving, not just tool configuration.

Stakeholders aren’t clueless—they can handle some technical detail, as long as you keep it clear and to the point. If you're unsure about the best technical approach, it's totally fine to take time to research it and follow up with a confident solution.

This also applies to how you communicate. Don’t lead with technical jargon—speak the language of impact.

🚫 #5: Explaining in Tech, Not Business

BI professionals often fall into the trap of explaining how something was built instead of what it means. Talking about joins, filters, or dbt models might impress other analysts—but to stakeholders, it sounds like noise.

BI Developer: “This chart uses a rolling 28-day average from our revenue model, adjusted with a parameter that filters the cohort by activation event and segments based on our retention logic.”

Marketing Director: “Cool... but is performance trending up or down?”

✅ Fix it: Tell the Story, Not the Stack

• Frame insights in business terms: "This decrease aligns with our new pricing rollout"

• Connect numbers to goals: "This trend impacts our Q3 retention target"

• Practice storytelling. Use clear language to explain complexity

I sometimes go too deep into the details of the calculations, and one thing I’ve learned is to start with something very simple—like what the metric means at a high level. If they ask about the computation, then explain. Great BI professionals aren't just fluent in SQL and calculations—they're fluent in the language of the business.

Conclusion

The difference between order-takers and strategic partners isn't technical skill—it's understanding that your job isn't building dashboards, it's driving better decisions. When you ask the right questions, design for clarity, own data quality, focus on solutions, and speak in business terms, you transform from a technical resource into an indispensable strategic partner.

When stakeholders start bringing you their biggest challenges instead of their smallest data requests, you know you've made it.