Here’s something I see happen all the time in Tableau:
An analyst spends hours building a dashboard.
They want it to look sophisticated and impressive.
And instead of just showing what the data means, they reach for something complex: loads of filters, charts packed together, color everywhere.
And they wonder why nobody actually uses it.
Most of the time, the issue isn’t their Tableau ability.
The problem is almost always that they’re optimizing for “impressive” when what viewers actually need is “clear.”
So in today’s newsletter, we’re going to cover:
- Why trying to look impressive is actually killing your dashboard’s impact
- 4 tips to communicate clearly in every dashboard you build
- Concrete examples you can steal and apply today
Let’s dive in.
The #1 mistake Tableau analysts make
Most people think they understand what a great dashboard looks like.
But what they build say otherwise.
Tableau analysts are notorious for saying:
“I want my audience to immediately understand the story in this data…”
And then they cram 14 charts onto a single view.
For example, we recently saw a dashboard that had:
- A title that said “Business Performance Overview”
- Three different color scales used across five charts
- Filters stacked along both sides
- A table at the bottom with 30 columns
WHAT ARE WE SUPPOSED TO DO WITH THIS?!
It has become an epidemic. Analysts optimizing for “impressive” instead of clear.
Here’s why it happens:
- They think complexity signals expertise.
- They believe the viewer will explore every part of the dashboard and find the insight themselves.
- They assume more = more valuable.
All of these are wrong.
Imagine you’re an executive opening a dashboard during a 10-minute gap between meetings.
You need one answer. Fast.
Except every dashboard in your inbox looks like a cockpit.
At first, you try to engage.
Then after clicking through three dashboards like this, you stop opening them.
“Just tell me the number. Tell me if it’s good or bad. Tell me what to do.”
This is exactly what happens every time someone opens your dashboard, glances at your viz, or tries to use the report you spent two weeks building.
So here’s a good rule of thumb:
If the viewer has to work to find the point, you’ve already lost them.
Nothing kills a dashboard’s impact faster than the trying to look smart instead of being useful.
Remember that.
Tip #1: Be clear about the question.
The very first thing your dashboard needs to communicate is: what question does this answer?
It doesn’t matter how beautiful the dashboard is. Your viewer needs to know what they’re looking at before they can rely on it.
Are you showing:
- Revenue or revenue vs. target?
- Customers or new customers vs. returning customers?
- Sales volume or sales velocity?
- Overall performance or performance by region?
Notice how this subtely completely changes how you read the data.
Before anyone can trust your dashboard, they need to know what question it was designed to answer.
One question. One dashboard. That’s the goal.
Tip #2: Be clear about what “bad” looks like.
The second thing you need to communicate is: what does a problem look like here?
- What’s the threshold that triggers concern?
- Is this metric trending the right direction?
- Has anyone tried to fix this before?
- Why does it matter if it’s off?
Viewers don’t care about numbers by themselves.
They only care once they understand the context: what’s normal, what’s not, and what’s at risk.
Don’t just show them a line going up.
Tell them whether up is good or bad. Show them the target. Add the reference line. Make “trouble” impossible to miss.
Tip #3: Be clear about what to do.
“We surface cross-functional KPIs to enable data-driven decision-making across stakeholder groups.”
Huh???
That’s dashboard-speak for: we don’t know what action this is supposed to drive.
Instead: Here’s what’s behind. Here’s why. Here’s what needs attention this week.
That's better! Phew!
A great exercise: try to write the one-sentence action your dashboard is designed to trigger.
If you can’t write it in one sentence, your dashboard doesn’t have a point yet.
Tip #4: Be clear about the transformation.
Give your viewer a complete story arc:
- [Where they start] — what situation are they walking into?
- [The problem] — what’s off, and why does it matter?
- [The answer] — what does the data tell them?
- [What’s next] — what should they do now?
Stakeholders don’t open dashboards because they love data.
They open them because they need to make a decision.
So don’t make them guess. Walk them from question to answer in as few clicks as possible. If someone can’t follow the story in 30 seconds, start over.
For example:
- Question: Are we hitting our Q2 sales targets by region?
- Problem: Three regions are trending 15% below goal
- Answer: The Southeast drop started in Week 6 and correlates with rep turnover
- Next step: Flag for sales leadership by Friday
That’s a dashboard with a purpose. That’s a dashboard people use.
That’s a wrap.
Build dashboards people actually open, not dashboards that impress other analysts.
If you want to go deeper on building dashboards that communicate at the highest level, that’s exactly what we do inside Next-Level Tableau.
Live sessions. Real feedback. Training that closes the gap between where you are and where you want to be.
Join Next-Level Tableau →
– Andy
P.S. If you want to see what "clear over impressive" looks like at the highest level, join us at NLT Live — a free, 5-hour virtual conference built by analysts, for analysts. 15+ speakers. Real work. No fluff. Save your spot → https://www.nextleveltableau.com/live