If you’ve ever built a dashboard that no one actually uses — this is for you.
It happens all the time.
And it usually has nothing to do with the data.
Most dashboards fail before they’re built because no one ever agreed on the decision the dashboard is supposed to support.
HERE’S THE UNIVERSAL DASHBOARD STORY:
Someone says they need a dashboard.
It’s urgent.
It’s critical.
The business is on fire without it.
So you build it.
You present it.
And then… nothing.
People open it once. Maybe twice.
Then they Slack you asking for the exact number sitting at the top of the first page.
This isn’t a you problem - it’s a no one agreed what this thing is supposed to do problem.
WHY DASHBOARDS ACTUALLY FAIL
Dashboards tend to fail for a few predictable reasons:
First: no one defined the decision the dashboard supports.
It usually starts with: “We just want visibility.”
Which sounds harmless, but really means: “We don’t know what we want, so give us everything.”
Second: the dashboard tries to serve too many audiences.
Leadership wants direction.
Marketing wants attribution.
Product wants engagement.
Finance wants revenue.
One dashboard cannot — and should not — do all of that.
Third: the kitchen sink problem.
Metrics get added “just in case.”
Suddenly there are 20 metrics in a single view — each with multiple filters — and the only person who can interpret the dashboard is the person who built it.
THE FIX: DECISION-LED DASHBOARD DESIGN
The fix is simple — dashboards should be designed around decisions, not data.
Most teams start from “What data do we have?”
High-performing teams start from “What decision do we need to make?”
Here’s what this actually looks like in practice:
1. Define the decision first
What decision is this dashboard meant to drive — repeatedly?
Not “What metrics should we include?”
Not “What data do we have?”
Examples:
Should we increase or decrease spend?
Should we shift resources to a different channel?
Should we invest more heavily in a specific product, creator, or feature?
Are we pacing ahead or behind plan?
If you can’t articulate the decision, you’re not ready to build.
2. Define the real audience and primary user
Dashboards built for “everyone” end up serving no one.
Pick one audience — maybe two — and treat them like the customer.
Who actually feels the pain when this information is missing?
Who will take action based on what they see?
If the answer is “technically anyone,” you don’t have an audience.
3. Identify the minimum set of metrics required
Minimum is doing a lot of work here.
Your job is to strip the dashboard down to:
The metrics that directly answer the decision
The diagnostics someone would check if that decision swings
Everything else is noise.
4. Define what “good” looks like
A dashboard without context forces people to guess.
Flat numbers mean nothing without targets, ranges, benchmarks, or expectations.
Without that context, you get Slack messages like:
“Is 7% good?”
“Should I be worried about this?”
Tell people where they stand.
5. Make sure it enables clear action
After someone looks at the dashboard, what should they be able to do immediately?
Increase spend?
Pull back budget?
Flag something?
Kick off an experiment?
If the user can’t answer “So what?” in one sentence, the design isn’t done.
WHEN DASHBOARDS ARE DECISION-LED, EVERYTHING GETS EASIER
Teams make decisions faster.
Leaders stop pinging analytics for numbers that already exist.
Analysts stop maintaining dashboards no one cares about.
Clarity replaces chaos.
Dashboards work when decisions drive the design — not the other way around.
If you want help applying this, I put together a free decision-first dashboard outline you can download.
It walks through defining the decision, scoping the metrics, and avoiding the kitchen-sink trap.
You’ll find the link here: https://thedatadrop.beehiiv.com/products/dashboard-requirements-worksheet
More soon.
- Michelle