And what it’s quietly costing your business every single day
“If you torture the data long enough, it will confess to anything.”
The illusion of visibility
Two kinds of creators—and one missing
- Data engineers: focused on pipelines, structure, and source systems.
- Data analysts/BI developers: focused on metrics, correctness, and basic visuals.
In a 2024 internal survey across 17 mid-market firms, only 12%
Suspect your dashboards are confusing, not clarifying?
When your dashboard gets replaced by a spreadsheet
Here’s the brutal litmus test for any dashboard:
“If the user says: Can you just give me the table instead?"
- In SaaS: A growth PM looking at MRR cohorts can’t see churn patterns due to stacked area charts cluttering the page. She exports raw data to Excel and manually compares monthly deltas.
- In e-commerce: A head of performance marketing is presented with a 12-chart dashboard showing CTR, ROAS, CPC, CPA—but none of them tell him why conversions dropped this week. He calls the analyst.
- In manufacturing: A plant manager sees machine downtime metrics by unit, line, and shift—but they’re buried in a spaghetti of bar charts and slicers. He asks for a CSV dump.
Dashboards as a decision interface
- It must highlight signals, not just show data.
- It must help users prioritize what matters.
- It must guide users toward action.
“Data isn’t scarce. Attention is."
Want to know which of your dashboards drive decisions—and which waste attention?
How good BI systems really work
One-slide focus mode
The most effective dashboards don’t show 15 charts per screen. They show one insight at a time, with signal detection, context, and options for drill-down.
Signal → Insight → Action
- In SaaS: “Conversion to paid dropped from 5.2% to 3.9% this week.”→ click to segment → reveal drop in mobile traffic → test mobile signup fix.
- In e-commerce: “Email revenue contribution fell by 27% MoM.”→ trace to deliverability issue → notify CRM team.
- In manufacturing: “Line 4 shows a 19% increase in idle time.”→ drill to operator shifts → identify root cause in handoff timing.
Why analysts can’t (and shouldn’t) do it all
Most analysts are under time pressure, focused on the mechanics: queries, models, calculations. Asking them to also design decision-ready interfaces is like expecting your backend engineer to lead your product design.
Only 2% of mid-level managers
So dashboards end up optimized for correctness—not clarity. For completeness—not usability.
Not sure if your dashboards are helping or hindering your team?
Think like an architect, not just a builder
- Data engineers are the structural engineers.
- BI developers are the builders and electricians.
- But without an architect—someone who designs for flow, comfort, and use—you end up with a house that’s technically sound, but hell to live in.
“Most dashboards are built by people who know how to lay bricks. But nobody draws the floor plan.”
What next?
- Audit your dashboards: Find out where your users get confused, fatigued, or export to Excel.
- Bring in design expertise: Not to “make it pretty”, but to make it usable.
- Treat BI as product: Apply product thinking—iterate, measure usage, and improve over time.