Dashboard KPIs often look cleanâbut that doesnât mean theyâre correct. Most business But if you dig beneath the surface, youâll often find that the KPIs driving decisions are based on flawed assumptions, outdated filters, or quietly broken logic.
In large organizations, this isnât just a reporting issueâitâs a strategic risk. Misleading KPIs distort performance, influence roadmaps, and misallocate budget.
This post outlines why dashboard KPIs often become inaccurate, the common KPI mistakes analysts and stakeholders make, and how to fix them before they erode trust in your data.
When âCleanâ Isnât Correct
At some point, every digital analyst has inherited a dashboard where the numbers donât fully add up. Conversion rates that look suspiciously high. Traffic that doesnât match backend logs. KPIs that havenât been revalidated since the last redesign.
These are not just minor issuesâtheyâre signs of KPI drift.
KPI drift happens when:
- Filters are applied and never reviewed
- Business logic changes, but data pipelines donât
- Metrics are reused out of context
- Exclusions are baked in, then forgotten
Real-World Examples of Dashboard KPI Drift
1. Revenue Attribution Gaps
A dashboard shows 10% growth in revenue from paid channels. But refunds, cancellations, or upsell flows hosted on other domains are excluded. The business celebrates a gain that doesnât exist in net revenue.
2. Misleading Conversion Rates
Marketing reports a 20% increase in conversion. You later discover the session count dropped due to changes in tracking or consent logicâso the denominator shrank, not the performance improved.
3. Legacy Filters Hiding Traffic
The dashboard was originally scoped to track www.site.com, but post-purchase upsells now occur on shop.site.com, which isnât included in the data model. A major revenue stream goes unseen.
The Cost of Broken KPIs
- Strategic misalignment: Teams chase the wrong goals.
- Loss of trust: Business leaders stop believing the numbers.
- Rework overload: Analysts spend more time fixing dashboards than driving insight.
These are not technical problemsâthey are communication and ownership problems.
How to Fix KPI Mistakes (and Prevent New Ones)
Hereâs a practical framework to restore trust in your dashboard metrics.
1. Re-document Every KPI
Make the business definition explicit:
- What is the metric measuring?
- Which events, users, or products are included or excluded?
- What data source is it based on?
2. Create âKPI Contractsâ
Establish shared definitions across teams. A KPI contract should define:
- Metric name
- Calculation logic
- Data source
- Owner
- Review cadence
3. Embed Assumptions in the Dashboard
Don’t bury context in a PDF or a Jira ticket. Add tooltip notes, expandable âinfoâ icons, or embedded documentation to dashboards.
If your metric only includes mobile traffic, say so directly on the chart.
4. Set Review Cadences
Review key KPIs quarterly or when:
- Thereâs a product flow or domain change
- A new tracking schema is released
- A stakeholder questions the data
5. Create âRaw vs KPIâ Audit Views
Maintain a view that compares raw data vs cleaned KPIs so analysts can:
- Spot gaps
- Explain discrepancies
- Validate transformations
Final Thought
A KPI is only as reliable as the logic behind itâand that logic needs to evolve as your business evolves.
As an analyst, your role isnât to just âreport the number.â Itâs to defend the number. And that means building transparent, explainable, and regularly reviewed metrics that teams can truly trust.
Donât just publish dashboards. Audit your KPIs, expose assumptions, and lead the conversation around what your business is really measuring.
- Check out my new Add-on for Google Tag Manager Audit here
- Check out my Looker Studio Course hereÂ
- Check out my Measurment Plan course here
