Most dashboards are confidently wrong
The number a business quotes in meetings is usually the one nobody has checked.
What happened
User metrics are not additive, category buckets are rarely exhaustive, and almost nobody reconciles the figure against the provider’s own interface. The number a business quotes in meetings is usually the one nobody has checked.
What changed
Every metric we ship is reconciled against the source platform before launch, and buckets are made exhaustive by construction so totals cannot silently drift. If a figure cannot be traced back to a source, it does not go on the dashboard.
Dashboards fail quietly. Nothing errors, no alert fires, and the chart renders. The number is simply wrong, and because it is presented with the same confidence as a correct one, it gets quoted in meetings and acted on.
The most common cause is treating a non-additive metric as additive. Unique users for January plus unique users for February is not unique users for the two months — anyone who visited in both is counted twice. Almost every analytics API will happily return both figures and will not warn you that summing them is meaningless.
The second is buckets that are not exhaustive. A traffic breakdown by channel that lists organic, paid, social and referral will quietly drop anything that does not match, so the parts do not sum to the whole and nobody notices because the chart still looks reasonable.
The third is that almost nobody checks the figure against the platform it came from. Open the provider’s own interface, run the same date range, and compare. When the two disagree, one of them is wrong, and finding out which is the entire job.
None of this requires clever tooling. It requires reconciling before launch and refusing to ship a figure whose provenance you cannot trace. A dashboard that shows fewer numbers you trust is worth more than one showing many you do not.