At a glance
Of every audit finding that landed on the Miro board in the last 90 days, the percentage that has been moved to the Done column. The headline number for “is the audit-board actually working as a delivery surface, or is it just collecting dust?” Pair it with the open count to grade the team’s flow: high open + low resolution rate is a queue forming; low open + high resolution rate is healthy clearance.
Calculation
Calculated automatically from your Miro data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading.Worked example
A UK fashion brand on Shopify has the Miro audit-board running for 4 months. Snapshot taken on 02 May 26. Trailing 90 days: 03 Feb 26 → 02 May 26 (89 days).
The team is closing all the criticals (good), most of the highs (acceptable), and roughly half the medium / low (typical). The composite 73% is an average dragged by the long tail.
What the merchant does: asks “is 64 created in 90 days the right intake?” Looking at the Throughput Trend, weekly closures are running at 4-5 per week (≈50/quarter). The intake of 64 is materially above closure capacity, which is why the rate sat at 73% instead of 85%. Two options: lift closure capacity (hire QA / shorten review loops), or lower intake (have the auto-dispatcher only push high+critical findings to Miro, route medium/low to a separate digest channel).
Compare to 30 days ago. Same store, snapshot on 02 Apr 26: rate was 81%, in the good band. The drop from 81% to 73% over a month traces to a redesign sprint that pulled the team off audit follow-up; expected behaviour, but the gauge lets the merchant SEE the cost of the deferral.
The dangerous reading: rate at 42% on a store with 30+ open findings. That is the “we cannot keep up” pattern, and the alert fires below 50%. By the time the rate is below 50%, the open count is usually compounding, the abandoned count is rising, and the team needs either a process intervention (capacity, scope, or both) or to disable auto-dispatch until they catch up.
Sibling cards merchants should reference together
Reconciling against the vendor’s own dashboard
Where to look in Miro’s own dashboard: Miro does not provide a native flow / cycle-time dashboard. The closest manual reconciliation is to filter the board by tag and inspect creation vs. last-modified dates over the last 90 days.Miro board → open the configured board → Tags panel →For most merchant teams the manual reconciliation is impractical (60+ cards with date filtering by hand), which is why this card exists. Why our number may legitimately differ from a manual count:vortexiq:finding→ Outline panel → sort bycreatedAtdescending → manually count cards in Done vs. cards not in Done across the trailing 90 days.
Cross-connector reconciliation:
Known limitations / merchant FAQs
Why is my rate stuck at exactly 100%? Three possibilities: (1) you have very few findings (e.g. 3 created in 90 days, 3 resolved); the rate looks great but the window is too thin to be meaningful, look at the absolute count of resolved findings instead. (2) Auto-dispatch is misconfigured and findings are not reaching the board; the denominator is artificially small. (3) The team is closing cards on creation as a workflow, which defeats the point of the audit-board. Check intake volume against the Throughput Trend sibling. Why is my rate exactly 0%? Either no closures in 90 days (the team has not engaged with the board) or the team uses a custom Done-state Vortex IQ does not recognise. Check the connector’sdone_column_id setting; the connector defaults to “rightmost column” but a hidden / collapsed column to the right can throw it off.
Does a re-opened card hurt my rate?
No. Re-opening does not subtract from the numerator; only forward closures count. Re-opening a card adds to the open count (which surfaces on Findings Open) but does not penalise this card. The reasoning: regressions are a separate phenomenon from closure discipline, and double-counting punishes the team unfairly when they correctly catch a regression.
The rate dropped from 80% to 65% but no individual finding changed status. What happened?
Window-edge effects. The 90-day window is rolling, so cards aged into the window or aged out of it. Specifically: if a closure happened on day 91 (just outside the window now) and a creation was on day 90 (just inside), the rate would drop without any active behaviour change. This is normal noise; look at week-over-week change rather than day-over-day.
Should I optimise this number directly?
No. Resolution rate is a downstream indicator, not a target. Optimising it directly leads to bad behaviour: closing cards without fixing the underlying issue, or refusing intake to keep the ratio healthy. Optimise throughput (more closures) and abandonment (fewer ignored cards) and the rate follows. Treating the rate as a target produces the dashboard equivalent of teaching to the test.
Why 90 days, not quarterly?
A rolling 90-day window updates daily; a quarterly window resets every 90 days and creates artificial cliffs. Rolling is fairer for spotting trends and avoids “end-of-quarter scramble” gaming. Practically, 90 days ≈ a quarter for benchmarking purposes.
My team uses Miro for ideation, not delivery. The findings are mostly low-priority brainstorm outputs. Does this card make sense?
Probably not, in that configuration. The audit-board pattern assumes the board is being USED as a delivery surface (cards represent committed work). If your Miro is a discovery whiteboard, the resolution rate is misleading because most cards are not meant to be “done” in the operational sense. In that case, route audit findings to a different surface (Jira, Linear, Asana) and keep Miro for ideation. The audit-routing settings let you turn off the Miro target while keeping Miro connected for other read-side cards.
A workshop generated 30 cards last week. They will all be tagged vortexiq:finding because the auto-tagger applied. Will my rate plummet?
Yes, in the short term. The 30 cards lift the denominator immediately; the closures lag by weeks. Expect the rate to drop 10-20 points within a week, recover over 4-8 weeks as closures catch up. The 90-day window is calibrated to absorb this kind of spike without false alerting in most cases. If the team runs many workshops, consider tagging workshop output with vortexiq:reference instead so it is excluded from the rate.
How does Vortex IQ know a card was created on the board “in the last 90 days”?
The Miro REST API exposes createdAt per item; the connector polls and persists this. The 90-day window is calculated against the current UTC time at request. If the connector was reconnected mid-window, only cards created since the connector’s first sync are guaranteed to be in the denominator (cards from before the reconnect may be missing if the original sync was incomplete).