MACC Collection Dashboard

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Data Collection Operations Dashboard
Collection volume, workforce and coverage — derived from the us-data-center capture bucket
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Total Collection Trend collection hours per period

Collection hours Episodes

Collector Ranking by collection hours

Breakdown

Processing Pipeline hours through each workflow node, first capture to delivery — the bar shrinks where hours fail or queue upstream

Succeeded Queued / running Failed

Auto-check Rejections why the checker rejected work · "-" means the checker recorded no reason

ReasonEpisodes ShareHours

Collector Data Table click a collector for their detail

Ramp-plan export: a person counts as a Training Operator on the days within 3 days of their first capture, and as a collector from then on — judged as of each row's date, not by their classification today, so days already exported keep the same split when the file is regenerated later. This differs from the page's trainee/collector filter, which classifies people by their current lifetime figures.
Collector Hours collected Hours passed human QC Human QC pass rate Days collected On programme Avg / collection day Avg / calendar day Days active Episodes Avg episodeDevicesTasks Data volumeLast capture

Individual Collector Detail uses the same filters as the overview

Select a collector to view details.

Classification where the line between trainee and collector sits

lifetime hours and days on programme
A collector clears both bars; anyone under either one is still a trainee. Days on programme is the last capture date minus the first — how long they have been doing this, not how many days they worked, which is the separate Days collected column in the table above. Somebody who captured on the 10th and the 14th spans 4 days having collected on 2. It counts whole calendar days rather than elapsed hours, so the 10th to the 13th is 3 whatever time of day they worked, and the bar is inclusive. Measured on the capture site's calendar, so the timezone selector cannot promote anyone.
This is a shared setting, not a filter — changing it changes what everyone sees. Both figures are measured over all the data, never the selected date range, so moving a line reclassifies people permanently rather than for this view. Failed recordings never count towards either, and never start anybody's clock. Set days to 0 to switch that bar off and classify on hours alone.