Screening flags responses that look careless or inconsistent — internal contradictions, duplicate submissions, very low self-rated confidence, thin coverage, and (once you have ~30 reads of one instrument) statistical outliers. Flagged runs are set aside from group averages; nothing is deleted, and an admin can re-include any run. It’s most meaningful once a cohort is large enough to compare against.
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How has it moved?
Repeated reads on the same instrument, plotted by when they were taken. The line is observed history — not a forecast.
A trend needs two or more promoted reads of the same diagnostic on the same unit.
Where does it sit, unit by unit?
The most recent read of one instrument, compared across the business units that have taken it.
How do the four instruments compare?
The most recent promoted read on each diagnostic, side by side.
Do the levels see it the same way?
The same instrument read from the front line, management, and the executive seat. Divergence between them is the signal.
Where do you stand against peers?
Each instrument's most recent read, placed against the sector benchmark it reported.
Did the change return capacity?
A before reading paired with an after reading on the same instrument, around a deliberate change. The delta is observed, not projected.
Before/after pairs require two promoted runs of the same diagnostic on the same unit; the second read closes the loop.
Combine reads into one executive picture
Select two or more promoted reads — across instruments, units, or campaigns — and Monderman combines them into one cross-diagnostic read with its own executive report.
Synthesis needs at least two promoted reads. Reads set aside by data-quality screening are excluded automatically.