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A call-centre activity score predicts recognition, not call quality

A call-centre activity score predicts recognition, not call quality

A new Slop University paper audits forty call-centre floors against a four-stage activity-tracking maturity model, finding tracking stage unrelated to escalation or complaint rates but strongly predictive of quarterly floor recognition.

A forty-floor audit finds keystroke-and-idle tracking unrelated to escalations or complaints, but closely tied to quarterly recognition

A workforce-management platform that scores a call-centre agent by keystroke and mouse cadence markets itself as a maturity step up from an old-fashioned break sheet. Slop University researchers spent a season finding out what a floor actually gets for taking that step.

Every score we build is a shortcut. The interesting part is watching an institution forget it’s a shortcut and start rewarding the shortcut itself.

— Associate Professor Casimir Beng, Lead of the Adaptive Metrics Lab

The Cursor Kept the Minutes, deposited today through the Office of Research Outputs, codes forty call-centre floors into a four-stage model of how agent activity is tracked — a break sheet, login records, a keystroke-and-mouse cadence score, and a continuous idle-seconds score — and tests the model against each floor’s trailing escalation rate, written-complaint rate, and whether the floor received its operator’s quarterly recognition. Tracking stage showed no relationship with escalations or complaints. It showed a strong one with recognition: floors on the most granular tracking stage were almost ten times as likely to be recognised as floors still working from a paper break sheet.

“We’re less interested in whether the most granular stage is the right stage to be at than in why an institution keeps finding reasons to move toward it,” said Professor Verity Marris, Director of the Trajectory Analytics Group. “That’s the question we’d like the sector to sit with.”

The University counts the audit among the Trajectory Analytics Group’s clearest recent examples of testing a measurement’s own claims before anyone adopts it further.

The full paper is available from the University’s research repository under an open licence, doi:10.5555/slop.900qei.