COACH’ S CORNER
BY MARK PEREIRA
ILLUSTRATION PROVIDED BY ADOBE STOCK
TURNING QA DATA INTO INSIGHTS HOW THEY CAN HELP CONTACT CENTERS.
Performance doesn ' t improve by accident. It improves when organizations take a disciplined approach to measuring real behaviors in interactions and use those insights to understand trends that drive coaching, training, and change.
Tracking individual call evaluations by memory— or by pen and paper— quickly becomes overwhelming, especially when quality assurance( QA) analysts are responsible for weekly or monthly quotas across 30, 40, or even 50 agents.
With most agents receiving six to eight evaluations per month, that workload adds up fast: a 40-agent team can easily generate nearly 300 QA reviews in a single month.
One call doesn ' t tell the story. Multiple evaluations reveal patterns: separating occasional mistakes from consistent behaviors and creating targeted coaching opportunities, such as improving call control to reduce average handle time( AHT)( also see my three-part series on AHT in the May, June, and July issues).
When analysts are moving from call to call and score to score at that volume, it becomes difficult to see patterns over time. Like:
•“ Why was Susie marked down for call authentication this week and was it the same issue she missed last time?“
•“ Why did Pat fail two evaluations for reasons that seem unrelated on the surface?”
Without structure, those answers get lost while QA data stays fragmented and becomes guesswork. And fragmented data rarely leads to meaningful improvements: if any at all.
As one principle has consistently proven true in call centers: QA data doesn ' t fail organization. What fails is treating it as a scorecard instead of a signal.
NOVEMBER 2026 15