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The spreadsheet is not the problem

It is a perfectly good scorecard. The problem is the sample size a human reviewer forces on you, and everything downstream that inherits it.

margin of error by sample size · 4,200 calls · 95% confidence
04812300 calls · ±5.5 pts2008001400
Margin of error by sample size
Calls reviewedMargin of error (points)
100±9.7
200±6.8
300±5.5
600±3.7
1000±2.7
1600±1.9
30 agents · 4,200 calls / monthsampled
Calls produced4,200
Reviewed at 10 per agent300
Coverage7.1%
Margin of error at 95%±5.5 pts

A team “improving” from 81 to 84 has not measurably moved.

The arithmetic

Ten calls per agent is a workload, not a sample size

The industry convention exists because ten calls is roughly what an analyst can get through per agent per month. It was never chosen for statistical reasons, and it does not hold up to them.

At that coverage, the margin of error is usually wider than the differences you are trying to detect. Month-on-month movement of two or three points: the kind that gets reported upward as an improvement, sits comfortably inside the noise.

Worse, the sample is rarely random. Calls get picked because they were short, or recent, or flagged. Whatever selection rule the analyst used quietly becomes the definition of your quality score.

None of this is an argument against spreadsheets. It is an argument against a sample chosen by how many hours somebody has.

Standard sampling arithmetic · check it in the calculator.

Side by side

Including the rows where the spreadsheet wins.

CriterionSpreadsheet + analystQXAI
Coverage of your call volumeA sampleA sampleBounded by analyst hours.As much as you buyAs much as you buyBounded by credits, not headcount.
Consistency between reviewersNoNoDrifts between analysts and across the week. Calibration exists to fight this.YesYesThe same scorecard applied the same way every time.
Evidence behind a scoreIf they wrote itIf they wrote itDepends entirely on how much the analyst typed in the comment box.YesYesQuoted transcript lines on every parameter.
Knowing which scores to distrustNoNoEvery score looks equally certain.YesYesA confidence figure per parameter.
Judgement on genuinely ambiguous callsBetterBetterA person who knows the account, the customer and the context will read a hard call better than a model. This is the spreadsheet’s real advantage.Flags themFlags themLow confidence tells you which calls to hand to that person, rather than replacing them.
Cost of doubling your coverageAnother analystAnother analystA salary, plus training and calibration time.More creditsMore creditsLinear, and you can stop.
Setup effortNoneNoneYou already have it.An afternoonAn afternoonRebuild your form as a parameter set, or start from a template.
Works with no budget at allYesYesGenuinely free.NoNoCredits cost money. Free credits on signup, then you buy a pack.

Check the arithmetic yourself

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