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Estimation Accuracy Tracker

Free tool

What consistent bias tells you that any single story can't

One story running over its estimate could be anything - a fluke, hidden complexity, a bad day. A consistent pattern across many stories - the team is reliably estimating 30% under actual effort, say - is a calibration signal, and it's the kind of signal that only shows up once you're tracking more than one data point.

What to do with a measured bias

A team that discovers it's systematically underestimating doesn't need to abandon story points - it needs to recalibrate its reference stories, the same process covered in calibrating your estimation scale. The bias itself is useful information, not evidence the whole practice is broken.

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