Human bias and overconfidence cause teams to miss estimates, yet studies show we estimate familiar work within 20-30% and can boost accuracy to 80%+ with feedback and training.
Estimating is a human task and our biases, backgrounds, and personalities shape the numbers we produce. When teams ignore these human factors they end up with wildly inaccurate forecasts, especially for unfamiliar work. The article shows that the problem isn't that people are fundamentally bad at estimating, but that hidden opinions and confidence gaps distort the process.
Common roadblocks include a single stubborn estimator, silent participants who go through the motions, new members intimidated by dominant voices, and the fear of stakeholder backlash if estimates look too optimistic. These dynamics erode team cohesion and make the estimation ceremony feel like a checkbox rather than a useful planning tool.
Research cited from Magne Jørgensen finds most software estimates land within 20-30% of reality, and a controlled study demonstrates that providing feedback on errors raises correct estimates from 64% to over 80% after a few rounds. The key insight is that feedback loops and training turn raw human intuition into a measurable skill.
For technical leaders the takeaway is clear: treat estimates as data, not opinion. Capture actual outcomes, give teams concrete feedback, and invest in focused estimating workshops or on-demand courses. When you surface bias, calibrate confidence, and practice regularly, estimation becomes a strategic asset rather than a source of friction.
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