What is bell curve rating?

What is bell curve rating?

Performance & metrics Updated September 2026

Bell curve rating forces performance ratings into a fixed distribution, commonly 20% top, 70% average, 10% low, regardless of how a team actually performed that cycle. Microsoft, Infosys, Accenture and GE have all publicly dropped it in favor of more flexible approaches.

Bell curve rating forces performance ratings into a normal, bell-shaped distribution, commonly a fixed 20% top performers, 70% average and 10% low performers, regardless of how a specific team’s appraisal results actually spread that cycle.

Why companies have been moving away from it

Microsoft publicly ended its stack-ranking system in November 2013 after it was widely blamed for damaging internal collaboration during a difficult stretch for the company. Infosys scrapped its bell curve in 2015, moving to an open-ranking approach without a forced distribution. Accenture dropped bell curve and forced rankings the same year, shifting toward continuous, real-time feedback instead. GE eliminated numerical ratings and its long-running forced-distribution system around 2015-16, replacing the annual review with ongoing, app-based feedback. The common complaint across all of these: a forced distribution can push a genuinely strong team to still rank 10% of its people as underperformers, and a genuinely weak team to still rate 20% as top performers, regardless of the team’s actual output that cycle.

Frequently asked questions

Is bell curve rating the same as forced ranking?

Closely related. Forced ranking is the act of ranking people against each other; bell curve is the statistical shape the results typically get mapped onto.

Do any large companies still use bell curve rating?

Some do, particularly where leadership values a consistent, comparable distribution across large workforces, but the broader industry trend has clearly moved away from it.

What replaced bell curve rating at most companies that dropped it?

Commonly continuous, more frequent feedback combined with calibration sessions to keep ratings consistent without forcing a fixed distribution shape.

See how performance calibration works as an alternative approach to consistency.

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