Model your attainment distribution. See if your quota is too aggressive or too soft.
Most companies set quotas top-down without modeling the attainment distribution — what percentage of reps will actually hit, and what happens to team morale and retention when too few succeed. Quota design is not just a finance exercise. It's a talent retention strategy. When the number is wrong, you don't just miss revenue: you lose your best people first, because high performers have options and won't stay in a losing game.
A well-designed quota produces a normal distribution of attainment across the team. Standard deviation matters as much as the average: a tight distribution (low std dev) means quota hit rate is predictable. A wide distribution signals either highly inconsistent territory quality or a coaching problem at the extremes. Reps who land below 70% attainment for two consecutive quarters tend to leave — not because they're fired, but because they self-select out. The cost of replacing an AE is 1.5–2x their OTE. Quota design is not a rounding error; it's a multi-million dollar retention decision. The levers that shift the distribution are: lowering quota, improving pipeline productivity (more opportunities per rep), or reducing performance variance through better coaching. Top quartile SaaS companies target 60–65% of reps at 100%+. The average across B2B SaaS is closer to 48%. That 12–17 point gap compounds: teams stuck below 50% quota attainment cycle through headcount, never build a senior rep bench, and consistently underperform their plan.
The target is 50–65% of reps hitting 100%+ of quota. Below 40% attainment is a quota design problem, not a performance problem. Above 75% and you're leaving money on the table — quota is too soft.
Quota attainment is actual revenue closed divided by the assigned quota for the period, expressed as a percentage. A rep who closes $900K against a $1M quota has 90% attainment.
Quota set too high, territory inequity, poor onboarding and ramp support, weak enablement, pipeline generation problems, or manager coaching gaps. Diagnose root cause before adjusting the number.
Diagnose root cause first: is it a pipeline problem (top of funnel), a conversion problem (win rate), or a quota-setting problem (number is unrealistic)? Each has a different fix. Don't cut quota without understanding which lever is broken.
Discuss this in #quota-planning with 194+ revenue operators in the community.