Sales Capacity Planner

How this works

Sales capacity planning starts with a simple equation and gets complicated fast.

The simple version: Reps needed = Revenue target / (Quota x Attainment). If you need $22M and each rep delivers $576K effectively ($800K quota at 72% attainment), you need 38 fully-ramped reps.

The complicated version accounts for ramp time (new hires produce less in their first year), attrition (you will lose reps and need to replace them), and the timing of hires (a rep hired in Q3 contributes less than one hired in Q1).

The attainment distribution problem

This calculator uses average quota attainment. In reality, attainment follows a distribution. In most B2B SaaS sales teams, the top 20% of reps deliver 50%+ of revenue. The median rep hits 60-65% of quota. The bottom 20% rarely surpass 40%.

This means "average attainment of 72%" masks critical variance. Your capacity plan looks different if 72% is the median versus if it is the mean skewed upward by a few top performers.

ORM's Optimized Sales product models attainment distributions, not averages. We segment your team by tenure, territory, product line, and deal source to identify where capacity is concentrated and where it is weak. A capacity plan built on averages will be wrong. One built on distributions will be right.

The ramp tax

New hires are expensive in ways that do not show up in headcount math. A rep with a 6-month ramp period produces roughly 50% of full capacity in their first year (assuming linear ramp, which is optimistic). If your attrition rate is 25%, you are constantly hiring replacements who operate at reduced capacity.

The "ramp tax" on your revenue capacity is substantial. A team of 20 reps with 25% annual attrition and 6-month ramp effectively operates at 85-88% of theoretical capacity, not 100%. Most capacity plans ignore this, which is why they consistently under-deliver.

ORM's take: capacity planning is revenue modeling

This calculator gives you a headcount number. What it cannot do is tell you which reps to hire (enterprise vs. mid-market), when to hire them (optimized for revenue timing, not budget timing), or where to deploy them (territories with the highest pipeline density).

ORM's Optimized Sales models treat capacity planning as part of the revenue system. We do not just tell you that you need 38 reps. We tell you that adding 3 mid-market reps in Q2 generates more incremental revenue than adding 2 enterprise reps in Q1, because the mid-market pipeline is denser and the ramp curve is faster. That level of specificity requires custom modeling on your data, not a calculator.

Common questions

How do you calculate sales capacity?

Multiply the number of productive reps by quota per rep, adjusting for ramp. A rep who starts in month two of the year does not carry a full annual number, and capacity plans that ignore ramp overstate the year before it begins.

How do you account for ramp time in a capacity plan?

Model each hire at a fraction of quota until fully ramped rather than assuming full productivity from a start date. Use your own observed ramp rather than a plan assumption, because the gap between the two is where most capacity plans break.

What coverage ratio should a capacity plan assume?

Work back from win rate rather than adopting a default. At a 25% win rate with 10% slippage the required pipeline coverage is roughly 4.4x, not the 3x most plans assume. Using a borrowed multiplier is the most common error in capacity planning.

Should capacity be planned on headcount or on quota?

Both, and they answer different questions. Headcount tells you whether you can hire and onboard in time. Quota capacity tells you whether the number is reachable. A plan that clears one and fails the other is not a plan.

When should a capacity plan be revisited?

Whenever attrition, ramp or win rate moves materially, and at minimum each quarter. Capacity models are built on assumptions that decay, and the first sign is usually the forecast missing while activity looks normal.