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How do we right-size rep capacity and assign quota without guessing?

Kory WhiteCurated by Kory White · Fractional CRO, CRO Syndicate
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How do we right-size rep capacity and assign quota without guessing?

Direct Answer

How do we right-size rep capacity and assign quota without guessing?

Use three inputs: historical productivity (ramp curve), territory size (accounts/pipeline), and geography/segment complexity. Assign quota at 85–95% of forecasted capacity to drive execution without burnout. Recalibrate quarterly.

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Operator Approach

Capacity planning is math + behavior. Start with productivity curves:

Rep Ramp Data (typical SaaS):

Once ramped, measure quota-carrying capacity by historical close rate × average deal size × territory pipeline.

Example:

Red flags (over-quotaed reps):

Capacity table:

Territory TypeAccountsAvg ACVClose RateQuarterly QuotaBuffer
Enterprise12–15$500K+20%$1.2–1.5M10%
Mid-market25–35$150–250K25%$750K–$1M8%
SMB60–100$30–50K35%$600–800K5%

Mermaid: Capacity Assignment Decision Tree

graph TD A["Assess Historical Ramp Data"] --> B{"Rep is Ramped?"} B -->|No| C["Apply 70% Capacity Factor"] B -->|Yes| D["Calculate Quota = Close Rate × ACV × Territory Size"] C --> E["Assign with 15% Buffer"] D --> F{"Result > Historical Attainment?"} F -->|Yes| G["Risk: Over-quotaed. Reduce 5–10%"] F -->|No| H["Assign Quota at 85–95% Capacity"] G --> I["Monitor Attainment Weekly"] H --> I I --> J{"2+ Quarters < 60% Attainment?"} J -->|Yes| K["Revise Territory or Support"] J -->|No| L["Recalibrate Quarterly"]

Sources: Pavilion Compensation Study, Bridge Group Territory Benchmarks, SaaStr Quota Setting Guide

TAGS: capacity-planning,quota-assignment,territory-design,ramp-curve,attainment-analysis,productivity-metrics,forecast-accuracy

FAQ

What three inputs drive right-sizing rep capacity? The three inputs are historical productivity (the ramp curve), territory size (accounts and pipeline), and geography or segment complexity. Quota is then assigned at 85 to 95% of forecasted capacity and recalibrated quarterly.

What does a typical SaaS rep ramp curve look like? Months 1 to 2 are 40 to 50% productivity, months 3 to 4 are 70 to 80%, and months 5+ reach 95 to 110% as fully ramped. Capacity planning has to account for this curve rather than assuming full output from day one.

Can you walk through the worked capacity example? A territory of 30 accounts at $150K average contract value with a 25% historical close rate yields 6 deals per quarter, or $900K of ramped capacity. Assigning $850K quota leaves a 6% buffer for ramp variance.

What red flags signal a rep has been over-quotaed? The red flags are attainment under 60% for 2+ quarters, dropping activity ratios on dials, meetings, and proposals, turnover above 15% per year, and forecast accuracy under 65%.

How does recommended quota differ across territory types? Enterprise reps carry 12 to 15 accounts at $500K+ ACV with a 20% close rate and a $1.2 to 1.5M quota at a 10% buffer. Mid-market reps carry 25 to 35 accounts for a $750K to $1M quota, while SMB reps carry 60 to 100 accounts for a $600 to 800K quota at a 5% buffer.

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sourcePavilionsourceBridge GroupsourceSaaStr
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