Revenue per Employee: SaaS vs VC

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(Note: this post has been updated for an error in the VC return math. I wasn’t properly compounding each year’s returns, understating how efficient firms can be.)

Revenue Per Employee: The GOAT of SaaS Metrics

I've long said that Revenue per Employee is the GOAT of SaaS metrics.

If 70% of tech company costs walk on two feet, you’d wanna know how much operating leverage you’re squeezing out of that spend. The simplest way? Stack your topline output (revenue) against your means of production (employees).

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Why This Metric is Elite

✅ Simple – No fancy adjustments, just revenue divided by headcount.
✅ Comparable – Works across industries and company sizes.
✅ Cuts through the noise – No GAAP tricks or stock-based comp fudging.

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The Debate: Are VCs More Efficient Than the Companies They Fund?

I recently got into a debate with a friend: Are venture capital firms actually more efficient businesses than the companies they invest in? (How meta.)

So, I decided to run the numbers (LOL) and find out.

As a baseline, the median public tech company we track is putting out about $400K per employee.

Some outliers:

• Block: $1.7M

• Airbnb: $1.5M

• Uber: $1.2M

• Affirm: $1.1M

• Etsy: $1.1M

• PayPal: $1.1M

(You’ll notice that fintechs and marketplaces absolutely RIPPP at scale.)

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Now to Compare…

Initially, I considered using publicly traded investment firms like The Carlyle Group, Thoma Bravo, and Warburg Pincus. But they’ve all become multi-strategy shops, making it tough to isolate their pure tech investing arms from their Quantum Credit Dislocation or Collateralized Synthetic Yield Optimization plays.

(I made both of those up after watching The Big Short for the 97th time.)

So instead, let’s throw some paint against the wall and estimate using VC firms that primarily invest in early- to mid-stage companies—think Benchmark, Index, or Founders Fund-ish.

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VC Firm Revenue: Management Fees + Carry

Venture firms monetize through two main levers:

• Management Fees – ~2% of Assets Under Management (AUM)

• Carried Interest – ~20% of profits exceeding an 8% hurdle rate

Management fees are recurring—the closest thing to "ARR" for a fund. Carry is performance-based and only unlocks when they exit investments.

Example Math:

• Fund Size: $3B AUM

• Employees: 20 employees per $1B AUM

• IRR: 25%

• Fund Lifecycle: 10 years

Annual Management Fees:

• 2% of $3B = $60M per year

Total Carried Interest (Compounded IRR):

• Final Fund Value after 10 years of 25% IRR:
  $3B × (1.25)¹⁰ = $27.94B

• Hurdle Value at 8% annual return:
  $3B × (1.08)¹⁰ = $6.48B

• Excess Profits (Above Hurdle):
  $27.94B – $6.48B = $21.46B

• Carry (20% of Excess Profits):
  $21.46B × 20% = $4.29B

🔥 Takeaway: The VC firm’s carry profit is $4.29 billion.

• Over 10 years that works out to $429M per year + $60M in Management Fees = $489M in total revenue per year

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SQUIRREL!

Before diving into comparisons, let’s pause on something wild:

A fund returning 25% annually (which is really good and not easy to do) actually makes 7x more off carry than management fees over its lifecycle.

Now, this isn’t easy. You could easily throw up a 12% IRR and be in a much less appealing situation due to the impact of compounding.

This clearly explains why some firms prioritize AUM growth (scaling 2% fees on a massive base) while others focus on absolute returns (maximizing carry on high IRRs).

(I digress...)

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Back to Efficiency—How Does Headcount Affect This?

The most sensitive factor in this analysis is the relationship between employees and AUM.

IRR also impacts revenue per employee, since higher returns generate exponentially more carry.

I’ve laid out scenarios across various staffing, fund size, and return profiles below.

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Scenario 1: Standard Venture Fund ($3B AUM, 20 employees per $1B, 25% IRR)

• Final Fund Value (25% IRR for 10 years) = $27.94B

• Hurdle Return (8% for 10 years) = $6.48B

• Excess Profits Above Hurdle = $27.94B - $6.48B = $21.46B

• Carry (20% of Excess Profits) = $21.46B × 20% = $4.29B

• Annualized Carry Over 10 Years = $4.29B ÷ 10 = $429M per year

• Management Fees = $60M per year

• Total Annualized Revenue = $489M

• Revenue Per Employee (60 employees) = $8.15M per employee

🔥 Takeaway: $8M per employee is more than 24x higher than the median tech company.

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Scenario 2: Lean, High-Performing Fund ($3B AUM, 30% IRR)

• Final Fund Value (30% IRR for 10 years) = $41.92B

• Hurdle Return (8% for 10 years) = $6.48B

• Excess Profits Above Hurdle = $41.92B - $6.48B = $35.44B

• Carry (20% of Excess Profits) = $35.44B × 20% = $7.08B

• Annualized Carry Over 10 Years = $7.08B ÷ 10 = $708M per year

• Management Fees = $60M per year

• Total Annualized Revenue = $768M

• Revenue Per Employee (45 employees) = $17.06M per employee

🔥 OK, This is getting outrageous.

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Scenario 3: Scaled Mega-Fund ($10B AUM, 30 employees per $1B, 20% IRR)

• Final Fund Value (20% IRR for 10 years) = $15.39B

• Hurdle Return (8% for 10 years) = $21.58B

• Excess Profits Above Hurdle = $15.39B - $21.58B = $5.81B

• Carry (20% of Excess Profits) = $5.81B × 20% = $1.16B

• Annualized Carry Over 10 Years = $1.16B ÷ 10 = $116M per year

• Management Fees = $200M per year

• Total Annualized Revenue = $316M

• Revenue Per Employee (300 employees) = $1.05M per employee

🔥 Even at mega-fund scale, VC firms crush tech companies on efficiency.

Final Comparison: Tech vs. VC Efficiency

• VC firms are way more efficient than the tech companies they fund.

• Even at moderate IRRs (~20-25%), VC firms generate 3-5x more revenue per employee than the best tech companies.

• At the top end (~30% IRR), elite VC firms can outperform elite tech by +20x on revenue per employee.

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And my ultimate takeaway? No one is beating OnlyFans. With an estimated $31M per employee, it’s in a league of its own. Mic (web cam?) drop.

Source

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Data Source: Koyfin

TL;DR: Multiples are UP week-over-week.

Top 10 Medians:

• EV / NTM Revenue = 18.0x (UP 1.1x w/w)

• CAC Payback = 28 months

• Rule of 40 = 52%

• Revenue per Employee = $397K

  

  Data Source: Koyfin

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Data Source: Koyfin

• Figures for each index are measured at the Median

• Median and Top 10 Median are measured across the entire data set, where n = 110

• Population Sizes:

  • Security: 17

  • Database and Infra: 14

  • Backoffice: 16

  • Marcom: 16

  • Marketplace: 15

  • Fintech: 16

  • Vertical SaaS: 16

Revenue Multiples

Revenue multiples are a shortcut to compare valuations across the technology landscape, where companies may not yet be profitable. The most standard timeframe for revenue multiple comparison is on a “Next Twelve Months” (NTM Revenue) basis.

NTM is a generous cut, as it gives a company “credit” for a full “rolling” future year. It also puts all companies on equal footing, regardless of their fiscal year end and quarterly seasonality.

Data Source: Koyfin

However, not all technology sectors or monetization strategies receive the same “credit” on their forward revenue, which operators should be aware of when they create comp sets for their own companies. That is why I break them out as separate “indexes”.

Reasons may include:

• Recurring mix of revenue

• Stickiness of revenue

• Average contract size

• Cost of revenue delivery

• Criticality of solution

• Total Addressable Market potential

From a macro perspective, multiples trend higher in low interest environments, and vice versa.

Multiples shown are calculated by taking the Enterprise Value / NTM revenue.

Enterprise Value is calculated as: Market Capitalization + Total Debt - Cash

Market Cap fluctuates with share price day to day, while Total Debt and Cash are taken from the most recent quarterly financial statements available. That’s why we share this report each week - to keep up with changes in the stock market, and to update for quarterly earnings reports when they drop.

Historically, a 10x NTM Revenue multiple has been viewed as a “premium” valuation reserved for the best of the best companies.

Efficiency Benchmarks

Companies that can do more with less tend to earn higher valuations.

Data source: Koyfin

Three of the most common and consistently publicly available metrics to measure efficiency include:

• CAC Payback Period: How many months does it take to recoup the cost of acquiring a customer?

CAC Payback Period is measured as Sales and Marketing costs divided by Revenue Additions, and adjusted by Gross Margin.

Here’s how I do it:

• Sales and Marketing costs are measured on a TTM basis, but lagged by one quarter (so you skip a quarter, then sum the trailing four quarters of costs). This timeframe smooths for seasonality and recognizes the lead time required to generate pipeline.

• Revenue is measured as the year-on-year change in the most recent quarter’s sales (so for Q2 of 2024 you’d subtract out Q2 of 2023’s revenue to get the increase), and then multiplied by four to arrive at an annualized revenue increase (e.g., ARR Additions).

• Gross margin is taken as a % from the most recent quarter (e.g., 82%) to represent the current cost to serve a customer

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• Revenue per Employee: On a per head basis, how much in sales does the company generate each year? The rule of thumb is public companies should be doing north of $450k per employee at scale. This is simple division. And I believe it cuts through all the noise - there’s nowhere to hide.

Revenue per Employee is calculated as: (TTM Revenue / Total Current Employees)

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• Rule of 40: How does a company balance topline growth with bottom line efficiency? It’s the sum of the company’s revenue growth rate and EBITDA Margin. Netting the two should get you above 40 to pass the test.

Rule of 40 is calculated as: TTM Revenue Growth % + TTM Adjusted EBITDA Margin %

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A few other notes on efficiency metrics:

• Net Dollar Retention is another great measure of efficiency, but many companies have stopped quoting it as an exact number, choosing instead to disclose if it’s above or below a threshold once a year. It’s also uncommon for some types of companies, like marketplaces, to report it at all.

• Most public companies don’t report net new ARR, and not all revenue is “recurring”, so I’m doing my best to approximate using changes in reported GAAP revenue. I admit this is a “stricter” view, as it is measuring change in net revenue.

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Operating Expenditures

Decreasing your OPEX relative to revenue demonstrates Operating Leverage, and leaves more dollars to drop to the bottom line, as companies strive to achieve +25% profitability at scale.

Data source: Koyfin

The most common buckets companies put their operating costs into are:

• Cost of Goods Sold: Customer Support employees, infrastructure to host your business in the cloud, API tolls, and banking fees if you are a FinTech.

• Sales & Marketing: Sales and Marketing employees, advertising spend, demand gen spend, events, conferences, tools.

• Research & Development: Product and Engineering employees, development expenses, tools.

• General & Administrative: Finance, HR, and IT employees… and everything else. Or as I like to call myself “Strategic Backoffice Overhead.”

All of these are taken on a Gaap basis and therefore INCLUDE stock based comp, a non cash expense.

Please check out our data partner, Koyfin. It’s dope.