When to Run Revenue per Head
Five hiring moments where the RPH delta changes the answer.
RPH is not an annual metric — it's a pre-hire checkpoint. These five moments mean run it before approving the role.
Revenue per Head gets checked at board meetings and ignored during actual hiring. That's backward. These five triggers mean check the math before the role is posted, not after the person starts.
Quick answer
RPH is not an annual metric — it's a pre-hire checkpoint. These five moments mean run it before approving the role.
Key points
- ▸ Before posting any requisition: project the hire's revenue contribution. If RPH delta is flat or negative, the role is probably wrong or the revenue story is wrong.
- ▸ During reorgs: headcount redistribution without RPH math usually means bloat gets moved, not removed.
- ▸ Annual planning: aggregate RPH vs prior year. Flat or declining RPH across a growth year is a signal that the next year's hiring plan needs tightening.
- ▸ After a big contract lands: the revenue numerator jumped. RPH math might justify a hire that didn't pencil last month.
- ▸ When evaluating layoffs: reverse the math. Who can leave while RPH stays flat or improves? RPH tells you capacity, not who deserves to stay.
- ▸ When comparing teams/departments: per-department RPH exposes where bloat actually lives.
Examples
- Pre-requisition triggerEngineering wants a new hire at $140k loaded. Projected revenue contribution: $120k year 1. Delta: -$20k. Role either gets redesigned or waits for more revenue to justify it.
- Big-contract trigger$600k contract closes. RPH math at new revenue level: current hire plan now makes sense. Approve.
- Layoff-evaluation triggerCompany of 20 at $3M rev ($150k/head). To reach $200k/head median: 5 seats need to come out. RPH math identifies which functions are over-staffed relative to peers.
When to use which tool
- Revenue per HeadRun at each trigger. Attach the projection to the requisition or reorg plan.Estimate whether the next hire raises or lowers revenue per employee after management time and ramp-up.
- Hire vs AutomateWhen the hire is a rote-task role, run both — automation may beat hiring outright.Should you hire a human at $X/hr or pay $Y/mo for a SaaS/automation stack? Efficiency bar comparison.
Related
- Revenue per HeadEstimate whether the next hire raises or lowers revenue per employee after management time and ramp-up.
- Hire vs AutomateShould you hire a human at $X/hr or pay $Y/mo for a SaaS/automation stack? Efficiency bar comparison.
- What Revenue per Head CalculatesWhether your next hire raises profit-per-employee or quietly adds bloat.
- Five Revenue per Head MistakesThe errors that make every hire look justified on paper.
- What Hire vs Automate CalculatesThe monthly cost gap between hiring a human and buying the SaaS stack that replaces them.
Frequently asked questions
› What if the role doesn't directly produce revenue?
Attribute a share of revenue based on the team's contribution. Sales roles get direct attribution; engineering gets a share of the feature revenue they enable; ops gets a share tied to scale.
› Is there a target RPH? Trust & accuracy
Industry dependent. Software services often target $200-400k/head. SaaS mature companies hit $400k-$1M. Consulting $150-300k. Compare to peers, not absolute numbers.
› How should I use a decision framework in real life? How-to
Use a decision framework to expose the tradeoff, not to outsource the decision. Write down the inputs, compare the output with your constraints, then ask what would change the answer. The strongest use is scenario testing: base case, conservative case, and failure case.
› Is this financial, legal, or tax advice? Trust & accuracy
No, this is not legal, financial, tax, medical, or professional advice unless the page explicitly says that use case is supported. It organizes assumptions so you can inspect them. Verify high-stakes choices with qualified people who can review facts, contracts, regulations, and downside risk.
› What assumption matters most in a decision model? Edge case
The most important assumption is usually the one you are least certain about and most emotionally attached to. Change that input first. If the recommendation flips after a small change, the decision is fragile and needs more evidence before you treat the model as useful.