Planning
The model I use to answer the two questions every exec team asks before a hiring plan is approved: what number can this team actually carry, and how much pipeline does it take to get there? Move the assumptions and the plan recalculates.
| Quarter | Starting heads | Hires | Attrition | Productive equivalents | Capacity (ARR) |
|---|---|---|---|---|---|
| Full-year attainable | — | ||||
sales target = ARR target × (1 − self-serve %)
Self-serve revenue is carried by the product funnel, not by quota-bearing reps. Loading
it onto AE quota is the most common way a plan silently becomes unachievable.
productive equivalent = head × (months productive ÷ 12)
A rep hired in month seven with a five-month ramp contributes almost nothing this year.
Ramp is modeled as a fraction of the year, not as a footnote.
capacity = productive equivalents × quota × attainment
Planning at 100% attainment is planning to miss. Historical attainment is the honest
multiplier.
pipeline required = target ÷ win rate, held as coverage against remaining
quota. Coverage below 3× on a 22% win rate means the gap is demand generation, not
selling effort.
Capacity tells you what the team can carry; it doesn't tell you whether the market can feed it. This section works backward from the pipeline number above to the raw demand the funnel must produce, and stress-tests it against the size of the reachable market.
ICP density. If only a fraction of the named market actually fits the ICP, effective TAM shrinks faster than headcount grows. I maintain an ICP-fit field at the account level so coverage math runs on real coverage, not list size.
Conversion is evidence of fit. Sustained lead→SQL and win rates at or above the plan's assumptions are the market telling you the message and motion are working. When they decay, it's a positioning or ICP problem — hiring more reps only scales the miss.
Pipeline sources diverge. Self-serve signups, inbound, and outbound convert at different rates and velocities. The funnel math above assumes a blended funnel; in practice I model each source separately so a plan that depends on outbound isn't silently leaning on inbound history.
This model is the bridge between the board number and the hiring plan. In planning season I run three versions — conservative, plan, and stretch — and present the headcount and pipeline each one demands. It turns "can we hit $24M?" into a specific conversation about recruiting lead time, ramp investment, and marketing spend, and it gives finance a defensible line between capacity and quota coverage.