RVNU #055: Is It a Pipeline Problem or a Capacity Problem?
The boring (85%/15%) math behind confident sales AE hiring for 2026 and beyond.
This is the time of year when we spread a cup of cheer while founders dust-off the “Annual Capacity Planning” spreadsheet and try to ‘math’ their way into: When, exactly, do I hire my next sales rep?
First for the cup of cheer - Wayne and I are hosting an RVNU sponsored ❄️Holiday Happy Hour ❄️ on 12.17 (YES TOMORROW) from 5:30-7:30pm. So if you are local in the San Francisco Bay Area - come join us for a festive drink at the local holiday pop-up, leave a comment that you would like to join and we will add you to the invite with exact location!
Ok, now the practical stuff…….If you are starting from scratch or stuck in annual planning - This newsletter tackles the following:
A simple 85% ‘right capacity’ formula that turns “I feel like we need more reps” into “Our future demand will exceed fully ramped capacity by 23%, so yes/no.”
How to hone in your company’s 15% variations of different growth motions, capital structure and industry — rewiring your risk tolerance, change signal and potential timing.
Pivot capacity planning from an annual burden to weekly monitoring by building an operating cadence (weekly, monthly, quarterly) so headcount decisions stop being emotional reactions and start being boring, repeatable checkpoints.
In 2026, the winners won’t be the companies with the biggest sales team headcount slide. They’ll be the ones who know the difference between a pipeline problem and a capacity problem, and who can walk into a board meeting and say, “Here’s exactly why we are (or are not) hiring another rep.”
The 85% standard “Should I Hire?” formula
Under every “how many reps?” debate is one simple equation: Future demand > Fully-ramped capacity ⇒ Start hiring. The “should I hire?” formula has the same core variables across B2B SaaS companies: Capacity=N×Q×A
Target new/renewal ARR (T)
Number of fully ramped reps (N)
Quota per rep (Q)
Expected attainment (A)
Time to hire (H) and ramp (R)
Step 1 – Define the target
Annual ARR target (T)
If new and existing business ARR are handled by different teams, break out ARR up for renewal next year new business revenue capture
How much each fully ramped rep can ‘realistically carry’ (Q × A), where:
Q = annual quota or renewal book
A = expected attainment (e.g., 70–80% for new, NRR for existing)
Rough max capacity today
[Max ARR capacity now] = [[# fully ramped reps] * Q] * A]
If Max ARR capacity now < T by more than 15–20%, you either:
Increase capacity per rep (better leads, better motion, better tooling), or
Add reps and account for ramping time
Step 2 – Add ramp and hiring lag
You’re never hiring for this quarter – you’re hiring for the quarter 6–12 months from now:
Time to hire (H): 1–3 months to recruit and close
Time to ramp (R): often 3–6 months to full productivity
If you want full capacity by Q4 and H+R = 6 months, the decision to hire is a Q2 problem, not a Q4 panic.
Step 3 – Add demand confidence
You only hire if you have some proof of demand:
Pipeline coverage (3–4× next-quarter target, for multiple months)
Stable or improving win rates and cycle times
No obvious “we’re just bad at qualification” red flags
Step 4 — Put it together (simple version)
You are close to “should we hire?” when all are true:
Target ARR in Q+2 > Capacity in Q+2 by > X%Target ARR in Q+2 > Capacity in Q+2 by > X% (e.g., 20%)
Existing reps are ≥80–90% utilized on truly qualified work (not just calendar noise).
Pipeline and win-rate trends support the target (not one lucky whale).
When those three are green, you pull the trigger.
Where the 15% customization lives
The math doesn’t care about your motion, your investors, or your category—it only cares about demand, capacity, and risk. Growth motion changes where you look for proof of demand; capital structure changes how brave you can be about hiring ahead; industry changes how slowly and expensively that demand turns into revenue.
Motions: sales-led vs PLG vs community
The formula is the same; what feeds “demand confidence” changes.
Sales-led motion
Demand signal = SQOs, pipeline coverage, outbound capacity.
Typical failure mode: add reps to compensate for weak ICP, bad messaging, or non-existent marketing.
Product-led motion
Demand signal = product-qualified leads, conversion from free → paid, expansion from existing users.
Headcount lever: more AEs / PLS reps only when PQLs are >100% utilized on high-intent conversations.
Community-led motion
Demand signal = community → pipeline conversion: events, Slack/Discord/meetup members turning into deals.
Headcount lever: add reps when community-generated opportunities are going stale or unworked, not when your Discord feels “busy.”
Same equation, different leading indicators.
Capital: bootstrapped vs VC vs PE
Your risk tolerance is not a vibe. It’s your capital structure.
Bootstrapped
Cash = runway. You hire last, not first.
Bias to:
Increase capacity per rep via ICP focus, better tooling, and ruthless disqualification before adding heads.
Use conservative attainment (60–70%) and slower ramp in your model.
VC-backed
Cash = growth engine, but boards now care about CAC payback and burn multiples.
Bias to:
Fund 1–2 “strategic” hires ahead of demand, but still prove repeatable pipeline before scaling.
Model CAC payback for every new rep: fully-loaded cost vs booked ARR over 12–18 months.
PE-backed
Cash = levered; efficiency is king.
Bias to:
Squeeze more out of existing team: territories, specialization, process, and enablement.
Only hire once reps are truly at (or above) target capacity and pipeline still outpaces coverage.
Same equation, but your acceptable variance and time-to-payback move with the funding model.
Does industry matter?
Yes, mostly in these ways:
Sales cycles: 90-day mid-market SaaS vs 18-month regulated enterprise changes ramp and forecast risk.
ACV: a $5K tool vs $500K platform changes how many deals a rep can carry and how many reps you need per segment.
Buying complexity: more stakeholders, RFPs, and security reviews mean more “selling hours” per deal, so capacity per rep is lower.
Industry doesn’t change the equation.
It changes the inputs: Q, A, H, R, and how noisy your demand signals are.
Capacity monitoring (the new annual plan?)
Finally, founders shouldn’t just look at the formula once a year; they should wire it into a simple operating cadence that surfaces “it’s time to talk about hiring” before it’s a crisis. Think of this as three layers:
Weekly: “Are we on track this quarter?”
Monthly: “Is our near-term capacity vs demand balance healthy?”
Quarterly: “Do we need to change headcount or hiring plans?”
Best practice is weekly pipeline reviews, monthly capacity checks, and quarterly hiring decisions, all anchored to the same model.
Weekly: deal + pipeline reality
Weekly is not about headcount decisions; it’s about input health:
Run a short pipeline review: coverage vs this quarter’s target, deal quality, stage distribution, demand volume.
Watch:
Has top of funnel demand (website visits, qualified lead volume, deal creation) slowed week over week or increased?
Are good opportunities going untouched or delayed?
Are reps clearly underutilized (too few high-quality calls / opportunities)?
Signal to start thinking about future hiring:
Multiple weeks where reps are consistently overloaded with good opps or response times slip.
Or the opposite: reps are underutilized → your problem is demand, not capacity.
Monthly: “capacity vs demand” check-in
Once a month, the founder can look at the 85% calculator like a mini MBR:
Update:
Actual bookings and attainment per rep
Next 2–3 quarters’ targets
Next-quarter qualified pipeline and win rate
Any new hires started (and where they are on ramp)
Ask the model:
If we changed nothing, does modeled capacity in Q+2/Q+3 cover our targets within our gap threshold (e.g., ±20%)?
Is pipeline coverage ≥3–4× for those same quarters, and is win rate/cycle time stable?
If, month over month, you see:
Future capacity gap > threshold and demand signals hold up → flag “start hire conversation” on the next GTM Leadership meeting
Gap closes or flips as demand softens → pause the impulse to hire and refocus on productivity
The idea: the spreadsheet becomes a recurring “is it time yet?” dashboard, not a one-off.
Quarterly: formal hiring decision
Quarterly is where you lock in yes/no on headcount:
Rebuild or refresh the model using last quarter’s actuals
Scenario-test: “What if we hire 1 AE now vs next quarter? What if we don’t hire at all?”
Include: ramp, attrition, runway, and CAC payback assumptions
In that QBR-style conversation, you want three slides or sections:
Capacity vs target for the next 3–4 quarters (from the sheet)
Demand health: pipeline coverage, win rate, cycle time trends
Risk view: cash, CAC payback, tolerance for a bad hire
The conclusion is binary:
“We will post and hire X reps for segment Y this quarter.”
Or “We will not add heads; instead we’ll focus on A/B/C to improve productivity.”
Quarterly is the only place you green-light headcount; weekly and monthly are just feeding better data into that decision.
AND FINALLY ( I can’t believe you made it this far)…before you add a single sales head to the plan, align on a short checklist here, get your inputs out on paper and if you want to pressure-test where you stand, take the GTM assessment (it’s completely free).
We hope to see our local SF friends and family tomorrow 12.17 for our ❄️Holiday Happy Hour ❄️ from 5:30-7:30pm, message us directly to be added to the invite.
Happy hiring (or not), folks - you got this!