The 6 Questions That Expose Risky OTEs
The Accountant Test for Sales Offers
A one-page model to avoid wasted interviews, spot risky comp plans, and choose the right team
If you are interviewing for remote sales roles, here’s an annoying truth:
Most candidates choose based on title, brand, and OTE. Then they learn the real math after they join.
This post gives you one sharp career insight you can use before you waste weeks in a process:
Run a simple “accountant test” on the team structure and comp plan so you can spot risk early and make better decisions.
This is also useful if you are a founder or sales leader scaling headcount, but I’m writing it for candidates first.
Use this in interviews today (copy these questions)
You do not need to sound intense. Just calm and specific.
Ask these 6 questions and listen for clarity:
Attainment distribution: In the last 2 quarters, what percent of reps finished above quota, around quota, and below 70%?
Ramp: What does ramp look like in months to first deal and months to full quota?
Pipeline source: What percent of pipeline is AE-sourced vs SDR-sourced vs inbound?
Sales cycle now: What is the average cycle right now for deals like mine, not last year?
Comp stability: What changed in quota, territories, or comp in the last 12 months?
Continuity: When someone leaves, what happens to their pipeline and accounts?
If they answer these cleanly, that is a strong signal.
If they dodge, you just saved yourself time, and this is the same logic behind my full sales interview red flags guide.
A quick example (why this works)
A candidate I coached was in late-stage interviews for a remote AE role.
Then she asked for attainment distribution.
They said ~30% hit quota and ramp “depends.” She stepped back that day and focused on teams who could explain the numbers clearly.
That one question saved her a month.
The red-flag checklist (quick filter)
These are the patterns that create wasted applications and bad offers:
They cannot share attainment bands, only “top reps crush it.”
Ramp is vague, or magically short for a complex sale.
OTE depends on rare accelerators and perfect territory timing.
SDR support exists on paper, but AEs still source most pipeline.
Sales cycle answers change depending on who you ask.
“We are still figuring out the process” is permanent.
Now let’s do the accountant view.
What you’re actually trying to measure
Forget vanity metrics. The outputs you want are:
Cost per $1 of new ARR
Payback months
Profit per rep per year (gross profit minus sales costs)
Breakeven attainment (the quota hit-rate where the model stops losing money)
Build those for each scenario, then compare.
The One-Page Model (4 scenarios)
Set up one sheet like a mini income statement for one AE. Then copy the column for each scenario.
Scenarios to compare:
AE self-prospecting + closing
SDR-supported (AE closes, SDRs prospect)
High base / lower variable (same OTE)
Lower base / higher variable (same OTE)
You can stack these (example: SDR-supported + high base).
Start simple first.
Quick version (90 seconds)
If you only do one thing, do this:
Get attainment bands and ramp.
Assume your outcome is the middle band, not the top band.
If breakeven requires “everyone hits quota,” the offer is a lottery ticket.
If leadership can explain the numbers clearly, that’s a strong sign the machine works.
That’s enough to avoid most bad offers.
Deep version (the 6 variables that decide the answer)
Most models fail because they assume perfect performance. These six inputs keep you honest.
1. Quota attainment distribution (reality, not hope)
Do not model “a rep at quota.” Model a spread.
Example distribution:
20% at 120%
50% at 80%
30% at 40%
This is the single biggest lever in the model.
2. Ramp time
Ramp turns “cheap hires” into expensive hires fast.
Use a simple ramp curve (even if it’s rough):
Month 1–3: partial productivity
Month 4–6: improving productivity
Month 7–12: steady productivity
3. Sales cycle length
Longer cycles mean:
costs pile up longer before revenue lands
you need more pipeline coverage to keep reps productive
4. Win rate
Win rate swings the model more than most comp tweaks.
Model it by scenario. SDR support might increase meeting quality and lift win rate. Or it might flood the funnel and lower win rate. Your model should be able to show both.
5. SDR-sourced pipeline percentage
If you add SDRs, define what they are buying you:
meetings per month
qualified opps created
% of pipeline sourced
If you cannot tie SDRs to pipeline math, you are funding vibes.
6. Retention-adjusted value (churn/expansion)
If you sell recurring revenue, “cost per sale” is incomplete.
At minimum, apply a retention haircut to new ARR. If your structure closes more deals but creates worse-fit customers, the spreadsheet will lie unless you adjust for it.
How to compare SDR-supported vs AE self-prospecting (the clean way)
Step 1: Put a “tax” on AE time
If AEs prospect and close, prospecting steals closing capacity.
So in your model, self-prospecting scenarios should reflect either:
lower effective quota capacity, or
lower win rate, or
longer cycle
Pick the lever that matches reality at your company, then sanity-check it.
Step 2: Force SDR value into measurable outcomes
SDRs must change one or more of these:
qualified pipeline created per month
win rate
cycle length
attainment distribution
If the only justification is “it should help,” the model will look good on paper and fail in execution.
Sensitivity tests (optional, quick)
If you want to pressure-test the offer fast, only toggle these three:
Attainment drops
What happens if your “average rep” is 10–20 points lower than planned?Win rate compresses
What happens if win rate drops a few points?Cycle extends
What happens if cycle stretches by 30 days?
If the whole structure collapses under mild downside, you built something fragile.
What the conclusion should look like
After running this, you should be able to say:
This structure works if average attainment stays above X%.
SDR support pays for itself only if it lifts pipeline by Y or win rate by Z.
Comp changes barely move the model compared to improving win rate, cycle time, or ramp.
Here’s the breakeven point where we stop losing money.
That’s the “accountant test.” Clear enough to make decisions, simple enough to defend.
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