It's planning season, and plenty of RevOps teams are staring at a 2027 number that was built from the top down: pick a revenue target, set a per-rep quota, assume an "industry standard" attainment rate, and back into a hiring plan. The math ties out neatly. Whether it can actually happen is a different question.
In the latest issue of Uncharted Territory, Gradient Works co-founder Hayes Davis shares a practical way to answer that question: a bottom-up spreadsheet model that connects the top-line plan to the hiring, ramping, and pipeline creation it depends on. The model is free to copy and adapt for your own team.
Meet their spreadsheet with your own
The model came out of our work with a RevOps team at a nine-figure, PE-backed SaaS company. Leadership had handed the team an aggressive plan that relied on hiring a lot of new reps and having them generate pipeline through outbound, even though the current reps weren't hitting their outbound numbers.
Hayes argues that the right response is neither silent compliance nor an outright refusal:
"Your first response might be to throw up your hands and say 'this is BS!' and start cleaning up your resume. That won't get you anywhere. A healthier response is to meet their spreadsheet with one of your own."
A bottom-up model lets you spot the risks and explain them in terms that finance-minded leaders already use. In this case, it led to a productive, data-driven conversation with leadership about where the plan was fragile and how to reduce that risk.
What's in the model
The Google Sheets template is read-only, so make a copy to use it. Two tabs drive everything:
- Full Model takes your inputs and models month-by-month bookings, pipeline generation requirements, and outbound coverage.
- Hiring applies cohort-based attrition and ramping to your planned new hires, then feeds that quota capacity back into the Full Model.
Two output tabs, Full Model (Quarterly) and Charts, roll the data up into a board-friendly view and visualize where the plan is most exposed. Inputs follow standard FP&A color coding, so anyone used to reading financial models will know where to look.
Risk #1: The hiring and ramp plan
Plans that depend on hiring for growth are fragile, and the timing of those hires makes a big difference. When most of the hiring happens early in the year, mid-year bookings depend almost entirely on how those new reps ramp.
The model lets you stress-test that dependency in a few ways:
- Attrition, set separately for ramped and ramping reps. Hayes suggests setting ramping attrition higher to account for mis-hires and reps who never ramp.
- Ramp curve, which sets ramping quota as a percentage of full quota for each month of tenure. Because the curve is applied to each hiring cohort separately, the blended team quota in any given month reflects reality more accurately.
- Attainment, applied to both full and ramp quotas.
On that last point, the post recommends caution:
"I've written about the perpetual decline in attainment before—the Bridge Group pegged median attainment at 51% in 2024—so it's a good idea to assume the worst here."
Risk #2: Outbound capacity
The second half of the model checks whether your team can realistically create the pipeline the plan requires. It uses one of our favorite metrics, opportunity creation rate (OCR): the percentage of accounts your reps engage that turn into an opportunity.
The model works backward from the bookings target. It uses average deal size, win rate, and sales cycle length to calculate how many opportunities you need and when you need them. It then compares that number with how many accounts your team can actually engage each month. The result is an implied OCR, which tells you how efficient your outbound motion would need to be for the plan to work.
"We typically see OCRs range from 6% to 12% for outbound teams. If your OCR is at the high end of that range at any point in the plan, there's a significant risk that you won't build the pipeline coverage necessary to hit the plan."
And if marketing or partner pipeline falls short, outbound has to cover the gap, which pushes the required OCR even higher.
Turn the model into a conversation
The model is most useful for running what-if scenarios and walking leadership through them. What happens if hiring takes longer than planned? What if ramping reps leave at a higher rate? What if deal size, win rate, or sales cycle length come in differently than expected? Each scenario shows a different bookings variance and a different required OCR.
"Worst case, the plan stays and you'll all have a sense of where you need to be very careful. Best case, you adjust the top-line in a way that reduces some of the execution risk."
Either way, you're answering one spreadsheet with another, and that's how you call BS responsibly.
Read the full post on Uncharted Territory → for the full walkthrough, including chart examples and the model's assumptions in detail. Then grab a copy of the model and test it against your own 2027 plan.
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