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Why 3x Pipeline Coverage Is a Terrible Strategy

An image of Jason Jordan, an expert in pipeline coverage
Clearly, the 3x pipeline formula is a drooling monster that must be slayed. Your weapon? Better math.

We have the data and we know the math. And now, we have a calculator that lets you easily figure out the right pipeline size to hit your quota.

The saying has been passed down from seller to seller over the years. By now, it’s set in stone. “The sales pipeline should be three times the annual quota.” You might know this as the “3x Pipeline Coverage” rule. The problem? It’s right as often as a broken clock.

I used to be a sales consultant, looking at teams from the outside in, and (plug alert!) writing books like “Cracking the Sales Management Code.” Then I became a chief revenue officer, and the pipeline suddenly became real. I’d sit down with sales reps for pipeline reviews, and we couldn’t answer the most basic question: “How big is big enough?” 

Filling the pipeline with 3x quota wasn’t working, and we didn’t know how else to figure out coverage. Maybe the 3x guidance was acceptable 30 years ago, back when we didn’t have reliable sales data, or sales operations and revenue operations teams to help us understand it. 

Today, there’s no excuse. We have the data and we know the math. Below, I share why the 3x guidance doesn’t work anymore, and how to calculate the right pipeline coverage instead.

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What is pipeline coverage and why does it matter? 

Pipeline coverage predicts how much potential revenue you need in your pipeline to hit annual sales targets. It depends on win rate (how much revenue you expect to close in your pipeline) and sales cycle length (how long it takes to close deals, on average).

For example, if a rep wins 10% of their pipeline revenue, and the sales cycle length is a year, then you need 10x pipeline coverage. 

Getting this prediction right matters for everyone on the team.

Sales reps need to know how large their sales pipeline needs to be in order to hit their numbers. If their win rate is low, they need to focus on building more pipe — for example, by prospecting. If it’s high, they need to focus on closing deals. Knowing which action to take is critical at a time when 72% of sellers expect to miss their quota, according to the 2023 State of Sales report.  

Sales managers look at pipeline coverage during pipeline reviews to coach reps on how they can hit their targets. Maybe they should make more calls to build revenue in pipe, or improve their objection handling to reduce sales cycle length.

Sales leaders use pipeline coverage as the primary input for creating a sales forecast. If you know all the numbers we’ve been talking about — pipeline coverage, win rate, and sales cycle length — then you can make an accurate prediction of how much your team will sell. 

In other words, “Understanding pipeline is essential to forecasting the health of the business — as well as enabling confident sales teams,” said Priyank Saxena, senior manager of CRM Applications at MathWorks.

The problem with the 3x pipeline ratio

The 3x pipeline coverage ratio works only when your win rate is exactly 33% and your sales cycle is exactly one year. (Why? If you sell a third of your deals every year, you need three times that number in your pipeline to cover them.) 

But how often do those numbers actually happen? A junior seller might have a win rate of 10%, requiring a pipeline with 10x coverage. A rockstar seller who closes 50% of their pipeline would only need 2x coverage. 

As for sales cycles, imagine one team sells software with a year-long sales cycle, and another sells hardware with a cycle of just two weeks. While the first team has one pipeline to last all year, the second team turns their pipeline over 25 times a year — which means they’ll need much less coverage to achieve their annual quota. 

Clearly, the 3x pipeline formula is a drooling monster that must be slayed. Your weapon? Better math.

How to calculate pipeline coverage for better coaching and forecasting

To calculate accurate pipeline coverage for every rep, start by recording their annual quota, average revenue (not deal) win rate, and sales cycle length. Use these to calculate how large the pipeline should be to hit quota. 

Here’s the formula:

Pipeline Coverage = Rep’s Annual Quota ➗ Rep’s Average Revenue Win Rate ➗ (365  ➗  Sales Cycle Length in Days)

So, for example: $100,000 ➗ 25% ➗ (365 ➗ 60 days) =  $65,757 needed in pipeline coverage.

Pipeline coverage that’s less than quota? That’s right. If the rep cycles through sales every two weeks, then they’ll hit their targets. Just reverse-engineer it to check: $65,757 x 25% win rate is $16,439 every two months. Multiply that by 6 to get the total for the year, and you have almost exactly $100k.

Now that you have the formula, you can use it to guide pipeline reviews and map forecasting that will get you closer to targets. Oh, and take the manual calculations off your plate by using this handy calculator:


Isn’t it nice to know that what we needed was eighth-grade math all along? Get more calculators for pipeline sizing and revenue forecasting at my Pipeline Math hub.

A happily ever after, now that the 3x monster is slain

Historically, the conversation between manager and rep has been: “Hey, your pipeline’s not three times your quota.” The new conversation needs to be: “Hey, I looked at the data. We’ve gotta get more stuff in, or win more stuff, or do stuff faster.” 

That’s meaningful coaching. It happens when we stop telling the pipeline how large it should be — and start letting the pipeline tell us what we should be doing. 

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Jason Jordan Sales management expert

Jason Jordan is a sales management expert and best-selling author of "Cracking the Sales Management Code" and "Sales Insanity." He helps B2B sales leaders become more effective in management challenges such as coaching, pipeline management, and forecasting. Jason is currently the director of research for the Sales Education Foundation, and he teaches in the MBA and Executive Education programs at the University of Virginia’s Darden School of Business. He resides in Charlottesville, Virginia, with his wife. 

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