Every enterprise sales rep has probably heard this rule of thumb: Fill up your pipeline with at least 3X your revenue targets for that period, and you’ll be in good shape.

But where’s the evidence that justifies that rule? Dave Kellogg, a Silicon Valley insider and serial enterprise software CEO, once poked fun at the decades-old adage: “It makes sense: 2X seems tight and 4X seems rich. So, through the Goldilocks Principle, we ended up with 3X.”

Sales managers use pipeline coverage to get a snapshot of how potential deals stack up to their revenue targets. Checking this metric early in the current sales period — or, even better, for upcoming quarters — can alert sales managers to the most pressing scenarios: deals that are slipping, not enough prospects to hit quota, etc. But the standard 3X rule isn’t a one-size-fits-all solution and won’t give sales organizations the accuracy they need to hit their numbers.

So how do you set the right goals for your organization’s pipeline coverage? Let’s take a look.

What is pipeline coverage and how do you calculate it?

First, we need to define pipeline coverage. Pipeline coverage is the sum of all your sales opportunities compared with your revenue target. For example, if your revenue target is $1 million and you have $1 million of pipeline, you have 1X pipeline coverage. In that situation, you’d need to close every dollar to make your quota. On the other hand, if you had $3 million in pipeline, you’d have 3X pipeline coverage.

What’s the difference between pipeline coverage and forecast coverage?

Where pipeline coverage captures all potential opportunities from brand-new leads to prospects ready to close, forecast coverage is a smaller, more focused view. Forecast coverage takes into account historical win rates and generates a weighted forecast for each opportunity.

Let’s use the hypothetical example above: a $1 million quota for the quarter and 3X pipeline coverage. Of that pipeline, you factored in historical win rates and calculated a forecast of $700,000 for the quarter. In that case, your forecast coverage is 70%.

How much pipeline coverage do you actually need?

There are multiple factors that impact your company’s ideal pipeline coverage:

• your product
• the segments you serve
• how long your sales cycles are
• and much more.

There’s no one-size-fits-all pipeline-coverage approach.

At Clari, we encourage companies to make informed decisions based on their data. So far, we’ve seen that 3.2X coverage at the start of the quarter has proven to be effective for opportunities that have been partially vetted by the sales team. But again, that 3.2X standard is based on our existing data that may or may not include companies and products that are similar to yours.

“There's wiggle room on every side and a lot of it has to do with deal execution,” says Kyle Coleman, VP of Growth and Enablement at Clari. “Let’s say your sales process is really efficient and your sales team is really humming and they’re closing every dollar that they qualify. They don’t need 3X coverage. They could get away with 1.5 or 2X coverage. On the other side of that coin, if your sales team is operating inefficiently and closing sub-optimally, then you might need 4 or even sometimes 5X coverage.”

So how do you find the magic number for your sales team’s pipeline coverage? Here’s a quick overview of some tools to figure that out.

Create synergy in your organization to turn pipelines into revenue

The people in your sales organization need to know how to work together and methodically use their pipelines to close more deals. You might have all the right data, but if your sales leaders aren’t capitalizing on the data to collaborate and coach their sales reps properly, you’ll lose out.

Consider the following example. Okta, which provides cloud-based identity management solutions to 6,000+ customers, was struggling with forecasting and pipeline generation in 2016, a year before it filed to go public. Executives knew they needed to change their inconsistent and manual management processes.

Okta chose Clari to consolidate data from all its major systems, including its CRM and business intelligence platforms, to create better visibility. The company went further by developing new definitions and processes, which triggered powerful collaboration among its go-to-market teams and other key stakeholders.

Okta shared its forecast and pipeline transformation in a case study by TOPO, a research and advisory firm.

3 strategies to healthy pipeline coverage

The Okta case study offers 3 steal-worthy ideas for sales managers to improve and capitalize on pipeline coverage:

1. Define specific expectations around behaviors. Simply instructing your sales reps to maintain a certain amount of pipeline coverage doesn’t offer much guidance. Give them specific action items to do weekly or monthly in order to continue generating new opportunities (e.g., meet with 3 new accounts each week, attend 3 networking events per month, spend 8 hours a week organically building your own list using LinkedIn).

2. Assign pipeline-coverage expectations to specific points in time. We all know we should plan ahead, but it’s easy to get caught up in your hitting your numbers this quarter. But what about 6 or 9 months from now? Guide your sales reps with specific, pipeline coverage goals for future quarters. Using historical data, you should be able to identify exactly how much pipeline you need for next quarter at a given time this quarter.

3. Alternate forecast and pipeline management meetings. Both pipeline and forecast need to be treated as high priorities throughout the revenue organization. If forecasts are dominating team meetings, your sales reps aren’t getting the regular support and feedback they need to cultivate healthy pipelines. Schedule weekly meetings with your sales organization, and alternate the focus between pipeline and forecast. Make sure to have detailed agenda prior to each meeting.

Pipeline coverage is a critical metric in your sales success, but at the end of the day, it’s only one piece of the puzzle.

“Efficiency, process and execution — that's what it all comes down to,” Coleman says. “Everything else — all the other analytics, all the other numbers that you have — completely depend on how well your sales team can actually execute.”