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The Conceit of Coverage (The Myth, Fiction, and Fact of PCR)

Updated: Oct 10, 2023

We live in an era of data-driven everything. Using data to help make sound sales decisions is a great idea. But sometimes the abundance of sales metrics can be overwhelming, confusing or even misleading. You should avoid complex, hard-to-reason-about metrics in favor of fundamental and intuitive factors that you can independently measure and control.


This note uses Pipeline Coverage Ratio (PCR) as an example of a common and widely-used sales metric that seems easy but can be both surprisingly difficult to interpret and unrelated to desired sales outcomes.


What is Pipeline Coverage Ratio?

PCR is typically defined as the ratio between pipeline and a revenue goal:

We frequently see advice that you need a PCR of "3.2" or "5 to 7" or whatever. As Bob Apollo notes in his blog post[1], you should be skeptical of that advice for several reasons:

  • Note the denominator involves a time interval. Specifying a PCR without that interval is meaningless. Does "3.2" apply to a quarter? A year??

  • As we will see below, PCR mixes fundamental sales factors together into a complex mess making it highly volatile, and difficult to control and interpret.

  • Worst of all, for many real B2B examples, PCR is uncorrelated to the sales goals you want to use it for.


What is pipeline coverage used for?

The core idea of PCR is a good one: a kind of insurance-policy estimate that enough deals are in process to support a sales goal. As Ben Affleck-Currie at Gary Smith Partners states[2], PCR is used to assure your board "that the sun will be shining this summer, and there won’t be a chilly wind come the Fall."


For instance, say at the start of the quarter you have a goal of $5M in new business for the quarter and $10M in total open pipeline right now. The PCR for the quarter as defined above is 10/5 = 2. The thinking goes that, so long as you have an average quarterly win rate of 50%, there is sufficient pipeline to cover the goal even if no new business comes in. If your win-rate estimate is less than 50%, then you might face a shortfall and require new business between now and the end of the quarter to make up for it. This sounds pretty reasonable!


So what's the problem with PCR?

Although it seems easy, PCR is deceptively complex and problematic:

  • In order to determine a required coverage ratio, you need to have an idea of win rates for the quarter. Win rate estimation requires care and is often computed in ways that are misleading (see our blog post on that [3]).

  • Total pipeline adds up the amounts of all open opportunities without regard to stages (except that it's often defined for sales-qualified and above stages), staleness, deal size, or other cohorts. The average win rate of that mix can be wildly unrepresentative of what actually closes.

  • PCR is very sensitive to large/outlier deal sizes.

  • It's only an "insurance policy" estimate—many sales operations generate a substantial amount of new pipeline that closes every quarter, and more over longer periods. PCR ignores new pipeline generation. And the PCR estimate itself is often too loose to provide guidance for required new pipeline.


Proof of these problems is illustrated by the following real-world case studies. The plots show historic 90-day PCR values (filtered by new and expansion business, for sales qualified and above deals, with close dates in the next 90 days) relative to actual amounts won over the next 90 days from each date. In other words, instead of a revenue goal in the denominator of the equation above, the actual amount won over the next 90 days is used. The gray vertical bars indicate the first week of each quarter.


Actual historic quarterly pipeline coverage ratios for Company A vary considerably from a low of below 3 to a high over 12. Company B's ratios vary between 7 and 15 or so. Both companies were healthy and, for the most part, growing over the displayed historic intervals. We have observed similar plots like this for dozens of companies.


These plots tell us that pipeline coverage ratio is not particularly correlated to sales outcomes. That means that a guideline like "average pipeline coverage ratio of 3x" or whatever doesn't really help you plan your business—and worse, might cause a false sense of security or alarm.


Managing Chaos

Managing your business to a target PCR may exacerbate that false sense of security. If your pipeline does not meet your PCR target, what do you do? Rally the troops, tell them that they need to get their pipeline up to meet your target. Will salespeople purge stale deals? Add less qualified ones? Inflate the amounts of existing deals?


In his book Understanding Variation: The Key to Managing Chaos, Donald Wheeler observes that:

Pressure to meet any arbitrary numerical goal will most often result in the distortion of either the systems, or the data, or both...

And

setting goals does nothing to change the system.

You absolutely should add more pipeline. What you want to know is how much pipeline you need to meet your plan. PCR does not reliably tell you that.


We really have just two basic issues here:

  1. What do you change to improve outcomes and meet goals?

  2. How do you know how much pipeline you need and when you need it?

Fortunately, both can be answered in a simple and direct way.


What to Do

Instead of managing inscrutable and unreliable metrics like PCR, simply manage to actual revenue goals directly. Model your sales process using basic factors you can control like win rates, deal generation, and deal size to estimate how much new pipeline you need and when you need it. Use that model to inform resource allocation. It can show you which deals are most impactful to work on, and which ones are most worrisome.


This is the simple and robust approach to sales forecasting and optimization that works for the short- and long-term. It illuminates the effects of changes in each factor, powering an informed discussion about how much lead flow, change in deal size, or increase in win rate you need to meet a plan. Simple, predictive, and easy. That’s Funnelcast.



References

  1. https://www.membrain.com/blog/exploding-the-3x-sales-pipeline-coverage-myth

  2. https://garysmithpartnership.com/pipeline-coverage/ (A nice skeptical take on this topic, worth reading and with good suggestions.)

  3. https://www.funnelcast.com/post/great-win-rate-expectations

  4. https://www.revenue-inc.com/blog/the-3x-sales-pipeline-coverage-ratio-is-wrong/

  5. https://www.propellercrm.com/blog/sales-pipeline-coverage (alternative formula)

  6. https://www.clari.com/blog/pipeline-coverage-best-practices

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