Quick, go ask any sales manager or Silicon Valley how much pipeline you need to make your quarter.
The answer you will hear: 3x. Always, everywhere, every time. Let’s talk about why that’s true, what it means, and what to do about it in this post.
First, let’s define some terms. What is pipeline? Pipeline for a period is the sum of the value of all opportunities with a close date in that period.
That is, quarterly pipeline for 2Q13 is the sum of the values of all opportunities with a close date on or before 6/30/13. (Note that in most companies saying before 6/30/13 as opposed to “on or before” cuts the pipeline in half. But that’s a different story.)
This begs the question: what’s an opportunity? I have two definitions: (1) the way you track deals in your salesforce automation (SFA) system, which these days is typically Salesforce.com, or (2) a possible deal that a salesperson is willing to be asked about every week by his sales manager on a forecast call. (By the way, I love definition 2 because that’s how “opportunity” really is defined from the viewpoint of the salesperson.)
This in turn begs the question: how do you value an opportunity? Most organizations should have rules for establishing the value of an opportunity, given its evolution in its lifecycle. Early stage opportunities should either count as zero or some agreed-upon placeholder value. Mid- and later-stage opportunities should have a value which is the likely amount that the deal will close at, including discounts and concessions made during final negotiations. (Always be sure that this value has been socialized with the customer and is not simply a figment of a salesperson’s overly active imagination.)
So where does the magical 3x coverage ratio come from? I don’t know the history, but I can say that long before I saw — and I mean years — my first salesforce automation system, I heard sales managers speak of the rule of three. It makes sense: 2x seems tight and 4x seems rich. So, through the Goldilocks Principle, we ended up with 3x.
Back then, it was kind of harmless; you couldn’t easily track the pipeline because deals and forecasts were being managed in a conglomeration of spreadsheets. But along came SFA with Siebel, and its democratization via Salesforce, and — bang — now every sales manager on the planet could quickly and easily calculate the total pipeline for a salesrep, for a region, and for the company.
What happened next should be no surprise.
Every time a sales manager had salesrep whose pipeline didn’t have 3x coverage, they beat the salesrep until they did. Every time an regional manager had a district manager whose pipeline didn’t have 3x coverage, they beat the district manger it did. Every time the worldwide sales VP had a country without 3x coverage, they beat the country manager until it did. Heck, it even worked on overlays: every time a product manager with a revenue number saw a country without 3x coverage of his/her product, they beat the local product manager and the local sales director until it did.
And, fairly quickly, every company on the planet had 3x pipeline coverage.
But, of course, it was all meaningless because it was a giant self-fulfilling prophecy. And one that many or most organizations still perpetuate today.
What management should do is to beat on salesreps to show the real pipeline, as they believe it exists, using well-defined staging and valuation rules. They should never mention the 3x, nor institutionalize any coverage ratio because, once you do so, you can be certain of only on thing: you will have that coverage ratio in your pipeline. Whether that pipeline actually converts into sales at the inverse of the ratio (so you can achieve your sales target) is an entirely different matter. And most of the time it certainly won’t.
We’ve taken a perfectly good metric and we’ve ruined it by generalizing it, institutionalizing it, and communicating it. Its predictive value is now zero. Such metric abuse should be a crime.
Instead, we need to think about the problem differently. To do this right, these coverage and conversion rates should be:
- Emergent. They should regressed from your actual data, not taken top-down as rules of thumb.
- Personalized. They should be tailored to a rep, a region, or product. Example: Joe usually closes 40% of his pipeline so 2.5x coverage should be good enough for him or France typically needs 3.5x coverage to hit its number.
- Secret. As you as you tell the head of France he needs 3.5x coverage you start the metric abuse cycle and destroy the predictive value of the metric. Instead, management should direct marketing or telesales should be instructed to focus on pipeline development when they see insufficient coverage, without any explicit reference to the 3.5x.
- Time varying and to-go based. As the quarter proceeds business closes along the way so coverage ratios can get quite complex. They need to be based on business to-go (to get to plan) and based on historic linearity patterns. While the math gets cumbersome, this complexity is good because it eliminates the possibility of a single number getting burned into the organizational consciousness. Instead of everyone saying “3x,” it actually sounds like: ”in week 7, France has 2.2x to-go coverage and they typically need only 2.0x to get to plan.” Some companies abstract this into a “waterline” that shows what coverage is needed by week given both personalization and linearity.
So the next time you ask a sales manager how much pipeline he/she needs to make a quarter, wait for them to say 3x, and then start asking questions.