One of the most unhelpful “rules of thumb” in B2B selling is the long standing and widely quoted myth that the benchmark standard when it comes to sales pipeline management is 3* quota coverage.

I’ve struggled to find any original research that justified this - and even if there was any, the concept has been around for so long that any original research must now be well and truly out of date.

This 3* rule of thumb is no more accurate (and not much more useful) than a stopped watch that happens to tell the right time twice a day.

So - what is the optimal level of sales pipeline coverage? If you’re looking for a lazy, simplistic general answer then I’m afraid you’re inevitably going to be disappointed - because the only universally accurate answer is “it depends”...

The sewer systems of of our towns and cities are struggling to cope with a phenomenon known as the “fatberg”. These fatbergs are formed by an unappetising combination of oil, grease, food waste and other materials that have no place in the system.

Unfortunately, as these fatbergs harden and grow, they cause obstructions that require specialist equipment to remove. The problem is largely avoidable, it’s obviously a pretty unappetising story, and you may wonder why I’m sharing it with you.

Something very similar is going on in many sales pipelines. They are clogged with so-called opportunities that haven’t moved for ages and are unlikely to close any time soon. And the longer you delay clearing them out, the harder it gets to remove them...

Sales forecasting is hard. For proof, you need look no further than the 2018 CSO Insights Sales Performance study, which reported that on average a little over 46% of all forecasted sales deals actually resulted in a win (never mind the timing).

Even the top performing sales organisations did only marginally better - at just under 54% forecasting success rate on a deal-by-deal basis. Now, there are obvious reasons why accurately predicting the outcome of every complex buying process is fraught with difficulty.

But it’s hard to avoid concluding that we ought to be able to do better. And I’m going to suggest that one of the reasons that organisations struggle to do better is down to simple statistical naivety...

If we’re in sales, there are two obvious monetary measures of our success: revenue and margin. Revenue is particularly important for organisations that are primarily concerned with driving top line growth. Margin is particularly important for organisations that are primarily focused on growing a profitable bottom line.

The relative importance of these two metrics can vary according to what type of business and what stage of development we are in, but I can’t recall coming across a B2B sales organisation that hasn’t defined one or the other (or both) as their primary success metric.

But what else should we be measuring?

Other than an appropriate level of product knowledge, what are the key attributes of a good B2B sales person? Interpersonal skills? Emotional intelligence? Business expertise? Curiosity? The ability to build rapport?

These are all critically important to modern B2B sales. I can’t imagine hiring anyone into a new sales role that didn’t exhibit these attributes to some degree or another, together with a commitment to continued self-improvement and personal development.

Hopefully, you feel the same way. But I want to highlight another couple of attributes that seem to me to be of central importance.

They are self-awareness coupled with self-honesty, and it’s hard to demonstrate one without the other. We don’t want our sales people fooling either themselves or us. But it’s not just a matter of encouraging these virtues. As sales leaders, we need to ensure that we do not unknowingly or unthinkingly suppress them…

One of the abiding urban myths that misinforms sales pipeline management is the idea that sales people need at least 3* pipeline coverage in order to achieve their quota. Where this “golden number” came from, nobody seems to know, but it’s a fair bet that it dates back beyond the Neolithic.

Another widespread urban myth is the idea that whenever you have a bigger sales pipeline, you end up selling more. It’s the sort of misconception that leads marketing teams to drive to create an ever-larger number of MQLs without any regard for how many of them ever actually result in any revenue.

The simple fact is that there is no one-size-fits-all answer to the question of what the optimum coverage ratio for any specific sales pipeline is…

One of the biggest challenges to the accuracy of any sales forecasting system lies in accurately predicting the close date. It’s a particular problem this month, at the end of the sales year, because aligning everything necessary to close a bookable order requires a great deal of preparation, and quite a bit of luck.

Wandering close dates are another common challenge, particularly because they rarely seem to wander closer to you, but always seem to prefer to drift off towards the horizon.

Now, I know this is hard. I know that sales people can always be prey to external events. But there are a handful of simple measures that every sales leader could and should put in place to mitigate the problem…

As we're all very well aware, complex sales are complicated. There are subject to a wide range of factors that are outside of our direct control. It's no wonder that forecasting if and when any individual deal is likely to come in is such a challenge.

Research by CSO Insights has shown that less than half of forecasted deals actually close on the date and at the value originally expected. Many close dates slip (often repeatedly) and many of these forecasted deals never close at all.

If you’re in a short cycle transactional sales environment, high deal volumes and the law of averages can blur the impact of this uncertainty. But if you’re involved in a high-value long sales cycle situation the impact on revenue can be much more serious…

Accurate sales forecasting is a particular challenge in high-value complex sales environments with lengthy sales cycles. Given that we are trying to anticipate the collective decision of a group of decision makers, it’s safe to conclude that perfection is an impossible goal.

But it’s also clear that every complex sales organisation has significant room for improvement when it comes to forecast accuracy. Studies by CSO Insights and others have concluded that average forecast accuracy on a deal-by-deal basis has remained stubbornly stuck for years at below 50%.

This tends not to be an issue in high-volume, low-value transactional environments, where the inability to accurately predict the outcome of an individual deal gets washed away by the law of averages. But if you’re only working on a limited number of high-value opportunities, a few misjudgements can make the difference between having an excellent quarter or missing by a mile…

Regular readers will recall that I am no great fan of the default approach taken by so many CRM vendors, in which individual opportunity forecast probabilities are based on applying the same percentage to every opportunity that has reached a given stage in the sales process.

Many CRM users simply accept the default “out of the box” percentages without questioning them, or validating them against actual outcomes, or are confused about whether the % is measuring progress through the process or the probability of winning.

It’s no wonder that sales forecasts are often so wildly inaccurate. But there is a better way of thinking about this…