Sales VPs today are spending exceedingly disproportionate amounts of time trying to figure out what is going on in their sales teams in order to ensure sufficient pipeline generation. This is an acute problem for sales and revenue leaders as it is often causes reps to fail to make quota. 

Pipeline generation is often measured via a key sales indicator called pipeline coverage. Pipeline coverage is generally measured by comparing a team’s pipeline value to the amount of deals their quota requires them to close. More specifically, pipeline coverage is calculated by dividing the sum of all your open opportunities by the quota required for a given period. In SaaS companies, a general rule of thumb is to have 4x pipeline coverage, meaning four times more open opportunities than what is required by the quota.

The Drivers of Insufficient Pipeline Generation

If you are not generating enough pipeline, or do not have sufficient pipeline coverage, the question then becomes: how do I solve it? Like most things, this depends on the root cause.

Typically, there are two drivers that lead to insufficient pipeline generation:

The first is quite simple: insufficient prospecting. This could be a quantitative aspect, meaning the sales team is simply not spending enough time prospecting and as a result do not generate enough opportunities every quarter for there to be sufficient pipeline. 

A second driver is a lack of engagement ability. This means that your sales reps may be spending enough time prospecting, or have sufficient prospecting activities, however they are unable to communicate effectively to potential buyers in a way that compels them to act. A lack of engagement ability can be exhibited in emails, phone calls, social media messages or in person meetings.

A Real-Life Example – Pipeline Generation

A sales leader at a commerce software company had problems both in terms of pipeline generation and pipeline coverage. They had a sales team of over 35 reps, with 14 sales development reps in charge of generating opportunities and 11 account executives tasked with closing deals. The company was already using industry standard CRM, marketing automation and sales engagement tools however fluctuations in the quantity and quality of opportunities meant that their pipeline coverage was less than 2x, significantly lower than the recommended 4x.

To figure out why this was happening, the company’s SVP of Sales turned to Cien. After syncing the company’s Salesforce data with Cien, he discovered that the main challenge wasn’t generating opportunities but closing them. Many deals were actually properly qualified by the sales development reps, and while the AEs were justifying losing early stage opportunities due to insufficient lead and opportunity qualification, something else was at play here. By measuring the value generated by the marketing, sales development and account executive teams to the overall revenue generation process, Cien was able to not just count deals, but also the value created by each part of the sales process to understand whether the problem was with the marketing, sales development or account executive team.

As it turned out, the company’s insufficient pipeline coverage was due to the fact that the account executives were not always successful at identifying the actual decision makers and looping in the relevant stakeholders.

In this case, applying artificial intelligence to their sales data helped the company solve two problems in a single stroke: understand the drivers of pipeline coverage and improve sales performance. 

By implementing Cien’s recommendations, the company could properly understand which reps needed to work on better opportunity qualification and which reps needed to spending more time prospecting. In addition, by helping the team identify it’s most valuable leads, the reps were able to focus on the most important deals, thereby increasing pipeline velocity by 22% .

Identify the Root Cause of Insufficient Pipeline Coverage

Cien looks at pipeline data as a whole and is able to understand the quality of the opportunities generated, and can re-classify the stages of deals based on each individual rep’s behavior. This can help to identify whether insufficient pipeline coverage is due to a poor lead generation by the marketing team, poor engagement skills from the sales development team or insufficient prospecting time by the AEs.

Not sure why your team is not generating enough pipeline? Request Cien’s Hidden Revenue Assessment and apply 100+ AI models to your CRM data to identify the root causes of insufficient pipeline coverage.