“Do we have enough pipeline?” Sales leaders hear this sentiment in their sleep. It’s what drives them. It’s also their #1 challenge. Historically we’ve seen this question answered by looking at pipeline coverage. Do we have enough pipeline heading into a specific period to succeed? Unfortunately, CROs aren’t always given enough factual information about the health of a funnel to see a clear picture. But, why?
Before they can answer whether or not salespeople can hit their numbers, it’s essential to break down how they are established. Where do revenue expectations originate? And how accurate and helpful are they in predicting a company’s forecast and growth?
Assessing funnel health is a common struggle that leads to missed forecasts. Reps want to feel good about their funnels, so they hide behind timing, pushes, and a focus on real opportunities in 1:1s. They inflate their funnels which results in an inaccurate view of them. Then, management roll up the forecast and misses the number.
Why Do Companies Care About Pipeline Coverage?
Short answer: Because there wasn’t a good alternative.
Longer answer: Sales teams have traditionally used pipeline coverage to help forecast the amount of business they’ll close during any given quarter.
This calculation is simple: pipeline/quota. So, if a company’s pipeline coverage is 3X, a rep with a $500,000 quota would be expected to have $1,500,000 in pipeline to meet their goal.
While easily understandable, pipeline coverage often creates a false narrative. Making predictions based on the sheer volume of opportunities fails to consider the actual health of those deals. How have they progressed? How much activity has occurred? Is the customer engaged and responding? Are we involved with the right buying group? That’s just the start.
Pipeline Quality vs. Quantity
Yes it’s important to understand the value of the pipeline and that relationship to sales goals, however today’s revenue teams should spend less time on coverage (quantity) and focus more on funnel quality. Why? Because at the end of the period, all that matters is whether or not the deal closed.
Of course, knowing if you have enough funnel to hit the target will always be necessary. But giving people false hope for deals by requiring 3-10x coverage isn’t a strategy, either. Genuinely understanding the quality of a deal creates proactive conversations early in the sales cycle and helps sales teams to course-correct where needed and forecast more accurately.
What’s Changed in the World of Pipeline Coverage
Two words: pipeline visibility. Pipeline coverage is an artifact from a time when sales teams didn’t have the proper tools to measure the health of an opportunity. Sales Leaders had no choice but to lean heavily on coverage because they never had an effective way to evaluate funnel health due to lack of trusted data.
Today, sales leaders can turn to revenue intelligence platforms to assess the sales funnel and see how it has evolved rather than interrogating reps or hoping they provide accurate views of their opportunities. Automation can capture all of the digital engagement with a customer. CROs can leverage that activity and engagement to assess the likelihood of winning a deal. Rolling this up through the entire funnel offers a clear depiction of where they will finish and why.
Many companies also use these platforms as early alert systems to prevent potential missteps and gaps early in the process. Hence, sales leadership can change the outcome before it’s too late.
The bottom line: companies should be looking to take advantage of new ways to gather and interpret data within the sales funnel. Machine learning is the future. And the future is now.
How Machine Learning Can Replace Pipeline Coverage
What else is better than Pipeline Coverage ratios? How about data-driven, machine learning predictions that assess the current funnel against historical wins and losses.
Time is your reps’ most significant investment. They should be spending their time on the deals that have the highest likelihood of closing. Machine learning offers a deep well of predictability that can help sales teams understand how well a deal progresses based on all the captured data in the CRM or anywhere a rep records information in emails, calendars, and notes. It can also help assess how well the deal is progressing based on previous sales that closed. With every successful deal, machine learning technology can better predict outcomes.
For example, a sales rep may begin to think that a particular deal is starting to shape up like a successful past deal. Or the deal may be falling apart due to low activity and engagement. Assessing each deal qualitatively based on past experiences can help sales teams and management determine the best course of action.
Sales reps will always look at a total pipeline and ask themselves if they have enough in it. Realistically, if you land a million dollars in sales and your team has $10 million in the pipeline, that’s excellent news. But the goal should always be to understand and better assess the actual health of each deal. Anything sales teams can use to help understand where certain obstacles lie and close more deals will help them improve their job performances. And from a manager’s and a CRO’s perspective, the goal is to always come up with an accurate forecast.
Without deep accountability, sales reps can sandbag opportunities and say they have enough pipeline. When that happens, predictability is impossible. For managers, it’s challenging to build trust with a VP or a CRO if sales forecasts are never correct. And for CROs, it’s imperative to build that trust and predictability with the board. The only way to solidify that chain of trust is for the entire sales team and managers to have a genuine understanding of what’s happening in the funnel. They might even find out that less of a pipeline is needed. It’s all about the data and working within a highly accurate feedback loop. You need a reliable forecast to create concrete goals and meet those numbers.
Everyone Wants to Close Deals and Do a Good Job
In an ideal environment, managers can be mentors, guides, and troubleshooters. And sales reps want to feel like they’re doing a good job and getting results. Using predictive data, not just a simplistic ratio, teams and managers can get an honest assessment of the pipeline which can help negate fears and set everyone up for success .
For more on Improving Pipeline Visibility, check out: The Ultimate Guide to Pipeline Management.