Let's play a quick game. Spot the outlier: the speed of light, the atomic mass, pipeline coverage ratio, and the Planck mass.
That's right, pipeline coverage is not a physical constant which can be treated as a universal truth.
So why do (almost) all sales teams, regardless of size, maturity, and industry use that same ratio? If every team and sales process is different, shouldn't they be treated differently? On top of that, since no one really knows where the mythical 3X multiplier came from, you've likely had some challenging conversations with your team that go something like this:
You: It looks like we're not quite where we need to be for next quarter.
Manager: Why?
You: Because we need more pipeline.
Manager: Why?
You: Because we need to have a 3X coverage.
Manager: Why?
You: ... it's a common practice ...
If you've had a conversation like this, you probably feel the same way you feel when a kid has asked "Why?" one too many times and has finally gotten to the fundamental question that you're expected to know the answer to as an adult. Too ashamed to admit that you don't know the answer, you simply blurt out, "Because I said so!" Of course, your sales team is not composed of children (at least we hope not) and the reason they're asking is well-founded—they simply need a better understanding of why they have a certain target so that they can understand whether or not they're spending their valuable time on the right tasks. Not spending enough time on future pipeline generation is just as detrimental as spending too much time on it and not enough on the current opportunities.
So, as a well-intentioned sales professional, anticipating the question, you try and tackle it.
But what you quickly found was that even if you were brave enough to try and calculate the appropriate pipeline coverage ratio for specific teams and business segments, you probably ran into one of the following issues:
- You didn't have the right data or it was out of date by the time you got it to the team
- The time spent revisiting historical data manually for each team was soul-crushing
- Even if you did have the data and patience to tackle the problem, you weren't really sure how to go about it
We're fortunate to be in the midst of an industry-wide revolution akin to the Enlightenment for sales. According to Gartner, algorithms and process automation are converging in ways that are permanently changing how sales organizations engage with prospects and customers. The deployment of AI-related technologies will be a vital part of the future of B2B sales organizations, and by 2020, 30% of all B2B companies will employ AI to augment at least one of their primary sales processes. Sales is now finally becoming a truly data-driven function which relies less and less on ad-hoc reporting and "rules of thumb."
So how can you create pipeline-generation goals with your team in a scalable yet intelligent way?
At Clari, we've already solved the problem of opportunity scoring and current quarter projection with our state-of-the-art AI engine by looking back at historical patterns, so we thought the logical next step was to create on-the-fly pipeline suggestions available for any business segment and team so they can know where they stand at any given point during the quarter and exactly how much pipeline they need to generate to hit the number.
Rather than having to manually inspect historical data for each segment and get the data out fast enough before it's out-of-date into a spreadsheet or BI tool, you can simply leverage Clari and have a conversation around real-time data based on facts and science rather than a rule of thumb. You can then focus on discussing strategies to close that pipeline gap rather than debate the numbers.