In a crude bit of irony, sales, which is so critical to the success of disruptive companies in the tech industry, is itself stuck in the Stone Age. As a caveman myself, I can tell you – I’ve spent over ten years in the field and built sales teams from the ground up at four companies including Nstein (acquired by Open Text) and my own Semantria (acquired by Lexalytics). Yet I’ve had to fire 90% of the salespeople I’ve hired – and my managerial colleagues across industry verticals have experienced much of the same.

Bringing sales out of the Stone Age

I founded to bring sales out of the Stone Age and into the 21st century and boost sales performance. What do I mean? Simple. We’re living in the world of pre-Moneyball baseball. Salespeople today are hired based on a manager’s past experience, gut feeling, and intuition. This process potentially invites discrimination and bias (humans are psychologically inclined to feel closer to those that look and act like them) and does a poor job of determining which sales reps will be the best in terms of sales performance for your company.

The process doesn’t get any better after salespeople are hired. Managers are forced to judge their teams’ sales performance based on crude metrics of input data (emails sent, sales calls made) and output data (revenue booked). To make matters worse, these numbers are all based on self-reporting – which is often cumbersome and inaccurate. Sales representatives are likely to be some of the busiest people in your organization. They don’t want to have to manually enter every sales activity into Salesforce and often don’t – leaving the data incomplete and inaccurate.

The main reason why it is so hard to hire and measure sales reps is the lack of data about their performance outside of quota attainment.

While you can easily find out what your developer has been doing simply by checking their GitHub or Stack Overflow accounts – no comparable transparency exists for salespeople. You often only know that a salesperson is underperforming when it’s already too late and you’ve missed your quarterly revenue target. I recently met with the CEO of one of the hottest startups in the Valley. He spends an hour every Monday reviewing his sales team’s calendars and counting all the customer meetings by hand in order to get an accurate picture. That’s wrong. This data should be collected automatically – without salespeople having to waste time entering it or CEOs having to waste time reviewing it.

Mistakes are very costly

What’s more – hiring the wrong person and leaving them unmonitored can be a costly mistake. A good salesperson commands a base salary of $100,000-200,000 per year. More importantly, they’re responsible for a sales pipeline of $2-3 million in revenue that won’t get closed until you hire a replacement who then needs to spend time getting ramped up, learning about the product and establishing relationships with customers. One of our investors, a VP Sales at Cisco, estimates the cost of wrong sales hires to be around $1.5 million dollars. What sales management needs is to be able to fix the problem before it gets to that point. In other words, managers need more data and visibility into their sales team’s work and performance.

What do we know about sales reps’ performance?

Let’s take a step back. When a salesperson first joins your team what do you know about them? Basically nothing. Yes, you may know about their track record in hitting and missing quotas, but whether that record will translate over to your company is anyone’s guess. How about once a salesperson has worked for you for two years?

OK, you know more at that point – how they’ve interacted with your customer base and how they’ve performed on a quarterly basis. But that’s about it. You know that your star salesperson closed ten times the number of deals as you’re worst performer but you don’t know why. What behavior does your star salesperson exhibit that your worst performer does not? That’s important because with the right training every member of your sales team can be a star and you can look for traits in potential hires that mirror those of your top performers.

Knowing whether your salespeople have failed or succeeded is easy – understanding the reasons why is far more difficult. Continuing to measure our salespeople’s performance the way that we do today is akin to judging a basketball player’s performance solely on the basis of their PPG. That will tell you who your top scorers are – but it doesn’t say anything about who was good at defense, passing, etc.

We built the world’s first AI-powered management platform for sales

Ultimately, what my team and I hope to accomplish at is to establish a more equitable system to evaluate sales performance – one that helps teach everyone the skills necessary to be successful. We’re starting with salespeople but our vision extends much further than that. With a system in place that relies on data instead of intuition, we can help everyone reach their true potential by identifying their strengths and weaknesses and outlining concrete steps through which they can improve.

Let’s not wait until employees have failed to take action. With the right mix of data and sales analytics, we can nip problems in the bud. Some people think of what we do as Moneyball for salespeople. We call it People Intelligence (PI) because BI is so 2009 😉 I do hope that you’ll join us on our quest to build a more equitable workplace.

Want to find out how can level up your sales team? Get a demo, or read our blog to find out what else we’re working on!