The CEO of Ideal Somen Mondal recently spoke with Sales for Life about using data to build high performance sales teams. This is a segment of his interview. To watch the full session on-demand as part of Digital Sales Camp, click here.
Using data to build a sales team is important because analytics is all over the news, specifically in HR. Goldman Sachs recently announced they use algorithms to hire. Silicon Valley uses algorithms to get away from hiring biases. Blind hiring has become a big thing.
At the end of the day a better sales team means more money for you and a more productive company.
Sourcing: Why It’s Broken
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It’s inefficient. Recruiters have to manually scan hundreds of resumes.
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It’s inaccurate. Recruiters spend, on average, six seconds of looking at a resume.
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This leads to people being lazy. They typically only look at the last title of someone’s resume.
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Bias. It’s a known fact that people with names such as Michael Smith are more likely to be interviewed than people with names such as Somen Model.
Interviewing: Why It’s Broken
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Relying on gut feel. Our data tells us only 13-22% of the time a recruiter can tell if a candidate is lying or not. Would you let a hedge fund manager use his or her gut feel to make decisions? Absolutely not. You want to use a science-based approach. This is why interviewing doesn’t work; it’s really based on your gut feel.
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Superficial similarity. A candidate walks in the door and you realize we both like the same basketball team. We both went to the same university. Immediately, based on these similarities, you have a bias towards this person.
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Sales managers and recruiters are easily impressed. A joke here, a good suit there. Salespeople are really good at convincing others they’re a good fit. But that’s actually not a good way to hire someone.
How many times have you been in an interview when you thought someone was great, but they ended up not working out?
These are the problems that we see in the traditional interviewing process. Laszlo Bock, the SVP at People Operations at Google, had a great quote about why interviewing doesn’t work. He stated:
“On the hiring side, we found that brainteasers are a complete waste of time. They don’t predict anything. They serve primarily to make the inverviewer feel smart.”
Scaling: Why It’s Is Broken
The first problem: it’s extremely time consuming. It takes about 40 hours to train each individual salesperson. People usually think the bigger the company, the bigger the pool, the more people you attract, and the easier it is to hire great salespeople. That’s actually incorrect. The larger the pool, the harder it is to sift through everyone and pick the right people.
The second problem: using referrals as a valid method to receive top-performing salespeople. As you’re scaling your sales team, you’re thinking of different ways to bring in candidates. One of the obvious ways is to put a referral system in place and try get as many people that are friends of friends and colleagues to come through the door. That actually doesn’t work. All the research has shown that top-performers only come from top-performers. The problem with the referral system is you’re getting referrals from everyone in the company.
Because of these two problems, it’s extremely hard to scale a team without a data-based approach.
On a personal note, I’ve had a lot of problems scaling a sales team. At my first company, we would hire two sales people knowing one would fail. Imagine the training cost, the loss in revenue for not having the right person. So I have first-time knowledge knowing how painful it is to hire the wrong people.
How Data Solves These 3 Problems
Sourcing Using Data
If there’s one thing you can do quite easily to improve their sales process, it’s to start doing assessments on everyone that comes through the door. From experience, we found that a data-based approach reduces time-to-hire from 41 days to 28 days on average (32% reduction).
Quality of Hire
Were the people hired doing better? The average productivity for a company using a data-based approach increased productivity by 20.7%.
Interviewing Using Data
One essential takeaway is to use a structured interview process. How many times have you gone into a company where one manager asks a set of questions, gives you the okay, and the second manager, maybe the VP of sales, asks you a completely unrelated set of questions. When those two people confer there’s inconsistencies because they asked different questions. That leads to bad hires.
A structured interview process will do three things for your hiring:
1. Increase validity
If you have a standardized way of asking people questions about their knowledge, skills and personality that are consistent among all the people you’re interviewing, you increase validity in your interviewing process.
2. Increase reliability
By having a standardized set of questions but asking them in the same order, you increase validity in the data you’re receiving.
3. Reduce errors
If you have a set numbers of questions, if you have the right order, if you introduce a systematic way to scale and rank each one of those answers, you can compile all of that data amongst all of the managers who are looking at the candidate and provide an objective case on whether this person should be hired or not.
Scaling Using Data
How do we fix all of the problems using data?
Automate as much of the manual tasks as possible. Resume sorting and pre screening typically takes up to 50% of a recruiter’s time. That can be shortened by a great deal by automating the process of sending out an assessment directly from your applicant testing services. All this functionality exists today. You can introduce this right now and reduce your time-to-hire by 32% by automating simple tasks such as resume sorting.
Leverage talent marketplaces that already have scale, personality and culture fit built in. There are traditional job boards that just look at your text resume. The new generation of job boards include assessment data pre built into it, so you don’t have to waste time just looking at someone’s work history or someone’s resume. You can take a more holistic approach of assessing candidates before you even bring them in for an interview.
Case Study: IntelliResponse
What numbers can you expect if you implement a data-backed approach to sales hiring? We looked at a company in Toronto called Intel Response, and noticed many common threads.
Challenges:
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Trouble scaling their team.
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Overworked HR & Sales Management Teams.
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Not sure how to assess culture fit.
We looked at a before and after and the numbers are really telling. The way we quantify a better hiring system is looking at three factors: time-to-hire, quality of hire and attrition rate.
Data-Backed Approach Improved Quality of Hire
In the world of sales, quality of hire can be defined as the improvement to ramp up period, as well as the performance of the sales reps. IntelliResponse noticed:
-Ramp Up Period: 42 Days (vs. 75 Days)
44% Improvement
-Performance: 127% of Quota (vs. 95%)
33% Improvement
-Time-to-hire: 16 Days (vs. 60 Days)
74% Improvement
-Attrition Rate: 35% Improvement
The #1 Thing People Forget: You Need To Show Company Culture
How many times have you gone to a job posting and it’s the same generic sales job with the same generic benefits that don’t give any colour to the company, the way people work there, or the culture in general? The best sales team attract the best salespeople because they attract by showing culture.
What does that look like?
Showing a video illustrating what it’s like to work at that company on a day-to-day basis. Interviewing some of the great sales people who work there. Interviewing the VPs of sales, the sales management. People want to see a progression in their career, they want to see what it’s like to close a deal there.
If there’s one thing you shouldn’t forget, it’s really going the extra mile and putting rich media on your website. Do whatever you can to show off the great culture you’ve built. This will act as a magnet to new candidates.
In Summary
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HR Tech is taking off.
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Specific problems for interviewing, sourcing and scaling are broken but you can fix them with data.
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Real world results: companies that have been successful implementing a data-backed approach.
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Showcasing your culture should be a major focus.
Data works, Gut feel doesn’t
Think about the movie moneyball and how they use data to pick the best baseball players. This is what’s happening in other industries and specifically, sales. Why sales? Sales is already a data-driven profession. Everything that happens after someone is hired is completely data-driven. How many calls are they making? How many opportunities are they creating?
Why isn’t everything before that data-driven? We’re now getting to that point.
Data-driven hiring is going to be a common tactic throughout the sales industry. If you use this approach, you’ll be way ahead of the curve.
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