Could artificial intelligence simplify the hiring process?

This week saw the launch of a new recruitment platform, which uses AI and machine learning to match companies with skilled tech talent.

Snap.hr has been heralded as a must-use resource for anyone serious about a career in tech. We caught up with founder Raoul Tawadey to find out more about the tech that powers the process.

So, how does Snap work?

Raoul: Snap connects companies to the best developers across the UK and Europe. I think what's great about it is that it's so quick to hire great people. Typically, if you're using job boards or LinkedIn to make hires, you've got to send out hundreds of requests or messages, or work very manually with a recruiter, which takes a long time. There are three people in that process too – you, the candidate and the recruiter – and that often takes 30 per cent longer to arrange everything than it would otherwise.

Because we connect companies directly with candidates, the whole process, on average, happens within 12 days. And that's the total time to hire. So that's much shorter than the process would usually take and this is pretty much made possible due to the fact that we use cutting edge technology specifically in the matching part of the process. So if you speak to recruiters and candidates, one of the big bugbears they have is that there's often a mismatch between companies and candidates with recruiters. They'll say, 'It's a real pain, this recruiter puts the wrong people forward all the time,' or 'They put me forward for the wrong roles.' And it's a process that can happen so much more efficiently when you're collecting a lot of data from CVs and from those who are hiring so that you know what they're looking for, or what they're hiring for.

And that's what we do.

At Snap when we take a CV, we look at all kinds of things from where a candidate has previously worked, the sorts of companies they've worked at, the experience they've had, and the education experience they have too. And we figure out from that implicit data what could be a good fit for them going forward.

From the company side we track every part of a company's hiring process. So we know when candidates get rejected, what stage they're getting rejected at, or when they get hired, what a successful hire looks like. A lot of previous recruitment companies might have just looked at a reach out as being a success, we look at a hire as being a success - when a candidate has jumped through all of those hoops. We figure out what's unique about that person who was hired and we apply machine learning to that so that we can replicate it at scale.

Read more: How is virtual reality disrupting the entertainment industry?

And where did the idea come from?

Before Snap I ran another company where we employed quite a large dev team and I just found it was such a struggle hiring people. Where to find great engineers was a real challenge and when you went through a recruitment networks, I just felt it was so opaque. Recruiters will send you CVs with very little context around that - they're these anonymised CVs where you have no idea who the candidate is or what they're really looking to do. Often you're being sold by the recruiter on the candidate and they're being sold on you as the company so you don't know how much of that is genuine and how much of it is just being influenced by the middleman.

So I just thought it would really make sense to have a genuine connection between a company and a candidate. That makes sense because when you hire someone you want them to stay in your company longterm. You want a retained employee who's really loyal to you because they really get what you're doing. And I think that only happens when the process is organic and both parties are connecting directly without any influence from a third party trying to make it happen.

Even though at Snap we have people called talent managers in the team, who work with candidates. They're all incentivised based on how well the candidate rates their experience with Snap and not around doing a deal. It's a slightly different set up and it's working really well.

So does this use of AI mean that recruiters should be worried about their jobs?

I think that's a really good question and the way that we always think about it is that there are parts of the process where the human intervention is really important. Looking for a new job is such a big thing, it's not something you take lightly. To provide a really awesome experience you always want to have someone on call to help you through it and answer any questions you might have about a company or a process, or to discuss how an interview went.

I think that this technology is changing the job of recruiters, rather than replacing them. I think that in future they will focus on things like feedback or discussing how you feel about a role, and I think humans will always be involved in that process. But a lot of the more basic level stuff around recruitment, for example matching a candidate with a company based on what they're looking for and what they're hiring for I think is something that can be automated and scaled, and that part is what is most time consuming about the recruitment process. So I think if you can automate that well, you take out 80 per cent of what is usually a very manual, labour-intensive job, and that 20 per cent that remains is super high value and very useful feedback that can only be given by a human.

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