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Mar 22, 2019

Candidates are quickly learning that with unemployment at 3.7%; jobs are easy to come by. In fact, in a recent survey, 72.8% of employers are struggling to find relevant candidates for available positions. One critical step you can take: make the application process easier. Specifically, when it comes to talent assessments.

This post is a third of four on how you can source, interview, assess, and schedule candidates with A.I. and not need a single line of coding knowledge.

Many of us have suffered through mind-numbing job assessments that ask, numerical (we can Google that), linguistic (can Google that too, and we do), and preferential scenario questions. If for some reason a company doesn’t trust you, they’ll also set up a live feed to watch you take the test. What kind of Big-Brother, Orwellian nightmare are we selling here folks?!

The time has come to shift our focus from easy to cheat, non-scientific tests, to data-based, neurological assessments that eliminate biases and push the best candidates to the top (rather than screening out those that don’t fit). Let’s look at two solutions today that take this approach:

1) Pymetrics – Founded by Harvard & MIT neuroscientist Frida Polli, Pymetrics is a cutting-edge games platform for assessing talent. Founded with mental exercises based on neurological games, (and more services coming soon) Pymetrics looks to flip the application process on its head.

By placing the assessment at the front of the application process, you eliminate the biases of those screening resumes. Pymetrics customized AI & Machine Learning algorithms not only help match skills to game responses; they also help increase diversity by balancing your existing talent pool with external, diversified groups. By using benchmarks that start with an even playing field, you can find candidates who would have never been considered otherwise.

Lastly, isn’t it rude when companies just slam the door in your face when you’re not a fit for their role? Pymetrics offers a job marketplace to match candidates with other company jobs that fit their profile. By offering candidates alternative job prospects, you get to play a part in employing virtually everyone that applies to your jobs!

2) Harver – As a recruiter, you get used to the mundane parts of managing requisitions. Open job, post job, screen resumes, schedule interviews, deliver interviews, recap, and repeat. At best, you’re talking with 25% of applicants, yet often you’re stretched too thin. Harver helps automate the tedious parts of your job so that you can focus on the human part of your job: connecting with people!

With AI matching technology that pairs candidates to open jobs, video engagement that showcases your brand and workspace, and online/mobile optimization, Harver provides a robust suite of solutions to assess candidates with meaningful data to support.

The Harver assessments cover culture fit, personality type, situational judgment, cognitive ability, language proficiency, and skills games based on role. Rather than relying on just one type, you can pick and choose the tests that fit the needs of your business.

Lastly, the Machine Learning algorithms used by Harver learn from every candidate’s responses. Over time, the system uses your feedback and hire data to hone-in on the best quality fit possible. I’m not sure about you, but the less time I need to spend adjusting models with existing staff the better!

By focusing on automation and leveraging machine learning, these two amazing systems trim down your mundane, brick-wall-to-forehead, tedious tasks, and allow you to get back to focusing on your candidates.

If you enjoyed this post like/comment to let me know, stay tuned for the next post covering A.I. for scheduling interviews.