Leaders of Analytics

Is the typical hiring and job search process broken?

It is definitely full of bias.

First, we get interested candidates to submit their resumes.

Then someone (typically not the hiring manager) will pick out the resumes that look most interesting to them.

Resumes that survive are typically carefully curated for someone to be able to form a positive opinion in just a few seconds.

Then the hiring manager will pick their favourites out of that smaller pile. At this point, the lion’s share of candidates has been excluded purely based on resumes.

Then comes the first interview. According to a study in the Journal of Occupational and Organisational Psychology, 60% of interviewers make their decision in the first 15 minutes.

What’s more, according to Hubspot, 85% of jobs are filled through networking. We prefer to hire someone we already know, because we think we have an idea of their ability.

We are genetically designed to make quick decisions based on limited data points, which is at odds with very complex decisions such as hiring the right candidate. We try to deal with this through resumes, but these documents are also heavily biased.

How do we limit our own biases and measure all candidates objectively?

How do we identify the rising stars and unique talents who don't yet have a long resume full of experience?

I recently spoke to Tim Freestone to get an answer to these questions and many more relating to hiring the right data and analytics candidates.

Tim is the founder of Alooba, the world’s first data and analytics assessment platform. Alooba’s tools help organisations around the world objectively assess the skills and capabilities of new candidates and existing team members alike.