Next Generation Recruiting for HR Professionals

When a multinational manufacture like Unilever distributes over 400 consumer goods brands covering markets from food and beverages to personal hygiene, many processes should be done at the same time with fast and accurate pace.

   Screening and assessing more than one million people per year who apply for jobs with Unilever is not a task for humans anymore. Artificial intelligence (AI) powered tools helps Human Resources (HR) professionals to recruit the most important people for their interests.

   Unilever recruits more than 30,000 people a year and processes around 1.8 million job applications, according to a recent article on Forbes.

   Human capabilities are limited, and the above process needs a tremendous amount of time and resources. To tackle this problem, Unilever partnered with Pymetrics. This is a company established in 2011 and implements AI recruitment techniques. Candidates use the platform from their own homes, in front of a computer or mobile device, and they asked to participate to a series of challenges.

   First, they are asked to play a selection of games which test their aptitude, logic, reasoning, and appetite for risk. Behind the games, machine learning algorithms are used to assess their suitability for whatever role they have applied for. Then, they must submit a video interview. AI is behind the evaluation again, with the use of a machine learning algorithm, examining the mixture of natural language processes and the body language.

   Unilever's chief of HR, told to Forbes that around 70,000 person-hours of interviewing and assessing candidates had been cut, thanks to automated screening systems. These technologies are also designed to give feedback to all applicants, even those who are not successful.

   Instead of a typical "black hole" saying "thank you very much for your CV", with this process all applicants get a couple of pages of feedback, how they did in the game, how they did in the video interviews, what characteristics they have that fit, and if they do not fit, the reason why they did not, and they should do to be successful in a future application.