With so many processes to coordinate and manage, artificial intelligence is quickly becoming essential for organizations of its scale. This applies to both research and development as well as the huge support infrastructure needed for a business with 170,000 employees.
Recently it announced that it had developed machine learning algorithms capable of sniffing your armpit and telling you whether you are suffering from body odors. While this may seem like "using a sledgehammer to crack a walnut", the technology which has been developed could well go on to be used to monitor food for freshness, helping to solve the problem of food overproduction and waste endemic in society.
As well as these smart, public-facing initiatives, though, artificial intelligence is being put to use behind the scenes to help screen and assess the more than one million people per year who apply for jobs with Unilever. If they make the grade and become one of the thousands who are offered a job, they have AI-powered tools to help them adjust to their new role and hit the ground running.
Unilever recruits more than 30,000 people a year and processes around 1.8 million job applications.
This takes a tremendous amount of time and resources. As a multinational brand operating in 190 countries, applicants are based all around the world. Finding the right people is an essential ingredient for success and Unilever can't afford to overlook talent just because it is buried at the bottom of a pile of CVs.
To tackle this problem, Unilever partnered with Pymetrics, a specialist in AI recruitment, to create an online platform which means candidates can be initially assessed from their own homes, in front of a computer or mobile phone screen.
First, they are asked to play a selection of games which test their aptitude, logic, and reasoning, and appetite for risk. Machine learning algorithms are then used to assess their suitability for whatever role they have applied for, by matching their profiles against those of previously successful employees.
The second stage of the process involves submitting a video interview. Again, the assessor is not a human being but a machine learning algorithm. The algorithm examines the videos of candidates answering questions for around 30 minutes, and through a mixture of natural language processing and body language analysis, determines who is likely to be a good fit.
Unilever's chief of HR, Leena Nair, told me that around 70,000 person-hours of interviewing and assessing candidates had been cut, thanks to the automated screening system.
She said "We look for people with a sense of purpose – systemic thinking, resilience, business acumen. Based on that profile, the games and the video interview are all programmed to look for cues in their behavior that will help us understand who will fit in at Unilever."
Referring to the video interview analytics for their future leaders program, she tells me “Every screenshot gives us many data points about the person, so we work with a number of partners and use a lot of proprietary technology with those partners, and then we select 3,500 or so people to go through to our discovery center.” After spending a day with real leaders and recruiters, Unilever selects about 800 people who will be offered a job.
The system is also designed to give feedback to all applicants, even those who aren’t successful.
“What I like about the process is that each and every person who applies to us gets some feedback,” Nair says.
“Normally when people send an application to a large company it can go into a ‘black hole’ – thank you very much for your CV, we’ll get back to you – and you never hear from them again.
“All of our 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 don’t fit, the reason why they didn’t, and what we think they should do to be successful in a future application.
