Is it conceivable that a robot decides on your suitability during a job interview? According to the audience at the Telekom MOST forum, it is. In fact, technology has been supporting HR for quite some time in ways not always known to the public.  

Take the problem of recruiting engineers or developers – a group most in demand. These people will hardly respond to general job ads and submit CVs, so companies have to make serious efforts to find and reach out to them. They also need to offer conditions enticing enough to grab their attention.  

HR specialists will tell you that a decent salary and workplace are a must, so companies have to come up with something more. But how are they to know what would attract a certain group of developers?  

Through technology, of course. Neticle, a Hungarian ICT company specialized in intelligent media monitoring, media analysis and social listening is helping them out. Neticle has developed search solutions that allow for downloading public web content, articles, comments, social media, and posts from a variety of platforms.  

Based on these, they can get an idea of the preferences of these people and also of their perception of the target company. If the engineers a company is trying to recruit chat on a platforms a lot about e-sports, say, as well as the benefits of working from home and these topics are recurring, Neticle will bring this information to their client.  

Data Decisions

What companies do with that data is entirely up to them, says Péter Szekeres, managing director of Neticle. They may choose to incorporate it in their job ads and, for example, mention, that home-working at their firm is allowed, or they might target this group on e-sports platforms.

Using data smartly and getting proper insight from it is a challenge, Szekeres says. There is already vast amounts of data out in the world, but most of it is not used for getting insights. A crucial first step is to decide what you want to use the data for, he adds.  

HR is a field that has much data generating potential, whether from psychology games, to candidates interview answers, to how a text is structured, and all this can be automatically processed and analyzed to pre-screen candidates. Skeletons get unearthed soon enough, unnecessary questions can be eliminated saving time for everyone. The question is how to use data to support business decision, Szekeres notes.  

“[Insight gained from] data is not supposed to replace a business decision, rather to make it more confident and reduce risks by not having to rely on intuition or experience only,” he explains.   

Hungary’s leading jobsite platform, profession.hu, manages an enormous amount of data, as you would expect.  

“Data is the basis of everything but what’s even more important is to have structured data and to use it with a purpose,” says Imre Tüzes, head of business development at profession.hu. “For us, success is when supply and demand meet,” he adds.  

Too Much Data?

But too much data can create a situation that is disturbing. This is when technology comes into the picture; it is supposed to serve. The expert cites a new application, Candidate Recommender, the beta version of which is about to finalized: it is an algorithm using artificial intelligence and match-making technology that makes a job search easier for both parties.

It does so by understanding written texts, such as a job description, which it analyzes semantically and then decodes who is needed for a job. The skill sets linked to the algorithm create a profile of what a company needs, saving time for recruiters who would otherwise need to run these searches in a huge database.  

The system screens, selects and ranks potential candidates, also based on how active a candidate is on the job market. This way profession.hu has a better chance of reaching out to them, Tüzes explains. This is a good example of how one can tap into the social footprint of someone and convert it into a product, he adds.  

But can technology take work over from HR-professionals entirely? Not really. Automation and AI should not work against humans; there are many examples of the cooperation of people and robots, for example, in the industry, Tüzes says. There is even a name coined for this, cobots, that take over boring and repetitive tasks.  

This approach is trickling down to all sectors, including recruiting. The recruiting process as a whole cannot be automated anytime in the future; there will always be areas where the human factor must be involved, the expert says.  

There are already automated systems working today that help prescreen and calculate matching scores and forward candidates to a phase where recruiters only need to take a final decision. But taking the final decision is beyond the sophistication of current know how or prognosticated automation systems, he adds.