Experimenting with Emerging Technologies in Attracting, Recruiting and on-Boarding Talent

As a further opportunity to learn and stay up to date, a couple of weeks ago I took part in an event on Data Analytics. My question (from a psychology perspective, I’m afraid it’s difficult to change) to the speaker, an expert and practitioner in the world of data, algorithms, artificial intelligence and decisions on all of these issues, was:

What, in your view, is most important for the “efficiency” of these analyses: data, technology, or the actual person?

And his reply was:

The team, the people who make it up.

I like that, I thought. That’s precisely what we see when we investigate and “experiment” with technologies in the world of attracting, recruiting and on-boarding talent within the company.

And it’s all about meeting a challenge: bringing together a group of human resources professionals working in recruitment for several multinational companies to share experiences in November, at the Ferrovial University. Staying up to date is essential! And so, in order to share what we learn along the way, Carla and I decided to start a trilogy of posts based on people and the technology for supporting people performance.

Let’s start the series…

Efficiency and people (hand in hand…)

First instalment: What technologies are / will be available for talent recruitment? How are they applied?

Let’s start with the data. According to Bersin ( 2017 Human Capital Trends Report), 38% of companies believe that artificial intelligence and robots will be the norm in 5 years’ time.

We ask Google (yet another Robot) what artificial intelligence (IA) and “machine learning” are all about…

• “Artificial Intelligence: how to resolve a problem in a non-natural way”
• “Machine Learning: using algorithms to analyse data, learn from them and obtain optimised predictions, minimising errors.” Sounds good… that’s sure to speed up work and add value!

Digging deeper

• Automatic screening algorithms and machine learning: This combination is speeding up improvements and efficiency in recruitment processes. What’s it all about? By analysing databases, the system learns from experience. For example, what are the characteristics of the most successful candidates, what messages have been better at dismissing certain candidates, what wording is used in employment adverts that attract the greatest response, or, simply, what applications meet our criteria best, based on key words.

Our experience: 6 days before the holidays, 3 p.m., Madrid, a conference with a Japanese man living in New York and 20 minutes for a demo. It all happened in a moment, and I’m still amazed. Why? Our expert selected several of the adverts we had on employment websites and compared them with vacancies published by the competition and his own database. The result in two words? Im…pressive. He predicted the performance/efficacy of my advert and suggested alternatives in real time to improve it: more neutral wording (to attract both sexes equally), more committed and friendly expressions, correct grammar and even warnings on the use of clichés.  WOW!

• Chatbots (based on AI): Chatbots can be programmed to improve candidate experience in the recruitment process (immediate engagement). Interacting with them in a quick and fun way, replying to their questions, asking preliminary questions on qualifications, experience and training, or ending the dialogue by agreeing next steps.

And from back office? Chatbots allow us to target recruitment questions on experience, knowledge or skills, obtain information on candidates (ranking) based on activity and qualifications, reply to frequent questions and arrange interviews. They can be used in emails, SMS, corporate webpages on social networks such as Facebook, applications such as Slack or even embedded in recruitment process management tools (ATS).

Our experience: We tried them together. Through Facebook Messenger, we started talking with the bot. It allowed us to apply for employment offers, it asked questions which we replied to with audios, and if we got stuck it helped us with screenshots. A good user experience!

But this is something we were already familiar with…  At Ferrovial we are pioneers in Spain in the development of a conversational bot for HR. Our famous “Qo” offers staff learning resources to help develop his or her skills… something which (only) looks simple. Bots do not learn on their own, they analyse and interpret the natural language and provide a reply (which has previously been programmed by a human being). It’s not magic. If you want a conversation to flow and sound real, you have to programme it. And how can you do that? By considering all the potential replies a human being could provide. That’s certainly a challenge!

• Video interview and facial-voice recognition: Using technology and neuroscience together, the initial candidate screening can be optimised, thus doing away with prior telephone checks and considerably reducing the number of CVs you need to read and the number of candidate appointments you need to make.

You first send a link to candidates for a video interview via mobile phone… at a time that best suits them. Then the candidates are ranked on best results, so that you only need to focus on visualising a few interviews. But the most significant advance is facial-voice recognition via these video interviews. Science fiction? With the correct technology, it is possible to detect whether what the candidate is actually saying is consistent with what his/her face or tone of voice is transmitting. Neuroscience helps recruitment processes not only on the basis of technical skills or professional experience, but also based on the emotional profile required for carrying out a certain job.

Our experience: When we saw how this worked, we thought it was almost scary because of how much is already possible… the future is here, and at times it can seem rather threatening. But in fact it is no more than an additional source of information (data on emotions from facial gestures, voice analysis, etc.). A person can detect another person’s state of mind, empathise with that person, go beyond what’s obviously there or what is hidden… this is something that machines can now do, only much more accurately.

• Virtual Reality and Glasses: Virtual reality should not be confused with augmented reality. Augmented reality (AR) consists in the incorporation of extra elements, in addition to those already there. In virtual reality (RV), however, everything is created digitally. Both technologies have many applications in attracting and recruiting talent, from offering a perspective of the positions on offer and showing ways of working within the company, to carrying out interviews remotely or with a virtual “avatar”, requesting candidates to perform certain tests or challenges, or even providing a guided tour as part of the on-boarding or induction.

This is not a game. In the strategy for attracting the best talent, RA and RV are innovative ways of transmitting culture, values, internal relations and ways of working. Helping the candidate to decide whether to join the company or not, and improving our employer profile. For new recruits, it is an easy and cost-effective way of getting to know the organisation… there’s no need to travel to the US subsidiary of the company, you can simply arrange a visit using a pair of glasses.

Our experience: Madrid – Barcelona. We were in a tiny room when we got this device… glasses of the future which opened up and worked by simply putting your mobile inside, voilà! We were able to see the meeting rooms in Barcelona, looking 100% real. And I heard someone laugh and say to me: “Just turn around!” and there was the interviewer. Only the interviewer was in fact 620 km away.

So, to the question, what is most important for you in the “efficiency” of the analysis: data, technology or people?

The team, the people making up the team.

According to a recent survey by Randstad, 82% of people looking for a job believe that the ideal interaction is a combination of technological and personal innovation.

A word of caution: Efficiency in processes is always required and valued in order to get more out of the same number of resources. But it must always be people-led in order to provide all that technology will take a while yet to replicate or surpass, or will indeed never be able to replicate or surpass.