Big data: the future of recruitment?

Big data is transforming HR practices and recruitment methods. By analyzing the ever-growing volume of data on the internet, big data makes it possible to hire better-suited profiles, predict a company’s turnover, and identify more relevant selection criteria… But it also raises questions about the automation of recruitment and about how candidates can polish their personal branding.

This story comes to us from the United States. Jade Dominguez, 26, who lives in South Pasadena, California, never went to university and taught himself programming. Yet he received an offer to become a programmer from a San Francisco start-up and has since been hired.

Someone, somewhere, in the “cloud,” thought he was brilliant. That person was in fact Luca Bonmassar, the co-founder of the start-up Gild. He discovered Jade Dominguez using a technology that focuses less on recruiters’ traditional criteria (degrees, recent experience…) than on simple questions: is the person effective? What can this individual do? Can their work be assessed?

Gild’s algorithm, which draws on data available on the web, had placed Jade Dominguez at the top of its list of programmers. The computer’s use of big data makes it possible to gather all kinds of data and use it for a variety of tasks, recruitment in particular.

Defining big data

What is big data? This term, widely used in marketing, refers to the ability, provided by very powerful algorithms, to process large volumes of data and, above all, to find correlations within it.

The concrete applications in the world of human resources are wide-ranging. They can be carried out as part of sourcing. This method makes it possible to find profiles on the internet in order to collect targeted applications for recruitment. This approach, which is slowly making its way into France, lets the computer analyze keywords and skills from candidates’ résumés and social media profiles. The goal: to try to determine whether a candidate will be a good fit for the company’s requirements and culture. A valuable time saver in the candidate recruitment stages.

An American insurance company thus realized, thanks to big data, that criteria such as which school a person attended were not relevant when it came to recruiting salespeople. The filter instead focused on factors like past experience in real estate or business. This allowed the company to boost its revenue.

Big data can also predict which employee profiles are more likely than others to resign, based on a cross-analysis of certain criteria (salary level, position in the hierarchy, seniority…). Statistical analyses can thus help identify the factors behind employee departures, even the motivations that push them to head for the door. In this way, the printer manufacturer Xerox reduced turnover by 20% in its call centers.

Questions about big data

While HR teams are still wary of using big data, not necessarily won over by this arithmetic approach to human resources, the proliferation of data on the web and advances in technology make this tool appealing. Even if it raises a few questions.

For example, the widespread adoption of this type of recruitment can lead to a standardization of the profiles being hired, because algorithms can search for candidates based on tightly defined criteria. So what becomes of the diversity, the richness that builds a winning team?

The risks of discrimination also appear very real. Some rejected candidates could argue that their exclusion was based on considerations not directly related to the skills and abilities required to fill the position on offer. Article 3 of the French Act of 6 January 1978 on data processing, data files and individual liberties states that every candidate has the right to be informed of the reasoning used in automated processing that assists in the selection of applications.

Access to digital footprints and their interpretation therefore require HR departments and recruitment agencies to follow rules of ethics and transparency laid out by the CNIL.

Big data should also not replace meetings and interviews, which remain essential, particularly for the most specialized profiles.

Low-skilled profiles are more likely to lend themselves to “automated” recruitment © Precepta

How to adapt your personal branding to big data?

In this context, where the traces left behind, particularly on social media, are taken into account and analyzed, candidates need to be especially careful. “A fiercely environmentalist Twitter user has little chance of being hired at Areva,” notes Jacques Froissant, for example, managing director of the recruitment agency Altaïde.

The classic rules of personal branding matter more than ever: leaving a positive footprint on the web, publishing clear and concise content that avoids inconsistencies in order to speak to the recruiter, and being mindful of what you post are all key elements. For instance, learn how to optimize your LinkedIn profile with the right keywords, and by creating a custom URL on it. So that you might have the chance, like Jade Dominguez, to be spotted and then hired thanks to your data?

These practices are all the more important now that LinkedIn has just acquired the American start-up Bright, an expert in data management and matching, which connects job seekers with companies, even when the job seeker has not applied and the recruiter hasn’t even thought of this type of candidate. The prospects are enticing: 80% of LinkedIn’s 270 million users worldwide are passive. That’s a lot of profiles that don’t appear on job sites.