​​​​Data analytics: the recruitment superpower

​​​​​​​Leonardo da Vinci created the world's first recorded résumé in 1482, and the structure of the document has more or less remained the same. Recruitment may be a slow to evolve industry, but big data analytics could shake all that up. Will predictive analytics displace human judgement entirely?

 ​​​​Data analytics: the recruitment superpower

After analysing a staggering 441,769 CVs, Colin Lee from Rotterdam School of Management, Erasmus University (RSM) has written an algorithm that uses big data to predict who will be invited for an interview ‒ with an accuracy of between 70 and 80 per cent.

The results of Lee’s experiment revealed that recruiters are more concerned with how many years of work experience candidates have, and care very little about whether or not the applicant’s skills and education are closely related to the job in question. Could this mean that an algorithm is more discerning the human judgement?

James Blake says no. As the founder and CEO of international data analytics firm Hello Soda, Blake’s business relies on the strength of data analytics, yet the Manchester-based tech dynamo believes that technology is a tool rather than a replacement of the HR function. “Data analytics can certainly supplement the HR function and, not only save time and money in vetting processes, will add a personalised aspect to what has now become a mostly automated business area,” he told Growth Business.

“HR professionals and recruiters can use analytics software in the hiring process to match candidates with the right roles and within an existing workforce to help determine optimal working conditions and training.” Blake explained that data analytics software can tell HR professionals a candidate’s location, their interests, and predict their personality scores to enhance CVs, applications, and training schemes, and these measures save time and help job-seekers into roles that are best suited for them and the business. But there will always be a need for a keen sense of human judgement. “Ultimately, people will always have to work with other people in some way.”

Supplementing – not replacing- tradition

RSM’s Lee used software that automatically scans digital CVs for a wide range of attributes, including experience, age, distance from the workplace and education, using real company recruiters’ feedback as a baseline. Contextual factors were also taken into consideration, such as ‘did the candidate apply in time’ and ‘was the candidate already employed by the company?’ He then designed a very detailed model of the job market that described every occupation in terms of the most common work activities performed in that occupation, before matching up the characteristics of the applicants receiving interview invitations to the occupations the applicants applied for.

Lee says his model can also predict which candidates are suitable for newly created occupations and that this use of big data to model the job market will become even more valuable once former applicants’ job performance is added to the database. “This would make it possible to predict a candidate’s future performance simply by scanning their uploaded CV,” Lee added.

Echoing the research, Blake highlighted the evolving role of HR teams. “Data analytics can help identify people that are likely to perform better in certain industries early in their career, for example based on their personality traits, so HR teams can tailor training programmes to nurture future talent and increase return on investment

“Relying on traditional applications, listed skills and education isn’t always the best way of telling how a candidate might fit in a certain role,” Blake said.

Hello Soda’s PROFILE platform takes thousands of data points from an individual’s digital footprint, including their social media profiles, and generates unique scores and summaries of their interests, hobbies, personality, location and travel, and more. In the HR industry, it can be used in-house, or by recruiters to connect individuals with ideal roles and schemes to increase the likelihood of job satisfaction, performance, and longevity. “For example, a person who has high scores in ‘Extraversion’ and ‘Openness’ would likely be good team-workers, adventurous, and open to travelling for work, whereas those with low scores in these are more independent, would be comfortable working from home, and are more likely to become an expert in one specific area as they prefer familiarity,” he explained.

The future of recruitment

Jeremy Tipper, consulting and innovation director at global talent acquisition and management firm, Alexander Mann Solutions, says that these types of predictive analytics are the future of the industry.
“Predictive analytics – including these types of algorithms – are the future of talent acquisition and shouldn’t be feared by hiring managers or recruiters. As it stands there’s too much wastage in recruitment that is both damaging to the candidate experience and potentially costly for businesses when it comes to identifying the right person for the role at hand,” he said. In his firm’s annual global recruiting survey this year, a staggering three quarters of those considered for a job do not even meet basic role requirements and, on average, 282 candidates are being considered for every role. “This is a huge number of applications to sift through, and with such a vast number to analyse, human error and unconscious bias are likely to come into play – which could cause the perfect candidate to slip through the net,” according to Tipper.

“By using predictive analytics, the hiring process can be streamlined to the benefit of all involved.”

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