Big Data and semantics are opening up new horizons for both employers and applicants and better career monitoring for employees.

Originally published on 9 July 2013 and updated on 22 July 2015

Two years to hire 100 people

According to recruitment website Monster, it takes an average of two years for an experienced head-hunter to shortlist one hundred applicants in a recruitment campaign (from around 300 initial applicants for the position).

So without some basic semantic analytics skills and tools, this is an almost impossible task. In the US, big data analytics have helped HR organisations improve the efficiency of the shortlisting process by up to 70%.

And yet research by Deloitte shows that only 6-7% of HR organisations have acquired advanced expertise in HR analytics, according to Deloitte, who recommend that an HR team needs analysis skills, database skills, and business consulting skills to ensure successful recruitment and talent management for the company. In 2015, despite awareness of the undeniable benefits of Big Data for HR, the technology is still in its early stages, according to a Deloitte consultant.

Google: using Big Data in moderation

Thinking of applying to Google? Rest assured: during the interview, you won’t be asked the usual multiple-choice questions or brainteasers like how many golf balls can you fit into an aeroplane.

“We found that brainteasers are a complete waste of time… They don’t predict anything,” says Laszlo Bock, Senior Vice President of People Operations at Google, to the NY Times. He also believes academic success is not necessarily an indication of an applicant’s future professional performance:  “After two or three years, your ability to perform at Google is completely unrelated to how you performed when you were in school, because the skills you required in college are very different.”  In fact, 14% of Google’s staff don’t even have a university education.

What is the source of these findings? From data analytics, which Google uses as part of its HR process to determine the number of applications to shortlist, assess existing managers’ performance and determine the ideal number of people in a team for it to perform well.

But data isn’t everything, as Laszlo Bock concludes: “I don’t think you’ll ever replace human judgment and human inspiration and creativity because, at the end of the day, you need to be asking questions like, O.K., the system says this. Is this really what we want to do? Is that the right thing?”

Big Data and the age of “HR scoring”

A LinkedIn report on global recruitment trends* revealed, among other things, that companies in Asia use Big Data to predict future HR requirements.

The data gathered is also analysed before the recruitment stage to track and limit turnover rates and assess employees’ overall performance, as Google does.

A similar approach has been adopted by Xerox. With the use of big data analytics, it was able to cut its attrition rate at call centres by 20 percent, according to Entrepreneur*. By analysing various sources of employee information, HR is now able to identify issues that lead to lower employee engagement more accurately and thus find ways to improve engagement – an example which illustrates Deloitte’s findings. Companies that use big data for HR perform twice to three times better in terms of successful recruitment, leadership and staff turnover. Analytics is also a way of measuring the efficiency of employee training programmes and staff performance. In an interview with French financial daily Les Echos, economist Pascal de Lima spoke of the age of “HR scoring and screening, to detect potential resignations, compare salaries, and budget HR planning by analysing various sources of data (on promotion, pay rises, salary levels, etc.).”

*Reference articles