“I no longer look at somebody’s CV to determine if we will interview them or not,” declares Teri Morse, who oversees the recruitment of 30,000 people each year at Xerox Services. Instead, her team analyses personal data to determine the fate of job candidates.

She is not alone. “Big data” and complex algorithms are increasingly taking decisions out of the hands of individual interviewers – a trend that has far-reaching consequences for job seekers and recruiters alike.

The company whose name has become a synonym for photocopy has turned into one that helps others outsource everyday business processes, from accounting to human resources. It recently teamed up with Evolv, which uses data sets of past behaviour to predict everything from salesmanship to loyalty.

For Xerox this means putting prospective candidates for the company’s 55,000 call-centre positions through a screening test that covers a wide range of questions. Evolv then lays separate data it has mined on what causes employees to leave their call-centre jobs over the candidates’ responses to predict which of them will stick around and which will further exacerbate the already high churn rate call centres tend to suffer.

The results are surprising. Some are quirky: employees who are members of one or two social networks were found to stay in their job for longer than those who belonged to four or more social networks (Xerox recruitment drives at gaming conventions were subsequently cancelled). Some findings, however, were much more fundamental: prior work experience in a similar role was not found to be a predictor of success.

“It actually opens up doors for people who would never have gotten to interview based on their CV,” says Ms Morse. Some managers initially questioned why new recruits were appearing without any prior relevant experience. As time went on, attrition rates in some call centres fell by 20 per cent and managers no longer quibbled. “I don’t know why this works,” admits Ms Morse, “I just know it works.”

Organisations have long held large amounts of data. From financial accounts to staff time sheets, the movement from paper to computer made it easier to understand and analyse. As computing power increased exponentially, so did data storage. The floppy disk of the 1990s could store barely more than one megabyte of data; today a 16 gigabyte USB flash drive costs less than a fiver ($8).

It is simple, then, to see how recruiters arrive at a point where crunching data could replace the human touch of job interviews. Research by NewVantage Partners, the technology consultants, found that 85 per cent of Fortune 1000 executives in 2013 had a big data initiative planned or in progress, with almost half using big data operationally.

HR services provider Ceridian is one of many companies hoping to tap into the potential of big data for employers. “From an HR and recruitment perspective, big data enables you to analyse volumes of data that in the past were hard to access and understand,” explains David Woodward, chief product and innovation officer at Ceridian UK.

Members of one or two social networks stayed in their job longer than those belonging to four or more

This includes “applying the data you hold about your employees and how they’ve performed, to see the causal links between the characteristics of the hire that you took in versus those that stayed with you and became successful employees. Drawing those links can better inform your decisions in the hiring process.”

Data sets need not rely on internal data, however.

“Social media data now gives us the ability to ‘listen’ to the business,” says Zahir Ladhani, vice-president at IBM Smarter Workforce. “You can look at what customers are saying about your business, what employees are saying, and what you yourself are saying – cull all that data together and you can understand the impact.

“Most recruitment organisations now use social media and job-site data,” says Mr Ladhani. “We looked at an organisation which had very specialised, very hard to find skill sets. When we analysed the data of the top performers in that job family, we found out that they all hung out at a very unique, niche social media site. Once we tapped into that database, boom!”

Ceridian, too, has worked with companies to “effectively scan the internet to see what jobs are being posted through the various job boards, in what parts of the country,” says Mr Woodward. “If you’re looking to open a particular facility in a part of the country, for example, you’ll be able to see whether there’s already a high demand for particular types of skills.”

Experts appear split on whether the specialisation required for executive recruitment lends itself to big data.

“I hire 30,000 call-centre people on an annual basis – we don’t hire that many executives,” says Ms Morse, adding “there’s not enough volume”. However Mr Ladhani disagrees, believing that over time the data set an organisation holds on senior management hires would become statistically valid.

As more companies start to analyse their employee data to make hiring decisions, could recruitment finally become more of a science than an art?

“The potential is clearly much greater now than ever before to crunch very large volumes of data and draw conclusions from that which can make better decisions,” says Mr Woodward. “The methods and computing power being used in weather forecasting 10 years ago are now available to us all . . . who knows where this may go.”

It is a trend worth considering – to get your next job, perfecting your CV could well be less important than having carefully considered the footprint you leave in cyberspace.

——————————————-

Case study: Demographic drilling down helps LV= recast recruitment ads

Kevin Hough, head of recruiting at insurance firm LV=, was a pioneer of ‘Big Data’ before he had heard the term.

The insurer has 5,800 employees across 17 UK sites. A year ago, the question of where best to target its recruitment advertising provided an innovative answer. “We took all of the postcode data from our HR database – where our current staff live and where they are located – and split that by their [seniority]” explains Mr Hough. “Using software called Geo-Maps, which works similarly to Google Maps, we could zoom in and out of clusters of our people to see where they are willing to travel from to get to work.

“On top of that we were able to overlay where people were applying from, taken from our recruitment data. The next iteration was where our Facebook and LinkedIn followers are from: the demographic of people following us, what interests them, the diversity and inclusion breakdowns, male and female and so on, on which social media platform.

“We were able to build up a profile of who our successful candidate was, the age demographic, and where people were hunting for jobs. What was really interesting was the reach some of our advertising was having, and more importantly some of the gaps.”

Recruitment advertising at LV= has subsequently been redesigned. The investment and expertise required to analyse the data were negligible, says Hough. “For Geo-Maps it was literally as basic as getting a licence for the software and uploading our data to it from a spreadsheet. Sometimes with all the clever systems that people have in organisations you can be blinded to the simple, raw data that is sat there.”

Next, LV= will add performance review data.

“The ongoing piece is to say of that group we recruited a year ago, which are still there? It helps to shape not only how we attract the people, but will even start to shape some of the roles themselves.”