Around two years ago we started to talk seriously about big data. We were told that 864,000 hours of video are uploaded to YouTube every year, and that 172 million people visit Facebook per year, 40 million visit Twitter, 22 million visit LinkedIn, 20 million visit Google+ and so on.
The McKinsey Global Institute wrote “the amount of data in our world has been exploding, and analysing large data sets – so called big data – will become a key basis of competition underpinning new waves of productivity growth, innovation and consumer surplus.” Today, big data isn’t really a new concept. But what are the implications for HR?
There is the argument that forms of social media or online data are semi-professional at best, and that to focus on such media from a recruitment perspective is not always accurate. But we have known for years that a number of CVs aren’t accurate, either. More importantly, how relevant can they stay using big data?
Recruiters will start their search online, but that’s where the digital component usually ends. Face-to-face interviews are the next step, followed by some sort of structured or general questioning to narrow the candidate pool. Despite the limited reliability and validity of these models, more accurate ones used by entities that have exposure to big data, such as government bodies and major corporations, are under utilised.
The size and perceived success of the company currently employing an applicant, his or her academic qualifications and commitment to projects all feature more prominently in the recruitment models devised. A large number of organisations do tailor recruitment processes depending on individual needs and the scope of the role, but perceptions about perceived skill in candidates still revolve around previous performance verified by referee checks.
Individual companies will develop “secret sauces” for sourcing, analysing and evaluating hires based on their own data and factual statistical analysis of the make- up of their ideal hire. As SAS, the Scandinavian Airline, says in an advertising spiel: “What if you could increase revenue by 66 per cent using human capital data to make confident, fact-based recruiting and hiring decisions?”
One method used extensively for executive and graduate recruitment has been assessment centres that use a mixture of interviews, extensive testing, experiential exercises and the like mixed with observations recorded by two or more observers per person. This seems to have some validity and reliability, but accessible data available to people involved in recruiting, as well as networks and similar structures, can lead to quicker and simpler hiring processes.
Proctor & Gamble, which has 130,000 employees across 80 countries, developed a single test, calibrated it with 180,000 people and validated it with 2000 employees with great success. People decisions at Google are based on data and analytics; therefore its HR processes are all data based. Luxottica reduced its time to fill senior roles with external candidates from 96 days to 46 days focusing strongly on big data underpinning all of the other models used.
Human capital data should allow for definitive identification of candidates to fill open roles. Basing hiring systems on data – and not intuition – is more likely to develop stronger teams. Further, when it comes to hiring, the single factor that is the best predictor of performance is not personality, interview presentation or prior work performance, but intelligence.
Big data is here to stay – it is constantly increasing in volume and velocity. We need utilise the research available against the traditional hiring processes to see what works for changing recruitment models and what doesn’t. The future belongs to those who figure out how to collect and use human capital data successfully, and if HR professionals can learn and expand their recruitment methods to include big data, then there are big gains down the line.
A workshop on big data will take place at AHRI’s National Convention. Details here.