There’s no denying that recruitment can be a very tricky business. A recent research study by Leadership IQ has shown that companies often make the wrong choice in candidate, with as many as half of all new recruits turning out to absolute flops in less than two years of commencing employment!
Recruitment is extremely expensive so you’d think that managers would take more care when making their hiring decisions. The main reason for the majority of these recruitment fails tends to stem from candidates’ personalities clashing with company culture. This is such a difficult problem to solve because whilst you can get a good view of the skills a candidate might have from their CV, it is nigh impossible to assess their personality until they actually start work, by which time it’s too late.
So, employers have started to look for ways to get around this problem and are now relying on big data analytics, as well as other innovative methods, to help make the hiring process more accurate and less time-consuming.
The benefit of big data analytics is that it allows employers to collect, organise, analyse and interpret data from everywhere, at any time. This data can be drawn from numerous places online, including job boards, social media, mobile devices, surveys, databases and websites. Once collected the data can be analysed and used to determine the next step in recruitment.
So, what does this mean for candidates? Well, it means candidates now have to focus on making sure they pay as much attention to their online data trail, as they do to their CV and application form.
Recruitment isn’t a game – or is it?
When candidates search and apply for jobs online, they should always spend a good amount of time thinking about what they’re writing and how they are going to come across to a potential employer. What candidates probably don’t realise, even in this digital, techie world, is that everything from sentence structure to the actual detail of what they are writing is now able to be analysed by various algorithms.
Recruitment companies are now using such algorithms in order to better determine candidates’ personalities and attitudes. This then enables the recruiters to better identify candidates who will, as well as those that won’t, fit in with a specific company’s culture.
Games are also being introduced into recruitment now since they are very effective in getting candidates to reveal certain aspects of their personalities, charterer traits and everything from emotional maturity right through to problem-solving ability. These algorithms and games are important to recruiters and the recruitment industry since it cuts through the time-wasters and can save a lot of money in the long run.
Recruitment’s crystal ball
The recruitment industry is a good example of how analysing the past can help us predict the future. In this manner, many recruitment firms are making good use of historical data that they have collected from thousands of previously successfully placed applicants, and using it to help them predict which new applicants are going to be the ‘best fit’ for employers, when compared with the historical career, personality and qualification data of previous candidates.
This data comparison exercise allows recruiters to effectively map out and predict the career paths of current applicants, which is not only a huge help to companies but is also of real use to candidates themselves and saves all parties involved a great deal of time and money too.
Interestingly enough, big data analysis has shown that candidates who have been unemployed for long periods of time fare no worse in this data comparison exercises than those who are still in work or who have been regularly employed. This is shocking because traditionally, companies and recruiters would always prefer to deal with candidates who have been in regular work, thus showing a definite selection bias.
However, big data analysis has shown that these days you can’t just rely on a candidate’s qualifications and prior work experience when trying to determine how good a performer they are going to be, or were in any of their previous roles. If someone is active online and clearly shows good reputation management, it may well be an excellent indicator of how reliable or trustworthy a candidate they might be, even if they’ve been out of employment for some time.
Real-time data through social platforms
As well as now relying on a great deal of historical candidate data, recruiters have a lot of real-time data at their fingertips thanks to social media. In the past recruiters and employers had to take a candidate’s CV at face value but no more; recruiters now have the ability to check out candidates’ social media profiles, blogs and websites whenever they like.
The concept of personal and professional social media profiles no longer really exists. Candidates should be using one to complement the other and always be conscious of the fact that they can be found and tracked online and that their online presence can and will affect their employability.
There are a large number of companies offering recruiters the tools needed to track candidates’ social media patterns and sentiment and therefore enable recruiters to build up a clear picture of applicants’ online reputations.
Big data enables recruiters to see how each individual applicant manages their online reputation with the key idea being that if, in these digital times, a candidate cannot manage their online reputation well, how can they be trusted to protect their future employer’s reputation.
Technology versus humans
Despite technology offering us so much, there are many who believe it can only take us so far. After all, you can’t actually reason with a computer; they are there to make things faster, simpler and more efficient not to totally replace human interaction.
Technical data and analysis are crucial to helping recruiters filter out the vast majority of unsuitable candidates, saving employers a lot of time and money, especially when it comes down to filtering out the top 5 interview candidates out of a possible 10,000 applications.
However, when it comes down to making a final hiring decision, you’ve got to be able to trust in human judgement. If you don’t use human judgement alongside big data analysis, you may find you end up with the same type of candidate each and every time you recruit, which is not ideal for creating an innovative, diverse and multi-cultural workplace.