In a recent LinkedIn survey of 8815 recruiters and hiring managers, 65% said they use data in their hiring practice – with technology-driven campaigns one of the site’s key trends for 2018.
This makes sense. With hiring the wrong individual incurring costs of as much as £132,000, workplaces need all the help they can get when it comes to finding and retaining the right staff – especially in fields like cybersecurity, where there are more roles than candidates.
How are UK organisations using data-driven technology like AI and candidate profiling to improve their recruitment process – and how can you do the same?
Data for optimising your recruitment process
In the first instance, data can be used to find and then screen candidates – cutting time and effort from the candidate search process.
Vacancies can be marketed to the right candidates by using data to optimise job ads for those with a specific mix of skills and aptitude. Data points like current salary, job title and interests all help recruiters engage with potential candidates using personalised messaging. Tools like Workable can then be used to sift through potential applicants in the pre-screening stage of the hiring process.
This process is complicated when candidate data is not publicly available – a particular problem in fields like cybersecurity, where recruitment managers typically struggle with low numbers of applications.
In these cases, recruitment professionals are forced to spend extra time finding candidates they believe are suitable. Here, data can be used to confirm Quality of Hire (QoH). These measures are often more subjective than those referred to above, but can still prove useful further along the screening process.
Data for candidate assessment
Recruiters have access to a range of online resources to test for QoH – such as the ‘talent scorecard’ developed by consultancy The Adler Group. Users make a 1-5 rating of their candidates’ primary, core, and situational fit factors following psychometric tests and interviews. In this way, Adler’s scorecard is designed to show how a new hire will fit within a team, how well they will learn on the job, and how quickly they will meet their colleagues’ productivity levels.
Candidate personality and fit are two areas that lend themselves to data-driven assessment. Criterion’s Psycruit – the tool we use at identifi global – presents recruiters with a range of testing programs that track reasoning, personality, emotional style, motivation, culture fit, and workplace potential.
Unlike recruitment tools such as interviews and references, these tools are unaffected by individual bias on the part of the recruiter – providing they’ve been trained to use the tools and data properly. As Dawn Klinghoffer, General Manager of HR for Microsoft Business Insight, notes, the ability to accurately track and interpret candidate data at a detailed level will be increasingly important for recruitment professionals over the next decade.
Data for workplace diversity
Data is also essential for tracking recruitment performance within businesses – and can even turn candidate hire into a competitive advantage.
Today, women represent just 8% of the UK cybersecurity workforce – so recruiters have an important role to play in increasing gender diversity. To do so, employers must know what candidates want – which means access to candidate data – and then build targeted recruitment campaigns based on this insight.
Tools exist to support recruiters. Textio’s ‘augmented writing’ software, for example, can boost candidate gender diversity by more than 20%. It does this by using big data to check job ads for phrases that may alienate female candidates. Words like ‘driven’, for example, might be changed to ‘collaborative’, – thereby making the language more inclusive.
As diversity assumes an increasingly central role in recruitment, big data will be key to helping recruiters utilise blind screening techniques and similar to build teams.
AI – your next step for data-driven recruitment?
Artificial Intelligence (AI) – which uses large candidate datasets – can be used to improve recruitment processes yet further, and will become more central to HR practices in the coming decade.
AI can be used, for example, to identify candidates that have applied for another job in an organisation, when they show an aptitude or range of skills that might be more suitable for a different role. This is especially useful in under-subscribed fields like cybersecurity.
We’ve written more about these intelligent recruitment systems here.
“It’s important to remember that AI-driven recruitment technology is in its infancy.”
It’s important to remember that AI-driven recruitment technology is in its infancy. In high-profile roles where candidate integrity is critical, hiring managers must be cautious about depending too heavily on automated systems. Candidates are unique; interviews, references and background experience should – in most cases – play a far more central role in the selection process.
AI is still useful to support recruitment, however. Recruiters bring their own biases to the candidate search process and can make poor character judgements – regardless of their level of experience. To combat this, AI tools can be used to analyse video applications with objective facial recognition technologies. These systems measure human qualities like empathy, deception, and anxiety via applicant body language.
Such developments sound like science fiction – but many larger organisations already depend on AI-driven systems for recruitment efficiency.
JetBlue Airways, for instance, uses video applications to screen for eight key character traits that distinguish helpful flight attendants from polite ones. “People will tell you they know the right kind of person for a given job. But what we think isn’t always what’s best. Once you get through the noise and beliefs that people gave and identify that right profile, you can have some solid impact in your organisation,” says Ryan Dullaghan, Manager of People Assessment and Analytics at JetBlue Airways.
This approach works. Using the findings from their video assessments, JetBlue has cut absenteeism by 12% company-wide – a considerable saving in terms of cost and risk.
Not every business can – or should – invest in AI-driven systems like those at JetBlue. But every organisation should reconsider how they use data to optimise and track their recruitment process and test for candidate quality and fit.
Even if you’re not using candidate data, then it’s very likely your rivals will be. And in competitive recruitment marketplaces – like those for cybersecurity, digital and IT professionals – this can mean the difference between leading the pack or falling behind.
Found this article interesting? Read our latest blog on the rise and rise of personality profiling in businesses.
