'Big Data' has now also entered the world of recruitment. According to a study by Deloitte, organizations and recruitment firms save money when they apply analytics and data on their search and selection processes.
The global assessment market is well over $1 billion in size, and includes international companies like Korn Ferry, Michael Page, SHL, DDI, CPP (Myers
Briggs) and literally hundreds of thousands of smaller companies that offer specialized assessments by role and job. If each of these firms would be able to improve their search en selection process by just 1%, then the savings to the industry (and their clients) could amount to millions.
According to Deloitte, companies would be wise to cut their search and selection process into three areas: top of funnel, middle or bottom of funnel and funnel. In each of these phases businesses would be wise to utilize various tools to analyse the abilities and 'match'. These tools range from automated tools as capacity or personality tests to labor-intensive steps as CV and reference checks.
What companies should understand is that the relative investment per candidate increases as candidates flow from the top to the bottom of the funnel. "Although it sounds straightforward, in practice, this is a design criterion that often go wrong", said Josh Bersin of Deloitte
According to Bersin the key step in the process is the so-called 'high-performer' analysis approach. For each function/role, companies should create a profile of the top 10% performers, including properties as skills, personality traits, experiences, and knowledge. Once this role blueprint is created, companies can use smart tools to compare candidates to this best practice group and as a result the recruitment 'fit' drastically improves.