The Science Behind Predicting Job Performance at Recruitment
Investigating the most effective measures of recruitment.
Abstract
Recruitment is a game of risk, where the chances of identifying a candidate who will turn out to be an effective employee are balanced against the risks of spotting someone who will not work out as expected. Recruiters use a wide variety of tools and processes to help them manage risks with hiring decisions.
If risks are effectively managed, recruiters are more likely than not to identify candidates who perform well in the job, though even under optimal conditions this process is far from perfect.
The complexity of understanding candidates and evaluating whether they really have the capabilities, necessary learning styles characteristics and motivations necessary for any given job, means that incorrect decisions are easy to make. Factor into this issues such as deliberate deception on the part of the candidate and the difficulties for recruiters only increase.
If recruiters get it wrong they risk costs including the need to quickly replace employees and the potential disruption that poorly-fitting employees may cause to the organization.
In response to this recruitment challenge, there is now over 100 years of scientific evidence on the effectiveness of different tools that can be used in the recruitment process. This evidence is based on the association between evaluations of candidates made during the recruitment process and how they subsequently perform in the role for which they are hired. In turn, this evidence should feed back into the hiring process, guiding recruiters as to which tools will most effectively allow them to manage risk.
This paper summarises scientific research on the effectiveness of different recruitment tools, explains key concepts and identifies considerations to be taken when using recruitment tools. The processes and legislative frameworks recruiters work within will vary between organisations and regions, so the information given here will necessarily need to be applied in a way that is consistent with these local frameworks.