Companies using automated hiring systems must change tack to include viable candidates or face an ever-shrinking talent pool.
A 2019 partnered study between Harvard Business School and Accenture reported 90% of employers used an Applicant Tracking System (ATS) and Recruiting Management System (RMS) to reduce the time and cost of locating new hires but 88% of the same employers also believe that automated vetting process dismissed many qualified candidates. The systems, which were installed to illuminate the cream of the crop thus continue to exclude millions of skilled workers.
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Often this is due to rigid parameters used as inaccurate proxies for the skill of candidates, for example any gap in employment leading to ineligibility of the candidate even when justified or necessary. The result: mutual harm as companies continue to bemoan employee shortages and candidates struggle with un- or underemployment.
Automated hiring systems still need human oversight
The automated systems enable companies to organize all recruitment processes in their pipeline: job descriptions are generated, interviews scheduled, candidates are even screened, scored, and shortlisted. The benign side of the systems, such as scheduling interviews and creating timeline targets do reduce the workload of recruitment managers on the hunt for candidates.
However, human oversight is a must for the functions with more potential for bias, i.e., the scoring of candidates. The exclusion of capable candidates by AI occurs time and time again and in the long run presents a loss of human assets to the company.
A widely covered example was Amazon’s 2018 use of AI recruitment that disqualified female candidates as less suitable for technical roles. Such methods of selecting candidates dash the hopes of many who have gaps in their employment, non-traditional qualifications, physical disabilities, or a host of other barriers to employment. These candidates could outperform their peers when given the chance and alleviate any shortages.
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By GlobalDataEfficiency in recruitment has become too much of a single-minded focus
In the last year, Covid-19 highlighted yet again the pre-existing issues facing automated recruitment as unsuccessful candidates shared their experiences of puzzling hiring practices. Yet, on the side of the companies there is an increasing demand for skills that is unmet, not just as seen in high street wanted signs, but, in, for example, a worldwide shortage of cybersecurity professionals, as reported by GlobalData. Only businesses who seize these “hidden” workers will reduce risks to their growth and receive returns on their investment in their employees.
A key suggestion from GlobalData to tackle the shortage is the use of broader and inclusive recruitment. Companies must draw from the underutilized assets of workers by creating bespoke automated recruitment systems. Most current automated recruitment attempts themselves lack the skills to deliver the right results. These systems need human managerial oversight that can use affirmative criteria to prioritize being able to spot and hire missing parts of the global workforce.
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