Automated resume scanning software that is inflexibly configured and overlooks potentially suitable workers is a major contributing factor to a “broken” hiring system in the United States, according to a new report from Harvard Business School (HBS) .
The HBS report (pdf), released on September 4, provides an overview of America labor market dynamics, including the widely reported mismatch between the more than 10 million vacancies – a record – and the more than 8.4 million unemployed actively looking for work.
Business owners complain that they cannot find enough workers and have to increase wages to attract new hires. At the same time, swathes of willing and available workers remain “invisible” to recruiters, who have become increasingly dependent on automated software inflexibly configured and filtering out large numbers of viable candidates, according to the report.
“Businesses are increasingly desperate for workers. As they continue to struggle to find the people with the skills they need, their competitiveness and growth prospects are put at risk, ”the report’s authors wrote.
“At the same time, a huge and growing group of people are unemployed or underemployed, eager to find a job or increase their working hours. However, they effectively remain “hidden” from most companies who would benefit from hiring them through the very processes these companies use to find talent. “
“Hidden workers,” according to HBS, include people with no traditional skills, caregivers, veterans, relocating partners and spouses, and people with physical disabilities.
The HBS study identified a number of factors contributing to the disconnection from the labor market, including a growing training gap and the inability to recognize and elevate the business case for hiring “hidden workers” . But automated CV analysis software is a major piece of software, with 88% of employers polled for the study saying highly qualified candidates were excluded from the hiring process because they did not meet the exact criteria in the description. of post, with this number rising to 94 per cent for mid-skilled workers.
Automated systems are the foundation of hiring processes, with over 90% of employers surveyed for the HBS report indicating they use platforms such as the Applicant Tracking System (ATS) and the Recruitment Management System. or marketing (RMS) to help recruiters. One of the problems, according to the study, is that these systems are configured to rely primarily on “negative” filters, such as an employment gap or lack of a college degree, to exclude those who are not. candidates.
“While employers may infer that candidates who have these attributes are not worth considering, applying ‘affirmative’ logic would seem a more logical approach to seeking talent,” the authors argued. . “Setting up systems to identify candidates with the specific skills and experiences associated with meeting basic job requirements held the promise of being more effective. “
This problem is compounded by outdated job descriptions, which, rather than being reassessed and written from scratch, are often “littered with legacy demands and ‘nice to have’ attributes rather than focusing on one. Limited list of skills and “must have” experiences that correlate with performance in the role.
Other adjustments to hiring processes that could help companies hire and the unemployed find jobs include targeting specific segments of ‘hidden workers’ – such as veterans, caregivers and people with disabilities – while establishing new metrics to assess talent acquisition, such as attrition rates and the time it takes for a new hire to reach expected productivity levels.
Already, companies that have changed their hiring processes to focus on “hidden workers” are reporting clear benefits, according to HBS. These companies said they were 36% less likely to face talent or skill shortages compared to companies that did not target “hidden workers”, while indicating that these workers outperform their peers on criteria such as attitude and work ethic, productivity, commitment, attendance and quality of work.