With increasing competition in attracting and retaining top talent presenting a significant challenge to businesses across industries, new innovative solutions in identifying candidates who are the ‘right fit’ for vacant positions have peaked the interest of the recruitment sector.
Jacqui Ford - CEO of professional staffing and recruitment body, the Federation of African Professional Staffing Organisations (APSO) - notes that solutions which assist in understanding the true capabilities of candidates would mean the end of recruiting ‘average’ employees. “This will seriously increase the chances of recruitment companies presenting the best professionals, with the required skills, and who is a good cultural fit for the hiring organisation.”
“The insights gained from utilising such solutions may also assist in job-seeker guidance, as one would be able to identify that a candidate who is looking for a job in marketing may be better suited for a position in sales.”
“A growing trend in terms of offering the sector such a solution is machine learning,” explains Ford.
She highlights that this form of Artificial Intelligence (AI) is being used globally to focus recruitment efforts and actively target top candidates.
A subset of AI, machine learning is commonly defined as giving computers the ability to learn without being explicitly programmed.
Ford says, “There is significant potential to improve the overall efficiency and operations of recruitment companies by simply being able to profile and evaluate candidates more accurately and quickly.”
“With this in mind, it is important to note that even with further technological integration, human recruiters would still be a vital and complementary part of the process. Their time, however, would no longer be spent on time-consuming and repetitive ‘grunt work’, but rather on interacting and engaging with clients and potential recruits,” she adds.
Experts in the field of machine learning have also highlighted how the technology can be used to scan through aspects of candidate information and identify potential hires, while also filtering out those who are not adequately skilled or who have been found to have lied or embellished facts on their resume.
Daniel Schwartzkopff - Commercial Director and Co-Founder of Cape Town-based tech start-up and machine learning specialists, DataProphet - explains that while people have traditionally used computers as calculators, they are actually much better at spotting patterns in datasets than humans are.
“Using machine learning algorithms, computers can now identify the equation as well as compute its result,” he explains.
In terms of recruitment specifically, Schwartzkopff notes that machine learning is being used most commonly to identify the best matches for a particular job.
He says, “A human recruiter will have a limit as to how many CVs he or she can read through in a day but, by using a machine learning algorithm, it is possible to scan through all possible CVs on file or on a social network like LinkedIn.”
“Machine learning algorithms have also been used to predict the likelihood of a person leaving their current job in the next three months; what the trends in industries and job titles are; as well as to accurately predict the market remuneration for a candidate based on their skills and experience,” Schwartzkopff adds.
Ford concludes that while uptake of machine learning technology is likely to take some time in South Africa, technological advances of the 21st century continue to offer industries the opportunity to improve on their existing structures and processes.
“As with the introduction and use of the web and social media in the past, it is important for industry leaders and professionals to keep up-to-date with trends to remain competitive in attracting talent and exceeding expectations of client companies.”