A research carried out by Ringier One Africa Media (ROAM) Group has revealed that 9 out of 10 applicants that apply for a job are not a good match for the advertised position. This is caused less by a shortage of jobs, but a fundamental misunderstanding of job requirements, both from employers and candidates.

After analyzing data sets from more than 12 million users, as well as from more than 100,000 employers, across Nigeria and Kenya active in the last two years, ROAM revealed that this anomaly is caused more by a fundamental misunderstanding of job requirements both from the employers and not necessarily as a result of shortage of jobs.

Speaking on the background of the research, ROAM Head of Jobs, Mattew Page, said, “We have recently conducted a data review and were shocked by this huge gap. Our initial hypothesis was that this is due to a shortage of jobs, gaps in the labour markets, and desperation. However digging deeper into our database, our analysis found that many candidates were indeed qualified for other available jobs, but did not necessarily apply for these. African employers and our clients indeed face a challenge in hiring the right people.”

“Hiring the right competency upfront typically returns 3x productivity for the employer. It also minimises the onboarding time required to get an employee up to speed. That is why we have launched smart employer products in the last months. These facilitate a smooth hiring experience for employers, through tech-enabled shortlisting and matching products that identify the best candidate for the best position”, adds Matthew Page.

Clemens Weitz, CEO of ROAM elaborates on the potential for economic growth: “Our research clearly shows that the education of the African job market has a long way to go - both on the seeker and employer side. Solving this challenge will unlock tremendous latent economic potential. Imagine an efficient economy, where all employees sit in the job that is a perfect, natural fit for their individual nature. Productivity and satisfaction would skyrocket. AI and machine learning have tremendous potential, and we plan to fundamentally solve this challenge in 2019.”