The hiring process is often long, expensive and labor-intensive for companies. After investing so many resources into recruiting top talent, it can be highly frustrating when new hires underperform or leave shortly after being onboarded.
This disconnect between perceived and actual skills is extremely difficult to gauge through traditional interviews and resumes alone. Unconscious biases like halo effects or demography can further cloud evaluations. By the time skills shortfalls are revealed on the job, it's often too late—the hire has already been made!
Machine learning models can then map candidates to specific role requirements based on these verified skill fabrics. You get rigorous talent-role fit scoring based on data instead of resumes or interviews alone. High-potential candidates are surfaced that may have otherwise been filtered out based on pedigree proxies like college brands.However, skills-based hiring is just the start. To build a high-performing workforce, you need to continually track and manage employee skills growth.