Case Study: World’s Largest Company achieves 60× interview-effort reduction and 4× broader hiring reach with SHL’s machine‑learning assessments

Data science helps establish cutting-edge technology team

World’s Largest Company faced a major challenge scaling its technology hiring: traditional signals like school or job history were poor predictors of on-the-job success and didn’t scale across diverse candidate pools. SHL addressed this by deploying Automata — a machine‑learning coding evaluator — alongside an IRT‑based adaptive analytical skills assessment to identify programming fundamentals and problem‑solving ability without relying on bios or pedigree.

SHL integrated these assessments into the applicant‑tracking workflow with automated proctoring and cloud delivery, using ML “deep dives” into code, predictive analytics, and data‑driven candidate classification to promote high‑potential applicants. The result for World’s Largest Company was dramatic: 60× reduction in interview effort, 4× broader reach (more inclusive and diverse talent), 100% interviewer satisfaction, and improved selection outcomes (e.g., campus reach scaled from ~4,000 to ~19,000 with selected candidates rising proportionately).