With over 50,000 employees, the customer’s HR department already faced significant challenges: even routine tasks were long, repetitive, and tedious. In recent years, these issues were compounded by challenges such as the need to address possible attrition and difficulty identifying future leaders in a diverse workforce.
They needed a digital solution to predict potential employee departures and identify leadership potential – based on data, not biased evaluations. Eventually, the goal was to increase employee retention, retain institutional knowledge within the company, and reduce reliance on manual processes and subjective evaluations.
We developed a custom predictive analytics solution powered by AI and machine learning algorithms. It includes two predictive models that automate the identification of employees likely to leave within 6/12/18 months and highlight those with high leadership potential.
Our approach included:
Implementing the predictive analytics solution has transformed the customer’s HR processes. The company now has early visibility into potential employee attrition, enabling proactive retention strategies.
Additionally, the automated identification of leadership potential has streamlined succession planning, reducing manual efforts and bias, and thus ensuring a more objective and data-driven selection process for competent leaders in critical roles.
By automating these processes, the customer’s HR teams save time and resources as they no longer need to manually process biased or inaccurate survey data. Instead, the ML models provide non-biased, up-to-date information automatically, with a desired frequency.
