Case Study: Clearpeaks predicts employee attrition and reduces retention risk with KNIME

How KNIME helps HR teams predict attrition with low-code machine learning

Clearpeaks worked with KNIME to help HR teams tackle employee attrition, a costly challenge that affects recruitment, training, onboarding, project continuity, and customer relationships. Using KNIME Analytics Platform, the team built a machine learning workflow to analyze employee data such as age, gender, education, salary, and business travel frequency to estimate which employees were most likely to leave.

KNIME implemented a solution that cleans and rebalances the data, trains and compares models including Random Forest, Logistic Regression, Naïve Bayes, and Gradient Boosted, and deploys the best model on KNIME Server for scheduled or on-demand scoring. The results are shared through Tableau dashboards and a KNIME WebPortal app so business users can explore attrition risk and simulate scenarios, such as salary increases. This gave HR directors access to attrition probabilities for each employee, helping them build better retention strategies, reduce attrition-related costs, and make more data-driven decisions.

Clearpeaks