In an ever-evolving world, Medtronic is at the forefront of the human resource management (HRM) revolution by integrating artificial intelligence (AI) to effectively improve employee retention. This innovative approach optimizes talent management, transforms HR operations, reduces turnover costs and improves employee satisfaction.
The medical devices company has significantly increased its focus on predicting employee retention through its Predictive and Advanced People Analytics (PAPA) team, using sophisticated tools provided by Dataiku. By predicting turnover before it occurs, HR specialists can take proactive steps to retain employees, saving substantial costs associated with turnover, estimated at 50% to 200% of an employee's annual salary, according to sources such as Gallup and Payactive.
Managers at Medtronic now use risk retention ratings, assisted by consultants and AI tools, to categorize employees from junior staff to CEOs. This strategy enables personalized support for key talent through professional growth and development opportunities. In some cases, this may also involve retention bonuses or workload adjustments.
Data Integration
The implementation of Dataiku has greatly simplified the data import and analysis process at Medtronic. This platform integrates seamlessly with Medtronic's HR data warehouse in Snowflake, facilitating the use of diverse data sources, including Workday history, salaries, bonuses, performance ratings, and aggregated results from the Organizational Health Survey. Data scientists at Medtronic use these tools to create predictive models that identify employees at high risk of turnover, enabling managers to implement timely corrective actions.
Achievements and improvements
The company's effective use of AI has achieved thousands of successful predictions of risk retention ratings to HR business partners and talent management specialists. This effort has identified approximately 200 U.S. employees with risk ratings much higher than initially assigned by their managers, potentially saving millions in avoided turnover costs.
