Employee Attrition Data Analysis In R

Here are some of the challenges the company faced: Availability of lucrative offers from other companies Expectations of high salary The right candidate in the wrong job Fewer opportunities to do something new Difficulties faced in work-life balance High level of stress and out-of-reach goals Unable to provide the right training

Explored the employees with HRMS Application Consolidated the five-year historical dataset Explored the datasets and removed outliers and anomalies The team identified 33 key attributes and build a data mart Build a predictive analytics employee attrition model on a training data set The employee attrition analysis model presented a set of characteristics along with statistics Validate attrition model based on the entire data set The employee attrition analysis model predicted and identified the employees who were likely to resign or stay in the organization. Developed a Dashboard for HR Leaders where they can structure out personalized/group strategies for retention.

With this, predictive analytics of employee attrition, HR can plan out retention strategies in order to keep hold of the valuable employee The company can recruit the best-fit resource by finding out the one who is likely to stay Removes bottlenecks and creates the space for the entry of new talents The new employee can bring in new thoughts, new ideas, creativity, and more innovation at work The company can refrain to pay rewards to undesirable employees These results helped the business to reinforce general perceptions of people in the business areas about the hotspots. It gives more mileage for HR to encourage investment in interventional strategies