Use machine learning to reduce employee turnover
A major issue for an organization in losing productive employees. In essence, this is loss of competitive advantage. But, what if the at-risk employees could be targeted prior to quiting?
Machine learning is a perfect solution. We can build high accuracy machine learning models to identify those at risk. Further, we can explain what factors lead to turnover. The end result is the ability to preemptively fix issues within an organization.
Once the ML solution is ready, we can distribute HR Analytics via a Microsoft PowerBI web application. HR and Management Professionals, regardless of data science knowledge, can then gain insights and make better decisions.
Use a web app to distribute predictive analytics throughout an organization. The following visualization tells the story of using R to implement a predictive model. Follow the seven tabs to learn how we went from concept to inception of a predictive analytics model. See how interactivity enables better understanding of the problem and solution. Actual model based on our article, HR Analytics: Using Machine Learning to Predict Employee Turnover.
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