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Chief Scientist talks predicting attrition at INFORMS Boston event


In case it wasn’t clear before – predictive talent analytics, curiosity, data science, and pizza go GREAT together!

Pasha Roberts, Talent Analytics

On the evening of February 24, a small but enthusiastic group from the Boston Chapters of INFORMS and the American Statistical Association gathered at Bentley University, along with Bentley University analytics students following online, to hear Talent Analytics Chief Scientist & Co-founder Pasha Roberts discuss the application of data science to workforce optimization.

After being introduced by Victor Lo, himself a pioneer of uplift modeling, Pasha explained the application of predictive concepts such as survival analytics, uplift modeling, and ensemble models to tangible customer situations. As Victor pointed out, this topic hadn’t been addressed at prior INFORMS Boston events, which prompted an excellent discussion with outstanding questions from an inquisitive audience of analytics and OR professionals.

Victor Lo, pioneer of uplift modeling.

In addition to providing many examples of predictive techniques, Pasha highlighted a detailed case study on using predictive modeling to reduce attrition by over 30%, yielding a multi-million dollar savings.

Overall, analytics managers and students walked away from the evening with a concrete understanding of the business value of talent optimization, showing how correlating “raw talent” to employee attrition can yield unprecedented results.

In case you missed it, request the recording and listen to Pasha’s full 1.5 hour presentation and accompanying Q&A.

Additional Resources on Predicting Employee Attrition

 




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