BUSINESS INSIGHTS

Jul 24, 2015

Demo Day: Better Hiring and Retention with Predictive Analytics

Mike Cornell Posted by Mike Cornell

Companies of all sizes put a lot of time and money into trying to recruit and hire the right people.  Sometimes those efforts are rewarded with the hiring of an outstanding employee who provides years of service to the organization, but far too often, the result is a mediocre employee who may-or-may not make it to see his next paycheck. 

Flow ChartAdvanced analytics can help.  With today’s analytics tools, we can easily mashup our traditional human resources data with external sources such as resumes, social media websites, and job boards.  This allows us to tell a much better story of who our existing and potential employees are as well as what indicators drive turnover in our organization.  These insights can then be used in more predictive analytics, which might help us be more efficient in choosing good candidates or to identify likely risk factors for potential and existing employees.

Our multipart video series on advanced analytics in human resources will step you through some examples of how this innovative form of “people analytics” can be used.  The examples will use data from large call center organization. The second video, titled “Better Hiring and Retention with Predictive Analytics”, shows how predictive analytics paired with an intuitive, interactive user interface can create a solution that leads to more efficient business processes and better recruiting and retention. 

Watch the video below!

Want to learn more about how advanced analytics can help your human resources efforts? Contact us for a consultation

 

AdvancedAnalyticsWorkshop
Mike Cornell

About The Author

Mike Cornell

Mike Cornell is a former BlueGranite employee. He is passionate about helping to solve business problems of varying size and complexity using data and analytics. Mike's specializations include big data platforms, cloud data platforms, advanced analytics, and data visualization and exploration. His technology interests include the Azure Data Platform, Hadoop Data Platform, Spark, R and Python for data analysis, Power BI, and SQL Server. Check out Mike's blog at http://www.datamic.net .

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