Turnover Analysis with Flight Risk

The impact of Employee Turnover on Business

Employee turnover, in businesses like Oil & Gas, Utilities, Retail and Financial Services has always been a problem.

The side effects of a revolving workforce, result in more significant training outlay inconsistent production, poor morale, and also, consequently, restricted or reduced profits.

The background of the Use Case

With the understanding that voluntary turnover is among the most significant challenges for the customer, we started our POC to comprehend the previous year’s turnover data.

Despite the fact that there were challenges in getting the necessary data which may be attributed to a lot of organizational elements starting from capturing the data and employee participation, Renew HR along with MintMesh presented a version which uses the information clustering mechanism that defines a data pattern for those men and women who left the business.

Our Analysis

With our clustering approach predicting the flight risk for every employee gets more scientific than a gut feeling.

According to each personal data, our predictive model was able to label the worker in various data clusters and arrive at the likely flight risk factor for each of these.

With this data HR and People Manager, managed to place a very clear strategy in place for all the employees and drive specific changes in the organizational level to deal with the same.

With the POC that introduced a data pattern which was contrary to the widespread belief that pay increase was the primary factor contributing to the people leaving the company, other aspects were typically overlooked by both the HR and Supervisor community but with our analysis, these issues were simple to address.

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