CASE STUDY

30% Reduction in Employee Turnover Rates Achieved by a Retail Chain Through the Implementation of Turnover Prediction Models

Sep 23, 2016

Business Challenge

Reducing employee turnover rate.

A leading retail chain wanted to understand the cause of the high turnover rate of its employees, their reasons for leaving, and target areas that can help increase retention.

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Situation

Impact on operations due to a significant increase in employee turnover.

The client had seen a significant increase in employee turnover in recent months, which was directly impacting their operations and ability to handle customers. This eventually started negatively impacting customer satisfaction.

Solution/Approach

Turnover prediction model to identify stores/areas at high risk.

We conducted data analysis on information gathered through surveys with employees to assess the reasons for turnover. We also developed a turnover prediction model with high accuracy and conducted regression on top factors to create clusters of high risk. The solution also provided customized dashboards for visualization of predicted turnover and stores/areas at high risk.

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Impact

Reduced levels of turnover and efficient risk mitigation planning.

The client gained better insights into the reasons for increased turnover. We deployed an on-time risk flag that predicted potential turnover and high-risk zones. The client was also able to improve its risk mitigation planning linked to seasonal absences, resignation trends, etc. Based on the insights, the client strengthened its recruitment planning, which helped in avoiding being blindsided by the loss of critical workforce. The major benefit was a reduction in turnover rate by up to 30%.

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