Abstract
When human resources (HR) professionals seek to make data-driven personnel decisions at their utility, they find few tools exist to help them to understand employee turnover across the entire organization. This article addresses this gap by adapting the Kaplan–Meier estimator, or KM curve, from the field of oncology and applying it to the City of Houston's Public Utilities Division. The analysis used historical employee rosters for the period from 2007 to 2016 to determine which groups of utility employees contribute most to turnover. Findings indicate that the majority of employees who left the organization did so either during their first seven years of employment or near their 20-year work anniversary. The resulting workforce plan includes recommendations for targeted intervention activities for these two groups. Other utilities can similarly apply the KM curve to develop an understanding of their patterns of turnover and to identify opportunities to increase employee retention.
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