Temporal Patterns of Functional and Dysfunctional Employee Turnover

This study examined temporal patterns in collective employee turnover over a 75 month interval. Time series models were fit to subgroups of functional and dysfunctional turnover. Dysfunctional turnover was defined as voluntary separation among high and average performers and functional turnover was defined as voluntary separation of low performers. Results provided support for the hypothesis that temporal patterns of functional and dysfunctional turnover differ. Patterns among high and average performers were similar, such that employee turnover across several global regions increased during or near July. In contrast, employee turnover among low performers tended to spike during or soon after October. Forecast (prediction) accuracy of turnover differed across groups based on individual performance level. Specifically, turnover among low and average performers was forecast with greater accuracy than overall aggregated turnover or turnover among high performers, the latter being the most difficult to forecast. After time-dependent variation (autocorrelation) was removed from global turnover among high, average, and low performers, these series were cross-correlated with similarly cleaned organizational performance outcomes (i.e., net sales, operating income, diluted net earnings per share). Results from these analyses indicated that organizational performance had a lagged negative relationship with turnover among high performers. The dynamic nature of the turnover and performance variables examined underscores the importance of considering employee turnover as a continuous process. As such, employee turnover should be proactively managed over time.