Using employee turnover data to forecast share price movements
Empirical evidence suggests that the financial performance of companies is inversely correlated with employee turnover. More interestingly, we look into this subject in more depth by assessing whether this relationship is exacerbated or dampened across particular industries or level of employee seniority. We also outline several alternative data providers we believe are best placed to provide such predictive turnover analytics.
The link between employee turnover rates and company profits
A study published by the Journal of Management found that a one standard deviation decrease in turnover rates was associated with a $151m increase in profits among the top 1000 Fortune companies. Although the study found that the mean corrected correlation between turnover and organizational performance is relatively low (at –.03), the relationship is stronger for managerial employees (-.08), in midsize organizations (-.07) and manufacturing & transportation industries (-.07).
Other studies have found that collective turnover (i.e. total turnover, including voluntary and involuntary) can hurt operational and financial performance by adversely impacting productivity, sales, profits and shareholder returns. In addition, high turnover can lead to higher accident rates, a reduction in manufacturing efficiency, increased customer wait times and inferior service quality. Intuitively this makes sense – the loss of human capital disrupts operations, increases recruitment costs and occupies the remaining workforce with short term distractions such as newcomer socialization and training.
At Neudata, we have noticed that many studies on this topic have analysed certain individual-level predictors. Specifically, it is not uncommon to find the following factors being identified as influential components of employee churn:
- Employee demographics
- Job satisfaction
- Organisational commitment
- Job embeddedness1