Purpose - The purpose of this paper is to introduce a novel direction of enquiry into predictions of employee turnover through the application of a qualitative method adapted from marital research. This method focuses on diagnosing the relationship, and has been able to predict divorce with an accuracy of over 90 per cent, as opposed to existing turnover prediction methods' modest success of about 30 per cent. By demonstrating that the method can be applied to turnover research, this study completes a seminal step in developing this promising direction of enquiry.
Design/methodology/approach - The Oral History Interview method for predicting divorce is adapted to employment settings, and tested on Australian legal and healthcare employees. A qualitative analysis of their responses maps the results from this inquiry onto separation-predicting processes identified in marital research. The results are compared to turnover data collected two years later.
Findings - Similar relational processes exist in marital and employment relationships when the marital relationship diagnostics method is applied to organisational settings, demonstrating the utility of this tool in the employment context. Preliminary turnover data indicate that some relational processes are significantly associated with employee turnover.
Research limitations/implications - Future research should examine the predictive power of this tool on a larger sample, and apply it to a wider range of professions, tenure, and positions.
Practical implications - The results indicate that it is viable to diagnose an employment relationship using this diagnostics method developed in marital research.
Social implications - The novel perspective offered in this paper has potential to greatly improve this employment relationship across jobs and organisations, thus improving organisational productivity and individual wellbeing.
Originality/value - Researchers of employee turnover and practitioners seeking to understand and manage it can benefit from this novel and practical perspective on employment.