Finnish Institute of Occupational Health press release 3 October 2024
Approximately one in five employees in the municipal and well-being services sector left their employer during the two-year follow-up. Three main characteristics shared by job changers were identified: younger age, shorter period of employment with the employer and intentions to change employer. The combined weighting of these factors in predicting turnover risk was more than 70 per cent.
Other factors did also emerge, but their weighting was only 1-4 per cent per factor. The likelihood of changing jobs was somewhat increased by a short time in the current position and working part-time. Of the work-related factors themselves, the most significant predictors of changing jobs are uncertainty about the continuation of work tasks and dissatisfaction with the level of challenge that the work poses.
"Our turnover risk prediction model demonstrates the characteristics, experiences and views that are common to those who change jobs. The accuracy of the model was also quite good. We were able to predict leaving the employer with an accuracy of 75 per cent using the 15 variables included in the model," says Jenni Ervasti, Senior Researcher at the Finnish Institute of Occupational Health.
The prediction model provides information on the working conditions prior to departure and on individual characteristics
There can be many actual reasons for changing jobs, and the employer is responsible for determining them; for example, by means of exit interviews. The variables included in the model shed light on the working conditions prior to leaving as well as the characteristics of the individuals, but not on the attraction factors that the new employer may have offered.
“Nonetheless, the prediction model demonstrates who should be focussed on at the workplace and what issues are worth collecting information about from employees, especially in sectors suffering from labour shortages,” Jenni Ervasti sums up.
"It is gratifying to see that issues with supervisors and dysfunction of work communities hardly emerged at all as factors for people leaving their workplaces. Supervisory work and the functionality of work communities have both continuously improved in our follow-up studies, and they are at a good level in both municipalities and well-being services counties," says Senior Specialist Risto Nikunlaakso from the Finnish Institute of Occupational Health.
Keva monitors the well-being at work and work ability of the municipal and well-being services sectors and regularly predicts the retirement of personnel.
"The study carried out in collaboration between the Finnish Institute of Occupational Health and Keva provides additional information on personnel turnover. One in three employees of municipalities and well-being services counties will retire over the next ten years. As the number of people leaving due to retirement is high, workplaces should ensure good working conditions in order to retain the current working-age personnel. This is particularly important for employees in the early stages of their careers," says Laura Pekkarinen, Research Director for Keva.
More information on predicting turnover risk
- The turnover risk prediction model was built using data from the Finnish Institute of Occupational Health’s follow-up study of employees in the municipal and well-being services sector, which included more than 61,000 employees.
- The model details how likely the respondents in the 2018 Kunta10 survey were to be employed by the same employer in the 2020 survey. All of the 158 questions or statements of the well-being at work survey were included in the model as potential predictors of intention to change jobs. The functionality of the model was ensured by utilising data from the well-being survey carried out on hospital district personnel in 2017 and 2019.
- The study "Development and validation of a predictive score for personnel turnover: a data-driven analysis of employee" has been published in the SocArXiv pre-print service.
- The "Employee turnover in the municipal and well-being services sectors" page contains a list of the most significant factors predicting the risk of employee turnover and tips for reducing it (in Finnish).
- The study on predicting personnel turnover risk was funded by the Finnish Institute of Occupational Health and Keva's Sustainable working life project, which has received state grants from the Sustainable Growth Programme for Finland financed by the EU Recovery and Resilience Facility.
Further information
- Jenni Ervasti, Senior Researcher, Finnish Institute of Occupational Health, jenni.ervasti [at] ttl.fi, +358 30 474 2806
- Risto Nikunlaakso, Senior Specialist, Finnish Institute of Occupational Health, risto.nikunlaakso [at] ttl.fi, +358 30 474 2505
- Laura Pekkarinen, Research Director, Keva, laura.pekkarinen [at] keva.fi, +358 20 614 2748
