PREDICTORS OF THE STAFFLAYOFFS IN THE SYSTEM OF PROVISION OF ITS SUSTAINABLE DEVELOPMENT

Abstract

The necessity of predictions of the stafflayoffs in the system of provision of its sustainable development has been substantiated. The article determines the staffstable development as a certain dynamic state of the staff management system, which characterizes its ability to maintain performance under the influence of internal and external disturbances, which is evaluated by a balance of quantitative and qualitative parameters. The assessment of the staff sustainability is based on the application of a system of indicators of fluidity, stability, mobility and turnover of the staff, which enables to determine the stability of staff and to identify the situation of its violation.The resilience of the staff is determined by the employer's ability to provide competitive conditions for the development of the staff as their correspondence to the average industry, specialty, other enterprises and complexity of tasks performed.In the article the most common of the layoffs, such as: dissatisfaction with the level of wages or working conditions, the lack of prospects for career growth; unfavorable atmosphere in the team and mischievous or uninteresting work have been identified and analyzed on the basis of an expert survey.The structure of predictive analytics to predict layoffs and prevent staff turnover has been defined. The predictors that signal about the probable layoffs and the violation of staff sustainability have been identified. Based on expert reviews, it is determined that the main predictors of layoffs are the following: uncompetitive wages of employees compared to the average in the market or in the industry; the level of wages does not increase according to the tasks performed; there is an excessive turnover of the staff as a whole on the enterprise or unit.It is ascertained that predictive analytics results in the implementation of social technologies for working with the staff with the aim of preventing excessive layoffs and creating a positive image of the company in the labor market.