Management System for the Formation of a Sustainable Human Resource in the Extractive Industry
Year: 2025
Type: article
Abstract: The article examines the problem of human resource sustainability in the extractive industry. It is determined that staff turnover is determined by the specifics of production, geographical factors, organizational structure, and the dynamics of structural changes in companies. The definitions of turnover, its stages and types inherent in this segment of the economy are considered. The results of the analysis of data on the values of the total turnover ratio and the reasons for layoffs in this segment of the economy are presented. The qualification characteristics of various types of turnover and the structure of losses during employment and dismissal of employees inherent in the considered area of the economy are determined. The possibility of using classification features as a means of diagnosing a situation is being investigated. Modern IT technologies are considered as necessary means to ensure an objective fixation of the situation. The expediency of developing management solutions for companies with a complex divisional structure is substantiated, based on aggregated data reflecting the movement of personnel and taking into account the standards established by the companies. The concept of forming a sustainable human resource is proposed based on the sequential implementation of the following stages: identification of the situation based on information contained in the databases of the company's automated system; classification of business units by type of turnover — deficit or surplus; implementation of measures to compensate for the instability of the human resource based on the results of classification; formation of an employee profile and a roadmap for its development. Due to the significant number of staff and taking into account the divisional structure of companies, the implementation of this scheme is possible only with the use of special applications that support.
Authors: Tatyana Khitrova, Olga Belomestnova
Institution: Baikal State University
Language: English
Topic: AI and HR Technologies
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W4411681133