Forecasting staffing needs in general education: HR-practices and staffing planning model for metropolitan schools

Abstract

Introduction. The development of human capital is crucial for preparing an effective response of the Russian society to the great challenges related to ensuring sustainable economic growth, development and implementation of new promising technologies, increasing labour productivity, and improving the quality of life of citizens. The key role here is played by the state of the education sector, on which the population's mastering of competences, knowledge and skills demanded by the economy and the labour market directly depends. Ensuring the training of highly qualified specialists considering the changing staffing needs of society and trends in the development of the digital economy refers to the urgent problem of management and forecasting of staffing in the Russian education system. Materials and Methods. The methodological basis of the study was formed by reports of international organizations, national agencies in the field of education, reports of working groups, as well as domestic and foreign studies in the field of forecasting the staffing status; official web pages of federal and regional executive authorities that carry out management and control in the field of education; websites of educational organizations of general and higher education; information from open data sources. Qualitative analysis of data using general scientific methods of cognition was carried out on the obtained set of data. Results. The analysed solutions have limitations that make it difficult to directly transfer them to the staff forecasting model for Moscow schools. They do not consider the peculiarities of Moscow education, for example, the directions of the Moscow education development strategy, specifics of the nomenclature of positions and certification of managerial staff, city projects of pre-professional education, optimization of administrative staff, etc. When creating a staff forecasting service for Moscow schools, it is necessary to consider the advantages of platform solutions that provide an integrated interdisciplinary approach using large amounts of data. At the same time, the forecast should consider the peculiarities of the Moscow education system that can affect the staff composition of schools. Discussion and Conclusions. Based on the analysis, a model solution for forecasting the staffing status of educational organizations in the metropolitan education system has been developed, including methodological approaches to evaluation; directions for assessing the dynamics of changes in the staffing status of schools; the structure of the staffing composition of Moscow schools; the structure of primary data; and a set of indicators.