FORECASTING OF FINANCING OF ENTERPRISE CONVERSION

Abstract

Purpose of the study. The task set by the President of Russia to increase the output of civilian products at the enterprises of the defense complex to 50% in 2030 requires the study of various ne-cessary resources, as well as models and methods of managing them. In the context of the econom-ic crisis caused by the coronavirus in 2020, the relevance of studying the possibilities of achieving this significant task is increasing. In this work, the goal is to develop a mathematical model, conduct modeling and assess the need for financing the growth of civilian output at enterprises in the re-search and development industry. Methods. A simulation model for multi-period forecasting of the financial state of the enterprise is used. Methods of processing big data are used to obtain the in-itial information. The means of regression analysis are used to determine the dependencies of the fi-nancial statements. Scenario analysis methods allow us to consider and highlight the significant fac-tors influencing the research goal. Results. A multi-period model of forecasting the financial and economic state of an enterprise has been developed to assess the consequences of an increase in ci-vilian production at enterprises of scientific research and development. The initial data of financial statements based on open data from Russian Agency for Statistics (Rosstat) were obtained, and the aggregation of reporting indicators was carried out. Simulation calculations were carried out in the scenarios of inertial growth, growth with an increase in efficiency, and replacement growth. The task of increasing the share of civilian products to 50% by 2030 at scientific and technical en-terprises in Russia will require significant additional funding, an estimate of about 1,300 billion ru-bles in an inertial scenario. The development and implementation of a program to improve the effi-ciency of enterprises significantly reduces the need for additional financing, the estimate is about 1,100 billion rubles with a slight improvement in efficiency parameters. Conclusion. The results of this study can be used to develop industrial development programs both at the industry level and at the level of individual enterprises. Increasing the output of civilian products will require significant funding. Development and implementation of operational efficiency programs of enterprises can significant-ly reduce the need for additional funding.