Optimization of The Budget of The Industrial Complex Transformation Strategy Based on Neural Network Modeling

Abstract

The purpose of the study is to develop and test methodological tools for optimizing the structure and directions of budget spending strategies for transformations of industrial complexes. The relevance of the study is due to the need to restructure business processes and models of strategic management in industry, as well as the overall increase in the efficiency of domestic enterprises in the conditions of the formation of the digital economy. Currently, Russian industry is developing mainly along an extensive path that does not provide a deep innovative transformation of business and the necessary increase in labor productivity.Materials and methods. The data source for the study is Rosstat materials on the development of industry in the Russian Federation, indicators of economic activity of industrial companies contained in SPARK-Interfax databases, as well as the results of monitoring activities of KPMG and the Agency for Strategic Initiatives. The methods of neural network modeling and budgeting, comparative quantitative and structural analysis, index approach and other tools are used in the work.The results of the study. The article substantiates the formation of budgets for transformation strategies of industrial companies based on groups of strategically significant expenses. The analysis has been carried out and the problems of the current budget structure of the transformation strategies of the industrial complexes of Voronezh, Lipetsk, Kursk and a number of other regions have been identified. A methodological technique has been developed that allows choosing the optimal option for allocating the strategy budget funds between the key areas of transformation of the industrial complex, characterized by the use of neural network modeling technologies and providing the greatest increase in revenue and labor productivity while maintaining the financial and economic stability of the enterprise. A neural network of direct signal propagation has been constructed, which is used to predict the values of financial and economic indicators of an industrial complex depending on the allocation of funds in the budget of its strategy. Based on the conducted modeling, the optimization of the budgets of the strategies of enterprises was carried out and the results of their transformation (in terms of increasing revenue and labor productivity) were predicted.Conclusion. The results of the study show that a significant increase in labor productivity in industry can be achieved by increasing the amount of financing and implementing measures aimed at digitalizing business processes, conducting R&D and introducing organizational innovations at enterprises. The analysis shows the high potential effectiveness of transformation strategies of all studied industrial complexes after optimizing their budgets. The highest indicators can be achieved at JSC “Industrial Complex “Energia”, JSC “Schetmash”, JSC “Kursk Electrical Equipment Plant” and other companies. The results of the study can be used by the management of industrial structures as scientific, methodological and practical tools for carrying out institutional changes at enterprises and industrial complexes.