PRIORITY AREAS OF APPLICATION OF ECONOMIC ANALYSIS IN THE CONTEXT OF DIGITALIZATION

Abstract

The article examines the transformation of the methodology of economic analysis under the influence of digital technologies. It is determined that digitalization changes the paradigm of analysis from retrospective to predictive. The author emphasizes the need to rethink the role of economic analysis under the conditions of digitalization. In particular, he argues that traditional economic analysis, which was based on periodic financial reporting, becomes insufficient for making management decisions in real time, therefore, in the process of analytical activity, it is worth combining methods of artificial intelligence, machine learning and big data for further prediction of the activities of business structures. The author identifies and describes in detail the key priorities for the development of economic analysis: predictive analysis and the use of Big Data, analysis of digital ecosystems, assessment of cyber risks and monitoring of sustainable development indicators (ESG) using automated systems. The paper describes the basic principles of predictive analytics, including key principles and methods of predictive analytics and various types of data that can be used to create predictive models, as well as tools and technologies that support this process. Particular attention is paid to the analysis of the effectiveness of digital business models, the need to implement the latest technologies and close cooperation with international partners to form a single digital market with the EU, which is a priority of the digital transformation policy in wartime. Given the existence of digital risks and cyber threats, it is proposed to consider economic analysis from the perspective of combining organizational (technical), financial and strategic processes. It is proposed to use ESG monitoring to track and assess the environmental, social and managerial aspects of a modern company's activities. It has been established that the combination of modern analytical tools, Big Data technologies, artificial intelligence and machine learning in the process of assessing analytical activities allows significantly increasing the accuracy, flexibility and predictive value of analytical models. It has been proven that digitalization improves the performance of business processes and provides sustainable competitive advantages for business entities in the long term.