METHODS OF ECONOMIC ANALYSIS AND STATISTICAL EVALUATION OF ENTERPRISE EFFICIENCY: THEORETICAL ASPECT
Abstract
The article examines the theoretical and methodological foundations of economic and statistical approaches to evaluating enterprise efficiency under conditions of economic transformation and intensifying global competition. It highlights the importance of economic analysis as a key managerial tool that ensures the rational use of resources, identification of performance deviations, substantiation of managerial decisions, and development of strategic forecasts. The study generalizes existing scientific approaches and systematizes methods applied to assess enterprises’ efficiency at different hierarchical levels. Special attention is paid to the functional role of economic analysis, including its informational, analytical, evaluative, diagnostic, control, and prognostic components, which together ensure a comprehensive understanding of business performance. The paper classifies traditional and modern methodological instruments, emphasizing general scientific and logical-economic methods, factor and comparative analysis, as well as advanced economic-mathematical tools such as econometric modeling, optimization techniques, game theory, and simulation modelling. A separate focus is placed on statistical methods, including index, correlation-regression, dispersion, and cluster analysis, which enable the quantitative assessment of interrelations, trends, and structural changes in enterprise activity. The study also discusses the growing relevance of integral indicators of efficiency, which combine multiple criteria into a single index and allow for effective cross-enterprise comparison and strategic ranking. The article identifies key limitations affecting the accuracy of efficiency assessment, such as data incompleteness, methodological inconsistency, subjectivity in indicator selection, and the influence of unpredictable external factors. It argues that overcoming these challenges requires integrating economic, financial, statistical, and expert approaches, supported by modern digital technologies for data processing and visualization. In outlining future development trends, the paper underscores the increasing role of Big Data analytics, artificial intelligence, machine learning, ESG metrics, and interactive dashboards in enhancing analytical precision and managerial adaptability. The study concludes that the evolution of economic analysis should follow the path of digitalization and methodological synthesis, transforming it into a dynamic and flexible system capable of ensuring sustainable competitiveness of enterprises in a rapidly changing environment.
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