ЗАСТОСУВАННЯ МАТЕМАТИЧНИХ МЕТОДІВ ТА МОДЕЛЕЙ У БЕНЧМАРКІНГУ, APPLICATION OF MATHEMATICAL METHODS AND MODELS IN BENCHMARKING

<jats:p>The article explores the theoretical and practical aspects of the application of mathematical methods and models in the benchmarking system as a modern tool for improving the efficiency of enterprise management. In the context of the digitalization of the economy, increasing competition and the need for prompt management decisions, the use of quantitative methods of analysis for comparing the performance of business entities is of particular relevance. It is substantiated that benchmarking is an important strategic management tool that allows you to identify best practices, determine reference indicators and adapt effective development models to the conditions of a particular enterprise. Considerable attention is paid to the study of the role of statistical methods, econometric models, multivariate analysis methods, optimization algorithms and machine learning tools in the process of forming an analytical base for benchmarking. The use of statistical methods in benchmarking allows you to: generalize large data sets; identify typical and limit values of indicators; assess the variation and stability of processes; determine statistically significant differences between objects; to form objective standards (benchmarks). Multidimensional analysis in benchmarking is used for: comprehensive comparison of objects by set of KPIs; reduction of data dimensionality without loss of essential information; identification of typical groups (clusters) of enterprises; formation of integral performance indicators; justified choice of standards (benchmarks). Thus, multidimensional methods allow to move from fragmentary analysis of individual indicators to a systemic vision of efficiency. The paper considers the possibilities of using correlation-regression analysis, clustering, factor analysis, Data Envelopment Analysis (DEA), as well as modern predictive models for assessing the efficiency of enterprises. It is proved that the use of mathematical modeling contributes to increasing the accuracy of indicator assessment, identifying hidden patterns and forecasting development prospects. The practical significance of the study lies in the possibility of using the proposed approaches to form an effective system of strategic analysis, planning and control of the effectiveness of enterprise activities in an unstable market environment.</jats:p>