Analyzing the Impact of Data Science Methods on Improving the Efficiency of Management Decisions

Анотація

The purpose of this study is to analyze the impact of data science methods on the effectiveness of management decisions in the current conditions of dynamic change and uncertainty, particularly in the context of martial law in Ukraine. The paper investigates how modern analytical tools contribute to improving the accuracy of forecasts, optimizing resources, and speeding up decision-making. To achieve this goal, the following methods of scientific knowledge were used: literature analysis - to systematize knowledge about Data Science methods; system analysis - to identify relationships between components of management processes; data visualization - to present results in an understandable form. The study was conducted in three stages: preparatory - analysis of scientific sources and identification of key issues; analytical - evaluation of the effectiveness of Data Science methods in various fields (business, logistics, marketing, etc.); and final - formulation of recommendations and conclusions. The results obtained indicate a significant impact of Data Science methods on the efficiency of management processes. The use of predictive modeling can achieve forecast accuracy of up to 85%, and clustering algorithms can improve targeted marketing strategies, which helps to optimize costs. In logistics, data science helps reduce delivery times and improve supply chain management. In the context of martial law, these tools ensure adaptation to rapid changes in the external environment and efficient resource management. The findings of the study emphasize the importance of integrating data science methods into modern management processes, particularly in improving the accuracy of decisions, optimizing resources, and reducing risks. Further research can be aimed at a deeper analysis of adaptive Data Science models for crisis conditions, as well as at studying the ethical aspects of the use of analytical technologies. The development of Data Science tools can be a key factor in economic recovery after a crisis. The integration of these technologies will not only improve the efficiency of management decisions but also help to create sustainable business models for long-term development.