Abstract
The article explores the vital subject of optimizing business process management, which is essential for enhancing the efficiency and competitiveness of enterprises. The study evaluates various perspectives, including economic, engineering, and managerial aspects, and underscores the importance of mathematical models over descriptive models in achieving precise and effective optimization. Descriptive models, despite their widespread use, do not guarantee optimal outcomes. The article emphasizes the need for mathematical models to accurately optimize business processes, considering various criteria and constraints. This approach aims to address the limitations of current descriptive models and advocates for the development of specific mathematical models to manage business process optimization under uncertainty. Key findings reveal that optimization in business process management has a significant impact on enterprise efficiency, productivity, and competitiveness. The process approach, which concentrates on enhancing individual business processes, is highlighted as a crucial paradigm in modern management. The research calls for further investigations to develop mathematical models that can deliver more reliable and precise optimization results, especially in uncertain conditions. In conclusion, the article supports the transition from descriptive to mathematical models in optimizing business process management to achieve maximum efficiency and competitiveness in enterprises. Future research will focus on developing mathematical optimization models for business processes, particularly those related to new product development under uncertain conditions. This shift is anticipated to offer more accurate and effective solutions for optimizing business processes in a dynamic and unpredictable business environment. Furthermore, the article highlights the need for continuous development and application of mathematical approaches to ensure that business processes are optimized effectively. It stresses the importance of incorporating various optimization criteria and constraints to achieve the best possible outcomes. By transitioning to mathematical models, businesses can better navigate the complexities and uncertainties inherent in today's competitive landscape, leading to improved performance and sustainable growth.
Published Version
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