Reorientation of the economic priorities of reengineering to the digital formalization of the operating space of the construction enterprise

Abstract

This work describes important transformations in the modern construction sector, associated with the reorientation of economic priorities through the use of reengineering and digital formalization of the operational space of a construction enterprise. Key aspects of this process are considered, such as the implementation of digital technologies, optimization of business processes and the use of innovative strategies to improve the efficiency of production operations. The work also examines the impact of these changes on the competitiveness of construction enterprises and emphasizes the need to adapt to new market requirements through the introduction of modern information technologies and optimization of management practices. This work serves as a basis for further research in the field of strategic management and digital transformation in the construction industry. In the implementation of digital technologies, which is based on data obtained automatically from IoT devices and sensors at the time of their collection. These devices and sensors are connected to machines, platforms and equipment, which allows the creation of information and mathematical models and methods. It also allows for the implementation of increasingly autonomous production and business processes that do not require constant human intervention and have the ability to self-optimize.
 The formalized nature of the methodology, as well as versatile analysis, including the reasoned reasoning of specialists and managers, contribute to increasing the validity of the decisions made regarding the reengineering of business processes. This is important so that the changes developed in the processes are the most effective and meet the strategic goals of the enterprise.
 The work describes the mathematical modeling of the processes that are the basis of digitalization of construction, which flow within the project. These models help optimize jobs based on various parameters such as cost, timing, business sustainability and environmental impact, as well as other characteristics defined by high-quality data (such as timeliness, relevance, accuracy and completeness).