Digital reengineering of business processes of construction development enterprises: system-innovative solutions and implementation methodology
DOI:
https://doi.org/10.32347/2707-501x.2022.49(2).273-281Keywords:
digital reengineering, construction development, digital ecosystem, process mining, value stream mapping, business processes, innovative resilience, strategic management, risk management, digital collaboration, data integration, flexible management models, transaction costs, operational logic, predictive analytics, digital transformationAbstract
The article addresses the issue of implementing digital reengineering of business processes in construction development under conditions of increasing market complexity and growing requirements for the innovative resilience of enterprises. Digital reengineering of business processes is interpreted not as automation of existing procedures, but as a radical redesign of operational logic using systems thinking, a process-oriented approach, and lean construction principles. The implementation methodology covers several levels: the strategic — with the definition of the value proposition and data and risk management policies; the process level — with the application of process mining tools and value stream mapping for empirical identification of bottlenecks and duplication of actions; and the design level — with the formation of a target integration architecture based on open interfaces, APIs, and controlled versioning. Special attention is given to personnel training and the development of competencies in digital collaboration, since a change in technology without a change in management practices does not ensure sustainable results.
Significant attention is devoted to process mining tools, which provide an evidence base for selecting candidates for reengineering. The article highlights key solutions (Celonis, Disco, ProM, Apromore, UiPath Process Mining, etc.) that allow diagnosing actual workflows, approval times, the number of RFIs, BIM collisions, and deviations from project schedules, thus improving forecasting accuracy and shaping flexible management models. The study also proposes an approach to piloting and scaling digital solutions through a system of hypotheses and indicators (approval time, collision levels, percentage of repeated data entry, safety incidents, etc.), which ensures verification of results and risk control. Evaluation of the effectiveness of reengineering is integrated into the change management process through a tree of indicators combining financial, technological, safety, and environmental metrics with the maturity criteria of project participants.
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