Traditional business process analysis methodologies, such as the Balanced Scorecard and conventional Key Perfor-mance Indicators (KPIs), are widely applied in manufacturing companies that operate under static business models focused on production efficiency. However, these approaches prove in-adequate for dynamic business environments, such as EPC (Engineering, Procurement, and Construction) companies, where projects continuously emerge and evolve. This paper introduces an innovative methodology designed to address these challenges by integrating Porter's value chain framework with System Dynamics methodology and artificial intelligence. The proposed approach enables a more flexible and adaptive analysis of business processes, allowing companies to capture the continuous flow of changes, revisions, and optimizations characteristic of dynamic project-based industries with the integration of AI capabilities and System Dynamics modeling methodology. Furthermore, the study presents a new KPI system tailored to this methodology and explores its practical application. A simulation model prototype was developed to validate the proposed framework, ensuring its alignment with real-world business dynamics. The findings contribute to the advancement of value chain analysis methods and provide a structured approach to performance management in dynamic industrial settings.
Integrating Value Chain Analysis and System Dynamics for EPC Project Optimization
Rozhok, Anastasiia;Revetria, Roberto;Ahmad, Khursheed;
2025-01-01
Abstract
Traditional business process analysis methodologies, such as the Balanced Scorecard and conventional Key Perfor-mance Indicators (KPIs), are widely applied in manufacturing companies that operate under static business models focused on production efficiency. However, these approaches prove in-adequate for dynamic business environments, such as EPC (Engineering, Procurement, and Construction) companies, where projects continuously emerge and evolve. This paper introduces an innovative methodology designed to address these challenges by integrating Porter's value chain framework with System Dynamics methodology and artificial intelligence. The proposed approach enables a more flexible and adaptive analysis of business processes, allowing companies to capture the continuous flow of changes, revisions, and optimizations characteristic of dynamic project-based industries with the integration of AI capabilities and System Dynamics modeling methodology. Furthermore, the study presents a new KPI system tailored to this methodology and explores its practical application. A simulation model prototype was developed to validate the proposed framework, ensuring its alignment with real-world business dynamics. The findings contribute to the advancement of value chain analysis methods and provide a structured approach to performance management in dynamic industrial settings.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.



