Managing Complexity in Mega Steel Projects: Leveraging Digital Technologies in India’s Steel Industry

Abstract

The growing size and technologic advancement of the industrial projects have contributed greatly to the complexity of project management especially in the industries which are capital intensive like the steel industry. During large steel projects, there is a high level of engineering integration, a complicated supply chain, regulatory limitations and a number of stakeholders interaction, which often results in schedule delays, cost increases and coordination issues. This paper explores structural factors that cause project management complexity in the Indian steel sector and suggests a combined model to enhance the effectiveness of project management. The research design was mixed-method involving a qualitative assessment and quantitative survey analysis. A total of 412 professionals working in steel sector projects such as project managers, engineers and senior management personnel were used as a source of primary data. The study used SWOT analysis, descriptive statistics, and structural relationship analysis to determine the major project management challenges and the causal factors behind the challenges. The results have shown that project planning and scheduling (Composite Score = 4.26), cost management (4.21), procurement management (4.20), and risk management (4.17) are the most significant challenges in project management. Root cause analysis reveals that these challenges arise from interconnected factors related to human competencies, organizational processes, and external environmental conditions. Statistical validation confirms that the People dimension (β = 0.412) has the strongest influence on project management effectiveness, followed by Process (β = 0.385) and Business Environment (β = 0.327). On the basis of these results, the proposed study is the Three Arm Clock Model of Project Management Effectiveness, which frames project performance as the dynamic interplay of People, Process, and Business Environment dimensions. Moreover, the study presents an AI-powered Project Management and Monitoring System (APMS) to increase risk prediction, decision support, and real-time project monitoring using digital technologies. The paper can add to the project management body of knowledge through offering a unified analytical approach towards comprehending the complexity of projects in a large industrial-scale infrastructure and also through offering a feasible contribution on how to enhance the performance of projects in the steel industry through digital transformation and data-driven management practices.