Integrating decision tools for efficient operations management through innovative approaches.

In a dynamic business environment, operations management (OM) is essential for enhancing efficiency, minimizing costs, and promoting sustainable growth. Traditional OM methods frequently encounter difficulties in balancing various criteria, including cost, quality, resource utilization, and adaptability, resulting in a lack of clear guidance for organizations in selecting optimal strategies. This study presents a novel decision-support framework that combines objective and subjective insights to improve OM strategy selection. This research is distinguished by its innovative integration of three advanced methodologies: CRITIC (Criteria Importance Through Intercriteria Correlation) for objective weighting, CIMAS (Criteria Importance Assessment) for subjective weight determination, and WASPAS (Weighted Aggregated Sum Product Assessment) for comprehensive strategy ranking. This hybrid weighting approach signifies a notable progression in operations management research, facilitating a balanced and practical evaluation of competing strategies. This study assesses five advanced OM approaches: lean management, automation, sustainability-driven operations, flexible workforce allocation, and data-driven decision-making, in relation to eight essential performance criteria. Our findings indicate that data-driven decision-making is a prominent strategy for achieving operational excellence, whereas alternative approaches exhibit distinct advantages across various performance dimensions. The results highlight the significant potential of multi-criteria decision-making (MCDM) techniques in assisting operations management leaders and policymakers in making informed, performance-oriented decisions. This study redefines the future of operations management by addressing efficiency and sustainability goals, offering a practical roadmap for organizations facing complex operational challenges.