Integrating decision tools for efficient operations management through innovative approaches.

Area of Science:

• Operations Management
• Decision Science
• Business Strategy

Background:

• Traditional operations management (OM) struggles to balance cost, quality, and adaptability.
• Organizations need clearer guidance for selecting optimal OM strategies in dynamic environments.

Purpose of the Study:

• To introduce a novel decision-support framework for enhancing OM strategy selection.
• To integrate objective and subjective insights for a balanced evaluation of OM approaches.

Main Methods:

• Utilized CRITIC (Criteria Importance Through Intercriteria Correlation) for objective weighting.
• Employed CIMAS (Criteria Importance Assessment) for subjective weight determination.
• Applied WASPAS (Weighted Aggregated Sum Product Assessment) for comprehensive strategy ranking.

Main Results:

• Assessed five OM approaches (lean, automation, sustainability, flexible workforce, data-driven) against eight performance criteria.
• Data-driven decision-making identified as a leading strategy for operational excellence.
• Alternative OM strategies showed advantages across different performance dimensions.

Conclusions:

• Multi-criteria decision-making (MCDM) techniques offer significant potential for informed OM strategy selection.
• The hybrid weighting approach provides a balanced and practical evaluation of competing strategies.
• The study offers a roadmap for organizations aiming for efficiency and sustainability in operations.