• The study highlights a critical framework for integrating analytics in fast-paced, consumer-centric markets. • Analytics capability enhances dynamic capability, driving improved firm performance. • Visibility, agility, and adaptability are key dynamic capabilities for survival in volatile supply chains. • Agility and managerial competency: Top drivers of firm performance in support vector regressor (SVR) feature analysis. The fast-moving consumer goods (FMCG) sector is facing several challenges due to rapid changes in consumer preferences, regulatory pressures, fluctuating resource availability, and complex supply chain operations. Firms are required to integrate data-driven insights into their decision-making processes to develop dynamic capabilities, which help the firms to sense changing market trends and become responsive to market demand by reconfiguring their resources. The main objective of this research is to empirically validate the effect of analytics capability and dynamic capability on firm performance. The theoretical foundation of this research is based on the dynamic capability view. A survey is conducted through a structured questionnaire, and 416 responses are collected from SC managers working in different firms within the FMCG sector in Pakistan. Hypotheses are validated using partial least squares structural equation modelling. The model is further validated, and the contribution of each input feature is measured by using a machine learning model, “Support vector regressor (SVR)”. This research adds to the current literature on sustainable supply chains by empirically testing how analytics capability, when integrated into dynamic capabilities, which include agility, visibility, and adaptability, allows companies, particularly in the FMCG industry, to react proactively to environmental and market dynamics, thus supporting SDGs like responsible consumption and production and sustainable communities.
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Munir et al. (2025) studied this question.
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