The Impact of Data Analytics on Centralized Distribution Center Operations in the Pharmaceutical Industry

Vishal Kumar Sharma ()

International Journal of Computing and Engineering, 2025, vol. 7, issue 6, 31 - 46

Abstract: Purpose: This article examines the transformative impact of data analytics on pharmaceutical distribution centre operations through centralization initiatives. The study investigates how analytics-driven centralization simultaneously addresses the seemingly competing objectives of cost reduction and service improvement in pharmaceutical distribution networks, exploring the multifaceted benefits across economic, operational, and strategic dimensions. Methodology: The research employs a mixed-methods approach combining quantitative operational data analysis from five pharmaceutical distribution networks representing 37 distribution centres over a 24-month period with qualitative insights from 28 industry practitioners. The study captures both pre- and post-centralization performance metrics, utilizing difference-in-differences analysis, time series modelling, and multivariate regression to isolate the causal impact of centralization initiatives. Findings: Centralized distribution operations yield substantial improvements including 14.7% reduction in operating costs, fill rate increases from 91.3% to 96.7%, 31% improvement in demand forecasting accuracy, and 73% reduction in compliance-related incidents. The research reveals that real-time visibility enables 94% faster decision-making, more efficient stock imbalance detection, and enhanced responsiveness to supply chain disruptions. Beyond operational benefits, centralization creates strategic advantages including improved customer satisfaction, competitive differentiation, and organizational agility. Unique Contribution to Theory, Policy and Practice: This study addresses a significant gap in the literature by integrating technological, operational, and organizational perspectives on pharmaceutical distribution centralization. It provides the first comprehensive framework demonstrating how analytics-driven centralization can simultaneously optimize cost efficiency and service levels in highly regulated environments. The research offers practitioners actionable implementation strategies and mitigation approaches for common challenges, while contributing to supply chain theory by establishing the synergistic relationship between network-level analytics and operational performance in pharmaceutical distribution contexts.

Keywords: Pharmaceutical Distribution Centralization; Data Analytics; Supply Chain Optimization; Inventory Visibility; Regulatory Compliance (search for similar items in EconPapers)
Date: 2025
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