DOI: 10.36347/sjebm.2016.v03i12.009

Pages: 709-723

Pharmaceutical supply chains in emerging and transitional markets have historically suffered from operational fragmentation, limited visibility, and inefficient distribution workflows. Prior to 2016, business intelligence (BI) systems predominantly operated in retrospective modes, offering descriptive analytics without predictive or prescriptive capabilities, while geospatial technologies remained confined to static mapping applications disconnected from operational decision-making. This paper addresses a critical gap in the literature: the lack of integration between geospatial analytics and workflow optimization in pharmaceutical distribution. We propose a comprehensive framework for geospatially enabled workflow optimization that embeds spatial analytics into BI-driven operational processes. The framework integrates outlet-level sales data, territory coverage metrics, travel-time analysis, and inventory movement patterns to operationalize spatial insights in demand forecasting, route planning, order prioritization, and territory optimization. Drawing on technologies available by 2016, including relational databases, GIS layering, ETL pipelines, and dashboard analytics, this research presents an original contribution by shifting spatial data from an auxiliary reporting tool to a central operational driver. The proposed model offers a transferable approach for multinational pharmaceutical companies and emerging-market distributors, with demonstrated potential to improve medicine availability, distribution efficiency, and commercial performance. This work synthesizes insights from 20 peer-reviewed studies published before April 2016, establishing both theoretical foundations and practical implementation pathways for integrated geospatial-BI systems in pharmaceutical supply chain management.