Sourcing analytics: A playbook for global supplier exploration and selection
Abstract
This paper provides a playbook for sourcing analytics, that is, exploring and selecting suppliers globally for critical components using analytics and publicly available data. The practitioners’ playbook presents a step-by-step procedure, from defining supplier selection criteria that match the company’s strategic goal, to supplier intelligence for identifying potential suppliers globally, bargaining power analysis for measuring leverage and supplier benchmarking for comparing and selecting the suppliers that best meet the criteria. We showcase the application of this playbook through the example of central processing unit (CPU) sourcing for Apple’s iPhone.
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Author's Biography
Kathleen Iacocca , PhD is an Associate Professor NT of Management & Operations at the Villanova School of Business. She holds a PhD in supply chain management from Rutgers Business School. Kathleen’s research interests include optimisation and supply chain management with applications in the healthcare industry and sustainability. Her current work considers relationships in the pharmaceutical supply chain that improve efficiency and yield cost savings. Another project that she is working on examines the current pharmaceutical distribution and pricing structure in the US. Kathleen’s research has been published in journals including Pharmaceutical Executive, International Journal of Production Research, International Journal of Pharmaceutical and Healthcare Marketing, and Socio-Economic Planning Sciences.
Anh Ninh is an Associate Professor in the Department of Mathematics at William & Mary, where he also serves as a faculty member in the M.S. programme in computational operations research (COR) within the Department of Computer Science. His work is highly interdisciplinary, with a focus on helping decision makers and making decisions in complex, unpredictable environments. His research integrates machine learning (ML) and analytics with traditional optimisation methods to develop innovative solutions for real-world challenges. A significant portion of his work centres on the healthcare sector, where he explores applications such as optimising clinical trial supply chains and enhancing the efficiency and resilience of pharmaceutical supply chains.
Yao Zhao is a Professor in Supply Chain Management at Rutgers Business School, and the co-director of Supply Chain Analytics Lab at Rutgers University. He holds a PhD in industrial engineering and management sciences from Northwestern University. His research interests lie in supply chain management, analytics and healthcare. Yao has published in leading operations research and management journals such as Operations Research, Manufacturing and Service Operations Management (M&SOM) and Production and Operations Management. Yao has consulted with many companies and government agencies, including General Motors, Estee Lauder, Verizon, MTA — NY Transit, Special Olympics, Johnson and Johnson, Fannie Mae, Defense Logistics Agency and US Navy, Korean Air-Cargo, Robert Wood Johnson hospitals and Water and Power Development Authority of Pakistan. Yao has launched a few popular courses on Coursera on supply chain analytics.
Citation
Iacocca, Kathleen, Ninh, Anh and Zhao, Yao (2025, February 26). Sourcing analytics: A playbook for global supplier exploration and selection. In the Journal of Supply Chain Management, Logistics and Procurement, Volume 7, Issue 3. https://doi.org/10.69554/NBSV6587.
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