Lunch Seminar in presence

Building BL26/B – Room 0.19 – ground floor
Department of Management, Economics and Industrial Engineering
Via R. Lambruschini,4/B

Srinivas Talluri
Michigan State University

Abstract:

In this paper we present a methodology, by utilizing a nonparametric multivariate cumulative sum control chart and data envelopment analysis in tandem, to evaluate and monitor distribution network performance by simultaneously considering multiple performance factors and their interrelationships. While these methods were previously applied individually, we demonstrate that their combined use can provide more powerful results in performance assessment, monitoring and improvement. Our approach contributes to the domain of supply chain analytics as it can provide new insights and understanding of business performance based on operations research and statistical methods to utilize real-time and past data. We demonstrate the application of our models on data gathered from The Dow Chemical Company, which is a multi-national vertically integrated chemical corporation.

Srinivas Talluri is the Hoagland-Metzler Endowed Professor and Professor of Operations and Supply Chain Management at Michigan State University.
His research interests are in the areas of supply risk, buyer-supplier relationships and supply contracts, sustainability in supply chains, technology management, and performance evaluation.
Sri’s methodological expertise lies in the areas of optimization methods (deterministic and stochastic models), game theory, empirical methods (statistical models), and data envelopment analysis. He has more than 100 journal publications in a variety of top-tier academic journals and has presented papers in various national and international conferences. Sri has over 12,000 citations of his work and an h-index of 52.
Dr. Talluri is one of the 116 fellows of DSI (Decision Sciences Institute) over the 50-year rich history of the organization. He has more than 20 years of teaching experience in the areas of supply chain management, operations management, operations research/management science, and statistics.   

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