【Topic】Statistical Challenges in Workforce Management for Labor-Intensive

Service Systems

【Speaker】Professor Haipeng Shen

【Time】2008-10-31, 11:00am-12:00pm

【Venue】Room 453, Weilun Building, School of Economics and Management,

Tsinghua University

【Abstract】Service operations, such as Telephone Call Centers or Emergency Departments in hospitals, are traditionally analyzed as queueing systems using mathematical queueing models. Recently, statisticians started to supplement these mathematical models with theoretically-interesting and practically-relevant statistical analysis. This is enabled by the availability of transaction-level (or call-by-call) data bases, such as those housed at the Technion’s SEE laboratory. In this talk, I shall focus on call centers data. Operationally, the service process in such call centers can be decomposed into three fundamental components: arrivals, customer abandonment, and service durations. Each component has a different mathematical structure, which requires a different style of statistical analysis. I shall discuss several new methodologies that have been developed for the analysis of such call-by-call data. Empirical analysis of the data has validated in some cases, and refuted in others, the applicability of existing queueing models to call-center operations. This has stimulated the development of further models that capture previously unaccounted-for phenomena, such as arrival-rate uncertainty and server heterogeneity. I shall also present some ongoing research aiming at addressing such phenomena.

【About the speaker】Prof. Shen has a B.Sc. in Mathematics from Peking University, Beijing, China, in 1998. His Master and Ph.D. are in Statistics, under the supervision of Prof.Lawrence D. Brown, from the Department of Statistics, the Wharton School, University of Pennsylvania. After graduation in 2003, he became an assistant professor in the Department of Statistics and Operations Research, University of North Carolina at Chapel Hill (UNC-CH). He is interested in statistical methodological research in functional data analysis, lognormal inference and time series analysis, as well as interdisciplinary research in areas such as labor-intensive queueing service systems, wired/wireless network modelling, and fMRI medical imaging. His research has been supported by various grants from UNC-CH, the National Science Foundation of the United States and the Greek Government.