The Harold and Inge Marcus Center for Service Enterprise Engineering (SEE)
Data-Based Science & Teaching
The SEE Center was established in 2007, within the Technion Faculty of Data and Decision Sciences, through the generous support of Harold (Hal) and Inge Marcus.
The goal of SEE is to serve as a worldwide hub for research and teaching in Service Engineering. This is achieved by developing engineering and scientific principles, which then support modelling, design and management of Service Enterprises, for example financial services (banking, insurance), health services (hospitals, clinics), government and tele-services (telephone, internet). Presently, SEE’s main activity is designing, maintaining and analyzing a repository of resources and data from telephone call-centers and hospitals, which is universally accessible to the extent possible. This is all preformed at the Technion IE&M SEE Lab.
Being more specific, the ultimate goal of Service Engineering, as we perceive it at SEE, is to develop principles and tools that are data- and science-based (often culminating in software), which support and balance service quality, efficiency and profitability, from the likely conflicting perspectives of customers, servers, managers, and society. Successful design, analysis and management of services must often be multi-disciplinary, fusing ingredients from Operations Research, Statistics, Industrial Engineering; Game Theory, Economics; Sociology, Psychology; Management Information Systems, Computer Science, Machine Learning and even more. (As frequent users of services, the relevance of these disciplines should be intuitively clear to most readers. Significantly, all are taught under the single roof of IE&M at Technion.)
Our background and interests render our research, and hence also our teaching, biased towards Service Operations and their Statistical Inference, viewing these through the mathematical lenses of Queueing Theory. But the latter must be scientifically-blended with alternative “views”, notably those of Marketing, Human Resources and Information Systems. The enabler of this multi-disciplinary view is data, which we are “collecting” at the SEE lab for the benefits of science, engineering and management.
On the map: Academic location of our colleagues, co-authors, students and guests who use the lab data. An academic location can be current or historical (displayed on the map as a separate layer). Historical: because the activity of the laboratory lasts 15 years, and the location can change over many years (excellent students grow up in his alma mater, and sometimes become professors in others …).