Service Enterprise Engineering (SEE) Lab

SEEStat Online

see minilogo (1)

The SEE Center was established in 2007, within the Technion Faculty of Industrial Engineering and Management (IE&M), through the generous support of 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.

SEE Data Resources: There are over 10 SEE data-bases, all of which cover operational log-files. The latter constitute histories of customers and servers, at the resolution of the individual transaction; in other words, records of all operational events at second-by-second resolutions. In particular, three SEE data-bases are internet-accessible for free use. These data originate in a small Israeli call center with 15 agents or so (Bank Anonymous, which was SEE’s first data base); in a large U.S. call center (USBank) with about 1000 agents; and a large Israeli hospital (HomeHospital) with about 1000 beds. An example of an active data-base is that of a large ambulatory hospital, with a medical staff of 300-400 physicians, nurses and administrators, who cater to about 1000 patients per day. The data-base covers the exact hospital location of each of these patients and staff, every 3 seconds since October 2013; as well as the full appointment book of the hospital, which specifies at second-resolution where each of these patients and staff should have been. This unique location data has been recorded via an RTLS (Real-Time-Location-System) that consists of 900 sensors, scattered over the ceilings of 8 clinical floors of the hospital. Additional data-bases in the making an planning include a comprehensive data-repository from a large bank (with millions of subscribers) and from a smart-city (physical) simulator. 

The SEELab is mourning the passing of our dear longtime friend and colleague Dr. Valey Trofimov. Being its chief data-scientist, Valery has actually been the "brain" of the SEElab since its inception (in 2007). Valery passed away on May 2018, and his many friends and research partners, world-wide, will greatly miss him. 

We invite you to learn further about Valery and share a memory in his memorial site