Service Engineering, #096324
Spring Semester, 2016
Service systems such as healthcare (hospitals), financial services (banks) and telephone and internet service systems currently make up 60-80% of Western economies. The course will emphasize telephone-based services, commonly experienced via customer contact centers. In many respects, service systems are similar to manufacturing systems, communication systems, and transportation systems, but there are important differences, largely due to the significant role played by humans in providing the service. There are significant challenges in providing services effectively. Fortunately, there is a growing service science that provides skills and tools to manage service systems. Since many engineers actually work in service systems, it is important to offer a course that introduces students to the state-of-the-art methods and tools in the field.
In this course, a service system will be viewed as a stochastic network. Thus, the main theoretical framework is queueing theory, which primarily involves a large class of stochastic models. However, the subject matter is highly multi-disciplinary; hence alternative frameworks will be useful as well, including ones from statistics, psychology, and marketing.
The course will provide a framework for modeling service systems and techniques that are useful to design, analyze, and operate service systems. Service systems are becoming more and more automated, which makes data available for design and automatic control of such systems. We will use real service system data from banks, hospitals, and call centers to demonstrate the use of the decision support tools.
Home assignments will be theoretical, empirical and practical. Students will implement the methods learned in their homework assignments. Empirical analysis will involve real data provided from the SEE Center (SEE = Service Enterprise Engineering) of the Technion – Israel Institute of Technology.
Practical analysis will be based on standard tools such as MS Excel, and the following service engineering tools: SEEStat (student version) and 4CallCenters. The former is a tool developed at the SEE Center and provides an online graphic-based interface for transactional data (e.g., from call centers and hospitals); the latter tool supports workforce management (staffing).
This course is suitable to students from a variety of backgrounds such as industrial engineering (including operations research, statistics, and information systems), electrical engineering, computer science, and mathematics.
Students should have completed an introductory course or courses in probability, statistics, or other, as well as an introduction to stochastic processes, such as course #094314 which teaches ‘Poisson Processes’ and/or ‘Markov Jump Processes.’
Dr. Galit Yom-Tov
Office: Blumfield Building, Rm. 519
Tel: (04) 829 4510; firstname.lastname@example.org
Teaching Assistant (TA):
To Be Determined
There will be three 50-minute lecture classes per week and one 50-minute recitation per week, led by a teaching assistant (TA). In the recitations, the TA will be teaching students how to use the tools needed to perform the assignments. Both the instructor and teaching assistants will hold office hours.
- Hall, R.W., “Queueing Methods for Services and Manufacturing”, Prentice-Hall, 1991.
- Fitzsimmons, J.A. and M.J., “Service Management: Operations, Strategy, and Information Technology”, McGraw Hill, 4th Edition, 2004 (or previous editions, which are also OK).
- Optional recommended: Lovelock. C.G., “Managing Services: Marketing, Operations and Human Resources”, Prentice-Hall, 1992.)
- Course website
- To introduce engineering students to the growing field of “service science.”
- To provide students with the necessary skill sets and tools to manage service systems.
- Introduction to service systems and queues (people, telephone calls, forms, projects, etc.).
- Analytical models, simulation, approximations (fluid and diffusion): How to use them as tools to support strategic, tactical and operational decisions.
- Measuring methods in face-to-face and computerized systems.
- Phenomena: Economies-of-scale, PASTA, Biased-sampling, expertise vs. cross-training, etc.
- Forecasting methods and demand management in service systems. For example: forecasting of number of calls to a call center.
- Stability of service systems.
- Operational quality of service. Planning of service systems. For example: staffing of call centers.
- Multi-disciplinary aspects: Operations research, Industrial Engineering, Statistics, Psychology, Marketing. For example: Analysis of customer patience during waiting for service
- Design and control of queueing systems.
- Implementation in various systems: emphasis on the interface of the customers to the system in face-to-face services and call centers.
Lectures will be presented using pdf files. The lecture files will be posted on the course website at least 24 hours before the lecture.
The TA will lead the recitation section, and this time will be used to go over additional problems that are similar to the homework assignments and to describe service system databases and programs used in those assignments. The TA will hold office hours to go over specific homework questions as well as questions about homework grading.
Course Expectations & Grading:
There will be 11 assignments during the semester. These homework assignments are to be performed in groups of up to 2 students (no more). Students are encouraged to divide the assignment between the group members, but everyone should understand all parts of the assignment. We take academic honesty extremely seriously, and expect the same of you. Copying of homework assignments will not be tolerated. The final assignment due date will be one week after the exam period.
In addition, there will be reading assignments for some of the classes.
Homework (mandatory): 30% (weight of each assignment may vary)
Mid-term exam (not mandatory): 20% (This exam will be based on homework assignment submitted till the exam date, and on the reading assignment.)
Final exam: 50% (need to get at least 55 in final exam to pass the course)
Approximate Weekly Schedule:
|1||Introduction to Service Engineering|
|2||Flow Models of Service Networks; Little’s Law|
|3||Measurements – The First Prerequisite; Working with Call Center Data|
|4||Models – The Second Prerequisite; Processing Networks; DS PERT/CPM|
|5||Fluid Models of Service Stations and Service Networks|
|6||Arrival Processes; Predictable and Unpredictable Variability|
|9||Markov Chain Models – Part I ; 4CallCenters Software Tool|
|10||Markov Chain Models – Part II; the Palm/Erlang-A Model|
|11||Economies of Scale; Approximations for Large-Scale Stochastic Systems|
|12||Quality-and-Efficiency Driven (QED) Queues Part I; Performance Approximations|
|13||QED Queues Part II; Staffing; Complex Service Networks;|
The strength of the university depends on academic and personal integrity. In this course, you must be honest and truthful. Ethical violations include cheating on exams, plagiarism, reuse of assignments, improper use of the Internet and electronic devices, unauthorized collaboration, alteration of graded assignments, forgery and falsification, lying, facilitating academic dishonesty, and unfair competition.