Business Process Management and Mining

Business Process Management and Mining

Spring Semester, 2016

(2.5 credits)



Business processes are pervasive and involved in virtually all aspects of our daily lives: in banks, telecommunication centers, web-services, and even in healthcare. Processes in organizations are there to ensure that business goals are achieved in the most efficient manner and that products and/or services are rendered with the highest level of quality. Business Process Management (BPM) is a research field that focuses on improving corporate performance by managing and optimizing a company’s processes. The BPM lifecycle includes (re)design, modeling, executing, monitoring and optimizing business processes. This course will cover the components of the lifecycle with emphasis on modeling, analysis and optimization of business processes.

The first part of the course will introduce basic BPM concepts such as modeling languages, qualitative and quantitative analysis of processes, and model elicitation techniques. In the second part of the course, the focus shifts to a data-driven methodology for BPM, namely process mining. The students will learn the three basic steps of process mining: discovery of models from data, alignment of the resulting models with data, and data-based performance analytics. The emphasis on process mining will be on performance analytics. The course materials will cover current literature on the subject. As part of the final grade, students will be required to present seminars on selected topics.





Arik Senderovich,

Office: Cooper Building, 413, Faculty of Industrial Engineering and Management.

Office hours: TBD.

Teaching Assistant







  • Mathias Weske, “Business Process Management: Concepts, Languages, Architectures,” Springer Berlin Heidelberg, 2nd ed., 2012
  • Wil van der Aalst, “Process Mining: Discovery, Conformance and Enhancement of Business,” Springer Berlin Heidelberg, 2011

Online Resources

Technion Moodle site.


Course Objectives

  • Students will learn the Business Process Management paradigm.
  • Students will learn to elicit, construct and discover process models.
  • Students will learn theoretical and data-based analysis of processes.

Course Topics

  • Introduction to Business Process Management (BPM)
  • Process modeling: languages, translation, and elicitation
  • Process mining: discovery, conformance, and analytics
  • Advanced topics: queue mining, , and process matching


Course Expectations & Grading


Key Dates


Assignments & Readings




 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.

ABET Outcomes

  • Ability to apply mathematics, science and engineering principles (a).
  • Ability to design and conduct experiments, analyze and interpret data (b).
  • Ability to design a system, component, or process to meet desired needs (c).
  • Ability to identify, formulate and solve engineering problems (e).
  • Knowledge of contemporary issues (j).
  • Ability to use the techniques, skills and modern engineering tools necessary for engineering practice (k).