Business Process Analytics

Dit vak wordt in het Engels aangeboden. Omschrijvingen kunnen daardoor mogelijk alleen in het Engels worden weergegeven.

Doel vak

After taking this course, the student will:

- be aware of the current possibilities to support BPM with information
- understand and be able to employ process mining techniques for the
purpose of process discovery, compliance checking, and improvement.
- know key technologies for analyzing large process model repositories.
- know and be able to employ basic as well as advanced NLP techniques
for the purpose of process analysis.
- know and be able to use process model simulation for testing and
improving process design.

Inhoud vak

There is a steadily increasing interest of organizations to use Business
Process Management (BPM) for documenting and improving their operations.
However, the associated manual effort for thoroughly eliciting,
documenting, and updating process knowledge in the form of process
models is often considerable.

Within this course, we put an emphasis on the technological and
analytical perspective and discuss how they can support organizations in
effectively and efficiently implementing BPM. In fact, techniques from
the fields of information retrieval, data mining as well as simulation
provide valuable foundations to reduce to the manual effort in the
context of BPM. Hence, we introduce and discuss four different
technological angles and demonstrate how each of these angles can
strengthen the different phases of the BPM life cycle. In particular, we
address the following technological areas:

1. Process Mining: The technology of process mining builds on the
analysis of event logs that were generated by information or workflow
systems. We discuss how process mining techniques can be used for
process discovery, compliance checking, and improvement and elaborate on
basic as well as advanced process mining algorithms. In addition, we
introduce current process mining tools for the application of process
mining in practice.

2. Process Model Collections: Many large organizations maintain process
model repositories with several hundred process models. Hence, manual
analysis efforts are time-consuming and cumbersome. Recognizing this, we
introduce key concepts to automatically analyze process model
collections. Among others, we discuss techniques for process model
comparison, process model search, and behavioral analysis of process

3. Natural Language Analysis: The automated analysis of natural
language, which is referred to as Natural Language Processing (NLP), has
been applied in many contexts. As an example, consider Apple’s Siri or
Google’s S Voice, which are capable of interpreting human speech. In
fact, also organizations and their business processes may considerably
benefit from natural language processing techniques. Hence, we introduce
the key NLP techniques that are relevant in the context of BPM. Among
others, we discuss techniques for process model content analysis,
process model quality insurance, and identification of improvement
potential in process models.

4. Simulation: The simulation of business processes is a tool that is
used to predict performance and to understand the impact of change. It,
for instance, allows organizations to test processes before they are
actually technically implemented in a system. Due to its usefulness for
organizations, we introduce the technological foundations for process
simulation and give an overview of process simulation tools.

The various lectures and instructions will be devoted to these
technological areas.


There will be lectures as well as work instructions.


The grading for students who follow this course in the scheduled period
will be based on two grades:

1. The first grade is based on a number of home assignments. The goal of
the assignments is to evaluate whether the students can successfully
apply the content from the lecture. Among others, the students will be
asked to mine a business process model from a given event log and to
automatically infer relevant information using natural language
processing tools from a given text.

2. The second grade is gained by participating in the regular exam
during the exam week. The exam is a closed book exam, which consists of
theoretical questions and small assignments. Selected chapters from the
books "Fundamentals of Business Process Management", "Process Mining",
and "Speech and Language Processing" will be the basis for this exam.

The overall result for this exam is the rounded, weighted average of the
first grade (50%) and the second grade (50%) provided that both grades
(unrounded) at least amount to a 5.00. If either of the grades is lower
than a 5.00, the overall grade for this course is determined by the
rounded, lowest grade of the two.

For all students who fail the course in the scheduled period or decide
to follow the course outside this period, the course is graded solely by
the grade for the re-exam. This is a full exam similar to the original
exam and the assignments. The re-exam is a closed book exam, too.


1. Fundamentals of Business Process Management. Dumas, M., La Rosa, M.,
Mendling, J., Reijers, H.A. Springer, 2013. ISBN: 978-3-642-33142-8
(Print) 978-3-642-33143-5 (Online).

2. Process Mining. Discovery, Conformance and Enhancement of Business
Processes. van der Aalst, Wil. Springer, 2011. ISBN: 978-3642193446.

3. Speech and Language Processing, Jurafsky, Dan, Martin, James H.
Pearson International Edition, 2008. ISBN: 978-0135041963.


This is an interdisciplinary course. Any student who is interested in
learning how technology can be used to improve business processes in
practice is invited to join this course.

Aanbevolen voorkennis

Students will, among others, benefit from the knowledge they acquired in
the courses Information Management and Business Process Management.
Motivated students, however, will be able to master the course without
prior knowledge from these courses.

Algemene informatie

Vakcode X_400650
Studiepunten 6 EC
Periode P4
Vakniveau 400
Onderwijstaal Engels
Faculteit Faculteit der Bètawetenschappen
Vakcoördinator dr. H. Leopold MSc
Examinator dr. H. Leopold MSc

Praktische informatie

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