Process mining is a technology from the field of business process management, it creates and analyzes business processes on the basis of digital traces in IT systems. Unlike conventional business process analysis, process mining uses event logs to automatically generate a process model. That gives a detailed overview about all the process instances. Potential bottlenecks during the process flow can be detected in the analysis. In the project described, a change management process in co-operation with the MLP Finanzdienst-leistungen AG has been analyzed. The most common tools were used and further-more compared in detail. This document has 2 pages, very similar but adapted for both teams who worked independently.

1. Process Analysis with Process Mining
Gröschel, Stand: 09.07.2016
MLP Finanzdienstleistungen AG
Oliver Wildenstein
Expert IT-Governance, -Compliance
and Process Management
Alte Heerstraße 40
D-69168 Wiesloch
Phone: +49 (0)6222 308 2971
E-Mail: oliver.wildenstein@mlp.de
www.mlp.de
Mannheim University of
Applied Sciences
Prof. Thomas Smits
Prof. Dr. Michael Gröschel
Department of Computer Science
Paul-Wittsack-Straße 10
D-68163 Mannheim
Phone: +49 (0)621 292 6764
E-Mail:
t.smits@hs-mannheim.de
m.groeschel@hs-mannheim.de
www.informatik.hs-mannheim.de
Analysis Dashboard (tool: Celonis)
The project has been implemented by Marcel
Eberling, Matthias König, Giang Pham, Daniel
Schneider and Maximilian Zittel, students of the BSc
course enterprise computing (in winter semester
2015/16).
Process mining is a technology from the
field of business process management, it
creates and analyzes business processes
on the basis of digital traces in IT systems.
Unlike conventional business process
analysis, process mining uses event logs to
automatically generate a process model.
That gives a detailed overview about all the
process instances. Potential bottlenecks
during the process flow can be detected in
the analysis. In the project described, a
change management process in co-
operation with the MLP Finanzdienst-
leistungen AG has been analyzed. The
most common tools were used and further-
more compared in detail.
Initial Situation
Many companies have established business
processes that do not correspond with the desired
target processes. Therefore, analyses aim to detect
weak spots in such processes. Long waiting and
pass-through times or the repetition of activities can
interfere with the process flow and reduce the
associated customer satisfaction. Also problematic
are deviations caused by compliance aspects in
predetermined procedures. In total, the change
management process for the adaption of IT systems
from MLP was satisfying but the process owner
wanted to objectify and complete his impression by
using analytical results.
Possible Solution “Process Mining”
The process workflows are usually logged within IT
systems. Traces left behind can be found in the event
logs. Process mining tools analyze these protocols,
visualize the actual procedures (actual processes),
and allow various different analyses and evaluations
of anomalies, pass-through times, variations and
others. A conformance check compares the target
process with the actual procedures. As a result, the
conformity gives a degree of consistency between
the desired processes and the actual implemented
activities. All members of the project team
participated in an online course offered by coursera
(MOOC) as an initial training on the topic.
Objectives
The project scope contained the following essential
points:
 Preparation and optimization of the event logs
provided by MLP.
 Performing analysis in annual comparison in
terms of anomalies and conformity with standards
such as ITIL and COBIT.
 Working with process mining tools and
comparison of different tools.
 Creating templates for the tools to repeat similar
analyses.
Project Management
With changing requirements, for example the design
of reports, which evolved during the project and also
the new topic of process mining, the project team
decided to use Scrum as an iterative method. As a
first step, different team rules have been defined as
well as ways of communication within the project
team. Then this was documented in the project
manual. Furthermore it was important to keep contact
to MLP to constantly adapt and prioritize the
requirements. At the same time the project members
participated at workshops for team building.
Process Mining Tools
The analysis was done with different common
process mining tools. The tools Celonis, Disco and
ProM were evaluated and compared in terms of
features and functions, usability, and integration
options. The tools can use event logs to create an
actual model as a so-called fuzzy model. This
provides a descriptive visualization of the process
and serves as a foundation for the evaluation and
analysis.
 ProM has an academic focus and offers various
possibilities for the process analysis. Such as the
offer and parameterization of different mining
methods, the conversion between models (Petri
nets and BPMN), and the visualization of analysis
results. By using plug-ins, this can be extended as
desired.
 Disco is easy to operate and offers various
possibilities for filtering data. Dashboards allow
you to identify important ratios and display them
constantly.
 Celonis has its focus on creating dashboards with
different complexities, using a wide range of
adaptabilities and filter options. The tool offers a
linking to productive systems with a real-time
analysis.
Results
In addition to the project manual and the
specifications document, a document with the results
about process mining has been acquired. The
created templates in the form of filter-recipes,
dashboards, automated process model generation
and their related manuals aid the customer to use
process mining for future process analysis. The
results of the analyses can furthermore be used as a
foundation for the customers’ process optimization.
The comparison of the tools offers MLP a base for the
selection of the proper tool for a widespread and long-
term usage.
Further information
 IEEE CIS Task Force on Process Mining (Hrsg.):
Process Mining Manifesto, http://www.win.tue.nl/
ieeetfpm/doku.php?id=shared:process_mining_
manifesto
 Coursera-MOOC on Process Mining:
https://www.coursera.org/course/procmin
 Tool ProM: http://www.promtools.org/
 Tool Disco: https://fluxicon.com/disco/
 Tool Celonis: http://www.celonis.de/

2. Process Analysis with Process Mining
Gröschel, Stand: 09.07.2016
MLP Finanzdienstleistungen AG
Oliver Wildenstein
Expert IT-Governance, -Compliance
and Process Management
Alte Heerstraße 40
D-69168 Wiesloch
Phone: +49 (0)6222 308 2971
E-Mail: oliver.wildenstein@mlp.de
www.mlp.de
Mannheim University of
Applied Sciences
Prof. Thomas Smits
Prof. Dr. Michael Gröschel
Department of Computer Science
Paul-Wittsack-Straße 10
D-68163 Mannheim
Phone: +49 (0)621 292 6764
E-Mail:
t.smits@hs-mannheim.de
m.groeschel@hs-mannheim.de
www.informatik.hs-mannheim.de
Analysis Dashboard (tool: Celonis)
The project has been implemented by Leontina
Baitinger, Timo Höfler, Hunar Mawlod, Timo Neu-
mann and Nils Viertler, students of the BSc course
enterprise computing (in winter semester 2015/16).
Process mining is a technology from the
field of business process management, it
creates and analyzes business processes
on the basis of digital traces in IT systems.
Unlike conventional business process
analysis, process mining uses event logs to
automatically generate a process model.
That gives a detailed overview about all the
process instances. Potential bottlenecks
during the process flow can be detected in
the analysis. In the project described, a
change management process in co-
operation with the MLP Finanzdienst-
leistungen AG has been analyzed. The
most common tools were used and further-
more compared in detail.
Initial Situation
Many companies have established business
processes that do not correspond with the desired
target processes. Therefore, analyses aim to detect
weak spots in such processes. Long waiting and
pass-through times or the repetition of activities can
interfere with the process flow and reduce the
associated customer satisfaction. Also problematic
are deviations caused by compliance aspects in
predetermined procedures. In total, the change
management process for the adaption of IT systems
from MLP was satisfying but the process owner
wanted to objectify and complete his impression by
using analytical results.
Possible Solution “Process Mining”
The process workflows are usually logged within IT
systems. Traces left behind can be found in the event
logs. Process mining tools analyze these protocols,
visualize the actual procedures (actual processes),
and allow various different analyses and evaluations
of anomalies, pass-through times, variations and
others. A conformance check compares the target
process with the actual procedures. As a result, the
conformity gives a degree of consistency between
the desired processes and the actual implemented
activities. All members of the project team
participated in an online course offered by coursera
(MOOC) as an initial training on the topic.
Objectives
The project scope contained the following essential
points:
 Preparation and optimization of the event logs
provided by MLP.
 Performing analysis in annual comparison in
terms of anomalies and conformity with standards
such as ITIL and COBIT.
 Working with process mining tools and
comparison of different tools.
 Creating templates for the tools to repeat similar
analyses.
Project Management
With changing requirements, for example the design
of reports, which evolved during the project and also
the new topic of process mining, the project team
decided to use Scrum as an iterative method. As a
first step, different team rules have been defined as
well as ways of communication within the project
team. Then this was documented in the project
manual. Furthermore it was important to keep contact
to MLP to constantly adapt and prioritize the
requirements. At the same time the project members
participated at workshops for team building.
Process Mining Tools
The analysis was done with different common
process mining tools. The tools Celonis, Disco and
ProM were evaluated and compared in terms of
features and functions, usability, and integration
options. The tools can use event logs to create an
actual model as a so-called fuzzy model. This
provides a descriptive visualization of the process
and serves as a foundation for the evaluation and
analysis.
 ProM has an academic focus and offers various
possibilities for the process analysis. Such as the
offer and parameterization of different mining
methods, the conversion between models (Petri
nets and BPMN), and the visualization of analysis
results. By using plug-ins, this can be extended as
desired.
 Disco is easy to operate and offers various
possibilities for filtering data. Dashboards allow
you to identify important ratios and display them
constantly.
 Celonis has its focus on creating dashboards with
different complexities, using a wide range of
adaptabilities and filter options. The tool offers a
linking to productive systems with a real-time
analysis.
Results
In addition to the project manual and the
specifications document, a document with the results
about process mining has been acquired. The
created templates in the form of filter-recipes,
dashboards, automated process model generation
and their related manuals aid the customer to use
process mining for future process analysis. The
results of the analyses can furthermore be used as a
foundation for the customers’ process optimization.
The comparison of the tools offers MLP a base for the
selection of the proper tool for a widespread and long-
term usage.
Further information
 IEEE CIS Task Force on Process Mining (Hrsg.):
Process Mining Manifesto, http://www.win.tue.nl/
ieeetfpm/doku.php?id=shared:process_mining_
manifesto
 Coursera-MOOC on Process Mining:
https://www.coursera.org/course/procmin
 Tool ProM: http://www.promtools.org/
 Tool Disco: https://fluxicon.com/disco/
 Tool Celonis: http://www.celonis.de/