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1.2 Limitations of Modeling 3

receipt of an e-ticket number by a traveler. The challenge is to exploit event data in
a meaningful way, for example, to provide insights, identify bottlenecks, anticipate
problems, record policy violations, recommend countermeasures, and streamline
processes. This is what process mining is all about!

1.2 Limitations of Modeling

Process mining, i.e., extracting valuable, process-related information from event
logs, complements existing approaches to Business Process Management (BPM).
BPM is the discipline that combines knowledge from information technology and
knowledge from management sciences and applies this to operational business pro-
cesses [93, 127]. It has received considerable attention in recent years due to its
potential for significantly increasing productivity and saving cost. BPM can be seen
as an extension of Workflow Management (WFM). WFM primarily focuses on the
automation of business processes [57, 61, 98], whereas BPM has a broader scope:
from process automation and process analysis to process management and the or-
ganization of work. On the one hand, BPM aims to improve operational business
processes, possibly without the use of new technologies. For example, by modeling
a business process and analyzing it using simulation, management may get ideas
on how to reduce costs while improving service levels. On the other hand, BPM
is often associated with software to manage, control, and support operational pro-
cesses. This was the initial focus of WFM. Traditional WFM technology aims at
the automation of business processes in a rather mechanistic manner without much
attention for human factors and management support.
Process-Aware Information Systems (PAISs) include the traditional WFM sys-
tems, but also include systems that provide more flexibility or support specific tasks
[37]. For example, larger ERP (Enterprise Resource Planning) systems (SAP, Ora-
cle), CRM (Customer Relationship Management) systems, rule-based systems, call
center software, high-end middleware (WebSphere), etc. can be seen as process-
aware, although they do not necessarily control processes through some generic
workflow engine. Instead, these systems have in common that there is an explicit
process notion and that the information system is aware of the processes it supports.
Also a database system or e-mail program may be used to execute steps in some
business process. However, such software tools are not “aware” of the processes
they are used in. Therefore, they are not actively involved in the management and
orchestration of the processes they are used for. Some authors use the term BPMS
(BPM system), or simply PMS (Process Management System), to refer systems that
are “aware” of the processes they support. We use the term PAIS to stress that the
scope is much broader than conventional workflow technology.
BPM and PAIS have in common that they heavily rely on process models.
A plethora of notations exists to model operational business processes (e.g., Petri
nets, BPMN, UML, and EPCs), some of which will be discussed in the next chapter.
These notations have in common that processes are described in terms of activities