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1.6 Trends 21

1.6 Trends

In this book, we position process mining as a powerful tool within a broader Busi-
ness Process Management (BPM) context. As indicated before, the goal of BPM
is to improve operational business processes by combining knowledge from infor-
mation technology and knowledge from management sciences. It can also be posi-
tioned under the umbrella of Business Intelligence (BI). There is no clear definition
for BI. On the one hand, it is a very broad term that includes anything that aims
at providing actionable information that can be used to support decision making.
On the other hand, vendors and consultants tend to conveniently skew the definition
towards a particular tool or methodology. Clearly, process mining can be seen as a
new collection of BI techniques. However, it is important to note that most BI tools
are not really “intelligent” and do not provide any process mining capabilities. The
focus is on querying and reporting combined with simple visualization techniques
showing dashboards and scorecards. Some systems provide data mining capabili-
ties or support Online Analytical Processing (OLAP). OLAP tools are used to view
multidimensional data from different angles. On the one hand, it is possible to ag-
gregate and consolidate data to create high-level reports. On the other hand, OLAP
tools can drill down into the data to find detailed information. Typical data mining
capabilities provided by more advanced tools are: clustering (discovering entities
that are somewhat “similar”), classification (discovering rules that can be used to
predict a particular property of an entity), regression (constructing a function that
models the data with the least error), and association rule learning (searching for
relationships between properties). Chapter 3 introduces these techniques and relates
them to process mining.
Under the BI umbrella many fancy terms have been introduced to refer to rather
simple reporting and dashboard tools. Business Activity Monitoring (BAM) refers
to the real-time monitoring of business processes. BAM is often related to Com-
plex Event Processing (CEP). CEP aims to react immediately if the stream of events
shows a particular pattern, e.g., generate an alert when a combination of events
occurs. Corporate Performance Management (CPM) is another buzzword for mea-
suring the performance of a process or organization. Typically, CPM focuses on
financial aspects. Recently, more and more software vendors started to use the term
“analytics” to refer to advanced BI capabilities. Visual analytics focuses on the anal-
ysis of large amounts of data while exploiting the remarkable capabilities of humans
to visually identify patterns and trends. Predictive analytics uses historic data to
make forecasts. Clearly, process mining also aims at providing advanced analytics
and some process mining techniques also heavily rely on advanced visualization and
human interpretation. Moreover, as will be demonstrated in Chap. 9, process mining
is not restricted to analyzing historic data and also includes operational support, i.e.,
providing predictions and recommendations in an online setting.
Also related are management approaches such as Continuous Process Improve-
ment (CPI), Total Quality Management (TQM), and Six Sigma. These approaches
have in common that processes are “put under a microscope” to see whether further
improvements are possible. Clearly, process mining can help to analyze deviations
and inefficiencies.