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1.7 Outlook 23

Whereas BI tools and management approaches such as Six Sigma mainly aim
at improving operational performance, e.g., reducing flow time and defects, orga-
nizations are also putting more emphasis on corporate governance, risk, and com-
pliance. Major corporate and accounting scandals including those affecting Enron,
Tyco, Adelphia, Peregrine, and WorldCom have fueled interest in more rigorous
auditing practices. Legislation such as the Sarbanes-Oxley Act (SOX) of 2002 and
the Basel II Accord of 2004 was enacted in response to such scandals. The recent
financial crisis also underscores the importance of verifying that organizations op-
erate “within their boundaries”. Process mining techniques offer a means to more
rigorously check compliance and ascertain the validity and reliability of information
about an organization’s core processes.
The many acronyms in this section—BPM, BI, OLAP, BAM, CEP, CPM, CPI,
TQM, SOX, etc.—are just a subset of the jargon used by business consultants and
vendors. Additional terms like “(Business) Process Intelligence” are used as varia-
tions on the same theme. What can be distilled from the above is that there is a clear
trend towards actually using the data available in today’s systems. The data is used
to reason about the process and for decision making within the process. Moreover,
the acronyms express a clear desire to get more insight into the actual processes, to
improve them, and to make sure that they are compliant. Unfortunately, most con-
sultants and tool vendors are unable to provide the support needed and need hide
behind a “thick layer of buzzwords”. This book aims to provide a clear and refresh-
ing view on the matter. Using recent breakthroughs in process mining, we will show
that it is possible to simplify and unify the analysis of business processes based on
facts. Moreover, the techniques and insights presented are directly applicable and
are supported by process mining tools such as ProM (www.processmining.org).

1.7 Outlook

Process mining provides an important bridge between data mining and business pro-
cess modeling and analysis. Process mining research at TU/e (Eindhoven University
of Technology) started in 1999. At that time, there was little event data available
and the initial process mining techniques were extremely naïve and hence unus-
able. Over the last decade, event data has become readily available and process
mining techniques have matured. Moreover, process mining algorithms have been
implemented in various academic and commercial systems. Today, there is an active
group of researchers working on process mining and it has become one of the “hot
topics” in BPM research. Moreover, there is a huge interest from industry in process
mining. More and more software vendors started adding process mining function-
ality to their tools. Our open-source process mining tool ProM is widely used all
over the globe and provides an easy starting point for practitioners, students, and
academics. These developments are the main motivation for writing this book. Even
though there are many books on data mining, business unintelligence, process re-
engineering, and BPM, thus far, there was no book on process mining.