The increasing importance of corporate governance, risk, compliance management, and legislation (such as the Sarbanes-Oxley Act and the Basel II Accord) highlight the practical relevance of conformance checking. Process mining can help auditors check whether processes execute within certain boundaries set by managers, governments, and other stakeholders. 3 Violations discovered through process mining might indicate fraud, malpractice, risks, or inefficiency; for example, in the municipality for which the WOZ appeal process was analyzed, ProM revealed misconfigu-rations of its eiStream workflow-man-agement system. Municipal employees frequently bypassed the system because system administrators could manually change the status of cases (such as to skip activities or roll back the process). 7

Show variability. Handmade process models tend to provide an idealized view of the business process being modeled. However, such “PowerPoint reality” often has little in common with real processes, which have much more variability. To improve conformance and performance, process analysts should not naively abstract away this variability.

Process mining often involves spaghetti-like models; the one in Figure 6 was discovered based on an event log containing 24,331 events referring to 376 different activities describing the diagnosis and treatment of 627 gynecological oncology patients in the AMC Hospital in Amsterdam. The spaghetti-like structures are not caused by the discovery algorithm but by the variability of the process.

Although stakeholders should see reality in all its detail (see Figure 6), spaghetti-like models can be simplified. As with electronic maps, it is possible to seamlessly zoom in and out. 1 Zooming out, insignificant things are either left out or dynamically clustered into aggregate shapes, in the same way streets and suburbs amalgamate into cities in Google Maps. The significance level of an activity or connection may be based on frequency, costs, or time.

Improve reliability. Process min-
ing can also help improve the reli-
ability of systems and processes; for
example, since 2007, we have used
process mining to analyze the event
logs of X-ray machines from Phil-
ips Healthcare1 that record massive
amounts of events describing actual
use. Regulations in different coun-
tries require proof systems were test-
ed under realistic circumstances; for
this reason, process discovery was
used to construct realistic test pro-
files. Philips Healthcare also used
process mining for fault diagnosis to
identify potential failures within its
X-ray systems. By learning from ear-
lier system failure, fault diagnosis
was able to find the root cause for new
emergent problems. For example,
we used ProM to analyze the circum-
stances under which particular com-
ponents are replaced, resulting in a
set of “signatures,” or historical fault
patterns; when a malfunctioning X-
ray machine exhibits a particular sig-
nature behavior, the service engineer
knows what component to replace.

Conclusion

Process-mining techniques enable
organizations to X-ray their busi-
ness processes, diagnose problems,
and identify promising solutions for
treatment. Process discovery often
provides surprising insight that can
be used to redesign processes or im-
prove management, and conformance
checking can be used to identify
where processes deviate. This is rele-
vant where organizations are required
to emphasize corporate governance,
risk, and compliance. Process-mining
techniques are a means to more rigor-
ously check compliance while improv-
ing performance.

Acknowledgments

I thank the members of the IEEE Task Force on Process Mining and all who contributed to the Process Mining Manifesto9 and the ProM framework.

 

References

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Wil van der Aalst (w.m.p. [e-mail]) is a professor in the Department of mathematics & Computer science of the technische universiteit eindhoven, the netherlands, where he is chair of the architecture of Information systems group.