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13.2 Process Mining: TomTom for Business Processes? 331

13.2 Process Mining: TomTom for Business Processes?

After comparing geographic maps with business process maps, we now explore
the analogy between navigation systems and information systems. Section 9.1.3 al-
ready mentioned navigation activities in the context of the refined process mining
framework (cf. Fig. 9.1) By establishing a close connection between business pro-
cess maps and the actual behavior recorded in event logs, it is possible to realize
TomTom-like functionality. Analogous to TomTom’s navigation devices, process
mining tools can help end users (a) by navigating through processes, (b) by project-
ing dynamic information on process maps (e.g., showing “traffic jams” in business
processes), and (c) by providing predictions regarding running cases (e.g., estimat-
ing the “arrival time” of a case that is delayed) [94].

13.2.1 Projecting Dynamic Information on Business Process Maps

The navigation systems of TomTom can be equipped with so-called “LIVE ser-
vices” (cf. www.tomtom.com) showing traffic jams, mobile speed cameras, weather
conditions, etc. This information is projected onto the map using current data.
In Chap. 8, we showed that a tight coupling between an event log and a process
model can be used to extend process models with additional perspectives, e.g., high-
lighting bottlenecks, showing decision rules, and relating the process model to or-
ganizational entities. The same coupling can also be used to visualize “pre mortem”
event data. Information about the current state of running cases can be projected
onto the process model.
The idea is analogous to mashups using geo-tagging (e.g., Panoramio, Hous-
ingMaps, Funda, and Flickr). Many of these mashups use Google Maps. Consider,
for example, the map shown in Fig. 13.8. Prospective customers can visit the site of
Funda to look for a house that meets particular criteria. Information about houses
that are for sale are projected onto a map. Figure 13.8 shows the houses that are
for sale in Hapert. Figure 13.9 shows another example. Now the map shows traf-
fic jams. Both maps are dynamic, i.e., the information projected onto these maps
changes continuously.
Both historic and current event data can be used to “breathe life” into otherwise
static business process maps. Similar to the visualization of traffic jams in Fig. 13.9,
“traffic” in business processes can be visualized. Besides process maps, one can
also think of other maps to project information on. Consider, for example, the so-
cial networks shown in Figs. 8.6 and 8.7. Work items waiting to be handled can be
projected onto these models, e.g., cases that are waiting for a decision by a manager
are projected onto the manager role. Some work items also have a geographic com-
ponent, e.g., a field service engineer could be provided with a map like the one in
Fig. 13.8 showing the devices that need maintenance. It is also possible to project
work items onto maps with a temporal dimension (Gantt charts, agendas, etc.). For
instance, a surgeon could view scheduled operations in his agenda. Hence, a variety
of maps covering different perspectives can be used to visualize event related data.