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322 13 Cartography and Navigation

As indicated in Sect. 9.1.1, we suggest adopting ideas from cartography.Inthe
remainder of this section, we discuss ways of improving process models inspired
by cartographic techniques. Some of these ideas are already supported by existing
process mining techniques, others point to further innovations.

13.1.1 Map Quality

Geographical maps are typically of high quality compared to business process maps.
For example, the maps used by navigation systems are very accurate, e.g., when
driving from Amsterdam to Rome relatively few discrepancies between reality and
the map will be encountered.
Process models tend to provide an idealized view on the business process that
is modeled. Imagine that road maps would view the real highway system through
similar rose-tinted glasses, e.g., showing a road that is not there but that should have
been there. This would be unacceptable. However, these are the kind of business
process maps used in many organizations. Such a “PowerPoint reality” limits the
use and trustworthiness of process models.
In Chap. 7, we showed various conformance checking techniques that can be
used as a “reality check” for business process maps. For instance, using replay the
fitness of a process model and an event log can be determined. We encountered many
real-life processes in which the fitness of the model and the log is less than 0.4. This
implies that less than 40% of the behavior seen in reality fits into the model.
Some will argue that road maps are easier to maintain than process models, be-
cause a road system evolves at a much slower pace than a typical business process.
This is indeed the case. However, this makes it even more important to have accurate
up-to-date business process maps!
Besides differences in quality, there are also huge differences in understandabil-
ity. Most people will intuitively understand geographical maps while having prob-
lems understanding process models. The dynamic nature of processes makes things
more complicated (cf. workflow patterns [101, 130]). Therefore, the perceived com-
plexity is partly unavoidable. Nevertheless, ideas from cartography can help to im-
prove the understandability of process models.

13.1.2 Aggregation and Abstraction

Figure 13.1 shows a map. The map abstracts from less significant roads and cities.
Roads that are less important are not shown. A cut-off criterion could be based
on the average number of cars using the road per day. Similarly, the number of
citizens could be used as a cut-off criterion for cities. For example, in Fig. 13.1
cities of less than 50,000 inhabitants are abstracted from. Maps also aggregate local
roads and local districts (neighborhoods, suburbs, centers, etc.) into bigger entities.