Empirical studies have shown that up to 54% of the analysed industrial process models has some kind of behavioural problems.
These incorrect models eventually bring to ambiguities and disalineament that can set in motion a vicious circle with adverse effect on all the subsequent activities.
Avoiding or detecting errors as early as possible are therefore prerequisites for any sound process modeling activity.

Mauro Gambini, Marcello La Rosa, Sara Migliorini, and Arthur H. M. Ter Hofstede. 2011. Automated error correction of business process models. In Proceedings of the 9th international conference on Business process management (BPM'11), Stefanie Rinderle-Ma, Farouk Toumani, and Karsten Wolf (Eds.). Springer-Verlag, Berlin, Heidelberg, 148-165.

 The amount of data collected and stored has grown exponentially in the last decade...

A complex task to deal with is finding the right level of granularity to guide you when modeling your business processes...

 The complexity of process models not only increases dramatically the opportunity  of errors, but also reduces the capability of analysing them ...