  Digital transformation forces companies to rethink their processes to meet
current customer needs. Business Process Management (BPM) can provide the means
to structure and tackle this change. However, most approaches to BPM face
restrictions on the number of processes they can optimize at a time due to
complexity and resource restrictions. Investigating this shortcoming, the
concept of the long tail of business processes suggests a hybrid approach that
entails managing important processes centrally, while incrementally improving
the majority of processes at their place of execution. This study scrutinizes
this observation as well as corresponding implications. First, we define a
system of indicators to automatically prioritize processes based on execution
data. Second, we use process mining to analyze processes from multiple
companies to investigate the distribution of process value in terms of their
process variants. Third, we examine the characteristics of the process variants
contained in the short head and the long tail to derive and justify
recommendations for their management. Our results suggest that the assumption
of a long-tailed distribution holds across companies and indicators and also
applies to the overall improvement potential of processes and their variants.
Across all cases, process variants in the long tail were characterized by fewer
customer contacts, lower execution frequencies, and a larger number of involved
stakeholders, making them suitable candidates for distributed improvement.
