Published November 24, 2020 | Version 1
Dataset Open

Research Data for "On the Composition of the Long Tail of Business Processes: Implications from a Process Mining Study"

Description

Fischer, Marcus; Hofmann, Adrian; Imgrund, Florian; Janiesch, Christian; Winkelmann, Axel: On the Composition of the Long Tail of Business Processes: Implications from a Process Mining Study. Information Systems. 2020. https://doi.org/10.1016/j.is.2020.101689 Abstract: "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. How-ever, 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." *** Using this data for academic publications is granted explicitly. *** The dataset was created by researchers working at the University of Würzburg.

Files

On the Composition of the Long Tail of Business Processes.ipynb

Files (46.3 kB)

Name Size Download all
Checksum: md5:c1a8912296ccec5da0064128f1c36426

PID: http://hdl.handle.net/11304/ff56cc47-7cdd-4e90-80aa-9e667e143945
4.2 kB Download
Checksum: md5:1eaa5990c3a4dae624a5f17bb88db2e7

PID: http://hdl.handle.net/11304/3362085e-6bee-4d0c-9f4c-7d7f1810c3eb
38.5 kB Preview Download
Checksum: md5:c84ba6b578db81e0bd9993cc505c8e1b

PID: http://hdl.handle.net/11304/af37f4ba-eb72-45ee-980f-38d5905066bd
1.5 kB Download
Checksum: md5:ff4510e2e532fd01a7aa172e4103a698

PID: http://hdl.handle.net/11304/cc97fd4d-0cb9-4f1d-986b-8fbeeb28da12
2.1 kB Preview Download

Additional details

Identifiers

b2rec
e9e0a50d2fa44e068ef12d51305e041f