Abstract | ||
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Business processes often exhibit a high degree of variability. Process variants may manifest due to the differences in the nature of clients, heterogeneity in the type of cases, etc. Through the use of process mining techniques, one can benefit from historical event data to extract non-trivial knowledge for improving business process performance. Although some research has been performed on supporting process comparison within the process mining context, applying process comparison in practice is far from trivial. Considering all comparable attributes, for example, leads to an exponential number of possible comparisons. In this paper we introduce a novel methodology for applying process comparison in practice. We successfully applied the methodology in a case study within Xerox Services, where a forms handling process was analyzed and actionable insights were obtained by comparing different process variants using event data. |
Year | DOI | Venue |
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2017 | 10.1007/978-3-319-59336-4_18 | Lecture Notes in Business Information Processing |
Keywords | Field | DocType |
Process comparison,Process mining,Business analytics | Business analytics,Business process,Computer science,Process modeling,Event data,Business process modeling,Process mining,Process management | Conference |
Volume | ISSN | Citations |
288 | 1865-1348 | 0 |
PageRank | References | Authors |
0.34 | 18 | 7 |
Name | Order | Citations | PageRank |
---|---|---|---|
Alifah Syamsiyah | 1 | 0 | 1.69 |
Alfredo Bolt | 2 | 18 | 2.35 |
Long Cheng | 3 | 91 | 16.99 |
Bart F. A. Hompes | 4 | 1 | 0.75 |
R. P. Jagadeesh Chandra Bose | 5 | 2 | 1.05 |
Boudewijn F. van Dongen | 6 | 1875 | 97.84 |
Wil Van Der Aalst | 7 | 20894 | 1418.27 |