Discovering Business Area Effects to Process Mining Analysis Using
Clustering and Influence Analysis
- URL: http://arxiv.org/abs/2003.08170v1
- Date: Wed, 18 Mar 2020 11:58:01 GMT
- Title: Discovering Business Area Effects to Process Mining Analysis Using
Clustering and Influence Analysis
- Authors: Teemu Lehto and Markku Hinkka
- Abstract summary: We present a novel methodology for discovering business areas that have a significant effect on the process execution details.
Our method uses clustering to group similar cases based on process flow characteristics.
We also present an example analysis based on publicly available real-life purchase order process data.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: A common challenge for improving business processes in large organizations is
that business people in charge of the operations are lacking a fact-based
understanding of the execution details, process variants, and exceptions taking
place in business operations. While existing process mining methodologies can
discover these details based on event logs, it is challenging to communicate
the process mining findings to business people. In this paper, we present a
novel methodology for discovering business areas that have a significant effect
on the process execution details. Our method uses clustering to group similar
cases based on process flow characteristics and then influence analysis for
detecting those business areas that correlate most with the discovered
clusters. Our analysis serves as a bridge between BPM people and business,
people facilitating the knowledge sharing between these groups. We also present
an example analysis based on publicly available real-life purchase order
process data.
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