Event interval analysis: Why do processes take time?

作者:

Highlights:

• A new framework is proposed to analyse process performance via information-poor log.

• It is built upon a new concept of event interval to systematically extract rich insights.

• It has been implemented as a plug-in tool within an open-source environment.

• It has been validated using a real log from an Australian insurance organisation.

• It has been applied to gain interesting performance insights from the industry log.

摘要

Through the application of process mining, valuable evidence-based insights can be obtained about business processes in organisations. As a result, the field has seen an increased uptake in recent years as evidenced by success stories and increased tool support. However, despite this impact, current performance analysis capabilities remain somewhat limited in the context of information-poor event logs. For example, natural daily and weekly patterns are not considered but they are vital for understanding the performance of processes and resources. In this paper, a new framework for analysing event logs is defined. Our framework is based on the concept of event interval. The framework allows for a systematic approach to sophisticated performance-related analysis beyond the capabilities of existing log-based analysis techniques, even with information-poor event logs. The paper formalises a range of event interval types and then presents an implementation as well as an evaluation of the proposed approach.

论文关键词:Process mining,ProM,Data mining,Business process management

论文评审过程:Received 20 August 2014, Revised 18 July 2015, Accepted 18 July 2015, Available online 29 July 2015, Version of Record 28 August 2015.

论文官网地址:https://doi.org/10.1016/j.dss.2015.07.007