Retrieving batch organisation of work insights from event logs

作者:

Highlights:

• First paper to systematically analyse batching behaviour in an event log

• Three types of batch processing are distinguished and formalised

• New algorithm to detect all batch processing types in an event log

• Specification and calculation of relevant batch processing metrics

• Extensive evaluation on artificial and real-life event logs

摘要

Resources can organise their work in batches, i.e. perform activities on multiple cases simultaneously, concurrently or intentionally defer activity execution to handle multiple cases (quasi-) sequentially. As batching behaviour influences process performance, efforts to gain insight on this matter are valuable. In this respect, this paper uses event logs, data files containing process execution information, as an information source. More specifically, this work (i) identifies and formalises three batch processing types, (ii) presents a resource-activity centered approach to identify batching behaviour in an event log and (iii) introduces batch processing metrics to acquire knowledge on batch characteristics and its influence on process execution. These contributions are integrated in the Batch Organisation of Work Identification algorithm (BOWI), which is evaluated on both artificial and real-life data.

论文关键词:Batch processing,Event log,Event log insights,Process mining,Business process management,Process metrics

论文评审过程:Available online 1 March 2017, Version of Record 24 July 2017.

论文官网地址:https://doi.org/10.1016/j.dss.2017.02.012