Retrieving batch organisation of work insights from event logs

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 (BOW), which is evaluated on both artificial and real-life data. (C) 2017 Elsevier B.V. All rights reserved.