Extending predictive process monitoring for collaborative processes

Daniel Calegari, Andrea Delgado
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Abstract

Process mining on business process execution data has focused primarily on orchestration-type processes performed in a single organization (intra-organizational). Collaborative (inter-organizational) processes, unlike those of orchestration type, expand several organizations (for example, in e-Government), adding complexity and various challenges both for their implementation and for their discovery, prediction, and analysis of their execution. Predictive process monitoring is based on exploiting execution data from past instances to predict the execution of current cases. It is possible to make predictions on the next activity and remaining time, among others, to anticipate possible deviations, violations, and delays in the processes to take preventive measures (e.g., re-allocation of resources). In this work, we propose an extension for collaborative processes of traditional process prediction, considering particularities of this type of process, which add information of interest in this context, for example, the next activity of which participant or the following message to be exchanged between two participants.
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为协作流程扩展预测性流程监控
对业务流程执行数据的流程挖掘主要集中在单个组织(组织内)执行的协调型流程。协作(组织间)流程不属于协调类型,它扩展了多个组织(例如,在政府中),增加了其实施以及发现、预测和分析其执行情况的复杂性和各种挑战。预测性流程监控的基础是利用过去实例的执行数据来预测当前案例的执行情况。它可以对下一个活动和剩余时间等进行预测,以预测流程中可能出现的偏差、违规和延迟,从而采取预防措施(如重新分配资源)。在这项工作中,我们考虑到协作流程的特殊性,提出了对传统流程预测的一种扩展,即在此背景下添加感兴趣的信息,例如哪位参与者的下一项活动或两位参与者之间要交换的后续信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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