Prescriptive business process monitoring provides decision support to process managers on when and how to adapt an ongoing business process to prevent or mitigate an undesired process outcome. We focus on the problem of automatically reconciling the trade-off between prediction accuracy and prediction earliness in determining when to adapt. Adaptations should happen sufficiently early to provide enough lead time for the adaptation to become effective. However, earlier predictions are typically less accurate than later predictions. This means that acting on less accurate predictions may lead to unnecessary adaptations or missed adaptations. Different approaches were presented in the literature to reconcile the trade-off between prediction accuracy and earliness. So far, these approaches were compared with different baselines, and evaluated using different data sets or even confidential data sets. This limits the comparability and replicability of the approaches and makes it difficult to choose a concrete approach in practice. We perform a comparative evaluation of the main alternative approaches for reconciling the trade-off between prediction accuracy and earliness. Using four public real-world event log data sets and two types of prediction models, we assess and compare the cost savings of these approaches. The experimental results indicate which criteria affect the effectiveness of an approach and help us state initial recommendations for the selection of a concrete approach in practice.

翻译：规范性业务流程监控为流程管理人员提供决策支持，指导其何时以及如何调整正在运行的业务流程，以预防或减轻不良流程结果。我们聚焦于在确定调整时机时，自动协调预测准确性与预测早期性之间权衡的问题。调整应及早进行，以便为调整生效提供足够的提前时间。然而，早期预测通常不如后期预测准确。这意味着基于不够准确的预测采取行动可能导致不必要的调整或错失调整机会。文献中提出了不同方法来协调预测准确性与早期性之间的权衡。迄今为止，这些方法与不同基线进行比较，并使用不同数据集甚至保密数据集进行评估。这限制了方法的可比性和可重复性，使得在实践中难以选择具体方法。我们对协调预测准确性与早期性权衡的主要替代方法进行了比较评估。使用四个公开的真实世界事件日志数据集和两种类型的预测模型，我们评估并比较了这些方法的成本节约效果。实验结果揭示了影响方法有效性的标准，并帮助我们提出在实践中选择具体方法的初步建议。