Prediction of Incompliance With Business Goals With Business-Related Data and Context Data

Proactive adaptation of business processes can prevent and mitigate future problems during the execution of business processes. For the proactive adaptation of business processes, adaptation decisions should be made based on whether a business process instance is heading to a business goal. Recently, much work struggles to improve predictive business process monitoring efficiency, i.e., accuracy and prediction earliness. As such, process designers can find more necessary adaptations and have more remaining time for the adaptations. Almost all of these previous efforts concentrate on business-related data generated by business processes. However, besides business-related data, context data has a huge impact on how a business process instance is unfolding to its completion. Context data should be noticed in the area of predictive business process monitoring. To remedy this shortage, in this paper, we propose a predictive business process monitoring framework based on a joint of business-related data and context data to predict incompliance with business goals. We evaluated the framework concerning the measures of accuracy, prediction earliness, and cost time based on a real-life online banana purchase process.