Specification-Driven Predictive Business Process Monitoring

Predictive analysis in business process monitoring aims at forecasting the future information of a running business process. The prediction is typically made based on the model extracted from historical process execution logs (event logs). In practice, different business domains might require different kinds of predictions. Hence, it is important to have a means for properly specifying the desired prediction tasks, and a mechanism to deal with these various prediction tasks. Although there have been many studies in this area, they mostly focus on a specific prediction task. This work introduces a language for specifying the desired prediction tasks, and this language allows us to express various kinds of prediction tasks. This work also presents a mechanism for automatically creating the corresponding prediction model based on the given specification. Differently from previous studies, instead of focusing on a particular prediction task, we present an approach to deal with various prediction tasks based on the given specification of the desired prediction tasks. We also provide an implementation of the approach which is used to conduct experiments using real-life event logs.Comment: This article significantly extends the previous work in https://doi.org/10.1007/978-3-319-91704-7_7 which has a technical report in arXiv:1804.00617. This article and the previous work have a coauthor in commo

Semantic enabled complex event language for business process monitoring

Efforts are being made to enable business process monitoring and analysis through processing continuously generated events. Several ontologies and tools have been defined and implemented to allow applying general-purpose Business Process Analysis techniques to specific domains. On this basis, a Semantic Enabled Monitoring Event Language (SEMEL) is proposed to facilitate defining complex queries over monitoring data so as to interleave temporal and ontological reasoning. In this paper, the formal semantics of SEMEL is discussed, and the implementation approach of SEMEL interpreter is also briefly described, which encompasses translation into an operational language

Predictive Monitoring of Business Processes

Modern information systems that support complex business processes generally maintain significant amounts of process execution data, particularly records of events corresponding to the execution of activities (event logs). In this paper, we present an approach to analyze such event logs in order to predictively monitor business goals during business process execution. At any point during an execution of a process, the user can define business goals in the form of linear temporal logic rules. When an activity is being executed, the framework identifies input data values that are more (or less) likely to lead to the achievement of each business goal. Unlike reactive compliance monitoring approaches that detect violations only after they have occurred, our predictive monitoring approach provides early advice so that users can steer ongoing process executions towards the achievement of business goals. In other words, violations are predicted (and potentially prevented) rather than merely detected. The approach has been implemented in the ProM process mining toolset and validated on a real-life log pertaining to the treatment of cancer patients in a large hospital

An agile business process and practice meta-model

Business Process Management (BPM) encompasses the discovery, modelling, monitoring, analysis and improvement of business processes. Limitations of traditional BPM approaches in addressing changes in business requirements have resulted in a number of agile BPM approaches that seek to accelerate the redesign of business process models. Meta-models are a key BPM feature that reduce the ambiguity of business process models. This paper describes a meta-model supporting the agile version of the Business Process and Practice Alignment Methodology (BPPAM) for business process improvement, which captures process information from actual work practices. The ability of the meta-model to achieve business process agility is discussed and compared with other agile meta-models, based on definitions of business process flexibility and agility found in the literature. (C) 2017 The Authors. Published by Elsevier B.V

Analisis Business Process Reengineering Untuk Mengevaluasi, Merekayasa Ulang, Dan Memperbaiki Monitoring Kontrak Pada PT Pln (Persero) Dist. Jatim Area Malang.

The purpose of this study was to determine the procedures of monitoring contract business process ongoing at PT PLN (Persero) East Java Distribution Malang Area, to identify the causes of monitoring contract business processes less efficient, and the proposed draft Monitoring Contract business processes based on analysis of Business Process Reengineering (BPR) method. There are many contract between PT PLN with the vendor requires efficient business processes so that the contract can be completed on time. Nowadays business process monitoring contract is less efficient because many processes are still done manually and repeatedly. By using the BPR method, the authors could find out the cause of the lack of efficiency in the monitoring contract business process. The results of this research are the design recommendations of new monitoring contract business process with the proposed solution, there are uses integrated Monitoring System Contract between divisions, streamlining the process with disappearing NVA processes and simplification of the process time for BVA. The design of the new process can show time savings in monitoring contract business process as much as 31.39% - 44.51%. Keywords: Business Process, Monitoring Contract, BPR.Abstract The purpose of this study was to determine the procedures of monitoring contract business process ongoing at PT PLN (Persero) East Java Distribution Malang Area, to identify the causes of monitoring contract business processes less efficient, and the proposed draft Monitoring Contract business processes based on analysis of Business Process Reengineering (BPR) method. There are many contract between PT PLN with the vendor requires efficient business processes so that the contract can be completed on time. Nowadays business process monitoring contract is less efficient because many processes are still done manually and repeatedly. By using the BPR method, the authors could find out the cause of the lack of efficiency in the monitoring contract business process. The results of this research are the design recommendations of new monitoring contract business process with the proposed solution, there are uses integrated Monitoring System Contract between divisions, streamlining the process with disappearing NVA processes and simplification of the process time for BVA. The design of the new process can show time savings in monitoring contract business process as much as 31.39% - 44.51%

Towards an ontology for process monitoring and mining

Business Process Analysis (BPA) aims at monitoring, diagnosing, simulating and mining enacted processes in order to support the analysis and enhancement of process models. An effective BPA solution must provide the means for analysing existing e-businesses at three levels of abstraction: the Business Level, the Process Level and the IT Level. BPA requires semantic information that spans these layers of abstraction and which should be easily retrieved from audit trails. To cater for this, we describe the Process Mining Ontology and the Events Ontology which aim to support the analysis of enacted processes at different levels of abstraction spanning from fine grain technical details to coarse grain aspects at the Business Level