Guided Interaction Exploration and Performance Analysis in Artifact-Centric Process Models

Abstract

Artifact-centric process models aim to describe complex processes as a collection of interacting artifacts. Recent development in process mining allow for the discovery of such models. However, the focus is often on the representation of the individual artifacts rather than their interactions. Based on event data, composite state machines representing artifact-centric processes can be discovered automatically. Moreover, the study provides ways of visualising and quantifying interactions among different artifacts. For example, strongly correlated behaviours in different artifacts can be highlighted. Interesting correlations can be subsequently analysed to identify potential causes of process performance issues. The study provides a strategy to explore the interactions and performance differences in this context. The approach has been fully implemented as a ProM plug-in; the CSM Miner provides an interactive artifact-centric process discovery tool focussing on interactions. The approach has been evaluated using real life data, to show that the guided exploration of artifact interactions can successfully identify process performance issues.

A Technique for Determining Relevance Scores of Process Activities using Graph-based Neural Networks

“…The model learns towards this goal rather than using heuristics (e.g., frequency, similarity, or distance measures); such techniques can provide more guidance for a process analyst considering a business problem [9].…”

“…However, the performance statistics solely relied upon frequency and were not learned in a similar way as our GGNN-based technique. An example of process model-based analysis was presented by van Eck et al [9], who designed an extension of their composite state machine miner, a process discovery technique. They coloured the process nodes according to their degree of artefact interaction; that is, the ('correlations between sets of artefact states or transitions' [9]).…”

“…An example of process model-based analysis was presented by van Eck et al [9], who designed an extension of their composite state machine miner, a process discovery technique. They coloured the process nodes according to their degree of artefact interaction; that is, the ('correlations between sets of artefact states or transitions' [9]). However, their technique did not directly permit root cause analysis with respect to performance indicators.…”

“…The right-hand process model indicates the most relevant path in terms of budget violations, and each process activity is annotated with a relevance score expressing its importance thereto. The process analyst can directly identify which activities should be considered for redesign and can also suggest which of these activities should be considered first (e.g., Process model-based analysis-that is, process analysis based on the discovered process model-is able to make users aware of the business processes behind the data and can subsequently guide process analysts as they improve these processes [9]. To facilitate analysis beyond the simple discovery of a process, the process model must provide information suitable for the improvement initiative.…”

Simplifying complex business process models through abstraction and Facilitating their reusability through business process model matching

“…process mining [183] and [103]. The exploitation and efficient handling of those process models has become even more vital in today's digitalization era, which poses further challenges and opportunities that need to be addressed [119]. Especially, process stakeholders who are part of an organization's senior leadership team and have an overall view of the organization's process landscape, need to rapidly comprehend complex business processes and exploit all important information available in process model repositories.…”