Analysis of process data and their social aspects

Abstract

Information systems support and ensure practical running of most critical business processes. There exist or can be reconstructed records (logs) of the process running in the information system with information about the participants and the processed objects for most of the processes. Computer methods of data mining can be used for analysis of process data utilizing support techniques of machine learning and complex network analysis. Process mining is able to analyze and reconstruct the model of running process from its process log. The analysis of participants behavior of running process from process log transformed into complex network of its participants is not very used approach, much frequently the quantitative parameters are analyzed. Here we show how data and process mining methods can be used for analyzing of running process and how participants behavior can be analyzed from the process log using network (community or cluster) analyzes in constructed complex network from the SAP business process log. This work formulated and developed a methodology covering data integration, pre-processing and transformation, data mining with following interpretation and decision support – the work was realized and experimentally verified on sets of real logs from SAP business process. The modified canonical process log structure is suggested with respect of SAP environment – this can be applied for any SAP system (principally). This approach constructs the complex network from the process log in the given context and then it finds communities or patterns in this network. Found communities and patterns are analyzed using knowledge of the business process and the environment in which the process operates. The results demonstrate possibility to cover up not only quantitative, but also qualitative relations (i.e. hidden behavior of participants) using the process log and specific knowledge of the business case. This approach was found as useful starting point for decision support analysis supporting managers with getting knowledge from process data (log). While process mining can provide the model (visual or formal) of running process, the complex network analysis can uncover behavior relations of participants, that are hidden in quantitative models of process log.