An Experimental Analytics on Discovering Work Transference Networks from Workflow Enactment Event Logs

• Main Authors: Hyun Ahn, Dinh-Lam Pham, Kwanghoon Pio Kim
• Format: Article
• Language: English
• Published: MDPI AG 2019-06-01
• Series: Applied Sciences
• Subjects: workflow management; work transference network; workflow enactment event logs; experimental analytics
• Online Access: https://www.mdpi.com/2076-3417/9/11/2368

Work transference network is a type of enterprise social network centered on the interactions among performers participating in the workflow processes. It is thought that the work transference networks hidden in workflow enactment histories are able to denote not only the structure of the enterprise social network among performers but also imply the degrees of relevancy and intensity between them. The purpose of this paper is to devise a framework that can discover and analyze work transference networks from workflow enactment event logs. The framework includes a series of conceptual definitions to formally describe the overall procedure of the network discovery. To support this conceptual framework, we implement a system that provides functionalities for the discovery, analysis and visualization steps. As a sanity check for the framework, we carry out a mining experiment on a dataset of real-life event logs by using the implemented system. The experiment results show that the framework is valid in discovering transference networks correctly and providing primitive knowledge pertaining to the discovered networks. Finally, we expect that the analytics of the work transference network facilitates assessing the workflow fidelity in human resource planning and its observed performance, and eventually enhances the workflow process from the organizational aspect.