Detecting and tackling run-time obstacles in social business processes
Source of Publication
Proceedings - International Conference on Advanced Information Networking and Applications, AINA
© 2017 IEEE. This paper presents an approach for detecting and tackling obstacles that could fail the execution of social business processes. Existing approaches target regular (non-social) business processes and thus, rely mainly on business logs that contain details such as who executes what, when, and where. However, interactions between a business process's three components namely task, machine, and person, are overlooked. This deprives process engineers from valuable details that could help detect and tackle obstacles. These details refer to task-2-task, machine-2-machine, and person-2-person interactions and are recorded in social logs. Both business and social logs are part of an architecture that includes monitor, solver, and crawler components. A system implementing the architecture is also presented in the paper and illustrates how logs are developed and structured using eXtensible Event Stream format.
Maamar, Zakaria; Sellami, Mohamed; Faci, Noura; and Lefebvre, Sylvain, "Detecting and tackling run-time obstacles in social business processes" (2017). Scopus Indexed Articles. 1335.