An approach for discovering data impacting the execution of a business process
Résumé
Organizations have an increasing need to adapt faster their Information Systems to technical, functional and legal changes. One way proposed in the literature is to make a deep process analysis in order to have a better comprehension of the business process (BP) and adapt it to its new context. In this paper, we propose a meta model for a BP contextualization solution. The solution links a BP with business data and contextual data (weather, urban traffic, etc.) using semantics. We apply it to a commodity palletization process from our commodity traceability project and we conclude that it provides business expert with additional contextual data that impacted the BP execution.