Business Rules Management and Decision Mining - Filling in the Gaps Leewis, Sam Smit, Koen Berkhout, Matthijs 2021-12-24T18:16:37Z 2021-12-24T18:16:37Z 2022-01-04
dc.description.abstract Proper decision-making is one of the most important capabilities of an organization. Adequately managing these decisions is therefore of high importance. Business Rules Management (BRM) is an approach that helps in managing decisions and underlying business logic. However, questions still arise if the decisions are properly improved based on decision data. Decision Mining (DM) could complement BRM capabilities in order to improve towards effective and efficient decision-making. In this study, we propose the integration of BRM and DM through a simulation using a government and a healthcare case. During this simulation, three entry points are presented that describe how decision-related data should be utilized between BRM capabilities and DM phases to be able to integrate them. The presented results provide a basis from which more technical research on the three DM phases can be further explored.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2022.755
dc.identifier.isbn 978-0-9981331-5-7
dc.language.iso eng
dc.relation.ispartof Proceedings of the 55th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.subject Business Rule Management Technologies
dc.subject business rules management
dc.subject cycle
dc.subject decision management
dc.subject decision mining
dc.subject improvement
dc.title Business Rules Management and Decision Mining - Filling in the Gaps
dc.type.dcmi Text
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