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dc.creatorPérez Álvarez, José Migueles
dc.creatorMaté, Alejandroes
dc.creatorGómez López, María Teresaes
dc.creatorTrujillo, Juanes
dc.date.accessioned2022-10-31T09:56:50Z
dc.date.available2022-10-31T09:56:50Z
dc.date.issued2018
dc.identifier.citationPérez Álvarez, J.M., Maté, A., Gómez López, M.T. y Trujillo, J. (2018). Tactical Business-Process-Decision Support based on KPIs Monitoring and Validation. Computers in Industry, 102 (November 2018), 23-39. https://doi.org/10.1016/j.compind.2018.08.001.
dc.identifier.issn0166-3615es
dc.identifier.urihttps://hdl.handle.net/11441/138500
dc.description.abstractKey Performance Indicators (KPIs) can be used to evaluate the success of an organization, facilitating the detection of the deviations and unexpected evolution of the behaviour of a company. The difficulty for enterprises is to ascertain what to do when a deviation is detected. In this paper, we propose a modelling approach to improve the operational business-level and to ascertain the possible actions that can be executed to maintain the right direction in a company. For business process-oriented companies, it entails knowing how KPIs can be affected by the business processes. It implies not only pointing outthat a system malfunction exists, but also to know what to do when a deviation is detected. Our proposal presents a methodology that covers: (1) an extension of the existing models in order to combine KPIs, goals of the companies, and the decision variables together with business processes; (2) a methodology based on data mining analysis to verify the correctness of the enriched proposed model according to the data stored during business evolution, and; (3) a framework to simulate the evolution of the business according to the decisions taken in the governance process, thereby supporting governance activities to achieve the defined objectives by exploiting goals and KPIs from the proposed model.es
dc.description.sponsorshipMinisterio de Ciencia y Tecnología TIN2015-63502-C3-3-Res
dc.description.sponsorshipMinisterio de Ciencia y Tecnología TIN2015-63502-C3-2-Res
dc.formatapplication/pdfes
dc.format.extent17es
dc.language.isoenges
dc.publisherElsevieres
dc.relation.ispartofComputers in Industry, 102 (November 2018), 23-39.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectGovernancees
dc.subjectBusiness processeses
dc.subjectDecisions supportes
dc.subjectFuzzy logices
dc.subjectModelling knowledgees
dc.subjectKPIses
dc.titleTactical Business-Process-Decision Support based on KPIs Monitoring and Validationes
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/submittedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticoses
dc.relation.projectIDTIN2015-63502-C3-3-Res
dc.relation.projectIDTIN2015-63502-C3-2-Res
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0166361517307819?via%3Dihubes
dc.identifier.doi10.1016/j.compind.2018.08.001es
dc.contributor.groupUniversidad de Sevilla. TIC-258: Data-centric Computing Research Hubes
dc.journaltitleComputers in Industryes
dc.publication.volumen102es
dc.publication.issueNovember 2018es
dc.publication.initialPage23es
dc.publication.endPage39es
dc.contributor.funderMinisterio de Ciencia Y Tecnología (MCYT). Españaes

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