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Ítem Improving the business processes management from the knowledge management(Association for Computing Machinery, 2016-01-01) Marta S. Tabares; Giraldo, Liliana; Aguilar, Luis; Universidad EAFIT. Departamento de Ingeniería de Sistemas; I+D+I en Tecnologías de la Información y las ComunicacionesThis paper proposes a model that integrates the knowledge management to the business processes management in order to improve the process performance. The proposal defines the knowledge management flow as an element that interacts with part workflows and provides rules and actions in the BPMN elements in order to improve the BPM. To achieve the aim, first, a survey was made in forty Colombian' companies in order to identify the state of the practice about business process management, knowledge management and their use through the workflows; then, different elements were identified and characterized in order to achieve the integration model proposed. This was experimented in forty business workflows of the companies analyzed. A use case shows how the interactions among model elements are, and how these can improve the process performance. This experience allowed to measuring the effect that the integration had in the business process management by means of a new metric that involve the knowledge management in the workflow. Finally, it was possible conclude that the knowledge management must be part to the BPM impacting directly the workflow, in order to improve the result offered to the organizational actors and customers.Ítem A methodology for Data Analytic Based on Organizational Characterization through a User-centered Design: A Position Paper(Institute of Electrical and Electronics Engineers Inc., 2020-01-01) Astudillo B.; Santorum M.; Aguilar J.; Universidad EAFIT. Departamento de Ingeniería de Sistemas; I+D+I en Tecnologías de la Información y las ComunicacionesData Analytic (DA) is currently a very important approach to obtain the best possible benefit of the data, but its degree of difficulty compared to other computational processes limits its implementation in organizations. In addition, it remains a term highly confused with respect to other areas of data science, such as data mining, and Big Data. There are few methodologies for its implementation, in addition, its complexity makes it non-participatory, with a certain degree of resistance on the part of the users. The knowledge and skills of users must be exploited when analyzing and producing the business intelligence necessary for the Data Analytic execution. In this position paper, we explore the possibilities of contribution through a Methodology for Data Analytic, which is extended with the incorporation of features extracted from a user-centered design (UCD) approach inspired by the ISEA methodology. This existing DA methodology, called MIDANO, will be extended using gamification techniques, to facilitate the applicability and understanding, in order to guarantee a participation of organizational actors, resulting in a Participatory Data Analytic Methodology. © 2020 IEEE.