Authors: Jesús Peral, Roberto Tardío
Tags: 2015, conceptual modeling
Currently dashboards are the preferred tool across organizations to monitor business performance. Dashboards are often composed by different data visualization techniques, amongst which Key Performance Indicators (KPIs) play a crucial role in facilitating quick and precise information by comparing current performance against a target required to fulfill business objectives. It is however the case that not always KPIs are well known, and sometimes it is difficult to find an adequate KPI to associate with each business objective. On the other hand, data mining techniques are often used for forecasting trends and visualizing data correlations. In this paper, we present a novel approach to combine these two aspects in order to drive data mining techniques into obtaining specific KPIs for business objectives in a semi-automatic way. The main benefit of our approach, is that organizations do not need to rely on existing KPI lists, such as APQC, nor test KPIs on a cycle, as they can analyze their behaviour using existing data. In order to show the applicability of our approach, we apply our proposal to the novel field of MOOC courses in order to identify additional KPIs to the ones being currently used.Read the full paper here: https://link-springer-com.proxy2.hec.ca/chapter/10.1007/978-3-319-25747-1_15
