Key Performance Indicators (KPI) measure the performance of an enterprise relative to its objectives thereby enabling corrective action where there are deviations. In current practice, KPIs are manually integrated within dashboards and scorecards used by decision makers. This practice entails various shortcomings. First, KPIs are not related to their business objectives and strategy. Consequently, decision makers often obtain a scattered view of the business status and business concerns. Second, while KPIs are defined by decision makers, their implementation is performed by IT specialists. This often results in discrepancies that are difficult to identify. In this paper, we propose an approach that provides decision makers with an integrated view of strategic business objectives and conceptual data warehouse KPIs. The main benefit of our proposal is that it links strategic business models to the data for monitoring and assessing them. In our proposal, KPIs are defined using a modeling language where decision makers specify KPIs using business terminology, but can also perform quick modifications and even navigate data while maintaining a strategic view. This enables monitoring and what-if analysis, thereby helping analysts to compare expectations with reported results.

This research has been supported by the European Research Council (ERC) through advanced Grant 267856, titled “Lucretius: Foundations for Software Evolution” (04/2011-03/2016) and the national project GEODAS-BI (TIN2012-37493-C03-03) from the Spanish Ministry of Economy and Competitiveness (MINECO). Alejandro Maté is funded by the Generalitat Valenciana under an APOSTD Grant (APOSTD/2014/064).