Measuring the success of business intelligence and analytics systems: A literature review

Abstract

Technology-based solutions such as business intelligence and analytics (BI&A) systems have become indispensable for organizations due to their ability to support decision-making. Recent developments in big data availability and more powerful analytical tools have increased the potential value of BI&A systems. However, academic and practitioner-oriented research suggests that the potential success of BI&A systems has not yet been fully realized by most organizations. Existing studies have attempted to evaluate the effectiveness and success of BI&A systems by proposing various success measures. However, these studies have generated inconsistent results, limiting the ability to compare and generalize the findings. Therefore, this study takes a step forward by proposing an updated, comprehensive, and consolidated set of success measures for this unique class of information systems. Using a systematic literature review approach, this study examined and synthesized BI&A systems success measures across 173 past studies using the DeLone & McLean IS success framework. Findings revealed success measures such as ease of use, information accuracy, and financial performance that are consistently applied to the measurement of BI&A systems, and importantly, other recommended measures such as system features, presentation format, and decision-making performance that are uniquely important to BI&A systems but infrequently applied. Finally, a comprehensive set of BI&A success measures is proposed for future empirical research studies and practitioner use.