Business Intelligence in different decision settings

Hin-Hey Karl Chung

Student thesis: Master thesis


Abstract: While Business Intelligence (BI) technologies advance and in practice more emphasis is placed on using data to improve decision-making (Gartner, 2013b; LaValle, Hopkins, Lesser, Shockley, & Kruschwitz, 2010), only few researchers have investigated BI from a decision-centric view (Kowalczyk, Buxmann, & Besier, 2013). In fact, although BI claims to enhance decision-making, the literature review reveals a major gap between the two research streams. On the one hand, decisions are treated differently depending on the decision setting. On the other, BI focuses mainly on technological and process-related aspects ignoring the decision characteristics. This paper attempts to close this gap by examining the BI output usage in various decision settings. Established decision-making frameworks with recent BI findings were examined in order to better understand the BI support. In particular, the frameworks by Thompson (1967) and Gorry and Scott Morton (1971) form the basis for classifying a decision properly. From a BI perspective the different BI tactics and devices identified by Shollo (2013) build the foundation for the study. The study, conducted at an online advertising company, finds different behavior in different settings and highlights the functional interaction between rational and socio-political processes making a technological determinism approach, as favored by the BI technological view, questionable. Instead, the insights imply a more setting dependent approach and show the different roles of BI. In a structured analysis setting the rational BI output inherently determines the ultimate decision while in other settings the BI information is neglected and other socio-political devices, such as the expert and stakeholder, gain more importance. Several recommendations are given based on the study’s findings and they call for more research on BI from a decision-centric view to keep the promise of improving decision-making by using BI.

EducationsMSc in Business Administration and Information Systems, (Graduate Programme) Final Thesis
Publication date2015
Number of pages74