Practices that organizations employ to enhance business intelligence agility

Abstract: In today's rapidly changing business environment, organizations strive to be agile in order to accommodate changes and seize opportunities. Since organizations use information system as a tool to serve their needs, it is important for these systems also to be agile. One prominent type of such systems is business intelligence, which provides organizations with information to gain and retain competitive advantage. This thesis focuses on business intelligence agility, which is widely discussed in practice however not extensively covered in information systems literature. Therefore, this thesis seeks to identify the practices employed by organizations to enhance business intelligence agility. To find the answer to the research question this thesis first compiles a theoretical framework on business intelligence, information systems agility in general and business intelligence agility in specific using academic literature and market white papers. This compiled framework is comprised of four enabling factors 1) sensing business changes, 2) development approach, 3) IT governance, and 4) technical factors. This thesis conducts a qualitative research based on semi-structured interviews with business intelligence experts. Based on analysis of the empirical data this thesis identified a set of practices organized in terms of the enabling factors. The practices in sensing business changes are enabling business staff to sense changes and incorporating business staff feedback into data requirements. Regarding development approach, this thesis identifies the practices as applying an iterative development approach, building collaborative team of skilled members, enabling a centric role of business staff, reducing use of approval documents and learning from each project. In IT governance, applying a centralized or decentralized development were the two practices. Regarding practices in technical factors, this thesis identifies integrating data through either building an enterprise-wide data warehouse or applying an appropriate modeling approach while managing multiple data warehouses, using multiple front-end applications, and adopting cloud business intelligence. The findings of this thesis provide organizations with a pool of practices that can be used to enhance business intelligence agility.