Self-Service Business Analytics and the Path to Insights : Integrating Resources for Generating Insights
Abstract: The nature of today’s business demands that Business Analytics (BA) extends to an operational level to better support employees in their decision-making. This is noticeable from the constant requests for new reports and changes in old ones at different employee levels. As a result, BA specialists or other power-users in functional departments are “bombarded” by these requests, and it becomes more of a bottleneck than ever before. This might lead inexperienced users to make critical business decisions without exploring the necessary data. SSBA addresses this need by allowing various employees at different levels across the organisation to independently build custom reports and explore previous ones without relying on the IT/BI department. As a result, the end-user role shifts from simply a consumer to a more consumer-producer role. Furthermore, organisations provide different kinds of tools and technologies for their employees to assist them in their daily decision-making. One major challenge in SSBA is that users might engage in a wrong or uneducated self-service step in their data selection or analysis, which will likely lead to wrong business decisions. Therefore, the industry needs to know how those users engage with technology and use the different resources available to generate value in terms of gaining insight from data. Also, from an academic perspective, literature on BA and DSS is abundant and covers many aspects in terms of design, implementation, use in organisations, and BA value’s speed of insight and pervasive use. However, SSBA is still under-explored, especially regarding the way resources in an SSBA environment are integrated to generate insight from data especially when employees are expected to be autonomous. Therefore, the aim of this dissertation is to explore and inform organisations about how business users develop insights in an SSBA environment. This study consists of a collection of five papers, whose findings provide answers to two research questions: RQ1— How do organisations enable an SSBA environment? And RQ2—How do users integrate resources during an analytical task in SSBA? In line with the research questions and the study’s aim, Service Dominant Logic was used as a theoretical lens. This dissertation employs an interpretive case study design to investigate SSBA. Three sources of empirical evidence have been used (semi-structured interviews, observations, and documents) to collect data from the top digital marketplace in Norway – Finn.no.From a theoretical perspective, by portraying Self-Service Business Analytics as an approach to data analytics enabled through the presence of different analytical services such as tools, technologies, and support to assist the user in achieving independence, this dissertation emphasises the central idea of a service environment and move beyond the classic description of BA and DSS. It also provides a showcase through empirical evidence on how to use S-D logic in IS research and how it could be employed as an analytical lens. Finally, this thesis contributes to both BA and S-D logic literature by theorising the resource integration patterns, modes of engagement and the self-service environment in business analytics. From a practical perspective, this thesis relates to the industry by highlighting five major points of interest in relation to information authorship, the criticality of the setup phase in SSBA, steps to solve an analytical problem, and the competencies involved.
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