User-Related Challenges of Self-Service Business Intelligence

Abstract

Self-service Business Intelligence (SSBI) allows non-technical users to use Business Intelligence in a selfreliant manner without the support of technical users. Many organizations struggle to utilize the potential of SSBI and experience implementation challenges. This study aims to explore user-related SSBI challenges by conducting 30 qualitative interviews with 2 SSBI implementation projects. Analysis revealed challenges that can help practitioners to avoid unnecessary obstacles when implementing and using SSBI, and guide researchers in simplifying the implementation process.

Beyond the Hype: Why Do Data-Driven Projects Fail?

“…Based on the interviews by Lennerholt and van Laere [32], challenges can include access and use of data, i.e., lack of possibilities to gain access to data, multiple data sources in different environments, unknown data sources, long time required to request access, difficulties in making data available, as well as data quality, i.e., faulty data in standard reports, difficulties in changing faulty data, no common definition of data, no awareness of using faulty data.…”

“…To sum up, partial practical insights were gained in different expert rounds, i.e., both case studies [4,9,28,33,34,39,49,51] and expert interviews [1,8,24,29,32]. The gained insights relate the challenges of datadriven projects to people [3,4,6,8,12,23,24,25,27,28,34,39,52], data [1,7,8,24,27,28,29,32,34,49], tools and technologies [8,27,28,34,39], as well as processes [8,24,28,33,34,39,47]. However, none of the extracted findings were further evaluated with a larger sample of data experts.…”

“…Known issues such as data access [7,8,32], data volume [1,49], data quality [24,27,29,32], legal issues [1], security issues [28], lack of technical expertise [12,23] were adopted and supplemented through other ones.…”

“…In the cited data-driven model on Google Flu Trends, the flu propensity, as measured by the number of influenza-related doctor visits, could be estimated based on the number of flu-related Google search queries [18]; however, it was overestimated by more than a factor of two in two consecutive years [31]. Furthermore, research has been showing increasingly that other aspects are essential as well, such as people [3,4,6,8,12,23,24,25,27,28,34,39,52], data [1,7,8,24,27,28,29,32,34,49], tools and technologies [8,27,28,34,39], as well as processes [8,24,28,33,34,39,47].…”

“…Partial practical insights on the challenges of datadriven projects were obtained in the expert rounds, including case studies [4,9,28,33,34,39,49,51] and expert interviews [1,8,24,29,32]. However, none of those findings were further evaluated with a larger expert sample.…”