Extending the understanding of critical success factors for implementing business intelligence systems

Abstract

Extant studies suggest implementing a business intelligence (BI) system is a costly, resource-intensive and complex undertaking. Literature draws attention to the critical success factors (CSFs) for implementation of BI systems. Leveraging case studies of seven large organizations and blending them with Yeoh and Koronios's (2010) BI CSFs framework, our empirical study gives evidence to support this notion of CSFs and provides better contextual understanding of the CSFs in BI implementation domain. Cross-case analysis suggests that organizational factors play the most crucial role in determining the success of a BI system implementation. Hence, BI stakeholders should prioritize on the organizational dimension ahead of other factors. Our findings allow BI stakeholders to holistically understand the CSFs and the associated contextual issues that impact on implementation of BI systems. IntroductionThe successful implementation of information technology (IT) innovations remains both a theoretical and a managerial challenge. Many IT implementation projects have a high-risk profile (Harrington & Guimaraes, 2005;Kutsch, Denyer, Hall, & Lee-Kelley, 2013) and various IT innovations introduced by organizations are either rejected or underused by end users (Sharma & Yetton, 2003).Business intelligence (BI) technologies have recently received considerable attention from both industry and acareceived (Chen, Chiang, & Storey, 2012). In a worldwide survey of IT spending (Gartner, 2013b), BI-related technologies (still) ranked among the top technology priorities of many chief information officers, with global BI software spending expected to grow by 7% over the previous year (Gartner, 2013a). Such enthusiasm can be attributed to the rising importance of BI systems, which have regularly been viewed as "a broad category of technologies, applications, and processes for gathering, storing, accessing, and analyzing data to help its users make better decisions" (Wixom & Watson, 2010, p. 14). Yet implementing a BI system does not only entail the purchase of a combination of software and hardware; rather, it is a complex undertaking requiring appropriate infrastructure and resources over a lengthy period of time (Yeoh & Koronios, 2010). In fact, cases have previously been reported where large investments in various BI initiatives over lengthier periods resulted in little or no benefits for the organizations implementing them (Williams & Williams, 2007).Despite the vibrant BI market and the complexities surrounding the implementation of BI systems, the critical success factors (CSFs) of BI system implementation initiatives remain poorly understood. A typical BI system implementation involves multifaceted technological, organizational, and process issues, sharing similar characteristics with other intelligence system (IS) infrastructural projects like enterprise resource planning (ERP) systems implementation (Popovič, Hackney, Coelho, & Jaklič, 2012). Still, most existing CSF studies have focused on identifying lists of CSFs and little con...

An integrated model for determining business intelligence systems adoption and post-adoption benefits in banking sector

“…Based on these, we therefore hypothesized that: H5: Top Management Support is positively related to BI Systems Adoption 3. Presence of Champion Premkumar et al (1997) and Yeoh & Koronios (2010) describe a champion as a highly enthusiastic person with in-depth knowledge of the business processes of the organization as well as the technological innovation being discussed and committed to the innovation. Champions actively support, and promote the project by creating awareness, provide information, political support, material resources, and play a significant role in gaining organizational acceptance of the innovation which are very important to impact successful adoption and implementation (Gu et al, 2012;Meyer, 2000;Premkumar et al, 1997;Wixom & Watson, 2001).…”

“…As a result, a lot of organizations have implemented BI Systems using Critical Success Factors (CSFs) and Maturity Models (MMs) (Dawson & Van Belle, 2013;Fedouaki & El Alami, 2013;Mungree, Rudra & Morien, 2013;Olbrich, Pöppelbuß & Niehaves, 2012;Olszak & Ziemba, 2012;Ong & Siew, 2013;Hribar Rajterič, 2010;Yeoh, Koronios, & Gao, 2008;Yeoh & Koronios, 2010). Currently, many organizations are using BI tools (for example,online analytical processing (OLAP), Data warehouse, Dashboards, Data Mining, Reporting, and so on) (Zaman, 2005) to deal with both structured and semi-structured data (Blumberg & Atre, 2003;Rudin & Cressy, 2003) to present value-added and meaningful reports which can then aid management in decision making.…”

“…In addition, extant literature shows that there are few empirical studies when it comes to organizational adoption of BI Systems based on adoption theories (DOI, TOE, INT) as many have been done at the individual level (Grublješič & Jaklič, 2015;Hou, 2014;Hou, 2012;Kester & Preko, 2015;Pilz & Ferraz, 2013;Yoon, Ghosh, & Bong-Keun Jeong, 2014). Also, most of the existing studies have focused mainly on Maturity Models (MMs) for measuring the current state of BI Systems as well as Critical Success Factors (CSFs) for BI Systems implementation in large organizations and Small Medium Enterprises (SMEs) in different parts of the world especially advanced economies (Dawson & Van Belle, 2013;Fedouaki & El Alami, 2013;Hawking, Jovanovic, & Sellitto, 2011;Hawking, 2013;Khojasteh, 2013;Mungree et al, 2013;Olbrich et al, 2012;Olszak & Ziemba, 2012;Olszak, 2013;Ong & Siew, 2013;Hribar Rajterič, 2010;Yeoh et al, 2008; ISSN: 2414-309X DOI: 10.20474/jabs-2.2.4 TAF Publishing Yeoh & Koronios, 2010). Again, there are very few studies that have looked at the post-adoption effects of BI Systems on organizational performance (Elbashir, Collier, & Davern, 2008;Hou, 2015).…”

Measuring the success of business-intelligence systems in South Africa: An empirical investigation applying the DeLone and McLean Model

“…Hence, understanding the drivers of and barriers to BIS success is very important. The success of BIS has not been fully investigated (Chaveesuk 2010;Yeoh & Koronios 2010). A search in the main electronic databases for journals, such as EbscoHost, Emerald, Google Scholar, Proquest and ScienceDirect, suggests that no academic research has validated the DeLone and McLean (2003) model of information-systems (IS) success in the context of BI in South Africa.…”

Analyzing business intelligence maturity

“…Other published work on critical success factors (Yeoh & Koronios (2010) and Olszak & Ziemba (2012)) focuses on CSFs for implementing BI systems; however Shanks & Bekmamedova (2012) have presented results from a project where they studied a large Australian financial services firm and found critical success factors that helped increase analytical maturity. In addition, when appropriate, we also use complementary theory as a means to introduce different perspectives and for being able to make the discussion concerning our case study as detailed and extensive as possible.…”