A Study of Business Intelligence Strategy Development by Large Organizations

A Study of Business Intelligence Strategy Development by Large Organizations

Carmine Carmine Sellitto (Victoria University, Australia) and Paul Hawking (Hawking Solutions, Australia)
DOI: 10.4018/978-1-5225-5718-0.ch018

Abstract

Organizations have adopted business intelligence solutions with a mixed degree of benefits. Some businesses highlight significant outcomes, while others identify limitations or shortfalls in the benefits derived. Notably, the alignment of business strategy with the adoption of business intelligence processes has been an important predictor of firms being able to achieve organizational wide benefits. The chapter uses a case study approach to document the informational needs achieved through aligning organizational strategy and the adoption of business intelligence solution at two distinct companies. The adoption approaches used by each firm, although different, reflect the important areas in which business intelligence is most useful—strategic alignment, governance, and information presentation.
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Introduction

Sourcing appropriate information that is timely, accurate, complete and relevant enables people to be confident and effective when it comes to business decision-making (Isik et al., 2013). Organizational decision-makers have historically relied on data derived from business transaction systems— systems that over time increased in both number and complexity as the organization expanded. Indeed, as such systems became more widely implemented, so increased the challenges of not only sourcing the appropriate data, but also integrating the data to enable its interpretation for decision-making processes (Hawking & Sellitto, 2017). In order to address these integration problems, firms implement whole-of-company Enterprise Resource Planning (ERP) systems. ERP systems allowed corporations to be more process effective, enabling them to achieve significant efficiencies as a result of transactions being aligned with one cross functional system that captured and stored and in a standardized manner (Davenport et al, 2003). Notably, such systems provide businesses with the essential information technology infrastructure that allows them to achieve growth, be competitive in their industry sector and manage process innovation (Chou et al., 2005).

The implementation of ERP systems resulted in numerous legacy systems being replaced, hence, addressing the integration issues. However, important issues persist in regards to analyzing the corporate data— particularly where legacy systems are still used. Hawking and Sellitto (2017) suggest that the persistence of legacy systems might be due to resource limitations not enabling complete integration or even a deficiency of these legacy functions in the new ERP system. Clearly, the persistence of organizational legacy systems that provide important data in management’s decision making activities needs to be addressed as an integration issue. Arguably, data sourced from legacy systems will require alignment and integration with data captured by ERP systems— reflecting the corporate data pool that can be analyzed and accommodated in appropriate report formats. Furthermore, as people’s informational needs underpin decision-making capacity, so have newer forms of computing technology systems resulted to directly facilitate this important activity. These computing systems embody a variety of offerings that include Data Mining (DM), Knowledge Discovery (KD), Collaborative Systems (CS) and Business Analytics (BA). The term Business Intelligence (BI) is proposed as a moniker that can be used to include all of the proceeding systems (Gibson et al., 2004; Olszak & Ziemba, 2007; Hawking & Sellitto, 2017).

For numerous organizations Business Intelligence has been a post-ERP systems implementation feature, allowing them to gain a deeper understanding of not only their data, but also processes and transactions. Howson (2007, p.2) defines Business Intelligence an activity that “…allows people at all levels of an organization to access, interact with, and analyse data to manage the business, improve performance, discover opportunities, and operate efficiently”. Indeed, the analysis of organizational can result in improved productivity and competitive advantage— particularly over other firms in a similar industry sector that have not achieved the same level of information system adoption (Watson and Wixom, 2007; Luftman & Ben-Tvi, 2010). Moreover, Business Intelligence might be considered to factor for companies to be competitive in agile and ever-changing markets and sectors (Luftman & Ben-Tvi, 2010; Watson & Wixom, 2007).

Although the concept of Business Intelligence has been reported for a number of years, limited research has examined Business Intelligence strategy and its support for organizational decision makers. The paper contributes to this important theme through two cases that examined the practices and experience of Business Intelligence strategy development and enactment. The strategies presented can provide insights for not only industry practitioners, but also researchers and industry bodies.

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