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TopIntroduction And Background
Organisations utilize a technology-driven process for analysing data and presenting actionable information in support of informed business decision-making. This technology-driven process is referred to as business intelligence (BI) and contributes toward revealing the position of an organisation in comparison to its competitors, market conditions, and future trends, as well as present demographic and economic information. To deliver value that aligns with the business objectives and priorities, business intelligence should have a well-executed methodology, processes, governance, and technology. However, the focus areas of BI efficiency are mainly targeted at infrastructure development, information access, becoming more proactive in terms of meeting data needs and having a better understanding of needs (February 2017). Although the data is there, it is not readily available and other business units do not know that such data exists (Olszak 2016). This suggests that it is not only about the data, but also about putting systems and processes in place to ensure that data is always available and easily accessible for decision-making (Trieu 2017; Wieder & Ossimitz 2015). Therefore, there is a requirement to deliver more effective decision-making support through the effective deployment of BI structures, processes, and technologies.
Decision makers at all levels devote substantial efforts to making appropriate organisational decisions (Al-Tarawneh 2012). Many important theorists and practitioners consider decision-making to be the most critical, core managerial function. Business decisions must be motivated and the best way to motivate a business decision is by having reliable and consistent supporting data that shows historical trends that can be used to predict future business outcomes (Marin & Poulter 2004; Field 2009). The high volumes of available data in businesses necessitated efficient extraction, storage, transformation, sharing, and disposal processes so that the data could be used effectively to support decision-making (Delen & Demirkan 2013; Richards 2017). Hence the importance of this research, to establish models or frameworks that can be applied by organisations to ensure effective decision-making within organisations.
This research fulfils the gap in terms of providing an effectiveness model that is geared towards the enhancement of decision-making capabilities within organisations. One could describe a model as something which translates strategic intent into operational capabilities. It serves as the foundation to achieve strategic intent. To ensure BI efficiency, organisations must therefore employ a strong focus on the multifaceted technological, organisational, and process-related nature of their BI implementation (Yeoh & Popovic 2016; Surbakti et al., 2019). Hence the importance of this study, to test the effectiveness of current BI implementations to ensure good decision-making capabilities within organisations.
The BI implementation scope is a rather complex undertaking requiring appropriate infrastructure and resources over a lengthy period that, if not managed well, may result in large investments with little or no benefits to the organisation (Delen & Demirkan 2013; Yeoh & Popovic 2016). A business intelligence strategy should take into consideration the appropriate framework, methodology, processes, governance, systems, and technology to deliver value that aligns with the business objectives and priorities (February 2018). The success of a BI initiative should be measured in terms of value creation: whether the BI solution gives the business the tools to get as much value out of their data as possible, while at the same time providing valuable insight that can be applied to leverage enough revenue to cover the cost of implementing the BI solution and make a profit (February 2018). The uniqueness of this study is test whether BI solutions deliver the value that it is intended for, the study is strategic in nature, and not technical in nature which differentiates this study.