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Strategic decision-making is one of the most important criterions for organizational success. The need for evidence-based decision-making is spreading quickly throughout organizations because it results in more precise and perceptive decisions. (Hocevar & Jaklič, 2010; Lönnqvist & Pirttimäki, 2006; Schwarz, 2009). However, one of the greatest challenges facing organizations today is making important and timely business decisions. Given the turbulence nature of many organizations concerning the new challenges and opportunities affecting organizational decisions, researchers have become increasingly interested in success and failure factors (Hyväri, 2006). Since, uncertainty cannot be eliminated from decision-making, the aim should be to reduce it to improve the chances of success in the task undertaken (Higgs, Smith, and Mechling, 2010).
In today’s competitive business climate, managers are facing a series of business challenges that are driving them to restructure the way they perform (Dayal et al., 2009). As managers face increasing globalization and the impact of strong market competition, it is important to have a well-developed decision-making process in place because with better decision processes, they can make targeted analysis (Berthold et al., 2010).
Unsuccessful managerial decisions have become a global issue because decision failures can have a negative effect on a firm’s competitiveness, performance, and business expansion (Dayal et al., 2009; Hocevar & Jaklič, 2010; Lönnqvist & Pirttimäki, 2006; Popovič et al., 2009).
Since, there is a need to make critical business decision quickly; organizations need analytical solutions that support smarter decision- making (Hocevar & Jaklič, 2010; Lönnqvist & Pirttimäki, 2006; Schwarz, 2009). Several studies indicate that information technology (IT) affects organizational characteristics and outcome which can create a competitive advantage for the organization. As a result, management spends billions of dollars implementing and maintaining information technology to improve decision-making (Dayal et al., 2009; Popovič et al., 2010; Jitpaiboon & Patel, 2015). Many analytical tools or technologies have emerged in the last decade to help manage business information (Liu & Shi, 2015). One technology of growing interest for addressing this challenge is business intelligence (BI).
BI is a rapidly developing technology that is widely used in many organizations to turn data into useful information and distribute this information when needed. BI systems support decision making on all levels of management (Olszak & Ziemba, 2007). Many managers believe that BI systems will create a much higher value for the organization. As a result, BI has become an important technology for many organizations to improve their decision making process. The tools are useful for analyzing a large amount of data. (Ghazanfari, Rouhani, Jafari, & Taghavifard, 2009). However, not all BI initiatives have fulfilled management expectations (Isik, Jones, & Sidorova, 2011).
Although, in the last decade, the technology industry has uncovered several ways to improve decisions, decision makers in the typical organization struggle to make successful critical business decisions. While large amount of data is being stored only a fraction of that data becomes business intelligence (Lönnqvist & Pirttimäki, 2006; Negash & Gray, 2008; Popovič et al., 2010). Decision makers have to deal with vast accumulation of data and poor data quality. (Stefan, 2009; Jourdan, Rainer, & Marshall, 2008). Therefore, it is important that organizational managers know how to use technology to share, manage, and increase the level of knowledge (Hocevar & Jaklič, 2010).