موفقیت هوش کسب و کار(هوش تجاری) : نقش قابلیت های BI و محیط تصمیم گیری

This study examines the role of the decision environment in how well business intelligence (BI) capabilities are leveraged for achieving BI success. We examine the decision environment in terms of types of decisions made and the information processing needs of the organization. Findings suggest that technological capabilities such as data quality, user access and integration of BI with other systems are necessary for BI success regardless of decision environment. However, decision environment does influence the relationship between BI success and capabilities such as the extent to which BI supports flexibility and risk in decision making

Business intelligence (BI) continues to be a top priority for many organizations, and the promises of BI are rapidly attracting many more proponents [29]. Organizations are grappling to make sense of the rapidly increasing volume, velocity, and variety of data generated by both internal and external resources. Consequently, BI has become a critical foundation of competition for many organizations and has consistently been ranked among the top two agenda items of senior executives over the last several years [57]. Business intelligence continuously ranks as one of the most widely searched terms on gartner.com [80] and remains a topic of interest in academic and practitioner research [74]. One overarching theme that has surfaced in the research is that the BI used within an organization must suit the problem space, or decision environment, within which it is used and that this match is key to BI success [20]. However, practitioner-oriented publications and academic research suggest that this success has not yet been realized in many organizations and that users do not necessarily make the connection between their BI capabilities and the decision environment [42]. BI capabilities are critical functions that help an organization improve both its adaptation to change and its performance [92]. Although BI capabilities have been studied from organizational [e.g., 27] and technological [e.g., 58] perspectives, some organizations fail to achieve BI success [50]. This may be because the relationship between the decision environment and BI capabilities has remained largely unexamined. Examining this relationship is important, however, because the primary purpose of BI is to support decision making in organizations [15]. The purpose of this paper is to provide a better understanding of BI success by examining the impact of BI capabilities on BI success in the presence of different decision environments. Specifically, the paper seeks to address the following research questions:

In this study, we examined the relationship between technological and organizational BI capabilities, decision environment characteristics and BI success. The results of the study paint an insightful yet occasionally surprising picture of the factors influencing BI success. Although some BI capabilities are found to be important for BI success regardless of the decision environment, other capabilities’ effects are moderated by the decision environment's characteristics. Still other BI capabilities, such as data quality, appear to have reached an acceptable level, and further improvements to such capabilities may not translate into greater BI success. These findings have important implications for both researchers and practitioners. From the research point of view, this study brings the BI research and the information processing literature together. While this study focused only on two types of decision environments, future research is necessary to incorporate the additional decision environments in the nine cells of the Gorry and Scott Morton framework. Including intermediary decision environments could provide more insight into where the inflection points are located. For example, at what point along the continuum of decision environments do technological capabilities enhance BI success the most? Future research could also draw on a sample taken from specifically targeted organizations to allow more in-depth comparisons of decision environments and information requirements from applications in different business sectors. While this study focused on decision environments, future research could incorporate other factors, such as decision makers’ roles, preferences and interests in organizational decision making or decision hierarchies and networks to examine decision propagation and consensus in an organization. From the practitioner's point of view, this study suggests that utilizing the right BI capabilities within the proper decision environment is important to allow an organization to realize maximum benefits from its BI investment. While user access and seamless integration with other systems is critical regardless of the decision environment, as organizations shift to using BI in less structured decision environments, they should pay additional attention to ensuring the adequate flexibility of their BI applications.