Unlocking the real business value of big data analytics: from insight to firm performance

Today, we are living in a society where information technology (IT) is seen as integrant part of firm’s strategy in any business environment. Considered the next frontier of innovation, big data analytics (BDA) applications can potentially contribute to firm performance and create competitive advantage. Although there is an extant IT Value research, specific BDA Value research is underdeveloped. In addition, with the ever-increasing investment in BDA, it is essential to provide a valid and reliable measure to capture the business value that arises from the usage of this type of technologies. Grounded in strategic management theories (Knowledge-based View and Dynamic Capabilities), this dissertation aims to better understand the determinants of BDA value and impact on firm performance. By providing an integrative research model with three perspectives (Knowledge, Capabilities and Data), we intend to extend BDA value research and offer support to executives in their IT strategies. Following a positivist approach and hypothetic-deductive research methodology, the models were conceptualized and were empirically validated by qualitative and quantitative instruments in European and American firms, using Partial Least Squares (PLS) techniques for analysis. Findings demonstrate although empirical research on BDA value has been increasing in the latest years, empirical literature that examines how business value can be extracted is limited and has much room for improvement. Considering a capability point of view, factors related with BDA value sustainability such as BDA use, dynamic capabilities, agility, strategic alignment and environmental volatility are the most relevant to achieve competitive advantage when compared with managerial and operational variables. In this regard, a top-down approach is encouraged. From the knowledge perspective, external knowledge management is particularly relevant in the creation of BDA value for European firms. Also, BDA applications support a better internal and external knowledge management facilitating the creation of organizational agility in several levels. Agility has a positive mediation effect between internal and external knowledge management and firm performance. On the other side, sharing knowledge with partners in some cases can harm the creation of business value, specifically in core business areas such as Production and Operations or Product and Service enhancement. In the latest years, big data has been increasing exponentially with the emergence of IoT. Hence, it is relevant to assess the impact of both types of big data in firms. In this sense, from a data spectrum, data quality moderated by the level of sophistication on business processes has positive influence in the creation of BDA capabilities. On the contrary, it impacts negatively in the achievement of IoT capabilities. Due to the specificities of IoT big data and early stage of adoption, it is a challenge to ensure a reasonable level of data quality, which compromises the creation of IoT capabilities and consequent competitive advantage. There are no significant differences between U.S and EU firms in the creation of business value through BDA and IoT technologies.