Big data analytics and competitive advantage : the strategic role of firm-specific knowledge

Purpose: While advances in big data analytics (BDA) provide valuable business insights and immense business value, many firms find it difficult to gain advantage from their BDA initiatives. Noting the strategic role of firm-specific knowledge, we develop a framework examining the relation between firm specificity of BDA knowledge and competitive advantage. We also examine the dynamic evolution of BDA capabilities and the associated knowledge management strategies. Design/methodology/approach: We review the resource-based view (RBV), capabilities life cycles and absorptive capacity perspectives along with the literature on BDA competitive advantage. Identifying two key BDA factors, application customization and data proprietorship, we develop a BDA competitive advantage framework. We also investigate the absorptive capacities employed by firms to advance their BDA capabilities. We use anecdotal cases to support our theoretical arguments. Findings: We propose that BDA solutions with vendor-based applications (noncustomized) and public data will not generate firm-specific knowledge and therefore not provide competitive advantage. In contrast, BDA solutions with custom applications and proprietary data will provide high-level firm-specific knowledge and potentially result in sustained competitive advantage. We further suggest the relevant absorptive capacities and the knowledge management strategies for BDA capability development. Practical implications: Our framework provides managers with insights into how to develop and enhance firm-specific knowledge from their BDA solutions to gain competitive advantage. Originality/value: Our study offers a new BDA firm-specific knowledge framework for competitive advantage.