Organizational Effects on BDA Adoption Outcomes in U.S. Public Sector Organizations

Abstract

Despite the benefits of big data analytics, many organizations are still being challenged to create enough value from their big data adoptions to offset the cost of the adoption. This problem is concerning for public sector organizations who operate with unique constraints and are less able to afford failed big data efforts. Prior research has found that organizational factors have the ability to influence adoption outcomes; however, there is a gap in the existing understanding of how and why organizational factors influence these projects in public sector organizations. Prior research has postulated that public sector managers are delaying potentially beneficial big data adoptions due to this uncertainty. This qualitative case study was designed to explore how and why organizational factors influence big data analytics in public sector organizations through an in–depth examination of such an implementation in state–level agencies in the Commonwealth of Virginia. The data collected included publicly available archival records and semi–structured interviews with eight subject matter experts from various commonwealth agencies, commonwealth–contracted external consultants, and members of academia with whom the commonwealth had collaborated on state programs. Thematic, network, and content analysis of the data revealed four key findings: (a) the organizational factors influencing big data analytics adoption outcomes are multifaceted and interrelated, (b) the management construct impacts existing human capital capacity, (c) processes and procedures enable value creation, and (d) the magnitude and direction of organizational factor influence vectors are time–mediated.