A Critical Analysis of Skills, Infrastructure and Organizational Capabilities Required for Big Data Adoption

Abstract

Big data has become an increasingly important asset for organizations across industries. However, adopting and leveraging big data analytics requires significant investments in skills, infrastructure, and organizational capabilities. This paper provides a critical analysis of the key factors’ organizations must consider when embarking on big data initiatives. A framework is presented delineating the core skills, infrastructure, and capabilities needed at individual, team, and organizational levels. Challenges and critical success factors are discussed through an industry-agnostic lens. Practical recommendations are provided for developing the proper foundations to extract value from big data. Realizing the potential of big data necessitates developing complementary strengths across the skills, technology infrastructure, and organizational culture. At the individual level, both technical expertise and business acumen are needed across roles. Data science skills must expand beyond specialized analysts to widen business literacy. Cross-functional teams are needed combining technical talent and business leadership. Leadership must foster data-driven decision making and governance. Absence of organizational readiness will constrain returns on analytics investments. Holistic assessments of existing maturity provide a gap analysis for shaping adoption roadmaps. Targeted pilots demonstrate value before enterprise-wide rollout. Talent pipelines, retention strategies and liaisons help overcome scarce analytics resources. Seamless flows of insights into operations and strategic planning enable widespread impact. With deliberate planning and change management, organizations can transform big data analytics into competitive differentiation.