Adoption of Big Data Analytics for Strategic Decision Making in a Technology Organization: A Qualitative Study
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Authors
Pillutla, Sreenu
Issue Date
2025-12
Type
Dissertation
Language
en
Keywords
Big Data Analytics , Strategic Decision-Making , Technology Organization , Business, Engineering, Science, & Technological Innovation
Alternative Title
Abstract
Big data analytics involves substantial data volumes and analysis of big datasets using statistical methods to uncover valuable insights. The problem addressed in this study was that organizational constraints create hurdles to the adoption of big data analytics for strategic decision-making, thereby decreasing the competitive edge and negatively impacting performance. Challenges exist across organizations, industry sectors, and countries in adopting big data analytics for strategic choices. The purpose of this qualitative exploratory study was to identify the organizational constraints that impact the adoption of big data analytics for strategic decision-making and to investigate how these impediments can be mitigated to achieve performance goals and gain a competitive advantage at a technology company. The theory of constraints framework was chosen to drive the research study. The research methodology that guided this study was a qualitative case study design. Snowball sampling was used to select 17 leaders at a technology company. Semi-structured interviews and focus groups were used to gather the data, followed by member checking. The instruments and participants in the study helped ensure triangulation and saturation. Thematic analysis was performed using manual coding and NVivo 14 software to generate themes. Results showed that various organizational constraints impede the adoption of big data analytics, including a lack of leadership support, organizational culture, data fragmentation created by internal groups and acquisitions, inadequate resource allocation, strategic prioritization, and regulatory and privacy challenges. Mitigation conditions included leadership commitment, data and tool consolidation, and strategic resource allocation. Competitive advantage can be achieved by optimizing product-market fit and leveraging insights from the customer journey. The study's primary contribution was to demonstrate that the constraints to big data analytics adoption identified by a product group at a technology company were fundamentally organizational rather than technical, with leadership support and cultural transformation representing the critical path to achieving a competitive advantage. The research offered recommendations that organizations require leadership support, cultural transformation, and skilled resources to drive data-driven decisions and achieve their performance goals. The study suggested that future research should examine quantitative approaches across broader populations, different geographical locations, and integration with artificial intelligence technologies.