Big data resource orchestration for analytics capability maturity
: a comparison of traditional and digital financial services firms

  • Pamela McCloskey

Student thesis: Doctoral ThesisDoctor of Philosophy


Big data analytics capabilities (BDAC) have been linked to firm performance in many and varied industries. A body of literature has emerged revealing that a synergistic bundling of resources is required, to develop a BDAC that improves firm performance directly, or indirectly via the strengthening of organisational capabilities. Despite the growing body of literature on the strategic role of BDAC, scant attention is paid to whether there are differences in the resources that underpin BDAC across firms, and how these resources should be orchestrated to create a BDAC. To address these questions, the core definition, and constituent components of BDAC require further clarification. There is also a lack of empirical studies examining BDAC in disrupted industries such as financial services, where it is necessary to pay more attention to the role of context. To address these gaps, this study compares the role of BDAC in the retail financial services industry, juxtaposing long established traditional firms with the new digital firms. A comparative case study methodology is used, comparing two traditional financial services firms with two digital ‘disruptor’ firms, in their development and deployment of BDAC. This study makes four contributions. Firstly, it makes a theoretical contribution by showing resource heterogeneity and path dependency in BDAC development. This leads to the second theoretical contribution which is to clarify the concept of BDAC by showing that there is not a singular BDAC, but rather different levels of maturity, which result in different strategic outcomes. A third, practitioner contribution is made with the proposal of a BDAC maturity evaluation framework. Finally, an empirical contribution is made by comparing BDAC development and deployment in two firm types, traditional and digital, in a key disrupted industry.

Thesis is embargoed until 31 July 2026.

Date of AwardJul 2024
Original languageEnglish
Awarding Institution
  • Queen's University Belfast
SponsorsNorthern Ireland Department for the Economy
SupervisorByron Graham (Supervisor), Michael Aldous (Supervisor) & Joanne Murphy (Supervisor)


  • Big data analytics
  • resource-based view
  • resource orchestration
  • dynamic capabilities
  • analytics capability maturity
  • competitive advantage
  • financial services
  • incumbents
  • new entrants

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