Capabilities for Big Data: An Empirical Study in a Global Pharmaceutical Company

Grishikashvili, Ketevani (2019). Capabilities for Big Data: An Empirical Study in a Global Pharmaceutical Company. PhD thesis The Open University.

DOI: https://doi.org/10.21954/ou.ro.00010a5a

Abstract

The increasing availability of large quantities of digital data (Big Data) and advanced analytic tools is driving many industries to change their practices. Currently there are limited theoretically informed, in depth empirical studies of the processes and activities that needed to leverage Big Data strategically. This research is a response to calls by international scholars for more in depth and theoretically informed studies of on Big Data (e.g. Brynjolfsson et al., 2011; McAfee et al., 2012; Wamba et al., 2015; Braganza et al., 2017; Mikalef et al., 2017).

The study frames Big Data as a new resource and adopts the Resource Based View (RBV) and the Dynamic Capabilities (DC) perspective in order to explore the enhancement of existing capabilities and development of new capabilities required to leverage this new resource. The empirical context of this study is a global pharmaceutical company. Employing a qualitative in-depth case-study approach, this research investigates why a Multinational Corporation (MNC) in the pharmaceutical industry adopted Big Data adoption and how it identified and developed capabilities for this new resource. Data from 24 in-depth interviews and observations of Europe, the Middle East and Africa (EMEA) and Global managers in two project teams were analysed and synthesised using thematic analysis methods.

The findings from this study show that the use of Big Data required new and enhanced capabilities that were developed through the action of dynamic capabilities, which operated as mediators between existing capabilities and the new and enhanced capabilities. Although some elements of these dynamic capabilities were embedded in the organisational processes, the activities of senior managers played a crucial role in their development and use. Further, the findings show that the organisation’s cultural transformation was critical for the operation of the dynamic capabilities identified and the new and enhanced Big Data capabilities. In the case study company the development of a Big Data capabilities was found to be an incremental, extended process.

The study makes a number of contributions. It provides an in-depth case study of Big Data preparation in the specific context of a MNC pharmaceutical company that is of value to both academics and practitioners. It provides a theoretically based and empirically validated model of the development of capabilities associated with Big Data adoption. Finally, it makes a contribution to academic theory by contributing to the ongoing discussion in the academic literature of the utility of the concept of Dynamic Capabilities.

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