Big data for big pharma

Abstract

Purpose Big pharma, which comprise the most important companies in the pharmaceutical sector, are ambidextrous organizations by nature. Big data can heavily influence this characteristic by simultaneously requiring adequate business process management. In fact, the impact of big data on business process management can assist big pharma in increasing process efficiency (which is related to the research and development pipeline) and process efficacy (related to product portfolio management). The purpose of this paper is to investigate this possibility and opportunity. Design/methodology/approach In the absence of specific scientific studies, as indicated by a review of the existing literature, the authors have adopted a grounded theory approach. This research has observed multiple cases (the 15 most important big pharma companies worldwide) through an electronic survey conducted on secondary data. The study has allowed the generation of a theoretical framework based on the (direct) relationship between knowledge process standardization (as the dependent variable) and big data (as the independent variable) in organizations oriented toward ambidexterity, such as big pharma in the specific scope of this research. Findings As big data utilization becomes widespread along the pipeline (or even along the value chain/supply chain), business process management increasingly uses (or tends to use) standardization, adopting process standardization as the main coordination mechanism to manage big knowledge. This theory is even more true when considering the moderating role of ambidexterity. An enterprise oriented toward structural ambidexterity (such as big pharma) that uses big data will require increased process standardization to manage big knowledge. Alternatively, an enterprise oriented toward contextual ambidexterity that uses big data will require increased output standardization. Originality/value Based on an analytical literature review, no research to date has focused strict attention on the influence that big data can have on business process management to improve the natural ambidexterity of big pharma. The main unique feature of this research relies on this point. The main value of the research originates from the theoretical framework reconstructed by grounded theory, which constitutes a powerful strategic tool to support executives and managers of big pharma in organizing business process management for their ambidextrous organizations using big data.