Data-driven organisation through the sociomateriality lens: towards an understanding of enablers and constraints

Abstract

A data-driven approach has become increasingly promoted as an important goal for organisations as it provides opportunities and triggers for actions relating to performance and competition. Organisations in all sectors, including education, are moving on a journey towards the goal of becoming a data-driven organisation, but this remains a significant challenge. However, as the amount of data continues to rise and be of importance in business and society, using analytical data to support decisions and actions has also become increasingly more acceptable than intuition and experience. This indicates the need for data-driven organisations in the data-driven era.

The dissertation discusses enablers and constraints and their impacts on the move and development towards becoming a data-driven organisation underpinning the sociomateriality lens, which to date, has not been investigated as the main focal area. Data for this study was collected using a face-to-face semi-structured interview and had to be gathered remotely using an online survey due to the COVID-19 restrictions in conducting fieldwork. The research investigation took place in a UK university as a research site that has been working to become more data-driven.

Drawing on the empirical evidence and analysis, two enablers and eight constraints, and their multi-faceted complex impacts were identified. The two enablers are (1) data insights underpinning decisions and performance and (2) data insights facilitating multiple perspectives for holistic understanding. The eight constraints are (1) the human element underpinning data insights but being ignored while implementing a more data informed approach, (2) data quality and data silos, (3) distrust in data and analysis credibility, (4) lack of harnessing multiple perspectives on data, (5) lack of human capability to engage with data, (6) emerging gap between data user, data provider, and implication of being data-driven, (7) differences in people’s perceptions of revealing the story in a data, and (8) diverse vision and attitudes of leaders/people alignment on being data-driven. These contribute to the theoretical model in this study. The proposed theoretical model demonstrates the following three aspects: the complex and dynamic movement of becoming a data-driven organisation, the sensitivity to those enablers and constraints, and the fragmentation among data users, data providers and technology (i.e., a data-driven approach). It is argued that the enablers and constraints, and their consequences need to be recognised. A full understanding of the organising and the dynamic interactions are, therefore, critical as an organisation moves on its journey to become data-driven.