TY - JOUR
T1 - Tension in the Data Environment: How Organisations Can Meet the Challenge
AU - Meadows, Maureen
AU - Merendino, Alessandro
AU - Dibb, Sally
AU - Garcia-Perez, Alexeis
AU - Hinton, Matthew
AU - Papagiannidis, Savvas
AU - Pappas, Ilias
AU - Wang, Huamao
PY - 2022/2/1
Y1 - 2022/2/1
N2 - Big Data is becoming ubiquitous - widely applied across organisations, industry sectors and society. However, the opportunities and risks it presents are not yet fully understood. In this paper we identify and explore the tensions that Big Data can create at multiple levels, focusing on the need for organisations to meet the challenges that can arise. We draw on insights from twelve papers published in the Special Issue of Technological Forecasting & Social Change entitled “Tension in the Data Environment: Can Organisations Meet the Challenge?” in order to build a ‘Multi-Layer Tensions Model’ that highlights key pressures and challenges in the BD environment. We find evidence of tensions of three types, which we summarise as “Organisational Learning”, “Organisational Leadership” and “Societal” tensions. We contribute, first, by identifying and developing a nuanced understanding of the tensions faced in the Big Data environment; and second, by elaborating on the capabilities that can be developed and the actions taken to maximise the benefits of Big Data. We end with a “Learning, Leading, Linking” framework, which points to implications for practice and a future research agenda.
AB - Big Data is becoming ubiquitous - widely applied across organisations, industry sectors and society. However, the opportunities and risks it presents are not yet fully understood. In this paper we identify and explore the tensions that Big Data can create at multiple levels, focusing on the need for organisations to meet the challenges that can arise. We draw on insights from twelve papers published in the Special Issue of Technological Forecasting & Social Change entitled “Tension in the Data Environment: Can Organisations Meet the Challenge?” in order to build a ‘Multi-Layer Tensions Model’ that highlights key pressures and challenges in the BD environment. We find evidence of tensions of three types, which we summarise as “Organisational Learning”, “Organisational Leadership” and “Societal” tensions. We contribute, first, by identifying and developing a nuanced understanding of the tensions faced in the Big Data environment; and second, by elaborating on the capabilities that can be developed and the actions taken to maximise the benefits of Big Data. We end with a “Learning, Leading, Linking” framework, which points to implications for practice and a future research agenda.
KW - big data
KW - tensions
KW - digital
KW - organisations
KW - society
KW - challenges
KW - Tensions
KW - Organisations
KW - Challenges
KW - Digital
KW - Big data
KW - Society
UR - https://www.sciencedirect.com/science/article/abs/pii/S0040162521007460?via%3Dihub
U2 - 10.1016/j.techfore.2021.121315
DO - 10.1016/j.techfore.2021.121315
M3 - Article
SN - 0040-1625
VL - 175
JO - Technological Forecasting and Social Change
JF - Technological Forecasting and Social Change
M1 - 121315
ER -