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Description
This study investigates the relationship between data analytics adoption and organisational performance, with a particular focus on the moderating role of industry-level gender composition. Prior research suggests that analytics rarely has a direct impact on business performance, but instead, it creates the appropriate conditions that lead to value realisation. Considering this, this paper examines how these conditions are shaped by the characteristics of the workforce and organisational context. The analysis is based on Dynamic Capability Theory and the Resource-based View and conceptualises analytics as an organisational capability and gender composition as an attribute which influences the decision-making processes within an organisation. For testing the relationship between the constructs, a panel data approach using sector-level data across multiple European countries over an extended period of time is employed. Analytics adoption is proxied by the implementation of enterprise systems and the use of data analytics and artificial intelligence to capture the extent to which organisations develop data integration capabilities. Organisational performance is measured through financial and operational indicators, and gender composition through the proportion of female representation within sectors and leadership roles. The model also includes control variables such as industry size and human capital, and it accounts for the fact that analytics impact is not immediate; therefore, lagged independent variables are added to mitigate reverse causality concerns. The findings mirror the results of previous research demonstrating that analytics' impact on organisational performance is conditioned by intermediate organisational mechanisms. Moreover, the findings contribute to a comprehensive understanding of the relationship between analytics and performance by integrating demographic and organisational factors into capability-based explanations. This study highlights the importance of fostering an inclusive and diverse organisational environment.
Keywords: data analytics, data-driven decision-making, organisational performance, gender parity
