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Abstract
Organisations are increasingly practising Business analytics (BA) to make data-driven business decisions amidst environmental complexities and fierce global competition. However, organisations find it challenging to operationalise BA outputs (such as analytical models, reports, and visualization) primarily due to a lack of (a) integrated technology, (b) collaboration and (c) governance. These factors inhibit organisations’ ability to make data-driven decisions in an agile manner. Embedded analytics, an emerging BA practice, has the potential to address these issues by integrating BA outputs into business applications and workflows, thereby promoting the culture of data-driven decision-making. In this research-in-progress paper, we integrate the diverse areas of literature on BA, embedded analytics, and dynamic capabilities theory and propose a research model that links embedded analytics to decision-making agility through the development of dynamic capabilities. The details of the framework highlight how organisations can get maximum value from data and analytics initiatives through operationalisation of BA outputs.
Recommended Citation
Shrivastava, Abhinav; Naseer, Humza; Kam, Booi; Boo, Yee Ling; and Ong, Kok-Leong, "Operationalising Analytics for Action: A Conceptual Framework Linking Embedded Analytics with Decision-Making Agility" (2023). ECIS 2023 Research-in-Progress Papers. 4.
https://aisel.aisnet.org/ecis2023_rip/4