Paper Number
1208
Paper Type
Short Paper
Abstract
While the adoption and implementation of business analytics (BA) has received extensive focus, research on operationalisation remains scarce. BA operationalisation requires the integration of analytical outputs and processes into core business operations, enabling stakeholders to consume insights in a timely fashion and at the right point-of-need. Drawing from resource orchestration (RO) theory, we used expert interviews to examine the following research question: How do organisations orchestrate their resources to operationalise analytics? We develop a framework that explains how structuring, bundling, and leveraging BA resources such as T-shaped skills and teams, data stack, and computational governance enable analytics operationalisation by embedding analytical outputs in business operations and reengineering BA value workflow, thereby making BA scalable and sustainable. Our study contributes to the BA literature by identifying the key features of operationalising analytics, which are critical to advancing BA as a means to competitive advantage.
Recommended Citation
Shrivastava, Abhinav; Naseer, Humza; Black, Stuart; Boo, Yee Ling; Kam, Booi; and Ong, Kok-Leong, "Operationalising Analytics Through Resource Orchestration — An Empirical Examination" (2024). ECIS 2024 Proceedings. 2.
https://aisel.aisnet.org/ecis2024/track07_busanalytics/track07_busanalytics/2
Operationalising Analytics Through Resource Orchestration — An Empirical Examination
While the adoption and implementation of business analytics (BA) has received extensive focus, research on operationalisation remains scarce. BA operationalisation requires the integration of analytical outputs and processes into core business operations, enabling stakeholders to consume insights in a timely fashion and at the right point-of-need. Drawing from resource orchestration (RO) theory, we used expert interviews to examine the following research question: How do organisations orchestrate their resources to operationalise analytics? We develop a framework that explains how structuring, bundling, and leveraging BA resources such as T-shaped skills and teams, data stack, and computational governance enable analytics operationalisation by embedding analytical outputs in business operations and reengineering BA value workflow, thereby making BA scalable and sustainable. Our study contributes to the BA literature by identifying the key features of operationalising analytics, which are critical to advancing BA as a means to competitive advantage.
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