Kalra, J;
Mills, G;
Papadonikolaki, E;
(2021)
Building data analytics capability to increase information processing capacity: The case of a professional service firm.
In:
Proceedings of the 28th International Annual EurOMA Conference 2021.
European Operations Management Association (EurOMA): Berlin, Germany (online).
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Abstract
Supply chain literature has emphasised the importance of data analytics capability in driving supply chain outcomes. Additionally, along with knowledge and professional judgement, providing data-driven analyses has become a critical component of professional service operations. However, there remains little understanding of how organisations build data analytics capability to reduce supply network uncertainty. A single case study of a professional service firm revealed analytics capability to be a combination of three capabilities, each with its distinct micro-foundations. We argue that the development of analytics capability requires the interaction of individual abilities and knowledge-bases with social and technical interorganisational processes and structures.
| Type: | Proceedings paper |
|---|---|
| Title: | Building data analytics capability to increase information processing capacity: The case of a professional service firm |
| Event: | European Operations Management Association (EurOMA) |
| Dates: | 05 July 2021 - 07 July 2021 |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | http://www.euroma-online.org/events/euroma-annual-... |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions. |
| Keywords: | Organisational information processing theory; data analytics capability; microfoundations; professional service operations |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10132590 |
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