Paper Number
ECIS2025-1996
Paper Type
CRP
Abstract
The rise of data products significantly impacts enterprise-wide data management. However, existing research predominantly emphasizes the data usage perspective, largely overlooking the provision perspective and the need for type-specific data product management. Drawing on information logistics as a conceptual foundation, this research integrates both data usage and provision perspectives. Through semi-structured interviews and an empirical assessment of 19 real-world data products from multiple organizations, we identify three distinct types: consolidating data products, centralized analytical data products, and decentralized analytical data products. The study also offers tailored, type-specific management approaches aligned with the unique provision and usage characteristics of each data product type. Advancing theoretical understanding by linking data provision and usage perspectives further emphasizes the importance of type-specific management approaches. Ultimately, the study provides actionable insights and a structured foundation for organizations to design and enhance their data product management strategies within the context of enterprise-wide data management.
Recommended Citation
Hackl, Tobias and Winter, Robert, "Managing types of data products in information logistic networks" (2025). ECIS 2025 Proceedings. 6.
https://aisel.aisnet.org/ecis2025/bus_analytics/bus_analytics/6
Managing types of data products in information logistic networks
The rise of data products significantly impacts enterprise-wide data management. However, existing research predominantly emphasizes the data usage perspective, largely overlooking the provision perspective and the need for type-specific data product management. Drawing on information logistics as a conceptual foundation, this research integrates both data usage and provision perspectives. Through semi-structured interviews and an empirical assessment of 19 real-world data products from multiple organizations, we identify three distinct types: consolidating data products, centralized analytical data products, and decentralized analytical data products. The study also offers tailored, type-specific management approaches aligned with the unique provision and usage characteristics of each data product type. Advancing theoretical understanding by linking data provision and usage perspectives further emphasizes the importance of type-specific management approaches. Ultimately, the study provides actionable insights and a structured foundation for organizations to design and enhance their data product management strategies within the context of enterprise-wide data management.
When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.