Capabilities, use and benefits from business analytics in management control: The crucial role of organizational size and data science departments
High expectations are placed on business analytics (BA) for management control (MC) departments. However, empirical evidence on benefits from BA for MC departments is scarce and ambiguous. We thus examine whether and how the extent of BA capabilities (BAC) and the extent of BA use in MC departments are related to transactional, informational, strategic, and transformational benefits. Drawing on socio-technical systems and contingency theory, and analyzing survey data from 322 large German companies, we find that the extent of BAC is positively related to the extent of BA use, which in turn is positively related to the extent of the benefits described above. While large firms are usually assumed to benefit more from digital tools, we find tentative evidence that relatively larger firms within our large-firm sample, despite a higher extent of BA use, perceive fewer benefits from BA in their MC departments. This moderating association is, however, only marginally significant. The BA use–benefits link is weaker still when a dedicated data science department is present, an association that is statistically significant for informational benefits. Drawing on contingency theory, we interpret this as being consistent with data science departments displacing MC departments from core analytical tasks and thereby eroding MC's ownership of data insights and the benefits MC departments perceive from BA. We contribute to socio-technical systems theory by showing that BA benefits depend not only on capabilities and use but also on MC departments' meaningful ownership of data insights, and to contingency theory by identifying organizational size and the rise of data science departments as boundary conditions of the BA–benefits link in MC.
Authors
- Martin R. W. Hiebl (ORCID: https://orcid.org/0000-0003-2386-0938)
- Thomas W. Guenther (ORCID: https://orcid.org/0000-0002-9860-8668)
- Xenia Boerner
Institutions
- Johannes Kepler University of Linz (AT)
Publication Details
- Journal
- International Journal of Accounting Information Systems
- Published
- 2026-09-28
- DOI
- https://doi.org/10.1016/j.accinf.2026.100790
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.00