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International Journal of Research and Scientific Innovation (IJRSI)

Integrating Strategic Leadership, Data Analytics Capability, and Geopolitical Awareness for Strategic Decision-Making: A Conceptual Framework

byDr.V.Anuradha; Dr.G.Ambedkar

Published June 5, 2026  •  Vol. 13, Issue 5, pp. 1774–1796Open Access
DOI: 10.51244/IJRSI.2026.1305000159

Abstract

There was a time when organizations had to deal with uncertainty rising in the markets, regulations and geopolitics but now with an additional pressure of increased data analytics usage on the inside of the firm, decision-making has become more challenging. Previous studies have focused on strategic leadership, strategic decision making based on data, and geopolitical uncertainty individually. Little work, however, has tried to explain the interplay of these three dimensions under conditions of uncertainty and at a high level via management decisions in their day to day work. This paper builds a conceptual framework which combines three specific variables namely strategic leadership, data analytics capability and geopolitical awareness in order to highlight the inter-dependency between them to support strategic decision making. The study has a literature review approach which has been structured with respect to analyzing the peer-reviewed studies of strategic leadership, business analytics, uncertainty management, strategic agility and organizational resilience. The literature is synthesized thematically and the constructs and relationships identified from the review and gaps are noted: The constructs and relationships identified from the literature review are synthesized thematically to identify the key constructs, relationships and gaps that inform the proposed model. The proposed model put together explains the effect of strategic leadership on the organizations' own interpretation of the evidence, strategic analysis of geopolitical (geo) signals, alignment of strategic priorities, and uncertainty management. Data analytics capability helps increase decision accuracy and evidence-based decision making and geopolitical awareness will enable decision-makers to understand external risks which might not be fully reflected on historical data. The model connects these inputs with the quality of decision-making, the effectiveness of the organization and resilience in strategic decision making. The leadership judgement, the ability to do some analysis and the skill to understand the geopolitical considerations showed up as three constituent parts of a decision making process in the study and should be packaged together in a management literature approach. It also suggests measurable leadership adaptability criteria and analytical capabilities, uncertainty management, the Quality of decision and resilience indicators. The proposed empirical test of the model can be quantitative, qualitative and/or mixed methods based studies in different industries and geopolitical settings.

Keywords: Strategic leadership; data analytics capability; geopolitical awareness; strategic decision-making; uncertainty management; organizational resilience.

JournalInternational Journal of Research and Scientific Innovation (IJRSI)
ISSN2321-2705
Volume / IssueVolume 13, Issue 5
Pages1774–1796
Publication dateJune 5, 2026
DOI10.51244/IJRSI.2026.1305000159
PublisherRSIS International
LicenseOpen Access

How to cite this article

Dr.V.Anuradha, & Dr.G.Ambedkar (2026). Integrating Strategic Leadership, Data Analytics Capability, and Geopolitical Awareness for Strategic Decision-Making: A Conceptual Framework. International Journal of Research and Scientific Innovation (IJRSI), 13(5), 1774-1796. https://doi.org/10.51244/IJRSI.2026.1305000159

BibTeX

@article{DrVAnuradha2026,
  title   = {Integrating Strategic Leadership, Data Analytics Capability, and Geopolitical Awareness for Strategic Decision-Making: A Conceptual Framework},
  author  = {Dr.V.Anuradha and Dr.G.Ambedkar},
  journal = {International Journal of Research and Scientific Innovation (IJRSI)},
  volume  = {13},
  number  = {5},
  pages   = {1774--1796},
  year    = {2026},
  doi     = {10.51244/IJRSI.2026.1305000159},
  publisher = {RSIS International}
}