Influence of Data Analytics Adoption on The Effectiveness of Strategic Decision-Making in Small and Medium Enterprises in Nairobi County, Kenya

Purpose: This study investigated the influence of data analytics adoption on the effectiveness of strategic decision-making among Small and Medium Enterprises (SMEs) in Nairobi County. Methodology: A descriptive correlational research design was employed, and data was collected from 89 SME managers through structured questionnaires scored on a five-point Likert scale. Analysis was conducted using SPSS, generating descriptive, correlation, regression, and ANOVA results, presented through tables. Findings: Data analytics showed a positive but weak correlation (r = .0.058, p = .918). The regression models explained only minimal variance, with R² values ranging from .001 to .043, confirming that data analytics adoption, in isolation, does not drive effective strategic decision-making in the sampled SMEs. The study concludes that while data analytics adoption resources are available within many SMEs, they remain underutilized and insufficiently aligned with strategic objectives. Investments are often directed at infrastructure without ensuring integration, user competence, or strategic governance. As a result, data analytics adoption has yet to translate into measurable improvements in decision quality. Unique Contribution to Theory, Policy and Practice: The study recommends that SMEs emphasize alignment of data analytics adoption with business priorities, strengthen user training, and adopt structured evaluation frameworks to link data analytics adoption spending to decision outcomes. Future research should explore mediating factors such as organizational culture, managerial competence, and industry dynamics, which may condition the relationship between data analytics adoption and decision-making effectiveness.