Effect of MIS-Enabled Big Data Analytics on Innovation Performance of BUA Cement
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Abstract
BUA Cement, a leading Nigerian manufacturer, faces challenges in leveraging its Management Information Systems (MIS) for advanced big data analytics, relying predominantly on descriptive data rather than predictive insights, which hampers innovation. The study aimed to examine the effect of MIS-enabled big data analytics specifically data integration and predictive insight on product and process innovation at BUA Cement. A cross-sectional survey design was employed, with data collected from 370 employees using questionnaires, and analyzed via multiple regression in SPSS v27. Findings revealed that data integration significantly influences product innovation (β = 0.589, p < 0.001), explaining 34.7% of its variance. Similarly, predictive insight significantly affects process innovation (β = 0.712, p < 0.001), accounting for 50.8% of its variance. This confirms that MIS-enabled big data analytics drives innovation performance in heavy manufacturing. It is recommended that BUA Cement upgrade its MIS for seamless cross-functional data integration and invest in predictive analytics tools for proactive process optimization. Academically, the study contributed to dynamic capabilities theory by linking data integration to sensing capabilities and predictive insight to seizing capabilities within an emerging economy context. Practically, it provided a strategic roadmap for industrial firms in Nigeria and similar economies to transition from traditional operations to data-driven innovation, thereby enhancing competitiveness, operational efficiency, and sustainability in the global market.
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