Abstract
In this study, we explore the interplay between predictive, descriptive, and prescriptive analytics, mediated by decisionmaking processes, and their influence on organizational performance. Our research employs a non-probabilistic sampling method, specifically the snowball sampling technique, with a sample size of 120.The independent variables considered encompass descriptive analytics, prescriptive analytics, and predictive analytics which collectively serve as the analytical backbone shaping decision-making within organizations. Decision-making, in turn, acts as a mediating variable, channelling the impact of analytics towards organizational performance. By scrutinizing the intricate interplay between analytics and decision-making, this research aims to elucidate the extent to which decision-making influences organizational performance, thereby shedding light on the pivotal role analytics play in modern organizational dynamics. The results and conclusions drawn from this research endeavour are anticipated to make a substantial and meaningful contribution to the understanding of how analytics-driven decision-making processes drive organizational effectiveness and efficiency in today’s complex business landscape, with implications for strategic planning, resource allocation, and performance optimization.
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