Transforming Traditional Business Models through Advanced Analytics and Data-Driven Decision Making

Abstract

The rising access to big data and sophisticated analytics tools has changed the nature of 
designing and transforming the business models of organizations in significant ways. The 
more conservative business models with a heavy reliance on experience-based decision 
making and fixed value propositions are proving to be less and less appropriate in highly 
dynamic and competitive markets. The advanced analytics and data-driven decision-making 
role of transforming traditional business models is examined in this study. The study seeks 
to investigate how analytics capabilities can influence the quality of strategic decisions, 
operational performance, creation of customer values, and innovation performance. A 
quantitative research approach was employed, utilizing survey data collected from 342 
managers and analytics professionals across manufacturing, retail, and service sectors. 
Statistical analyses, including descriptive statistics, correlation analysis, and multiple 
regression, were applied to assess the relationships among analytics adoption, decision
making effectiveness, and business model transformation. The results reveal a strong 
positive relationship between advanced analytics maturity and business model innovation, 
particularly in revenue diversification, customer personalization, and cost optimization. 
Predictive and prescriptive analytics were found to significantly enhance strategic agility 
and decision accuracy. The research comes to a conclusion that analytics-based decision
making is an essential facilitator of business model sustainability change instead of being a 
technological improvement. The results present empirical data on why analytics plays a 
strategic role in redefining value creation and capture mechanisms and combine their 
theoretical values with practical implications to organizations seeking to undergo digital 
transformation.