A Hesitant Fuzzy SWARA Methodology for Big Data Maturity Assessment

Abstract

Big data analytics empowers organizations to make faster, more accurate, and cost-effective decisions compared to their competitors. While the potential benefits of big data are widely recognized, effective integration into long-term corporate planning remains a challenge. This study evaluated the big data maturity of a company operating in the food and retail sectors using the DELTTA (data, enterprise, leadership, targets, technology, and analysts) model. Given the complexity of big data maturity assessment, the study incorporated hesitant fuzzy (HF) numbers into the Stepwise Weight Assessment Ratio Analysis (SWARA) method to determine the relative importance of each maturity dimension. Subsequently, expert responses to the Big Data Readiness Assessment Survey were analyzed to evaluate the company’s maturity level across all dimensions. The Hesitant Fuzzy SWARA application revealed ‘data’ as the most critical dimension, while ‘enterprise’ was identified as the least important. Furthermore, survey findings highlighted the company’s strength lies in its ‘Analysts and Data Scientists,’ offering a notable advantage in big data management. Based on these insights, strategic recommendations were formulated to strengthen the company’s big data capabilities, streamline operational processes, and enhance decision-making efficiency.