Data Analytics for Sustainable Business: Practical Insights for Measuring and Growing Impact
Authors: Rahaman Md Mizanur , Gonee Manik Mia Md Tofayel , Rahman Noman Inshad , Islam Md Rashedul , Aziz Md Munna , Rahman Bhuiyan Mohammad Muzahidur , Das Kallol 
Published: December 2024

The current landscape indicates that sustainability is gaining traction as one of the core business strategies. The use of data analytics to monitor and improve sustainability measures in organizations has remained one of the most effective approaches. Thus, this study examines the impact of Big Data Analytics (BDA) capabilities on process eco-innovation and sustainability performance across industries. We focus on four core capabilities—information technology, personnel expertise, management, and BDA—and their role in achieving sustainability goals. Our results reveal that predictive analytics can significantly reduce carbon emissions by 15% over five years, with emissions projected to drop from 100 metric tons in 2024 to 65 metric tons by 2030. Additionally, energy consumption accounts for 33% of overall resource usage, followed by carbon emissions (33%), water usage (24%), and waste generation (10%). Comparative metrics indicate a 30-40% reduction in carbon emissions, water consumption, and waste generation after adopting sustainability practices, underscoring the importance of data-driven innovation. Our findings highlight the varying needs across industries: the financial sector demands real-time decision- making, healthcare focuses on cost optimization, and retail prioritizes customer satisfaction and operational efficiency. Furthermore, regulatory compliance and resource heterogeneity shape BDA adoption, influencing organizational performance. This study offers practical insights into how industries can align analytics with eco-innovation, driving sustainable growth and operational excellence. These results emphasize the transformative potential of predictive analytics in enhancing sustainability, making BDA a critical component of future industrial strategies. The current landscape indicates that sustainability is gaining traction as one of the core business strategies. The use of data analytics to monitor and improve sustainability measures in organizations has remained one of the most effective approaches. Thus, this study examines the impact of Big Data Analytics (BDA) capabilities on process eco-innovation and sustainability performance across industries. We focus on four core capabilities—information technology, personnel expertise, management, and BDA—and their role in achieving sustainability goals. Our results reveal that predictive analytics can significantly reduce carbon emissions by 15% over five years, with emissions projected to drop from 100 metric tons in 2024 to 65 metric tons by 2030. Additionally, energy consumption accounts for 33% of overall resource usage, followed by carbon emissions (33%), water usage (24%), and waste generation (10%). Comparative metrics indicate a 30-40% reduction in carbon emissions, water consumption, and waste generation after adopting sustainability practices, underscoring the importance of data-driven innovation. Our findings highlight the varying needs across industries: the financial sector demands real-time decision- making, healthcare focuses on cost optimization, and retail prioritizes customer satisfaction and operational efficiency. Furthermore, regulatory compliance and resource heterogeneity shape BDA adoption, influencing organizational performance. This study offers practical insights into how industries can align analytics with eco-innovation, driving sustainable growth and operational excellence. These results emphasize the transformative potential of predictive analytics in enhancing sustainability, making BDA a critical component of future industrial strategies.