A Data-Driven Intelligent Decision Framework Integrating Digital Marketing, Supply Chain Management, Operations Management, and Business Management for Sustainable Operational and Financial Performance

Abstract

Digital transformation increasingly requires organizations to connect customer-facing digital activity with supply-chain execution, operational efficiency, and financial performance. This study has provided an intelligent decision framework based on data as a fusion of Digital Marketing, Supply Chain Management, Operations Management and Business Management. The DataCo Smart Supply Chain dataset was used to clean, precisely match and aggregate 180,519 transaction-item records and 466,728 web-log records into a lifecycle-valid product-week panel. Two digital indices were built, regression modelling was adjusted, robustness analysis was performed, a 17-indicator product decision framework was created, and leakage-safe predictive modelling was done using chronological train, validation, and reserved-test splits. While a 12.2% decline in the chances of conditional late delivery was a significant result, seven out of nine outcomes were significant, such as a 151.5% increase in transaction items, a 203.2% increase in units sold, a 198.5% increase in net revenue, and a 360.9% increase in total loss magnitude, with the profit margin remaining unchanged. The framework identified 5 strategic product groups consisting of 36 products. The late-delivery model obtained the best results with ROC-AUC 0.773 and average precision 0.854, with no support for negative-profit prediction. The results reveal that taking a broader holistic view of digital growth and fulfilment reliability, alongside the operational constraints and financial risk are required to achieve sustainable performance and return on investment, and that this is far more important than relying on individual marketing or sales metrics.