Nowadays, the mix of Machine Learning and IoT is fundamentally changing Supply Chain Management to transform the traditional slow-moving linear pathway into an adaptive and intelligent network. As the term suggested earlier, the supply chains suffered human ownership and decision-making and were basically connected through untimely communication. Today, the term digital supply chains refer to connected capabilities that enable real-time monitoring, forecasting abilities, and an automated operational level. In this chapter, we show how ML and IoT can be leveraged to realize smarter procurement, optimized logistics, intelligent risk management, and enhanced customer engagement. Specifically, we explore the application of predictive maintenance, demand forecasting, anomaly detection, and intelligent automation towards building supply chains that are not merely reactive and resilient but are also self-learning and self-improving. Equipped with these interactive insights, concrete examples, and recommendations on setting up smart supply chain environments, we want the reader to feel comfortable mapping the entire life cycle-from design to development to implementation-of their technology-based ecosystem.