siliconindia | | JULY - AUGUST 20259demand signals, purchase history, inventory movement, route information & logistics data, enterprises are using AI/ML to bring innovation at scale to help supply chain decision-making.In my current experience and capacity to lead a large-scale supply chain digital transformation, here are some of the key areas where AI/ML (and, as a natural extension, Generative AI) is driving significant innovation in the supply chain.Advanced Demand Forecasting: One of the key contributions of AI/ML to supply chain decision-making is the ability to enhance demand forecasting accuracy. Machine learning algorithms analyze historical sales data, market trends, and external factors to generate more precise demand forecasts. This reduces the likelihood of stockouts or excess inventory and allows for better resource allocation.Network Inventory Optimization: Inventory optimization is another area where AI/ML creates a lot of value. Leveraging network analysis, we can dynamically adjust inventory levels based on real-time demand fluctuations, supplier performance, and external factors such as weather and geopolitical events. By automating inventory replenishment decisions, organizations can achieve optimal stock levels, minimizing carrying costs while ensuring product availability.Route Optimization: AI-driven route optimization is transforming logistics and transportation management. To identify the most efficient routes, machine learning algorithms consider various parameters, including traffic conditions, fuel prices, and delivery schedules. This reduces transportation costs and minimizes carbon footprint, aligning supply chain operations with sustainability goals.Collaborative Planning and Supply Chain Visibility: The integration of advanced analytics and AI/ML is a foundation for collaborative planning. By providing stakeholders with real-time, actionable insights, we can break down silos and enable cross-functional collaboration. Supply chain visibility using control towers is key in gaining near real-time visibility of supply chain operations. This becomes particularly crucial in addressing supply chain risk and disruption. When equipped with accurate and timely information, supply chain professionals can collectively formulate adaptive strategies to mitigate risks, respond to changes, and ensure the supply chain's resilience.Well, can we really say the last words on this topic? The short answer is a resounding `No.' Advanced analytics & AI/ML are evolving at such breakneck speed that it is getting tough to stay ahead of the game. However, one thing is for sure ­ AI/ML and advanced analytics are surely shaping the future of a digital and connected supply chain. A digitally connected supply chain is the way forward to handle the disruptions and volatility modern supply chains present to enterprises. In this current world, when macro and micro socio-economic conditions continue to throw curveballs, being well connected and leveraging digital innovations via advanced analytics and AI/ML is the winning formula. Well ­ for now, at least!
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