AI in Demand Forecasting and Supply Chain Management

• Blockchain Council
• October 21, 2024

Artificial intelligence (AI) has been making a bigger impact in retail, especially when it comes to predicting demand and managing supply chains. With retail becoming more digital, AI is giving companies the tools they need to stay competitive. By helping streamline processes, improving accuracy, and cutting costs, AI is also making retailers more responsive to what customers want. 

AI’s Role in Demand Forecasting

Demand forecasting has always been vital for retailers, but older methods often struggle with large datasets or sudden changes in consumer preferences. AI steps in to help retailers by using machine learning models that can process huge amounts of data quickly. It goes beyond just looking at historical sales data—it also uses real-time information like market trends, weather forecasts, and social media insights to predict customer demand more effectively.

Take Walmart as an example. The retail giant has integrated AI into its supply chain system to forecast demand, especially for perishable goods. By keeping track of data like product temperatures during transportation, Walmart can estimate when an item will be at its freshest. This lets them stock shelves at just the right time, reducing waste and avoiding delays.

Danone, another big name in the retail sector, has managed to reduce lost sales by 30% thanks to AI-powered demand forecasts. Their AI systems analyze data on consumer behaviors, market conditions, and historical trends to keep inventory at the right levels, ensuring products are available when needed but not in excess.

Similarly, RELEX Solutions has worked with One Stop, a convenience store chain in the UK, improving stock availability in stores by 5% shortly after using AI. This improvement came from refining their forecasting model to include a variety of factors that influence demand.

Boosting Supply Chain Efficiency

Supply chain management has seen significant benefits from AI. Global supply chains come with plenty of challenges, such as unpredictable demand and shipping delays. AI helps by enhancing the precision of demand forecasts and allowing retailers to monitor their supply chains in real-time.

One big advantage is minimizing human errors. AI can predict issues in supply chains more accurately, cutting errors by anywhere from 20% to 50%. This results in saving money and making better use of resources. For instance, companies can improve logistics, reduce excess stock, and prevent running out of products, ensuring smoother day-to-day operations.

AI also brings real-time tracking into supply chains. Retailers can monitor inventory and shipping schedules more closely, which helps improve customer satisfaction. For example, a retailer might use AI to notify customers when stock levels are low, encouraging quicker purchases. Meanwhile, staff can focus on more strategic work, such as improving customer experiences, rather than spending time on manual inventory tasks.

The Master Artificial Intelligence (AI) Learning Path ensures you’re equipped to handle AI-based demand forecasting and supply chain management with more confidence.

Making Inventory Management Smarter

Managing inventory in retail is both time-consuming and expensive if done poorly. Many retailers face difficulties in balancing overstocking and understocking items. AI has emerged as a key tool to help retailers find this balance. By using its predictive abilities, AI helps companies anticipate what stock they’ll need, cutting down on excess products that may not sell.

Retailers are increasingly using AI to track more than just sales. It considers things like seasonality, promotions, and other external influences that affect consumer behavior. AI tools can then suggest the best stock levels for each situation. This way, stores stay stocked adequately without overinvesting in products that might go unsold.

Cutting Costs and Boosting Operational Efficiency

AI is driving down operating costs by reducing inefficiencies. Its demand forecasting abilities cut back on unnecessary spending from overstocking and help prevent losses from items running out of stock. By predicting demand more precisely, retailers can avoid markdowns and refine their pricing strategies.

Many businesses are also moving toward automating certain supply chain tasks using AI. By automating routine tasks, such as reordering stock or managing shipments, AI frees up employees to focus on higher-value work that directly benefits customers. Instead of spending time tracking inventory manually, staff can shift their attention to developing customer loyalty programs or optimizing store layouts.

Conclusion

AI’s role in retail is only increasing, particularly in demand forecasting and managing supply chains. Its ability to quickly process and learn from large amounts of data is giving retailers a competitive edge. By optimizing inventory management, cutting down on errors, and improving customer satisfaction, AI is helping businesses become more efficient and responsive.