AI Forecasting

Did you know that businesses using AI for demand forecasting have seen forecast accuracy improve by 30-50%, inventory levels reduced by 20-30%, and carrying costs cut significantly? These results transform how companies approach one of the toughest forecasting challenges: intermittent demand. Intermittent demand—the erratic, low-volume demand for certain products—has long frustrated demand planners. These items […]

For many retail and manufacturing companies, growth often comes from acquisitions, bringing valuable products, new customer segments, and increased complexity. Forecasting demand across thousands of SKUs – each with unique patterns and often housed in disconnected systems – can quickly overwhelm traditional methods. The result? Risky stockouts for high-demand items, costly overstock of slower-moving products, […]

In today’s fast-paced AI landscape, accessing advanced models is critical for improving demand forecasting accuracy and making data-driven decisions. Businesses that want to stay competitive need more than simple forecasting tools—they require models capable of handling complex patterns and delivering precise results, even as their data evolves. With its growing library of state-of-the-art (SOTA) models, […]

Demand forecasting plays a central role in the ever-evolving world of manufacturing. Accurately predicting future customer needs is the cornerstone of efficient inventory management, production planning, and, ultimately, business success. While valuable, traditional forecasting methods often struggle with the complexity of modern markets. This is where machine learning (ML) steps in, offering a powerful arsenal […]

In the fast-paced world of supply chain management, the pressure to minimize inventory is constant. Every dollar tied up in unsold stock is not available for other investments. But what if the pendulum swings too far the other way? Can skimping on safety stock hurt your bottom line? The answer is a resounding yes, and […]

A constant struggle exists in manufacturing: ensuring enough inventory to meet customer demand while avoiding the financial burden of excess stock. This delicate balance is where the concept of safety stock comes in. It acts as a buffer zone, safeguarding against unexpected demand surges or supply chain disruptions. However, determining the right amount of safety […]

Improve your time series forecasts by understanding the reasons behind accuracy variations. Ever built a time series model that seemed perfect for January, only to see its accuracy plummet in February? You’re not alone. Time series data is inherently tricky, and accuracy can fluctuate significantly. This blog post dives into the culprits behind these fluctuations […]

In the ever-evolving world of supply chain management, accurate demand forecasting is the cornerstone of success. However, for many supply chain analysts, the go-to tool remains Excel, a familiar yet fundamentally flawed solution. While Excel offers a surface-level ease of use, its limitations become increasingly problematic as data sets grow and supply chains become more […]

Excel’s limitations don’t have to be your supply chain’s Achilles’ heel. A powerful escape hatch is waiting for you: Artificial Intelligence (AI). AI-powered forecasting solutions revolutionize how businesses predict demand, ushering in an era of unparalleled accuracy, real-time insights, and a proactive approach to supply chain management. The potential benefits of AI-driven forecasting are significant. […]

In today’s fast-paced world, businesses need agile and responsive supply chains. These chains must adapt to disruptions, respond to evolving consumer demands, and optimize inventory levels, all while maintaining efficiency and profitability. However, many companies are still clinging to traditional supply chain planning tools, which can be costly to implement, slow to adapt, and ultimately […]