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3 Demand Forecasting Myths Debunked

Logility

That’s why adapting forecasting methods is essential to navigate the diverse and constantly changing demand patterns effectively. In this article, we’ll explore why a dynamic forecasting approach is beneficial and necessary for today’s demand planners to maintain accuracy and efficiency.

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Demand Forecasting Software: Demystifying AI

Logility

Demand forecasting plays a crucial role in business success, as it helps predict customer demand and plan inventory effectively. However, traditional forecasting methods often fall short in accuracy. Fortunately, with the advent of artificial intelligence (AI), demand forecasting software has undergone a significant transformation.

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ChatGPT and the Revolution of AI-First Forecasting

Logility

While traditional forecasting methods have served us well, they often fall short when addressing the evolving challenges of today’s dynamic business landscape. In this article, we’ll explore the fusion of AI-first forecasting with traditional models and its immense value to the supply chain.

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Get Started Using Machine Learning for New Product Forecasting

ToolsGroup

Adding to this already uphill battle, we don’t have trustworthy new product forecasting methods because forecasting new products with no sales data is very hit-and-miss. Machine learning (ML) provides an effective weapon for your new product forecasting arsenal. Why is new product forecasting important?

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Causal Forecasting Brings Precision to your Forecasting

Logility

Causal f orecasting shines a light on , and isolates, actual demand signals from market “chatter,” thus improving forecast quality. What Exactly Is Causal Forecasting? . First, what it’s not is a replacement for demand forecasting. The Benefits Offered by Logility’s Causal Forecasting Solution.

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Don’t Wait to Innovate: 3 Key Benefits of Causal Forecasting

Logility

That’s precisely what demand forecasting feels like for many businesses today. Enter causal forecasting. Unfortunately, many companies hesitate to use causal forecasting, thinking it’s too complicated or resource-hungry. What is Causal Forecasting? That’s where causal forecasting comes into play.

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Can Improving Forecast Accuracy Address Our Demand Planning Woes?

Logistics Viewpoints

If “the forecast is always wrong,” is improving forecast accuracy even the solution to our demand planning woes? Artificial intelligence and machine learning ( AI/ML ) can improve forecast accuracy, but a bigger problem is the failure to set accurate expectations around forecasting models, not the accuracy of the models themselves.