Logistics Viewpoints
APRIL 4, 2024
Given that we are in the age of AI/ML, I often think of how the small deli where I worked was a perfect training ground for applying AI/ML in fresh supply chain planning. There are various use cases of AI/ML for fresh demand planning of products, from producers to large grocery chains and even small delis in suburban Pennsylvania.
Supply Chain Shaman
SEPTEMBER 13, 2023
She wrote, “I have been working in the supply chain for 35 years, and we are still trying to solve the “demand” issue. Solving from a supply side seems to work for many companies I work with. Over the last two years, I actively engaged technologists and business leaders to redefine demand planning.
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ToolsGroup
MARCH 3, 2021
This article will explore the different retail channels and reveal tips for finally mastering demand forecasting for the fashion industry. Demand planning for direct and indirect channels. The COVID pandemic certainly introduced demand shifts and supplier challenges which have been clearly demonstrated in the fashion industry.
Logility
SEPTEMBER 20, 2023
Unlocking the human planners’ full potential and continuing to provide the best service for companies’ users is only possible by putting these planners in control of the latest evolutions in AI and machine learning (ML). Statistics, ML & AI in Demand Planning Software: Are All Created Equal?
Speaker: Eva Dawkins - Senior Consultant, Supply Chain
We know technology improvements can improve supply chain operations and add significant value for companies even in turbulent times. However, to pull this off, companies must first establish crucial supporting people processes - in particular, planning processes.
Logility
JUNE 7, 2023
Top 3 Demand Forecasting Mistakes —How To Avoid Them with Demand planning software Demand forecasting is a critical facet of successful business operations, acting as the helm guiding companies through the rocks hiding beneath the water of market demands. Neglecting these can distort your forecast.
ThroughPut
MARCH 25, 2024
In supply chain management, accurately distinguishing between demand planning and demand forecasting is essential yet challenging. The consequences of conflating demand planning with demand forecasting are significant, impacting inventory management, customer satisfaction, and financial health.
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Artificial intelligence designed for demand planning brings the following benefits: Immediate forecast error reduction of 15-40%: this drives optimal service & stock levels. The planner gets insight into the drivers of demand: what is the impact of seasonality, price changes, or promotions?
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