Problem:
Retailers often face challenges with overstocking or stockouts due to inaccurate demand predictions, leading to lost sales or excess inventory.
AI Solution:
Use machine learning models to analyze historical sales data, seasonality, market trends, promotions, weather patterns, and regional events to accurately forecast product demand at a granular level (e.g., per store, per product, per week).
Benefits:
- Reduces inventory holding costs
- Improves product availability
- Enhances supply chain efficiency
- Minimizes waste, especially in perishable goods
Example Implementation:
A grocery chain uses AI to predict how many units of each product are likely to sell in each store over the next two weeks, adjusting orders automatically to suppliers, reducing spoilage, and ensuring shelves are stocked during peak periods.
