Automatic Replenishment

Demand Forecasting and Automatic Ordering System

Product Overview Product Advantages Product Function Business scenarios Related cases

Product Overview

The replenishment system automatically identifies restocking and inventory cycles, calculating daily restocking needs based on sales forecasts, safety stock, available inventory, displays, and losses. This helps reduce supply chain costs, improve efficiency, and enhance customer service.

Product Advantages

Rich replenishment models

There are different ordering methods for different situations, including dynamic ordering, static ordering, and continuous ordering.

Efficient inventory management

Provides customers with an automated and convenient restocking prediction system, along with advanced inventory management methodologies.

Product Function

AI sales forecasting

Using big data analysis and advanced AI models, the system predicts sales with high accuracy, considering factors like seasonality, pricing, promotions, and external elements like weather.

Smart replenishment

Based on demand forecasts, the replenishment system automatically calculates reorder quantities, taking into account sales needs, safety stock, inventory levels, expected delivery, display, and waste.

Order visibility

Automatic replenishment make the calculation process visible and traceable. Historical sales data, including seasonality and other factors, guide manual replenishment decisions.

Retailer-supplier collaboration

Thanks to Dmall supplier collaboration platform, suppliers can view inventory and order status, enabling full information sharing and online processes between suppliers and retailers.

Business scenarios

Regular replenishment

For best-selling products, the system calculates demand based on sales forecasts and dynamic safety stock, implementing a "sales-driven procurement" strategy.

Promotional replenishment

Automates promotional replenishment, eliminating manual stock allocation. This not only frees up labor but also ensures more accurate ordering.

New products and new stores

New stores and products have limited data and higher variability. The system uses sales data from similar products/stores as a reference and combines it with current inventory levels to place orders.

Fresh Produce

When selecting fruits and vegetables, consumers may encounter damaged or slow-moving items. Therefore, the system adds a buffer for fresh product waste on top of the sales forecast when ordering.