Automated Replenishment: The Key to Excellence in Inventory Management

Today’s demanding customers require brands and retailers to provide a seamless omnichannel experience. Customers expect to have products available where they shop and where they want them delivered. Managing these expectations is almost impossible for brands and retailers that use manual methods and Excel spreadsheets to replenish products. Studies show that automated replenishment can reduce carrying costs by up to 25%, improve availability by 60% and reduce time spent on replenishment by up to 90%. Given these statistics, automating the replenishment process is the way to go.

What is Automated Replenishment?

Automated replenishment software accesses data on the centralized pool of inventory available for use across all storage locations: stores, warehouses, distribution centers, franchisee stores, and vendor inventory. It also accesses data on orders from any sales channel that includes the physical stores, marketplaces, and webstores. Software such as Vin OMS uses data from multiple sources: past sales history, seasonal demand, new product sales velocity, and product obsolescence. Using advanced inventory management techniques, it can predict the required quantities and automatically trigger replenishment. Increasingly, AI techniques manage this process in an intelligent manner to collate and analyze inventory data and present suggestions.

Automated replenishment tracks sales velocity and inventory levels in real time. It eliminates manual errors associated with traditional methods and thereby decision lag in triggering the replenishment.

The following table provides a quick comparison of manual and automated replenishment.

Automated replenishment strategies play an important role in the following areas:

• Managing multiple SKUs (stock keeping unit) inventory across multiple stores and warehouses
• Enabling endless aisle of products and knowing how to fulfill them
• Aligning availability of inventory across multiple marketplaces and stores

Automated replenishment strategies

Automated replenishment strategiesAutomated replenishment strategies are complicated by the bullwhip effect (shown in Fig 1). Bullwhip effect makes the reliability of demand forecast to be lower as it moves upstream from the retailer to the manufacturer despite shared downstream demand information. Despite the bullwhip effect, automated replenishment strategies deliver value with improved availability of products, reduced out-of-stocks, optimal levels of inventory, and reduced inventory carrying costs.

Fig 1. Bullwhip effect

Forecast based replenishment: In this strategy, the software analyzes the sales history to anticipate future demand based on past demand over a specified period. Based on these calculations, the software automatically reorders the forecasted demand by considering the available inventory across all storage locations.

Min-Max: In this strategy (shown in Fig 2), the reorder is automatically triggered when the inventory levels reach the minimum threshold value specified for the SKU. The ordered quantity will ensure that the maximum threshold value would be achieved when the reorder quantity is received.

Fig 2: Automated Replenishment Process

We will now turn our attention to handling common scenarios associated with temporary surges in demand causing out-of-stocks and constraints imposed by the suppliers, which cause the bullwhip effect mentioned above.

Out-of-Stock Scenarios

In an out-of-stock situation, a customer’s total order can be partially fulfilled or unfulfilled. A software such as Vin OMS would automatically generate a purchase order to ensure the order can be fulfilled either through the normal channels (where the inventory will first be received in the warehouse and then fulfilled) or drop shipping the order directly to the customer.

Constraints in Automated Replenishment

Order quantity: Suppliers may impose constraints due to their production schedules and setup changes that require one or more of the following

• require MOQ (minimum order quantities)
• orders to be in multiples of a number
• limitations on the frequency of orders.

These are examples of complex minimum order quantities.

There could be other constraints such as

• lot multipliers (multiples of an integer to enable a vendor to pack the item efficiently),
• price multipliers, where the marginal unit price decreases with increase in quantity ordered
• EOQ (economic order quantity) represents the ideal quantity that minimizes total inventory cost

Key features of Automated Replenishment

1. Multi-location replenishment: Software triggers an order from a centralized location (such as headquarters) for various storage locations that includes stores, warehouses, and distribution centers.
2. Automated PO generation:Software automatically generates a PO (purchase order) that can be sent without further intervention or presented for approval before it is sent out.
3. Demand forecast: Software predicts trends using past sales history, seasonality and order patterns. Artificial intelligence tools and machine learning techniques embedded in software can be used to better predict the quantities to be ordered and what levels of inventory should be available at each storage location.
4. Rule-based triggers: Rules can be defined to be triggered based on the following parameters:
   • SKU
   • Location
   • Company
   • SKU-Location combination

   Rules can be configured to prioritize suppliers based on past relationships, cost, supplier lead times and delivery schedules.

5. Real-time dashboards: Real-time dashboards on orders, inventory levels across all storage locations and information on receipt of items.

Fig 3: Automated Replenishment Process

Automated replenishment (see Fig 3) is no longer something that can be an afterthought. It is an important strategic tool for e-commerce brands and retailers to optimize the inventory that they have in stock to ensure efficient, scalable growth. By embracing system-driven and data-driven strategies, it will be easier to ensure your customers always find what they’re looking for, exactly when and where they want it.

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