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Inventory Replenishment: How A Retail ERP System Can Improve Accuracy

Charting inventory data on wall chart

Drawing from historical and vendor performance data, retail ERP solutions can help create an optimal replenishment system similar to a just-in-time (JIT) strategy.

JIT fulfillment, a production control system that reduces carrying costs and inventory stock-outs while meeting product demand, is a term more often used in the manufacturing environment than in retail. Here’s why: Engineers are able to calculate how much an assembly line at a manufacturing plant can produce at any given point. Automotive manufacturers, for example, are able to increase or decrease car production “just in time” according to the vehicle production orders they receive.

Retailers don’t operate with that same product order accuracy, unless they can say with certainty that they’ll sell an exact number of specific items on any given day. Instead of JIT inventory fulfillment, a retailer’s optimal replenishment model should fulfill customer demand and avoid the risks of carrying costs and stock-outs. This requires knowing your inventory cycles and any external influences that can affect demand.

Therein lies the predicament: Having too much safety stock will incur carrying costs. But if you don’t have safety stock and more people than you projected want to buy a product, you’ll have many unhappy customers. Your optimal replenishment model should seek 100 percent customer satisfaction.

That’s when your historical data and analytics, which will be different for each retailer, come into play. For example, a grocery store’s historical data for milk might reveal an average daily sale of 103 gallons during a specific month, ranging from a high of 120 gallons in a day to a low of 50 gallons.

Having historical sales data will help you decide the amount of safety stock that you’re comfortable with. Retailers vary in their risk tolerance; some don’t want to risk stock-outs, whereas others are fine with a 5 percent safety stock.

That risk tolerance also depends on inventory turnover. Food items, for example, have a limited shelf life because of expiration dates, so grocery retailers must be better at demand planning. Home improvement retailers, on the other hand, can keep inventory on the shelf much longer because most products they sell don’t have an expiration date.

In addition, the optimal inventory replenishment model depends on vendor capabilities. Ideally, a vendor’s retail management system should integrate with your retail ERP system for greater visibility into your distribution process. At a minimum, a vendor’s system should be able to create and send purchase orders via electronic data interchange (EDI) for a more streamlined ordering process.

If you move toward a replenishment model that decreases safety stock and increases reliance on projected demand, you’ll need to rely more on vendor performance. Of course, if your vendor delivers inventory with a consistent lead time, you’ll be better able to create an optimal replenishment system with the ideal amount of inventory.

A retail ERP system helps to identify the optimal inventory replenishment model by gathering historical sales data, calculating a product sales forecast, recommending the amount to reorder and tracking vendor performance.

For example, your retail ERP system could calculate average daily sales for a particular item during an inventory cycle. Let’s say you have 10 pairs of boot-cut jeans in stock and sell an average of two pairs per day. The vendor’s lead-time cycle is seven days. With only 10 pairs left, you’ll end up with an inventory shortage. Your retail ERP system will then recommend that you order 14 pairs in order to cover the seven days until you receive another shipment. 

When refining your inventory replenishment system, it shouldn’t come at the expense of customer service. A retail ERP system can minimize the growing pains of continuous improvement, enabling your operations to quickly adjust to the demands of a changing retail market.