4 Ways Retail ERP Systems Improve Inventory Replenishment

Businessman working with notes and figures

A retail ERP system is able to do most of the heavy lifting when it comes to automating inventory replenishment processes, but its forecasting strength is in the data details.

For retailers starting to automate their replenishment processes, take a look at how these four replenishment methods managed by a retail ERP system can improve your inventory management needs.

  1. Reorder point: Retailers should consider this method as the first step in transitioning to an automated inventory replenishment process. With a reorder point, a replenishment order is placed when the inventory quantity falls below the safety stock level. The ideal safety stock level can be identified after analyzing average sales for a specific time period.

    For instance, let’s say a medical uniform retailer observed that it sold an average of 10 blue scrubs each month for the past year. So when inventory falls below 10 at the end of the monthly inventory cycle, the retail ERP system will automatically place a replenishment order. The potential risk, however, is not factoring seasonality or trends, which could result in out-of-stock inventory. 
     

  2. Lot-for-lot replenishment: If it is desired for every unit sold that it be replaced, retailers can use a lot-for-lot replenishment model. For every item sold (in a user-defined period of time), the same amount is reordered. This is ideal for maintaining a minimal level of inventory. However, with this replenishment method, retailers could incur increased shipping costs for frequent lot-for-lot reorders.
     
  3. Average usage: This replenishment method requires reviewing sales history and calculating the average sales for a specific time period. The calculation is used for forecasting a replenishment schedule based on sales per day or for another defined time period. Average usage method is helpful in factoring a predictable inventory increase during a certain time, known as seasonality. So if a retailer consistently sells more T-shirts in June compared to other months, the replenishment order every June should factor that expected spike in sales.

    Keep in mind that the time period to calculate the average usage would likely vary according to the individual item or category of items. Also watch for any statistical spikes, such as demand for skinny jeans being lower this year, for example.

    Retailers can improve their average usage accuracy by manually adjusting the forecast according to trends. If the retail ERP system is forecasting to stock a specific amount of black cardigans for February, but the retailer knows that black cardigans are in high demand, the system should allow the retailer to make appropriate adjustments.
     

  4. Demand planning: This replenishment method individually applies statistics and other analytics to determine the best inventory replenishment schedule for a specific item. The method is often useful for creating an automated replenishment schedule when sales vary widely. For instance, what’s the best replenishment schedule for a specific T-shirt if 100 were sold June, 50 in July and 500 in August? The demand planning method is able to smooth out those extreme spikes to calculate the ideal replenishment schedule.

Retailers should improve their inventory management by automating much of their replenishment processes through a retail ERP solution. While the automated replenishment process can be as simple or sophisticated as needed, the capability depends on the quality of data the retailer provides to the system. That’s why some retailers choose the simplest replenishment method; they don’t have the time to put detailed information for every individual inventory item.

When starting out with automating inventory replenishment, it’s best to take a continuous improvement approach. Don’t try to implement the perfect automated replenishment system on day one. Instead, apply a method that is incrementally better than what was done in the past, and make a commitment to continuously improve your processes.

LS Nav allows businesses to achieve optimum stock levels. Discover all of its inventory management and demand planning functionality. 

Author: Wm. Matthew Street, Solutions Consultant/Retail Product Lead at ArcherPoint

To learn more about inventory replenishment, schedule a demo of ArcherPoint's Retail Management Solutions.