A supplier may have the most sophisticated ERP software, the most experienced personnel, and the proper warehouse inventory to fulfill any demand. However, even with everything in order from the supplier side, without accurate and timely store inventory the risk of stock outs can be high and go unnoticed until the next cycle count at each store. Whether the supplier is maintaining its own perpetual inventory or relying on data feeds from the retailer inventory, positions can get out of balance due to several issues like shrinkage or improper receiving of shipments. In addition, inaccurate inventory means fewer sales opportunities.
Two ways to improve inventory are through statistical analysis of historic point of sale (POS) system data and direct input from store personnel in the replenishment process.
Providing statistical analysis over sales can alert central and store level personnel to situations that may need to be addressed. For example, there could be a situation where systemic inventory levels are positive, but that item is not showing sales over a certain period. Simply following the numbers would mean inventory levels are maintained; however, the store could almost certainly face stock-out conditions as the suggested stock level of a replenishment system may not meet the demands of the consumer. The store’s rate of sale would not be calculated correctly due to lost sales of the item being out of stock. By examining how frequently an item is sold out and how quickly it sells once it’s back on the shelves, the retailer can make a judgement call to raise inventory levels and evaluate if stores can sustain a higher sales velocity due to that increase.
Let’s look at a national bookstore. A review of sales trends may indicate that only one copy of a particular title sold in the past 10 weeks; however, the system can’t calculate an appropriate stocking level due to numerous out of stock conditions. As soon as the book was back in stock, it flew off the shelf. Perhaps the title was re-issued as an anniversary edition; maybe the rights were sold to develop into a movie. More copies could have been sold, but the inventory levels did not match consumer demand. Increasing the number of books on the shelves allows the store to increase sales.
Store Personnel Input
Most vendor managed inventory (VMI) models are managed centrally with no involvement from store personnel, even though they are closest to the end product and can be the “eyes” of accuracy. In a recently developed model, store personnel are notified after the daily replenishment has run, but prior to actual orders being generated and sent to the distribution facility, as well as given access to that day’s suggested order. They have the opportunity to review the order and make adjustments to those suggestions based on their knowledge of the actual inventory at their store, while also adjusting the inventory level for future replenishments. In addition, store personnel are given a level of flexibility that allows them to add items that, based on their knowledge of local buying habits, they know can sell and increase sales at their location. Store involvement is not mandated by the process, but optional and time sensitive. If action is not taken by a certain time, then the final decision is left to the central team as it would be in a typical VMI setting.
The consumers of a general electronics store tend to vary, depending on area demographics. The suggested inventory levels may not be appropriate for all stores. Some items may not sell in certain locations, taking up valuable shelf space, while the same products may be popular elsewhere, constantly sold out because demand exceeds the maximum limits set by central office. By allowing store personnel visibility into a suggested order, the retailer can have the right inventory at the right location, minimizing the potential for overstock or out-of-stock conditions. In addition, by having access to the complete catalog, personnel can adjust the planogram for that store, maximizing sales potential.