Wal-Mart is not your friend. Inefficient retailing has existed for a long time. In order to succeed, retailers, especially those who run large chains, need to predict the desires of fickle customers, buy and allocate complex sets of merchandise, set the right prices, and ensure that individual products are promoted appropriately. There will always be gaps between supply and demand, often wide ones, which will lead to stores holding too much of what customers do not want and too little of what they do.
The collapse of product life cycles and the fragmentation of the mass market have made merchandising decisions even more complicated, and the penalties for errors even more severe. Retailers continue to pay high costs for their inability to get the right products to the right places at the right time despite spending billions of dollars on point-of-sale scanners and other new computer and communication systems. Approximately 8% of items customers come to buy are out of stock, and 30% of all goods are priced at a discount.
During the first quarter of 2001, K-Mart alone wrote off $400 million in excess inventory, causing its net income to decline by 40%. There aren’t all problems like this, but they still represent a constant drain on the bottom line, especially for businesses that sell items with a short shelf life, such as Christmas cards, computers, or apparel.
Fortunately, now there is hope for a solution. There are emerging software tools that are helping to revolutionize the entire supply chain, from purchasing to inventory management to pricing. Retailers can maximize their returns by implementing merchandising optimization systems, which determine the correct quantity, placement, and price of items they sell. Their data-processing techniques allow them to predict future patterns of demand and supply at the item and store level by using existing inventory and sales data. The science of merchandising is turned into an art.
Several early adopters of the new software—including Gymboree, J. J. KB Toys, ShopKo, and Penny’s were among the retailers who reported success, with gross margins increasing 5-15%. The efficiency of retail processes has also increased significantly. For example, planners at one chain saw a 20% increase in productivity. The customer satisfaction of retailers has also improved, as shoppers can find desired merchandise at fair prices when they shop.
We will discuss merchandising optimization systems in this article, which is intended for retailers, wholesalers, and consumer goods companies. Throughout the merchandising chain, we’ll explain how their processes change.
This is how it works
Business uses optimization software all the time. The airline and hotel industries have already adopted yield-management applications to manage capacity and pricing. Until recently, however, retailers were unable to optimize their merchandise. The problem, ironically, wasn’t a lack of data, but rather too much information. It was simply too expensive to analyze the data stores collect from hundreds of stores, thousands of products, and millions of transactions.
Things are changing now. The continual drop in computing cycles is enabling sophisticated optimization applications to be used on corporate servers and desktops. The retailer’s existing management systems such as Retek, JDA, and SAP serve as the basis for these applications. Complex algorithms are applied to the data to model demand at the store and SKU levels. These applications are usually browser-based, so anyone, from the CEO to the store manager, can access them.
