Before 2009, department managers at Publix Super Markets would make stocking decisions based on their own knowledge of how things were selling and what promotions were planned. When a manager changed positions or went on vacation, however, that individual expertise was lost.
Three years ago, the chain of 1,058 supermarkets based in Lakeland, Fla., installed an inventory replenishment software system that uses sales data and information about upcoming promotions to more accurately predict demand and automatically order appropriate stock.
"This is more efficient and takes some of the guesswork out of it," says Maria Brous, director of community and media relations at Publix. "And people can be on vacation or change positions, and [the system still works]."
Publix Super Markets
Top grocery retailers and others along the supply chain manage inventory today with data massaged by advanced algorithms that take many factors into account, rather than a department manager's experience and instinct.
The trend toward using data to manage inventory isn't new, but it has picked up steam and sophistication in recent years, experts say. "I definitely see much more sophistication in the industry as compared to when I started in the business [in 1990]," says Rod Daugherty, senior director of product strategy for Manhattan Associates, a supply chain optimization software provider. "Our prospect base is looking to squeeze more water out of the rock from an inventory point of view."
Squeezing "more water out of the rock" in most cases means reducing the amount of money tied up in inventory that isn't selling while having enough inventory on hand to satisfy customer demand.
Creating Accurate Forecasts
In its most elementary form, stock optimization involves subtracting sales recorded at the cash register from inventory, which provides an accurate view of what remains on the shelves. This data can then be tracked over time to predict future sales. But new stock optimization systems are more sophisticated and take into account factors such as seasonality, shrinkage, supplier reliability, promotions and other factors.
"It starts with forecast optimization," Daugherty says. "There are a couple of things that customers gain from better forecasts. They get closer to what demand actually is, and they require less safety stock, which is a big component of your inventory investment."
Reducing the investment in safety stock – the stock a store orders above what actually needs to meet demand – is achieved by a sophisticated understanding of all of the elements that affect inventory and demand. Loss plays a role. It can take the form of stolen merchandise, which obviously is not recorded by the store's point-of-sale system, spoiled or damaged product that can't be sold, or even product that is not properly recorded by the point-of-sale system because of clerk error or some other problem.
"Shrink is an ugly problem," says Marek Polonski, vice president of Applied Predictive Technologies in Arlington, Va. "The problem with shrinkage is that it throws your inventory out of whack, and you don't get the profit you expect." For example, if a shoplifter walked out with a carton of Tylenol, the retailer's inventory would show the carton on the shelf, but customers wouldn't find it there, resulting in lost sales.
Applied Predictive Technologies
Stolen merchandise is the most well-known form of shrinkage, whether it is shoplifted by hungry teens or pilfered by dishonest employees. In 2011 worldwide, shrinkage from theft equaled 1.45 percent of retail sales, according to the U.K.-based Centre for Retail Research.
Retailers can use many different strategies to reduce this form of shrinkage, from installing video cameras to putting easily stolen items in locked cases, Polonski says. However, each strategy might impact sales. Retailers will sell fewer razor blades if customers need to ask a clerk to unlock the case each time, for example, so retailers should measure the potential effect of these strategies by testing them in a small number of stores.
Retailers can address shrinkage due to spoilage with better inventory management. If a store uses historical data to predict how much milk to order, for example, less will go out-of-date before being sold. "One of our natural foods customers reduced shrinkage 23 percent by doing a better job of replenishment buying," Daugherty says. "They scientifically know how much safety stock they should carry based on the facts."
Another form of inventory management, which retailers don't always consider, is simple error on the part of clerks. For example, a clerk might see a customer has 10 cartons of yogurt at checkout and decide to scan one and hit "times 10" on the register, without realizing they include different flavors and different stock keeping units. "Then you've lost all the integrity of the demand data for that product," Daugherty explains.
Retailers need to factor shrinkage into their forecasts to manage inventory accurately. If a store's average shrinkage is 1.45 percent of sales, then the retailer should add a corresponding volume of stock to the forecast. Taking a manual inventory naturally helps a store more accurately account for loss, but that approach is expensive and not always practical.
Besides shrinkage, other factors–such as promotions and seasonality–can have intermittent effects on inventory.
While every inventory management system takes into account sales from previous, corresponding sales periods, a more sophisticated understanding of seasonal sales might include related items that sell well at the same time. "On the one hand, you see the product that relates to the holiday, but you can also look at the total basket and see what else people put in it," Polonski says. "So if people are buying turkey around Thanksgiving, they may also be buying potatoes and cranberry sauce."
An inventory management system also helps buyers along the supply chain slow down ordering when appropriate. Russell Parker, senior vice president of marketing, brand management and inbound logistics for natural foods distributor Nature's Best, says his inventory system knows when to tell buyers to stop ordering a seasonal product. Computerized inventory systems can "remember" what happened the previous year and recommends smaller orders in advance of declining sales.
Demand also is affected by promotions. It would be fairly simple for a category manager to keep track of promotions and order more of the product being promoted, but a sophisticated system could track how such promotions affect the sale of related products. For example, if Jif peanut butter is on sale, should the retailer order less Skippy?
Furthermore, the system could tell the buyer precisely when to order the promoted product to take best advantage of manufacturer-sponsored promotions and shipping schedules. For a distributor, the management of promotions is essential because of the sheer volume of them, and the potential financial impact of having too much or too little inventory in the warehouse. "Let's say a store buyer tells us two months in advance about a promotion for a product we buy from our supplier every two weeks," Parker says. "We add that information to the system when the order comes in, but it doesn't necessarily come to the attention of the buyer then." Rather, the system considers the reliability of the supplier, the expected demand and other factors to determine the most financially advantageous moment to order the product. "That way the buyer doesn't have to think about the order and use Post-it notes or emails. The software brings up the order in the proper way," Parker says.
Better Ordering Procedures
Besides forecasting, an inventory management system includes improved ordering procedures. For example, knowing what days of the week are optimal for receiving inventory could boost sales and customer satisfaction and reduce spoilage.
"The question to ask is, what is the right day for me to order the truck to come in, and what time of day, to maximize that inventory face time with the customer," Polonski says. "Having frequent deliveries is good on the one hand because I have lots of inventory, but it's also more expensive."
Test the best days by varying delivery dates and times among stores, and then examine the data to see if one schedule improved sales over another, Polonski suggests. "Let's say my stores normally get a big delivery on Friday. I could hypothetically send two smaller trucks, one on Tuesday and one on Friday. You don't know if it will really help, and it costs more, so you choose a group of stores and run an in-market test," Polonski says. "Then I can measure the impact of being well-stocked...on sales. Do I see a sales lift? Or would people have bought something else anyway?"
Clean, accurate data and sophisticated software lead to success in modern inventory management. By making decisions based on data rather than instinct, retailers and others in the supply chain are decreasing safety stock and increasing customer satisfaction.