Dive Brief:
- British grocer Morrison’s has implemented ordering software that automates replenishment of 26,000 shelf-stable products and claims accuracy down to the individual product and store level, according to Chain Store Age.
- When combined with the company’s predictive technology, the program can learn and adapt as it processes vast quantities of sales data. It can also adjust ordering to factor in holidays and weather disruptions.
- The technology processes data from more than 13 million daily transactions across Morrison’s chain of 491 stores. It has reduced out-of-stocks by 30%, according to the company.
Dive Insight:
Automated ordering technology has been around for a while, but its accuracy and sophistication continues to increase as more retailers adopt it for their store operations.
In the U.S., Whole Foods and Target are two companies that have seen recent success with automated ordering known as order-to-shelf or “store ready” distribution. As customers purchase products, automated systems set in motion a fulfillment process that ends with just the right number of products being delivered to that store, moving directly from the loading dock to the shelf from which they were taken. It’s an exacting technology that saves stores space, time and labor.
As competition and low margins continue to squeeze retailers, grocers are looking for ways to increase efficiency and save on labor, which takes up a sizable portion of supermarkets’ expenditures. Automated ordering technology, as companies like Morrison’s, Whole Foods and Target have shown, can not only save on costly out-of-stocks, but can free up backroom space, make shelf replenishment quicker and less disruptive, and more.
These automated systems tend to work best with packaged, shelf-stable goods that are easy to stock and ship. Fresh produce and other perishable items, on which supermarkets increasingly focus, can be tougher to automate due to varying size, quality and availability. It’s also unclear how automated ordering holds up when e-commerce demand, which is difficult to forecast, enters the equation.
