The Case of the Missing Aubergine

IN Artificial Intelligence — 11 October, 2018

Earlier this summer, an aubergine shortage at a supermarket in Cheltenham, UK, captured the imagination of the Twittersphere after a ‘devastated’ local resident expressed his dismay at being greeted with an empty bay when he went to find the vegetable.

The Case of the Missing Aubergine

A flurry of memes and tweets mourning the loss of Cheltenham’s aubergines ensued, calling for Tesco to #BringBackOurAubergines. The Twitter user who had been championing the cause was even invited on local radio to discuss the shortage, and the ‘news’ was covered by multiple national newspapers, including The Sun, The Daily Express and the Metro.

There is, of course, more than a small element of humor here, and it was a Twitterstorm in a teacup, but the episode does highlight one of the biggest issues facing the grocery sector: shelf gaps.

For shoppers, it’s obviously frustrating to turn up to a local store and find that they can’t buy what they’re looking for. But for the supermarket, an empty shelf often means not only lost sales in the near term, but ultimately, the potential loss of long-term customer loyalty.

A Careful Balancing Act

Ensuring that there’s enough stock to meet customer demand, but also not so much that it goes to waste, requires a careful balancing act, and most replenishment tactics in the grocery sector aren’t fit for purpose. Getting the balance right is especially hard when dealing with fresh as there is no room for error: overstocking leads to produce being consigned to the ‘bargain bin’ or, worse, thrown out.

Until now, most supermarket replenishment software has been based on fixed rules, which often fail to accommodate the myriad influences on consumer behavior. Indeed, with a wide range of external factors likely to impact when and why people buy specific products, a new approach is needed to prevent both empty shelves and unnecessary waste.

AI-based solutions can generate probabilistic forecasts of customer demand based on hundreds of different variables including weather, promotions, and holidays. They then determine the optimal order quantities for every product and every store, every day, based on a weighted optimization of competing goals such as waste and out-of-stocks, which can result in a 30 percent reduction in shelf gaps.

Blue Yonder is already successfully ensuring that just the right amount of aubergines, lettuces and other fresh food are delivered to supermarkets across Europe. Its AI-based Demand Forecast and Replenishment solution delivers millions of daily replenishment decisions to guarantee the right level of product on the shelves, automating this time-consuming manual process and enabling retailers to focus on creating the very best customer experience.


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