New figures from the British Retail Consortium show a 1% drop in like-for-like sales year-on-year before the crucial Christmas trading period.
As retailers enter what should be their busiest time of the year, these figures underline the importance of retailers increasing the efficiency of their operations and reducing their costs as much as possible, says Uwe Weiss, CEO of Blue Yonder, the world leader in AI and machine learning for retail supply chain optimisation. Uwe suggests that, in the current climate of uncertainty, optimising the supply chain may hold the key to unlocking costs that can help retailers improve their profitability and improve the customer experience.
A wide range of factors may have contributed to the sales slump that retailers are currently experiencing. Lingering concerns over Brexit and the state of the economy, along with the recent increase in interest rates, has meant that consumers are saving their money rather than splashing out at the shops. In addition, the October half term holiday may have resulted in more families spending their money on going to attractions and on days out, rather than shopping. Many retailers may not have accounted for the drop in demand, meaning products that they purchased have been left on the shelf.
For Uwe, intelligent use of data can be an important solution in helping retailers to reduce their costs and accommodate inconsistent customer demand: “The recent fluctuations we have seen in the retail market clearly show the importance of accurately predicting customer demand. Retailers simply cannot afford the burden of wasted stock on their bottom line, particularly with the possibility of fewer sales just around the corner and a reduction in demand. In addition, retailers have to maximise their sales potential. This means having as many products out on the shelves as possible, so that when consumers come into the store they have a better chance of finding what they are looking for. This can increase both sales and brand loyalty, because if customers know that they can find their favourite products in a store, they are more likely to return.
“Retailers are sitting on an enormous amount of data that they can use to make increasingly accurate customer demand predictions. Internal data, such as past sales and product pricing, and external information, such as public holidays, weather petterns and even football matches, can be integrated with AI technology to accurately forecast customer demand.
“Replenishment can then be optimised and stock level decisions automated, across thousands of product categories and hundreds of stores. Combining their data with advanced AI and machine learning technology can help retailers to insulate themselves against fluctuating customer demand, ensuring that they do not waste precious resources on over-stocking and always have the product available to satisfy their customers”
Blue Yonder Replenishment Optimization is an artificial intelligence solution that allows automated store replenishment to efficiently reduce waste. The solution utilises a wide variety of data points to create accurate and granular forecasts of customer demand, with a weighted optimization of waste levels and product availability, its automated decisions reducing the burden of making manual interventions on retailers.