Artificial Intelligence in Retail — Solving UK’s Brexit Stock Problem

IN Artificial Intelligence — 22 November, 2017

Data has never been a more valuable commodity and artificial intelligence in retail could finally help businesses cash in their checks.

In the current pre-Brexit climate, retailers face uncertain trading conditions. Coupled with a depreciation of the pound, analysis from the British Retail Consortium has indicated that food commodity costs have risen by an average of 17%. What, then, are the uses of artificial intelligence to drive positive, valuable change in the volatile UK Brexit retail sector?

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Data insight protects your bottom line

Margins are tighter and competition is increasingly fierce, causing grave concern for a number of British retailers, especially those handling produce with a limited shelf life. While overseas consumers can take advantage of their strong currency against the pound, British retailers are paying up to 20% more for anything they import.

“With retailers suddenly having to pay much more for their stock, it is more important than ever that they ensure produce levels are managed correctly,” explains Uwe Weiss, CEO at Blue Yonder. Machine learning and artificial intelligence, however, could provide retailers with the crucial insight to make the right stock decisions, optimize their operations and strengthen their vulnerable bottom line.

“Retailers simply cannot afford to waste stock, whether that is food that spoils before it can be sold, or branded goods that are out of season or out of date before they reach the shelves. There is a real risk that, if retailers cannot optimize their supply chains, consumers will begin to see some of their favourite products go missing from the shelves.”

Why artificial intelligence in retail?

If it’s data that holds the key to making more informed stock decisions, why do retail businesses need artificial intelligence?

The volume of data is too complex for the human brain to process in isolation. With innovative AI technology, however, external insights such as weather is consolidated with POS and product consumer behavior data. The end result is fully optimized, automated replenishment, boosting retailers’ profits and ensuring they remain competitive.

How can you capitalize on AI?

Blue Yonder Replenishment Optimization is a machine learning solution that allows automated store replenishment to efficiently reduce waste.

The solution utilizes 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. The automated decisions reduce the burden of making manual predictions.

“When this data is combined with advanced AI technology, stock replenishment optimization solutions then predict accurately customer demand and automate stock level decisions, across thousands of product categories and hundreds of stores,” continued Weiss.

“By using the data at their disposal to optimize their stock levels, retailers ensure that, even though they may have to pay more for some products, they maximize the profitability of these products.”

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