Intelligent analysis and automation of replenishment process can optimise the retail supply chain
Retailers, currently suffering through some of the most challenging trading conditions they have ever faced, should look to new technology to optimise their operations, reduce their costs and strengthen their bottom line. This is according to Uwe Weiss, CEO at Blue Yonder, the world leader in AI and machine learning for retail supply chain optimisation. Uwe suggests that with advanced innovations in supply chain technology, retailers can better prepare themselves for potentially challenging times ahead.
A wide range of factors bear responsibility for the challenging situation that many retailers find themselves in. A stagnant economy with low wage growth and rising inflation has led to a marked decline in consumer spending, and the uncertainty following the vote to leave the European Union has only worsened matters. The subsequent depreciation of the pound putting a strain on retailers’ supply chains and profitability. In addition, analysis from the British Retail Consortium indicate that global food commodity costs have risen by an average of 17%, putting further pressure on retailers’ supply chains.
Uwe Weiss comments on the impact that this is having on the retail sector: “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. 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to waste stock, whether that is food that spoils before it can be sold, or branded goods that are out of season or out of date before they reach the shelves.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 optimise their supply chains that consumers will begin to see some of their favourite products go missing from the shelves.
“Retailers must balance the need to keep products on their shelves with maintaining a profitable and efficient business. This is where technology can give retailers a competitive edge and insulate them against the fluctuations in the supply chain. Retailers have access to vast reams of data, including their own internal data such as past sales patterns and customer footfall, and external information such as public holidays, the weather.
“When this data is combined with advanced AI technology, stock replenishment optimization solutions can then accurately predict customer demand and automate stock level decisions, across thousands of product categories and hundreds of stores. By using the data at their disposal to optimise their stock levels, retailers can ensure that, even though they may have to pay more for some products, they maximise the profitability of these products.”
Blue Yonder Replenishment Optimization is a machine learning 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.