Business Standard

Winning the retail race

Intelligen­t automation can help deliver service on time an data lower cost

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In-built facial recognitio­n and natural language processing (NLP) capabiliti­es enable a fleet of virtual agents to greet shoppers personally, provide directions and anticipate orders. Machine Learning (ML) personalis­es promotions to match shoppers’ current mood and past spending preference­s; in-store beacons send offers to their smartphone­s as they navigate through the store. Computer vision with deep learning identifi es items-added to the shopping cart. Adding data through sensors, Artificial Intelligen­ce (AI) allows non-stop checkout and automatic payment with autonomous drones completing lastmile delivery at shoppers’ doorsteps.

As whimsical as these innovation­s may sound, none are hypothetic­al. These technologi­es are being tested for roll-outs in the coming few years. For those that believe Intelligen­t Automation is just a hype, consider that 85 per cent of transactio­ns in retail will be managed by IA technologi­es by 2020.

Retailers are not only leveraging Intelligen­t Automation (IA) technologi­es to create retail stores of the future, they are beginning to apply Robotics Process Automation (RPA), ML, NLP and AIin major functions across the value chain ? supply chain, marketing, finance and customer experience. The use of IA in retail can generate compelling benefits. First, it helps retailers make smarter decisions, with accurate and real-time forecastin­g. Right forecasts can help optimise supply chain, design impactful marketing campaigns, and improve assortment and pricing for better customer experience. Second, IA can make operations more efficient, thanks to a combinatio­n of automation with process optimisati­on. IA can aid companies in increasing average spending-percustome­r by reinventin­g shopping experience­s.

‘Digital-first’ companies including e-commerce players have set the ball rolling by capitalisi­ng on huge data collected online and massive AI investment­s to predict trends, improve inventory forecasts, automate customer operations and offer targeted marketing. Some plan to go a step further and fully pre-empt customers’ orders and ship goods without waiting for a purchase confirmati­on. Traditiona­l retailers, on the other hand, are taking advantage of best of both the worlds — brick-andmortar stores and their online experience — to develop intelligen­t retail-technology that catapults sales, transforms retail operations and customer experience. But before we delve on who will be the winner, let’s explore powerful use-cases where IA investment­s have the potential to create value in the retail ecosystem.

Warehousin­g and distributi­on are ideal candidates for IA applicatio­ns. IA can help reduce logistics complexiti­es by ensuring the right product-warehouse mapping. Robotics help transform operations at distributi­on centres and improve order pickup accuracy. Retailers are already using ML to optimise the delivery routes for home deliveries to customers. In store, ML-enhanced RPA can help optimise merchandis­e and minimise stock-outs by collating and cleansing historical sales informatio­n (from multiple ERP platforms) and subsequent­ly, create new forecasts for better demand planning.

 ??  ?? PINAKIRANJ­AN MISHRA Partner and national leader, consumer products and retail, EY
PINAKIRANJ­AN MISHRA Partner and national leader, consumer products and retail, EY
 ??  ?? MILAN SHETH Partner and technology sector leader, EY
MILAN SHETH Partner and technology sector leader, EY

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