149 R E TA I L & C PG Armed with business intelligence captured in Eon’s platform, brands can identify the materials in the product, provide accurate sustainability information to customers, and authenticate the garments for resale or recycling at the end of their life cycles. This could help them introduce new offerings such as clothing rental, resale, reuse or recycling services, or peer-to-peer exchanges and digital wardrobe apps. “EON assigns every product a cloud-hosted digital identity, turning it into a connected asset that ‘speaks’ to brands, customers and their partners,” says Rajagopalan. “Once an item has a digital footprint, it can be stewarded through a transparent, sustainable and data-driven life cycle – from production through customer use, reuse, resale, next-life and regeneration.” Implementing solutions to accurately calculate the environmental impact of their products is also empowering retailers and CGs to identify opportunities for reducing water use and the carbon emissions and waste produced in the manufacturing and supply chain processes. “Many are looking for opportunities to improve the timeliness and granularity of the data they are measuring – whether it’s coming from farms, factories or fleets – to better understand baseline metrics and set corporate, divisional or product line goals that can be continually improved over time,” says Rajagopalan. “IoT sensors and realtime measurement can be the key to meeting these sustainability goals.” Improving demand forecasting is also an effective way to reduce waste. “If a retailer is able to order or produce the right amount of an item or product, they are less likely to send waste materials and inventory to landfill sites,” says Rajagopalan. “However, it is challenging to accurately predict consumer demand for products at the best of times – and it has become even more difficult with the shocks to loyalty, supply chain constrictions and demand spikes brought on by the pandemic.” Traditionally, retail employees must manually review food items to visually assess potential spoilage, which is labour intensive, time consuming and unlikely to be consistent or accurate. The retailer would then need to ensure continual diligence in order and inventory management to reduce markdowns and writedowns. Now, several Microsoft partners are applying artificial intelligence (AI) and other technologies to improve both forecasting and markdown optimisation. “Shelf Engine, for example, uses Microsoft Azure and other technologies to help grocers and suppliers increase profits while reducing food waste by completely automating the ordering process for highly perishable items,” says Rajagopalan. “The solution accurately predicts “ Microsoft recognises that we have a responsibility and opportunity to help organisations address critical environmental challenges” SHANTHI RAJAGOPALAN
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