149 “ Organisations should focus on three pillars: data readiness, ecosystem collaboration and workforce enablement” To survive and thrive, retail and consumer goods organisations are pivoting from traditional, reactive supply chain management to data-driven intelligence and real-time planning. The days of fixed spreadsheets and manual, after-the-fact adjustments are fading. In their place, advanced analytics and AI are enabling companies to anticipate changes and respond swiftly. This shift is well underway and many use cases for generative AI have already been established worldwide. Digital intelligence offers opportunities to optimise and streamline operations, enhance costeffectiveness by reducing expenses and improve decision-making with better data and insights for informed choices. Agility and adaptability are crucial for creating a supply chain that can respond quickly to changes in the environment. “Generative AI can produce insights, forecasts or content from large data patterns and has proven especially powerful in tackling supply chain volatility,” says Miller. “For example, generative models can simulate demand scenarios based on historical data and external variables such as weather or social trends, enabling more accurate planning. For instance, Japanese fresh food supplier Super Hosokawa recently used AI to tackle the perennial challenge of overstock and waste in grocery stores. As part of a 2024 governmentbacked project, Super Hosokawa worked with forecast model developer Imamura Shoji, supermarket cooperative Kyushu CGC and RETAIL & CG
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