Ranendra Datta
Ranendra Datta is a seasoned technology and business leader with deep experience at the intersection of IT, supply chain, and commercial transformation in the FMCG sector. He has served as Head of Information Technology for Global Manufacturing and Supply at GSK, Chief Information Officer at SABMiller India and Director Solutions and Integration for ABInbev Asia Pacific, where he played a pivotal role in modernising enterprise technology platforms and enabling data-driven decision-making across manufacturing, distribution, and sales operations. Over the course of his career, Ranendra has worked closely with senior leaders across supply chain, finance, sales, and marketing, helping organizations navigate complexity, scale operations, and respond to rapidly changing market dynamics. Beyond his operating roles, Ranendra has been an active participant in CIO and supply-chain leadership forums, engaging with peers across FMCG and consumer-driven industries. His perspectives are shaped not only by hands-on implementation experience, but also by sustained dialogue with global technology and business leaders on how digital capabilities can meaningfully improve planning, resilience, and execution. Through the TalkwithMasters series, Ranendra shares reflective, experience-led insights aimed at helping CIOs and business leaders move beyond tools and trends — and focus instead on building practical, adaptable capabilities that stand the test of real-world disruption.
Masternotes by Ranendra Datta
Modern Supply Chain
Demand Forecasting in FMCG: A CIO’s Perspective on Navigating Uncertainty
Why Demand Forecasting in FMCG Is Never Just About Numbers. A CIO’s reflections from the inside. If there is one topic that has consistently sparked animated discussion in every boardroom, supply chain review, and CIO peer forum I’ve been part of, it is demand forecasting. Not because people don’t understand its importance—but because almost everyone has, at some point, felt the pain of getting it wrong. Early in my CIO journey, I remember sitting in what seemed like a routine review meeting. The numbers on the screen looked precise, confident, and reassuring. Accuracy percentages were healthy, charts were clean, and there was a quiet sense of comfort in the room. A few weeks later, that comfort disappeared. In one of the regions, some states were sitting on piles of slow-moving inventory, while another set of states was scrambling to meet demand. The factors of seasonality, weather, impact of state excise tax on pricing, cost and demand such factors require delicate manoeuvring and compiling of huge data sets. The forecast hadn’t failed because the math was wrong. It failed because it didn’t reflect how the business actually behaved amid a small blip and all factors affecting the impact of demand forecasting were not considered in the forecast. Over the years—through many conversations with planners, commercial heads, supply chain leaders, and fellow CIOs across Industry—I’ve come to believe something quite strongly: demand forecasting is not really a forecasting problem. It is a decision-making and cultural mindset problem. This is not a theoretical piece. It is shaped by lived experience—my own and those of peers I’ve learned from along the way. I want to talk candidly about why forecasting is so hard in some industries and in some it is easy and where it usually breaks down, and how CIOs can approach demand planning in a way that genuinely improves business outcomes.
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