Modern Supply Chain

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.

Ranendra Datta

When Demand Started Moving Faster Than Supply? For decades, demand planning was built on a comforting assumption: demand moves slower than supply. We forecast, we plan, we make inventory available, and the system absorbs small errors through buffers. That assumption quietly collapsed with the rise of D2C and quick commerce. Today, demand doesn’t wait for your planning cycle. It forms in real time, triggered by a viral reel, a micro-promotion, a weather spike, or a delivery promise shrinking from two days to ten minutes. In India, platforms promising 10–30 minute delivery have redefined not just consumer expectations, but manufacturer response expectations as well. When a quick-commerce player asks an FMCG brand, “If we deliver in 8 minutes, why do you need 2 days to replenish?”, it’s not rhetoric—it’s a structural challenge to the old operating model . This is where demand sensing moves from theory to necessity. Demand sensing is not about predicting the future better. It is about detecting what is changing right now—early enough to still do something about it. In D2C and quick commerce, that window is measured in hours and days, not weeks.

Dr. Rakesh Sinha