Pallavi Nigam, Global Logistics Lead – Integrated Supply Chain, Mondelez International, describes an industry paradox: data is becoming the new fuel, yet decisions still run through silos, spreadsheets and midnight messages.
Technology is the enabler; people are the engine
Heavy investment in control towers has not displaced the WhatsApp call from a regional distributor about a breakdown or a demand spike, because nothing beats the judgement of someone with 20 years of experience. When a forecasting model predicted a 15% uptick in biscuit sales in one region, a regional manager flagged a competitor’s promotion that the data had not captured. Blending both signals shaped the supply plan.
Jnana and Buddhi
She turns to the Bhagavad Gita, where Krishna advises Arjuna to act with knowledge (jnana) and wisdom (buddhi). Data is jnana, the raw knowledge, but supply chain leadership requires buddhi: knowing when to trust the algorithm and when to trust the voice on the other end of the line. Her organisation is investing in real-time visibility platforms, API-first architectures and AI-driven anomaly detection, while empowering regional leaders to decide.
Culture Over Technology
A smart supply chain, she argues, is predictive rather than reactive; it sees the wave before it crashes. During the pandemic, companies with control towers but no supplier relationships or backup plans were crushed, while those with trusted supplier networks, shared data and teams trained to act fast gained market share. The difference was culture, not technology.
The Next Five Years
Within five years, she predicts, the gap will lie in what companies do with data before competitors know there is a problem. Winners will master speed and autonomous decision-making, knowing three weeks ahead that a supplier is failing, while autonomous systems make thousands of micro-decisions so that people can focus on strategy rather than firefighting. Data-driven supply chains, she estimates, will operate at 8-12% lower cost by removing excess inventory, inefficient routes, supplier redundancy and forecast errors.
The Readiness Divide
Is the wider ecosystem ready? Not yet, though it is moving faster than most expect. The top 10% of companies are building control towers while the remaining 90% still run on phone calls, WhatsApp groups and relationships. The resistance is economic rather than lazy: a small operator with 20-30 trucks cannot justify ₹50 lakhs on a data system, and the skills to manage APIs and data pipelines are scarce. In five years, she expects the top 30% to be data-driven, the middle 40% in transition and the bottom 30% largely conventional.
