Life sciences supply chains are among the most complex in the world. Every day, supply chain leaders must balance shifting demand, constrained supply, and strict regulatory requirements, all while ensuring patients get the medications they need. The margin for error is small, and disconnected, stage-by-stage planning just cannot keep up.

How do you plan for a technology that doesn't exist yet, while keeping today's production lines running? That's the challenge Bekaert faced with its titanium fiber-based porous transport layers, a breakthrough component powering industrial-scale green hydrogen production

Heineken operates one of the world's most complex brewing supply chains, producing more than 350 brands across 160 breweries and serving nearly 190 markets. At this scale, planning requires continuous alignment of demand forecasts, production capacity, and inventory flows across dozens of operating companies — a challenge compounded by the historical reliance on locally developed planning tools that varied from market to market.

For years, supply chain organizations approached demand forecasting by looking backward, with historical sales trends, seasonal cycles and prior purchasing behavior forming the foundation for most planning decisions. But in an environment shaped by geopolitical instability, tariffs and volatile consumer demand, many organizations are realizing that the forecasting models of the past simply can’t keep up with the disruptions of today.

When shippers and retailers exchange the most timely information, they can fill empty trucks and match backhaul in near real time.

Emre Akbag, managing director of Siemens Digital Logistics, details how managers can anticipate supply chain changes rather than always being in reactive mode.

With almost constant supply-chain disruptions, the need for adaptive planning is crucial, says Andrew Bell, chief product officer at Kinaxis.

Because companies are more interconnected than ever, concern for one's supplier and its suppliers as well is paramount, says Miguel Cossio, senior director at Gartner.

Thanks to AI, quantum computing in industrial organizations is closer than you might think.

Artificial intelligence presents an opportunity to redefine planning and bridge the gap in decision-making.