Better forecasts won't fix excess and obsolete stock. What happens after a risk is detected is where the value lives, and that's an orchestration problem, not a prediction problem. For the last decade, the supply chain technology conversation has been dominated by one word: forecasting. Better demand sensing. Smarter promotional lift modeling. Probabilistic planning. Machine learning everywhere. And to be fair, the math has genuinely improved — forecasts in Life Sciences and

The review boards exist for good reasons. The way most of them run, in 2026, isn't one of them. Every Quality and Operations leader in Life Sciences has had the same week at some point. A non-conforming batch is on hold. A material is approaching expiry. A supplier deviation needs a disposition. The decision sits with the Material Review Board or the Inventory Review Board and three weeks later, it's still sitting there. Nobody is doing anything wrong. The reviewers are dilig

Why perishable goods companies need a standardized, AI-driven layer for inventory operations — one their ERP was never built to provide In the perishable goods business, time is the enemy. Every day a pallet sits in a warehouse, every forecast that misses, every purchase order that lands a week late — each one quietly chips away at margin. The damage rarely announces itself. It accumulates. But before you can fix that, there's a more basic question worth sitting with. And in