Supply chain planning in an era of constant volatility

For a long time, supply chain planning in food and beverage manufacturing was built around a fairly simple assumption: tomorrow would probably look a lot like today.

Forecasts were refreshed weekly or monthly. Safety stock policies stayed relatively stable. Demand patterns were predictable enough for experienced planners to manage through a combination of spreadsheets, intuition, and operational experience.

With what feels like a never ending stream of supply shocks, that environment has completely disappeared.

Today, food and beverage manufacturers are dealing with constant movement across almost every part of the supply chain. Inflation continues to squeeze margins, while rising financing costs are increasing the pressure associated with working capital tied up in inventory. Promotions create sudden spikes in demand, and weather patterns shift purchasing behavior overnight.

Retailers are tightening OTIF expectations while consumers expect fresher products, faster availability, and fewer compromises on quality. Plus, at the same time, manufacturers are operating with narrower operational windows than ever before.

A forecasting error in another industry might create inconvenience, but in food and beverage, it can create spoilage, waste, missed retailer orders, emergency production changes, and margin erosion all at once.

That is what makes supply chain management so difficult today. Businesses are no longer balancing one or two variables at a time, but are continuously balancing service levels, working capital, shelf life, production capacity, transportation constraints, retailer commitments, supply shocks, ingredient inflation, and changing demand conditions simultaneously. And, they’re often trying to do this at SKU level, where operational requirements can vary significantly product by product.

Why static planning is starting to break down

Despite this growing complexity, many planning processes still operate in fundamentally static ways. Forecasts are built at fixed intervals, teams manually reconcile changing demand conditions, and inventory decisions are escalated through disconnected systems and spreadsheets. Plus, operational responses often happen only once disruption has already become visible.