FAQs

It means a person reviews and, where needed, guides or extrapolates the model’s output, rather than publishing the raw model result unchecked. The model still does the core analytical work.

By adding more relevant variables to the model and by keeping a human in the loop who understands the market well enough to question a result that does not make sense.

It is a statistical relationship between two variables that has no real causal connection, such as cheese consumption and bedsheet-related deaths. A model can find these patterns, but they will not hold up as genuine market drivers.

Chicken thigh prices follow a repeatable seasonal pattern tied to summer grilling demand. Red meat prices respond to a wider, less predictable mix of supply, demand, and speculative factors, which requires human judgement to interpret correctly.

No. Commodities with stable, seasonal demand patterns forecast well with AI alone. Commodities driven by shifting supply, demand, and speculation need human oversight alongside the model.

The clearest cases are harvest-driven. Agricultural supply concentrates in specific months, pushing prices down at harvest as supply peaks and up as stocks draw down in the months that follow. Weather shapes this further, affecting yields, timing, sometimes both in the same year.

Demand follows its own calendar. Heating fuel spikes in winter. Grilling season reliably drives beef prices. These cycles hold because the behaviour behind them (how people heat their homes, when they buy for summer) doesn’t change quickly.

Inventory connects the two. Stocks build when supply runs ahead of seasonal demand and draw down when demand outpaces supply. That cycle reinforces the price rhythm. It also makes a shifting pattern visible early. When inventory is building or drawing differently than usual, the pattern is already moving.

The cost gap between materials has moved more than the absolute prices. The strategic question is less about timing a single purchase and more about reassessing material mix in light of how differently each category has responded.

For test liner, Expana’s forecasting team estimates roughly 90% of the increase has already happened, with limited upside and a seasonal decline expected into year-end. The same fundamentals approach is applied across other packaging commodities.

That is still uncertain. The main variables are how quickly crude and shipping flows resume through the Strait of Hormuz and whether shippers trust the route. Estimates for Gulf aluminum supply alone returning to pre-war levels run to one or two months, with broader normalization harder to pin down.

Paper is comparatively cheap right now because of post-COVID overcapacity, and some companies are already exploring a shift. The advantage depends on how quickly aluminum and plastic prices normalize now that a peace deal is in place, so weigh any switch against the forecast outlook rather than the current spread alone.

Because the exposure differs. Europe relies heavily on Middle Eastern feedstocks and imports, so the Hormuz closure hit it hardest. The US has a strong domestic feedstock base for plastics and was more insulated, while its aluminum prices are driven more by 50% import tariffs than by Gulf supply.

The main wildcard is El Niño, which Expana forecasts could be the strongest in a century. If it materializes, algal bloom risk in Chilean aquaculture zones could tighten supply meaningfully — changing the calculus for both the fresh and frozen channels heading into a period when frozen imports typically build seasonally.

All major suppliers currently face a 10% baseline tariff, with Canada exempt under USMCA. A proposed Section 301 duty would add 12.5% on Chilean and Norwegian product specifically, pushing buyers toward Faroe/Denmark and Iceland, which would stay at the 10% baseline. Canada’s zero-tariff position is also less secure than it looks, with USMCA expiry risk and no formal US-Canada talks underway.

It comes down to supply, not demand. Producers weren’t freezing material at scale when fresh prices softened, leaving domestic frozen stocks lean. With below-trend import volumes adding to that thinness, the frozen line is holding simply because there isn’t much of it — not because buyers are chasing it.

Chilean producers are keeping fresh shipments moving even in a soft market because fresh transactions settle in around 30 days versus 90+ days for frozen. That cash-flow preference means sellers absorb price pressure rather than redirect product to the freezer, so supply stays elevated and the benchmark drifts down despite the Norwegian shortfall.

All forecasts are reviewed quarterly by Expana’s analyst team. Where a significant market development occurs between scheduled reviews — such as a major supply disruption, trade policy change, or sharp demand shift — an intra-quarter update is published alongside analyst commentary explaining the revision.

Forecasts provide quarterly price targets up to three years in advance. This gives procurement and finance teams the forward visibility to support longer-term sourcing strategy.

Expana publishes price forecasts across more than 2,600 agrifood commodities, including proteins, dairy, grains, edible oils, packaging materials, and fresh produce. Coverage spans global and regional markets, with forecasts available at category and sub-category level.

Start with governance. Establish who makes decisions, and how quickly, when a trigger hits. Do that before a trigger hits. Then map your five most exposed categories by origin concentration and known grey rhino risks. The combination of governance and scenario clarity is what makes the rest of the work executable. Scenario planning without governance to act on it has limited value. Governance without scenario context has limited direction.

Those sourced from a small number of geographically or politically concentrated origins. Tree nuts like hazelnuts and almonds, grown in only a few countries, are structurally fragile. Pistachios, with major origins in Iran, Turkey, Syria, and China, carry both climate risk and significant geopolitical exposure. Energy and fertilisers are currently under compounding pressure from multiple active conflicts.

Track leading indicators across three dimensions for each category: climate and weather patterns, geopolitical developments, and macroeconomic signals like yield curve movements and unemployment trends. The harder challenge is organisational: documenting this knowledge so it survives team changes, and having a governance structure that is ready to act when signals escalate rather than simply noting them and moving on.

More often than most risk plans assume. Analysis of the past four decades shows at least one significant black swan event almost every year. Financial and geopolitical shocks are the most frequent and the most severe. The planning implication is straightforward: black swans are not rare outliers. They are a recurring feature of the operating environment.

A black swan is a sudden, high-impact event that was not predicted in advance, and arguably could not have been. The COVID-19 pandemic and the 2008 financial crash are common examples. A grey rhino is the opposite: a large, obvious risk whose warning signals have been visible for months or years, but which organisations consistently fail to act on until it becomes a crisis.

Urner Barry’s salmon prices and salmon index are incorporated into the Expana platform, alongside salmon forecasts and expert insights.