What the Iran conflict teaches us about Supply Shocks

The conflict involving Iran has disrupted flows through the Strait of Hormuz, one of the most critical energy corridors in the global economy. A significant share of oil, LNG and related products typically moves through this route.

When that flow is constrained, even partially, global markets react quickly. Brent crude has moved above $100 per barrel, with knock-on effects across gas and fertiliser markets. Shipping routes are being adjusted, insurance costs are rising, and delivery times are becoming less predictable.

Even firms that do not directly purchase oil are exposed. Energy feeds into transport, packaging, heating and production inputs across most sectors. Once disruption hits a chokepoint like Hormuz, the effects cascade through supply chains.

Two simple economic concepts explain most of what we are seeing.

The first is supply and demand. When a major supply route is disrupted, available supply tightens. Prices adjust upward to ration that supply across global buyers.

The second is what economists call low short-run elasticity of demand. In practical terms, this means that businesses and consumers cannot quickly reduce their use of fuel, shipping or energy-intensive inputs. When supply falls even slightly, prices often rise sharply because demand does not adjust in line.

This is why price movements can feel disproportionate. Physical shortages may be limited or temporary, but prices respond immediately to expected constraints.

A third layer, often overlooked, is risk pricing. As geopolitical uncertainty rises, insurance premia, shipping costs and financing costs all increase. These can become a meaningful share of total delivered cost, particularly for firms reliant on international logistics.

Taken together, this creates a familiar pattern: higher prices, more volatility and less predictability.

The impact is rarely contained within oil markets. Logistics firms face higher fuel and insurance costs. Manufacturers see rising input prices, especially where energy or transport is a large component. Agriculture is exposed through fertiliser and fuel. Retailers feel the effect through both supply chain costs and consumer demand.

What matters for businesses is not just the level of prices, but the instability. Budgeting becomes harder. Pricing decisions become riskier. Contract negotiations become more complex. In other words, the issue is not simply that costs are rising. It is that they are moving in ways that are harder to forecast.

Events like this are often treated as external shocks that businesses have to absorb. That is partly true, but it is also incomplete. The firms that manage these periods well tend to do one thing differently: they translate macro uncertainty into quantified, decision-ready inputs. That means moving from “oil prices are rising” to “this is what happens to our margins, pricing, and supply chain under different scenarios”. This is where simple economic thinking becomes operationally useful.

Most firms know they are exposed to energy and freight shocks. Far fewer have quantified that exposure or built clear decision rules around it.

This is where RG Economics comes in and can help.

1. Stress-test your cost base against energy and freight scenarios: Rather than relying on broad assumptions, this involves building a simple but robust model of how your costs move under different price paths, for example Brent at $90, $110 and $130, alongside changes in LNG and freight rates. Using your last 12–24 months of invoice data, volumes and contract terms, the output is a clear view of EBITDA sensitivity and a set of trigger points such as when margins fall below acceptable levels or when contracts need to be re-priced.

2. Quantify and diversify supply chain risk using real data: Where supply chains rely on a small number of routes or suppliers, disruption creates outsized risk. This project would compare alternative shipping routes and secondary suppliers using real data on lead times, insurance premia, reliability and landed costs. The result is a risk-adjusted sourcing strategy, including how much volume should be allocated to backup suppliers even if unit costs are slightly higher.

3. Set inventory levels based on “time to survive” and “time to recover”: Instead of relying on rules of thumb, this approach calculates how long the business can continue operating if key inputs are disrupted, and how quickly suppliers are likely to recover. Using consumption rates, current stock levels and historical disruption patterns, the output is a set of inventory targets by product or input, alongside a quantified view of the working capital required to support them.

4. Build disciplined hedging and pricing strategies based on data: In volatile markets, the risk is reacting too late or locking in costs at the wrong time. This involves back-testing simple hedging strategies against historical price data to define sensible hedge ranges, alongside building pricing models that link specific input costs to product-level decisions. The output is a set of rules, when to hedge, when to reprice, and by how much, based on data rather than instinct.

Global shocks cannot be controlled, but exposure to them can be measured and managed. Firms that treat this as a data and decision problem tend to respond faster and with greater confidence than those relying on instinct.