When Market Risk Becomes an Operating-Model Problem

Recent disruptions across commodity markets have exposed something considerably less visible than price volatility. For many companies, what initially appeared to be a market-risk or hedging problem quickly became a test of the operating model itself, revealing weaknesses in how market information is gathered, interpreted, communicated and translated into commercial decisions.

As trade flows were disrupted, physical availability tightened, and backwardation returned to markets that had become accustomed to contango, the immediate consequences were naturally visible in prices, premiums and forward curves. Yet these were only part of the problem. Processes designed for relatively stable market conditions became too slow, established reporting lines struggled with the speed and complexity of events, and market intelligence was often fragmented across functions that were assessing different parts of the same exposure.

Commercial teams, procurement, risk, finance and operations were looking at the same disruption through different lenses, often without a single function capable of connecting the implications across the organisation. As uncertainty increased, so did the volume of information and the number of assumptions surrounding it. “Potentially”, “may”, “might” and “could” occupied internal discussions, and linguistic hedging quickly replaced past convictions about the market.

The lesson from recent disruptions is not simply that companies need better forecasts or more market information. It is that many organisations need to reconsider how market intelligence, risk and decision-making are connected, particularly in markets where disruption can no longer be regarded as an occasional deviation from otherwise predictable conditions.

Contango concealed weaknesses in the operating model

For a prolonged period, many aluminium and commodity businesses operated in an environment where contango was familiar and expected, physical material was generally accessible and disruptions, when they occurred, could often be absorbed without fundamentally changing established commercial processes. This environment shaped not only expectations about the market but also the internal structures companies developed to operate within it.

Inventory could be carried with confidence, procurement decisions generally had more time, financing assumptions reflected relatively predictable forward curves, and commercial teams could optimise around established physical flows. Market intelligence could pass through several layers of an organisation before reaching the ultimate decision-maker without necessarily compromising the quality or timing of the decision.

In effect, favourable market conditions compensated for some organisational inefficiencies. Processes that appeared robust were not always genuinely robust; in some cases, they had simply never been exposed to conditions in which the cost of slow or fragmented decision-making became immediately visible.

The return of backwardation changed this dynamic. When nearby material became more valuable, physical availability tightened and the commercial cost of waiting increased; weaknesses the market had previously absorbed moved rapidly and escalated. A reporting process suddenly became too slow, an exposure previously seen mainly as a price risk became an availability problem, and inventory that had been treated largely as working capital became strategically important.

The consequence was that procurement, physical positioning, inventory management, financing and hedging could no longer be considered independently. Backwardation tested much more than hedging strategies. It tested how quickly an organisation could recognise that the market had changed, establish what that change meant for its own exposure and convert that understanding into coordinated action.

Price risk was only one part of the exposure

Commodity businesses naturally translate disruption into price because price provides the most immediate and measurable indicator of changing market conditions. Topics around the LME price, regional premiums, forward curves and appropriate hedging positions tend to dominate the early stages of a disruption.

Yet when the physical market is disrupted, these questions can quickly become secondary to wider commercial concerns. The organisation needs to know whether the required material is available, which alternative suppliers have capacity, whether logistics routes remain viable, how much inventory is actually available rather than already committed, which customers or products take priority, and how the business responds if the disruption lasts longer than expected.

These questions cut across different parts of the organisation. Procurement has the clearest view of physical availability, trading is the first to see the implications for the forward curve, finance sees the liquidity and working-capital consequences, operations understands production constraints, and sales knows which customer commitments are most difficult to alter. Market intelligence brings the broader view of the external supply-demand balance and the behaviour of competitors and counterparties.

The difficulty arises when each function understands its own component of the exposure, but the organisation lacks a mechanism for connecting them. A company can, for example, hedge its underlying metal-price exposure effectively and still find itself commercially exposed because it cannot obtain the required product, specification or volume in the location and timeframe required. Financial hedging can protect against a movement in price, but it cannot replace missing physical tonnes, restore logistics route or satisfy a customer whose material cannot be delivered.

This distinction is important because it changes the purpose of market intelligence during periods of disruption. Rather than simply explaining what has happened to the market, intelligence needs to establish how the external disruption transmits through the company’s physical, commercial and financial exposures.

More information increased the noise

One weakness exposed during periods of disruption is the assumption that more information leads to better decisions. In practice, uncertainty often produces the opposite effect, as organisations generate more reports, more calls, more scenarios, and more internal commentary at the same time; external information becomes less reliable.

Information begins arriving simultaneously from suppliers, customers, procurement teams, traders, consultants, news services, operations and senior management networks. The challenge shifts from obtaining information to determining which information is sufficiently reliable and commercially relevant to influence decisions.

This is where market intelligence needs to move beyond information collection and establish a clear hierarchy between confirmed facts, credible market signals, analytical assumptions and scenarios. These categories can all be useful, but they should not carry the same weight, particularly when decisions involving physical commitments, inventory, or substantial financial exposure must be made quickly.

Confirmation that a smelter has curtailed production, for example, is fundamentally different from market speculation about how long the curtailment may last. An assessment that alternative supply of the same deficient products could become available is different again from confirmation that tonnes have actually been offered, and delivered. If these distinctions are lost as information moves through the organisation, assumptions quickly start being treated as facts.

This is also where language becomes revealing. “May”, “might”, “potentially” and “could” are inevitable when markets are uncertain. The problem starts when they dominate the information space and the organisation loses a clear distinction between what it knows, what it believes and what remains an assumption.

Market intelligence needs to connect directly with commercial decisions

Historically, market intelligence in many industrial organisations has existed as a supporting capability, providing market analysis to procurement, demand intelligence to commercial teams, long-term outlooks to strategy functions and periodic market updates to senior management. That structure works well when the market moves in familiar patterns, but disruption puts very different demands on the function.

Market intelligence increasingly needs to connect commercial exposure, physical flows, procurement, inventory, financing, hedging and operations, not because it should assume responsibility for each of these areas, but because the organisation needs a clear view of how developments in one area affect the others.

Knowing the estimated volume removed from the market is useful, but insufficient on its own. The organisation also needs to understand where those tonnes were destined for, which exact products and customers are most exposed, whether alternative producers have available capacity, how freight routes and lead times could change, what inventory exists downstream, whether premiums and forward curves are exposed and where the company’s own position sits within this changing physical market.

This requires market intelligence to work across the organisation rather than remain confined to a single function. It also needs direct access to decision-makers so material market developments reach them quickly and without losing clarity through multiple reporting layers.

Risk needs to be embedded within market intelligence

Perhaps the most significant change here is philosophical and behavioural. Companies are designing their operating models around the expectation that disruption is recurring rather than exceptional, which means geopolitical events, logistics interruptions, trade-policy changes, energy shocks and sudden changes in forward curves can no longer sit exclusively within the stress-scenario section of an annual strategy exercise.

A greater element of risk needs to be embedded directly in the market intelligence function and in how normal market analysis is conducted. A conventional market outlook asks what is most likely to happen to supply, demand, prices and trade flows. A disruption-ready intelligence framework needs to step up in scenario modelling by asking what could materially alter that outlook, how quickly such a change could develop, where the organisation would first feel its effects, which indicators could provide an early warning and what commercial decisions would follow if the risks materialise.

This does not mean operating permanently in crisis mode or treating every disruption as equally likely. It means recognising that the range of commercially relevant outcomes has widened, and that being unprepared for a major disruption can be far more costly than expected.

Risk becomes part of the core market intelligence framework rather than a separate scenario added to the base case.

The objective is to be prepared, not to predict everything

The natural response after a major disruption is often to focus on what the organisation failed to anticipate. That misses the more important lesson, because no market intelligence function can identify every geopolitical event, infrastructure failure, policy intervention or interruption to global trade in advance.

The objective is to improve general readiness, interpretation and response so the organisation can recognise what matters, assess the implications quickly and act with greater clarity. The strongest organisations will not necessarily be those that predict the next disruption first, but those that already understand their exposures when it occurs and can rapidly distinguish between a temporary market reaction and a development requiring a change in commercial behaviour.

That requires an organisation to know which signals matter, which assumptions need to be challenged, where decision rights sit, which stakeholders need to receive information and what actions become appropriate as different scenarios develop. Speed remains important, particularly in tight physical markets, but without analytical discipline it can simply accelerate the wrong decision.

The quality of the market intelligence function should be judged by how effectively it reduces uncertainty and gives the organisation enough clarity to make timely, commercially sound decisions.

Building market intelligence for disruption

Recent disruptions have provided an uncomfortable test of commercial operating models across commodity markets. They have exposed fragmented intelligence, slow reporting structures and, in some cases, an excessive dependence on familiar market conditions, while also demonstrating the value of integrated intelligence, clearly mapped exposures and short connections between market signals and commercial decision-makers.

The distinction will become increasingly important as disruption becomes a more regular feature of global commodity markets. Companies do not need to predict every geopolitical event, logistics interruption or sudden change in market structure, but they do need operating models capable of absorbing these events without letting market uncertainty overwhelm the decision-making process.

This gives the market intelligence function a broader role than articulating external views and passing information where is needed. Its purpose is increasingly to connect developments in the external market with the organisation’s physical, commercial and financial exposures, establish which developments materially change those exposures and provide decision-makers with sufficient clarity to act.

Ultimately, the question is whether the organisation is structured to use that understanding when the market becomes difficult.