Commodity Price Risk Analytics

2018 has been a year of tectonic shifts. From US sanctions on Russia and China to President Trump announcing his decision to pull out of the Iran deal and the indirect consequences of these actions, to the shutdown of lead smelters in China, for environmental reasons, without notice as well as anything in between has created ripples in the commodity markets. The supply of key raw materials is one announcement away from being crippled and the market constantly operates in a state of fear.

Price fluctuations are aplenty and, consequently, the global supply chain is at greater risk than ever before. In a globally interconnected market, change catalysts act quickly; There is a lack of predictability and not an absolute cause-and-effect chain. Reality is hazy and there is a high potential for misreads. In times like these , it becomes essential to foresee commodity price movements, predict potential impact accurately and decisively prescribe ways to manage a risk before it manifests into an unmitigable disaster.

A recent conversation with the Procurement leader for a Fortune 500 company put things into perspective. He said,” Given the global and timely nature of newsfeeds, we know what has happened almost the moment that it does. But if our approach to market events is reactive rather than proactive, then we will always be one step behind.” The inherent value in having a well-oiled commodity price risk analytics (CPRA) system cannot be expressed more succinctly. Global geopolitical tensions, negotiations between Britain and EU in the face of Brexit, the middle-east oil crisis, trade and financial uncertainties, are things that threaten to break into global supply chains and cause havoc. Constantly fluctuating commodity prices cannot be passed down to consumers in their entirety leading to profit shrinkage

A commodity price risk management program can help. Not all organizations can, or should, implement highly sophisticated mechanisms, however, most can improve upon their commodity price risk capabilities. To gain a competitive advantage from their analytics’ capabilities, companies need to first define their risk management metrics. A well-rounded commodity risk profile will help organizations to get a clear view of its net risk across business and customer segments. While determining a commodity’s risk profile can be quite challenging but, these three steps, if followed, can unlock the answers to most questions.

1. Calculate potential net commodity exposure

2. Calculate potential exposure based on current price projections as well as impact on financial metrics like EBITDA, cash flows etc.

3. Define options for managing commodity price risk

WHAT ARE THE COMPONENTS OF A COMMODITY PRICE RISK ANALYTICS SYSTEM?

While these steps are essential to define the structure to manage commodity risk, it is just that without a robust and well-tailored CPRA solution. It is the CPRA solution that helps make procurement intelligent due to its Artificial Intelligence-powered capability of managing market dynamics. CPRA has two important capabilities:

1. Early Warning System:

A machine learning-based tool that crawls the web in real-time to capture global events and builds models to measure and predict their impact on the availability of resources in the supply chain. Such a system is driven by a library of events, a historical dictionary of all previous relevant events and their supply chain impact. Moreover, this system learns constantly. All feedback is iteratively analyzed, and all alerts sent out and predictions made are ranked for importance per the feedback. Therefore, the longer such a system is in play, the better and more tailored it gets, with the ideal end state being that users see only that information that has an impact on their life.

2. Buyer’s Recommendation Engine:

A strategic decision-making tool that predicts the right buy price for a commodity and recommends an appropriate procurement action based on market data and external unstructured data. The predictive component of the engine is driven by an intelligent forecast that informs buyers about future demand by using market analysts’ reports weighed by their accuracy. Once a forecast is locked in, the prescriptive part of this solution calculates price exposure at different times, for different prices and buying quantities, and prescribes an action. Like the Early Warning System, the engine learns iteratively to prescribe a better set of actions.

HOW DOES A COMMODITY PRICE RISK ANALYTICS SOLUTION WORK?

A well implemented CPRA solution can enable businesses to reach a higher level of risk management maturity. However, the devil is in the details. The value of any insights and recommendations brought forth by the tool depends largely on what is fed to it. Therefore, it is important that the focus be on the process of converting market data, structured and unstructured, into information and then the desired outcomes will follow.

This is how a CPRA tool functions from end-to-end:

1. Data of several types, like commodity & exchange rates, inventory, order & demand, budget and margin, and spend, is fed into the tool through an ingestion layer.
2. This data is pulled into the data models used for predictive analysis that informs buyers of future commodity prices.
3. Probable future prices combined with the previously calculated net exposure for different commodities gives buyers a view of the impact of events and market insights.
4. Future prices of commodities as well as the impact of events is fed into a ‘Scenario Builder’ module that builds what-if scenarios.
5. Simultaneously, a constraint modeler creates a list of constraints which together with the what-if scenarios is fed into an optimization engine
6. The result of this process is the creation of reports and dashboards, that can be easily consumed by an executive audience at a glance, as well as strategic execution ideas that will help procurement leaders be more proactive in their buying decisions.

With an AI-driven Commodity Tech solution like CPRA in an organization’s IT portfolio, executives can breathe easy. Tracking of key commodities and their price drivers, intelligently predicting market prices of commodities, and prescribing actions that proactively hedge price risk put together makes for a powerful weapon in the armament of a user in the Procurement domain. An integrated solution that learns iteratively, like the one presented above, provides holistic insights and recommendations. Executive users can, therefore, breathe easy knowing the price risks of tomorrow were already hedged for yesterday.