What Are Companies Doing to Stay on Top of Commodity Risk? (Part 6)

See previous posts in this series here: (Part 1, Part 2, Part 3, Part 4, Part 5)

Before I spoke at a recent event, I decided to ask my wife Lisa Reisman, a woman who has spent much of her career managing metals commodity price risk, what true best practices she saw today on a foundational level. She told me that in her view, the most adept procurement and finance materials risk management organizations have built commodity and supplier management dashboards to track key variables. Moreover, these organizations tend to think of these efforts as an information/knowledge challenge first rather than a technology enablement one. In other words, a dashboard could be Excel. Or it could be a BI platform. Or it could be a customized commodity risk management tool. But the point is that it exists, is current and prices a shared view across the organization into local commodity pricing, overall exposure, open positions/contracts, settlement dates and the like.

Lisa suggests that with this information, organizations are carrying out a range of activities. These include aggregating the buy to enable hedging, to buy forward in rising markets, to create more effective budgeting/planning/forecasting, etc. And with a shared understanding of demand, positions, pricing, etc. they're also bringing in expert analysts from banks and commodity research firms to offer commodity perspectives, forecasts, and to explain the key variables they track that are correlated with pricing in specific markets. It's important to note in this regard that knowledge process outsourcing (KPO) firms like Beroe and Smart Cube which do commodity research by relying on inexpensive offshore labor sources are not necessarily the answer here (though they could be valuable).

Rather, companies are augmenting the "arms and legs" these firms and their own resources can provide with true experts on both a global and regional basis for the commodities they track.

With these expert inputs and dashboards, Lisa suggested that advanced teams are setting out statistical modeling for demand planning and forecasting and doing more to correlate factors on the supply side. Central to this is the continual gathering of intelligence and building tools around the approach, constantly looking for correlations and testing hypotheses. As one large, global best-practice commodity management organization recently told Lisa and MetalMiner: "We want to get better at explaining the unexplainable," which is to say they don't just think about predicting where a price might go, but they need to explain to all their stakeholders why prices are rising and falling. For example, what makes up recent volatility increases? When do things correlate? When do correlations break down?

And it goes without saying that best practice commodity management groups are always focused on identifying new sources of supply as well as supply alternatives.

Next up in the conclusion of this series -- applying sourcing optimization tools to commodity management.

Jason Busch

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