Predicting Future Commodity Developments

The world is always being surprised by the size of commodity-market changes. For something as basic and well understood as commodities, you would think it would be straightforward to predict future outcomes. But experts, strategy makers, and leaders generally fail in this regard—often big time—because social interactions, business dynamics, geopolitical forces, and the bio and physical forces of the earth unfold in complex ways, shaping commodities supply, demand, and price in unforeseen ways, and making prediction impossible. Still, policy and strategy makers have made some progress in the last fifty years. For a start, we know much more about how complex systems operate, and we have learned techniques for characterizing complex environments and projecting possible outcomes so policy and strategy makers in the face of all the uncertainty can make better decisions.

The language of complex social-physical systems provides us a tool for understanding many global trends and creating strategies for how we might respond. What is a social-physical system? It is a complex dynamic of social, political, economic, physical-environmental forces interacting with each other as one interlinked system. Every player in the system is a stakeholder, playing a role and acting in that system. Change in one type of force, social or economic or physical, inevitably affects the others, and it’s not possible to understand the dynamics of one arena in isolation from the others. Social-physical systems can be defined at many levels or scales: the highest level is the Earth system, but any real world issue, like the copper commodity market, the urbanization of Southern California, the development of renewable-energy sources in Europe, or the development of Russian oil and gas reserves above the Arctic Circle, can be defined as a social-physical system. At whatever the level or scale, the result of the cross-acting social-physical forces is a complex adaptive system that behaves in nonlinear ways and is largely unpredictable.

Resilience Thinking and Complex Systems

Much of my understanding of the basic dynamics of a complex adaptive system comes from a small but brilliant book called Resilience Thinking: Sustaining Ecosystems and People in a Changing World by Brian Walker and David Salt. This book provides a great framework for understanding a social-physical system and very useful metaphors for visualizing such a system.

According to Walker and Salt, the complexity of the many linkages, actions, and effects that make up a social-physical environment system is such we can never predict with certainty what the exact response will be to any act or input in the system. The system is relatively stable, but the unfolding behavior of the system cannot be predicted by understanding the individual mechanics of the component parts or any pair of interactions.

Another feature of a social-physical system is that it has the potential to exist in more than one kind of stable state in which the dynamics of the specific forces, structure, interactions and responses would be different. A system will transition from one state to another when changes in several interlinked forces result in a crossing of a threshold and the complete reconfiguration of the system to a different state or dynamic. Shocks and disturbances to a system, such as from a natural disaster, market disruption, etc., can push the system across a threshold into a different state or dynamic, often with unwelcome surprises.

Resilience is the capacity of the system to absorb disturbance, to undergo change, without crossing a threshold to a different system state with its different identity and dynamic. This capacity to undergo some change without a radical change in general dynamic is defined as the resilience of the system. The more resilient the system, the more anti-fragile (a term from Nassim Nicholas Taleb, the author of The Black Swan and Antifragile: Things That Gain from Disorder) it is.

In the metaphor of a ball moving in a basin, the ball is the current state of the system. The basin in which the ball is moving is the set of possible states that can be reached by the system with the general dynamic of the interlinked forces. The system is stable as long as the ball stays in the basin. The boundary or lip of the basin is the threshold. Within the basin, the ball tends to roll to the bottom. In system terms it tends toward some equilibrium state. The shape of the basin is always changing as external conditions change and so is the position of the ball. The net effect is the system is never in equilibrium (i.e., with the ball stuck at the bottom). The distance of the ball from the threshold measures the system’s resilience. The resilience of the system is how much change can occur in the basin and in the ball’s (i.e., the system’s) trajectory before the ball (system) leaves the basin. The closer one is to the threshold, the less it takes to be pushed over. If the conditions cause the basin to get smaller or the ball to be moving faster, resilience declines, and the potential of the ball (system) to cross into a different basin becomes easier.

While social-physical systems involve many interlinked forces, their trajectories in a basin are often governed by only a handful of driving forces. To prevent the ball from leaving the basin, it would be important to identify and understand the drivers that could cause the ball to cross the threshold, know where the threshold actually is, and enhance those aspects of the system that would enable it to remain resilient or adaptable. This can include moving the thresholds, moving the current state of the system away from the threshold, or making a threshold difficult to reach. If the system is stuck in an undesirable basin dynamic, it might be impossible or too expensive to manage the threshold or system’s trajectory, and it might be necessary to transform the very nature of the system.

The scale of the system that we’re focused on (usually a global market or geographic region) is connected to and affected by what’s happening at the scales above and below, both in time and space. For example, the annual maintenance activity for an urban highway system is linked to the longer scale for transportation investments in that urban area that are linked to business growth in the region and demographic changes, etc. At each scale, the system is changing, but the linkages across scales play a major role in determining how the system at another linked scale is behaving. Disturbances at lower scales can influence the dynamic of a system at a higher scale. In the end, every system is composed of a hierarchy of linked morphing systems operating at different scales (both in time and space).

So What Insights about Commodities Can We Develop with This Complex-Systems Lens?

Change is normal: Plan for Change. One reason commodities markets are constantly changing is technology innovation. Innovations can help lower production costs, develop new production sources, create new products, and enable increased demand. They can’t be individually predicted, but a wide variety in innovations will shape commodities outcomes throughout the world for the foreseeable future. The scope and scale of impacts on commodities from technology innovation:

  • Agriculture-seed hybrids and herbicides. Technology innovation by large corporations has had a tremendous impact on global food supply and the costs of food. Several large companies like Monsanto, Syngenta, Bayer, Dow Chemical, BASF, and DuPont now dominate the business of food supplies. A key competitive factor for these companies that drives corporate decisions is their ability to innovate in the future.
  • Commercialization of solar energy. The demand for solar-energy solutions is a major factor in national energy policies in both developed economies as well as developing economies. That demand is directly influenced by the production costs of the solar solutions as well as the cost of production for competitive hydrocarbon supplies. Africa is a continent with a lot of sun. It’s also a continent that lacks electricity in many parts. The rapidly falling costs of solar panels may mean that much of Africa’s growth in electricity demand could be supplied by solar.
  • Cyberattacks on financial institutions. Commodity markets are global, and buyers and sellers in different parts of the world depend on a secure global payments systems. The Society for Worldwide Interbank Financial Telecommunications (SWIFT), a network that banks use to move money around the world, recently announced its concern about cyber-heists. Experts believe many attacks have yet to be discovered because the criminals are always getting better.

Future market outcomes can’t be predicted because of the complex interactions of market, political, economic, social, and environmental forces.

  • Global Economy. Most commentators discuss the world economy as if it’s a static system where good logic should enable reasonable projections in the short term (the next year) and the long term (the next decade). Because the global economy is a complex system, it’s just not possible to predict anything. A recent headline in January 2016 in the Wall Street Journal before the World Economic Forum in Davos said, “Welcome to the Crisis Economy, Where Tumult Reigns.” The article argued the “economic and geopolitical outlook appears more unsettled this year than in the past” because of the uncertainties in geopolitics, commodities, energy, and the financial markets. But that unsettled state didn’t stop the article from including projected single-point growth rates for China, the United States, Japan, Russia, and the Eurozone for 2016. The article was correct to highlight the important uncertainties facing the world. But it should not have shown single-point forecasts for the different nations. Instead it should have argued that when tumult reigns the range of potential economic outcomes for the different nations in 2016 could be quite wide and then it should have provided some indication of those ranges. So instead of saying the growth rate for China’s GDP was going to be 6.3% in 2016 compared to 6.8% in 2015, it should have said the growth rate for China’s GDP could be as low as 3% and as high as 8%. This range of 3% to 8% has a very different implication for commodities markets than the single point of 6.3%.

Extreme change may indicate a threshold boundary is about to be or has been breached.

  • A recent article in The Economist on May 28, 2016, “Global Warming: In the red. The end of El Niño sees temperatures soar across the world,” said that the current year would most likely be the warmest on record, and by a wide margin. A major factor in the high heat could be the just-ending El Niño, the Pacific Ocean dynamic of changing atmospheric heat and moisture. The article makes links between the recent high temperatures, the ocean’s heat-storing abilities, and climate change, but says those are tenuous, and that “the complexity of climate systems means temperature variations cannot be explained by a single cause.” For those watching though, the ball might have just left the basin. Supply of agricultural commodities is affected by both the immediate and long-term heat and moisture changes in the atmosphere and clearly will be severely impacted by future higher temperatures. At the same time, warmer temperatures in the upper-latitude and Arctic areas could change the mineral and metal supply opportunities. New sources for many materials may become financially viable in the next 20 years.

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