If you follow technologies serving the commodities markets, you will have likely heard of ‘blockchain’. And if you have heard of it, but are still confused about what it might mean for your particular niche of the industry, you’re probably not alone. These days, it seems that many experts, both inside and outside the industry, are holding up blockchain as the panacea to improve any number of commercial processes, from wholesale trade enablement to retail inventory tracking, and everything in between. If one listens to the buzz, you could certainly conclude that blockchain is the Swiss army knife of commerce…but, is it?
Historically, information technology (IT) and operational technology (OT) have developed along separate paths. Today, these two paths are converging, especially at organizations in the manufacturing, commodity, and energy sectors. This convergence is transforming the supply chain, enabling a smarter, more dynamic, more efficient supply chain through data and advanced analytics.
The benefits of using big data and advanced analytics to make better decisions are widely accepted. Making an informed choice is better than using intuition or continuing on your current path and hoping you are on the right one. The more data you have, the more analysis you can do, and the more accurate your assessment of your choices is. But timing matters.
Copper and Iron Ore stockpiles across the world have risen steadily in the last 12 months. Recently there has been news of record levels of iron ore stockpile in China. Apparently there’s enough Iron Ore to build 13,000 Eiffel Towers. As for Copper inventories, one can look at how stockpiles have increased at LME registered warehouses. If one adds increase in bonded copper stocks held in free trade zones in China, to this mix – it will be easy to see how Copper stockpiles have risen over the last 12 months.
Microsoft, Google, Apple, Amazon, IBM, Yelp and Niantic all have something in common. They are leaders in the technology delivering augmented reality. From education, engineering, travel, and healthcare to retail shopping, gaming, and sports – industries are utilizing augmented reality to make a difference in how humans are gathering and visualizing information. How does this impact commodity trading?
According to a recent report from the McKinsey Global Institute, the data analytics revolution has started to gain momentum, but most companies are capturing only a fraction of the potential value from data and analytics. One of the biggest obstacles is data silos. Most of a company’s data is generated and stored in different systems throughout the organization, and these systems are separate, isolated programs.
Anyone observing the Australian energy market would be aware of the steep increase in electricity prices over the last few years. The rise has been so sharp that Australia has one of the highest electricity prices in the world today. Numbers show that real electricity prices for business have increased by almost 60% between 2003 and 2013.
Companies involved with commodities management are very well aware of how price fluctuations, geopolitical risk, and other external factors beyond their control make it very challenging to retain a competitive edge. However, in a volatile business environment where every advantage counts, many companies are still relying on antiquated, error-prone spreadsheets to manage functions including trading, risk management, operations planning, origination, and scheduling.
If your company is still using spreadsheets for commodity or energy trading and risk management (C/ETRM), they most likely contain errors that are already causing irreparable damage.
The rise of big data, computing power, and advanced analytics enables companies to gain valuable insights from data. Artificial intelligence, machine learning, the Internet of Things, and drones are just a few innovative tools now available to help companies gain a more complete view of their businesses and make better decisions. For risk managers, using big data and risk analytics provides an unprecedented ability to identify, measure, and mitigate risk.
Big data is considered “the new oil” because of its tremendous value and its ability to reveal insights once mined and refined, but unlike oil, data is readily available to any company willing to access it. It is being generated constantly from both internal and external sources. Collecting and analyzing all this data requires big data analytics.