In a world where every trade brings its own set of responsibilities and risks, how can commodity businesses stay ahead?
Commodity businesses face ever increasing challenges from a multitude of different sources. While it’s always been a complex business, the intricacies have increased exponentially with the advent of issues and challenges like net zero, sustainable practices, and complex geopolitics. These days, simply finding and executing what looks like a profitable trade brings along with it innumerable other responsibilities, reporting requirements, and legal issues. Connecting the trade and all the complexities that might need to be managed and reported is a tall order adding risk and reducing profitability.
Commodity businesses increasingly need more agility to address the rapidly changing business environment – with trends towards faster, more cost-efficient, and automated processes. There is a real need to improve supply chain efficiency and optimise asset values through improved operational performance. And on top of this, there is an ever-increasing emphasis on managing risk of all kinds, from geopolitical risks such as trade wars to market and price, credit, legal and operational risk.
Trade finance has become another key area to manage, not least of all because data demands from internal teams, partners and regulators have all increased. Traditional sources of finance such as large banks have either exited the business due to the perceived risk levels or demand an increasingly rigid set of preconditions, increasing the already significant reporting burden on traders. Here geopolitics is also in play as financing can be used to instil certain western mandates on issues like climate, sustainability and so on. This is often unpalatable in other parts of the world, which may look to alternative sources of funds that are perceived to be less onerous on the lender or, seek more innovative approaches to financing, such as using PPAs or alternative funding sources. The financing area is also complicated by sanctions, political shifts in currencies and attempts to normalise transactions in alternative currencies to the US Dollar, and other such issues.
As the pace of trading increases because of technology deployment like algo trading, for example, and a need to trade shorter increments, access to data also becomes increasingly important. There is more data of all types available than ever before, with various companies exploring how satellite data, for example, can lead to better optimisation and decisions. This data all needs to be accessible, analysable, and presented in a format that allows people to visualise and get insights from it but most importantly, it needs to be available in the right place, at the right time and of reliable quality and latency. Hence, data management is an important issue in most commodity firms.
Most trading organisations are already attempting to respond to these challenges as they arise, incorporating new job roles or responsibilities alongside digital point solutions. But the problem with this approach is that, in failing to create a holistic view of all the current challenges, the business creates additional inefficiencies and operational risk. Almost everywhere one looks in almost all commodity businesses, there is repetition and doubling down on activities. In part, this seems to be caused by traditional siloed organisational structures where departments use various types of data to perform specific business activities and create other types of data. Both the input data as well as the output data is often also needed in other parts of the business, yet these data sources are often local and department-specific perhaps even stored in spreadsheets. The current emphasis on data management and digitalisation is in part one attempt to solve this inefficiency.
Another aspect of this problem is lack of standardisation within the industry. While periodic attempts are made to standardise various types of data, the usual result is failure because most companies view what they do as proprietary, strategic, and competitive. Many attempts at creating data standards then result in a standard with exceptions and add-ons – i.e., not a standard at all! While standardisation of various types of data could help significantly with streamlining business processes and data sharing, it seems unlikely to happen so what is the alternative to this approach?
If you’re curious to learn more about how to simplify complexity in commodity trading, read our full whitepaper.
Want to read more?
Subscribe now for monthly updates
By submitting your details you agree that we can store your data and communicate with you. You can opt out of these communications at any time. Read all in our Privacy Policy.
