How Commodity Analytics is Driving Efficiency in Dry Bulk Trading

Carlo Robiati

Dry bulk commodity trading can be a complex and rapidly evolving process, characterised by volatile price trends, changing regulations, and shifting supply and demand patterns. Access to up-to-date and meaningful commodity analytics data is critical for anyone involved in the production, consumption or trading of commodities, as it provides valuable insights into dynamic changes in the market. As technology evolves, commodity data analytics tools bring transparency and efficiency to an otherwise opaque sector helping organisations to make informed decisions related to the buying and selling of dry commodities.

How commodity data analytics provide a competitive edge

Commodities such as coal, iron ore, and grain are indispensable raw materials for industries like steel, construction, and agriculture. The supply and demand of these products can be influenced at any given time by a range of factors which can affect production volumes, transportation routes, shipping rates, and stockpiles.

Modern technology enables the collection and analysis of unstructured, disparate, and lagged commodity data and turns it into meaningful information. Artificial intelligence (AI) algorithms and modelling tools are capable of processing, analysing, and interpreting this complex data and identify patterns in global trade. Fused with satellite imagery and maritime data, innovative commodity analytics tools such as the DBX Platform can provide not only real-time monitoring and tracking of the global dry bulk commodities supply chain, but also predict future market trends. Utilising commodity data analytics organisations can mitigate risk, select the most cost-effective shipping routes, choose the best timing of shipments, optimise operations, and comply with regulations.