This commentary appeared in the print edition of the Jan. 6, 2020, Journal of Commerce Annual Review and Outlook.
With a predicted slowdown in the global trade outlook for 2020, companies will face increasing pressure on finding efficiency and cost reductions in their supply chains. If they take advantage of today’s technology, they have a huge opportunity to address latent inefficiencies by digitizing processes, improving workflows, and embracing new business models, where data can be shared more efficiently, more effectively, and more securely among permissioned participants involved in the end-to-end shipment cycle.
Global trade is comprised of some of the largest, most complex ecosystems in the business world today, but it is incredibly inefficient, owing to antiquated processes that are cumbersome, reliant on multiple peer-to-peer connections, and often very manual.
It is clear from speaking with customers and network members across the globe for the past two years that our industry is ready for change. Companies and the people that lead them have seen the problems and know there is a better way; and they’re willing to embrace solutions that can help transform their business and our industry. However, replicating what we do today and have done for years is not enough. In fact, it’s the last thing we need to do, and if that’s what we accomplish in the next two years, we will have left far too much on the table as an industry.
New technology brings opportunity for new business models. An open, neutral platform such as TradeLens is one such solution that can benefit all participants. Powered by blockchain, the platform enables permissioned participants to share sensitive data across geographical and organizational boundaries in a structured manner, increasing real-time access and visibility in a more efficient, effective, and secure manner. This technology opens the door to cross-­organizational process efficiencies in ways we haven’t seen before.
However, it is unrealistic to expect any one platform to solve everyone’s problems. Therefore, interoperability will be key. We will continue to work collaboratively with organizations and industry groups such as UN/CEFACT, DCSA and others to establish and adopt common, workable data standards that facilitate adoption of standards across the many and diverse participants in the global supply chain.
As a final point, data quality is critical. AI and machine learning are great new technologies, but if the base data is flawed, the guidance derived will be of little value. Everyone involved in global supply chains has a responsibility and vested interest in improving data quality.