Disruptive Technologies – A 2021 Update
A ComTechAdvisory Report
DISRUPTIVE TECHNOLOGIES AND THE IMPACT ON CTRM AND CM It could be argued that the pace and level of change in commodities related industries is unprecedented and the technologies that enable is market is both driving and being driven by those changes. In the end, the industry is evolving towards a more integrated supply chain orientation with an emphasis on optimization, collaboration, efficiency and better controls, and all of this does and will continue to impact CTRM and CM software. As analysts, we have been observing the move away from large monolithic and siloed applications towards ecosystems of more agile and focused applications that use rich API’s to tie them together. Increasingly, these specialized applications are being deployed in the cloud and on cloud infrastructures that provides controllable scalability and improved performance and security. Microservices are increasingly being used within this context. Digitalization is also helping with the elimination of the more obvious manual repetitive processes that plague the industry. Increasingly workflow solutions, RPA, AI and ML are also being deployed to ensure process flow adherence, better operational controls and more streamlining by reduction/automation of common manual processes, with provisions for better identification of exceptions requiring human intervention. We also note a trend towards event-driven calculations and processes. Yet another area of CTRM/CM impact is in enhancing the user experience and provision of advanced data
visualization. While VR and augmented reality may still be a way off in terms of everyday use on the trading floor, innovating better ways to view and analyze data is increasingly becoming a key attribute of the modern CTRM and CM solution. Some vendors, such as FIS, have included 3D visualizations of risk surfaces as part of their native capabilities, more often advanced risk analysis techniques have been accomplished via data integration to solutions such as Matlab which provide more advanced and powerful data visualization tools and capabilities than one might find in most CTRM solutions currently available. Natural language processing (NLP) is being used today in some CTRM solutions, such as Molecule’s ETRM/ CTRM platform, to enable users to more quickly capture deal data. Though perhaps some way off, we may see other, potentially more efficient ways of interacting with CTRM software made available, such as use of voice commands supported by AI. AI and advanced workflow automation may also be used to better enable users to more efficiently navigate multiple screens and applications in order to complete tasks and activities.
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