| | JUNE 20258E ERGYTech ReviewIN MY OPINIONNATURAL LANGUAGE PROCESSING AND FORECASTING OF ENERGY PRICES­A MASSIVELY MISSED OPPORTUNITY FOR OUR INDUSTRYBy Erin Boyd, Chief Digital Commercial Transformation Officer, The AESNatural language processing-while you may not know it by its official name, this field of artificial intelligence is no doubt an inescapable part of your daily life. Whether it be asking Alexa the temperature, dictating to Siri a text message, verbally providing your four-digit pin after stating the reason you're calling the bank, all before ever speaking with a live agent, even your spam filter and spell check, these are but a handful of the countless examples of natural language processing's pervasiveness in everyone's everyday life. Natural language processing, or NLP, is a field of artificial intelligence that enables computers to understand, interpret and manipulate human language. Combining the power of computer science and computational linguistics to make human language intelligible to machines, NLP enables your computer to extract meaning from text and speech and respond or react appropriately. The power and potential use of NLP are immense. Large-scale analysis can be automatically performed to glean insights and meaning from massive amounts of unstructured text data - think social media comments, customer support tickets, online reviews, news reports, etc. Routine processes can be automated in real-term to efficiently and accurately sort and route information 24 hours a day and without the need to ever interact with a human. The sentiment of your customers about your company and their interactions with it can be quickly gleaned. For an industry ripe with complexity and industry-specific language, NLP is a boon as it can be tailored to the energy industry's many intricacies and acronyms. This powerful capability, however, is not being fully advantaged by us. Rather, our use of NLP in the industry, and particularly utilities, is in sticking with the obvious and, dare I say it, mundane--interactive voice response in call centers, capturing customer satisfaction, automating the routing of certain requests or documents. While these are all undoubtedly valuable, we are missing a massive trick in one of the most foundational elements of our business ­ forecasting prices. For an industry so dependent on managing energy price risk, we are woefully behind. NLP's capability to forecast prices has already been discovered and deployed by the financial industry, with this success being chronicled in academic journals and via financial blog gurus alike. That NLP is a natural transition in the mainstream forecasting journey is not surprising. To illustrate why, allow a brief sidetrack in the form of a history lesson.Prior to the 1980s, economic theory, and with it finance, a subfield of economics, was dependent on the fundamental psychological assumption that individuals and firms, or what we'll refer to as economic agents, are rational. When new information arrives, economic agents immediately update Erin Boyd
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