Connected Strategy for Hydrogen Value Chain ^ Top ^ 38 ROBOTIC PROCESS AUTOMATION (RPA) With implementing RPA, E&U providers who automate their business process recognize a significant decrease in errors, usually over 60%. Fewer errors – more satisfied customers, implies that RPA improves customer service and customer management which is crucial for E&U companies to have a competitive advantage on the market. United Utilities, a United Kingdom-based water company, has been a pioneer in using RPA in automating its back-office processes. Since 2017, they automated more than 20 processes, with another 12 in development. The company´s Head of robots, Wallace Dean says, Compared to traditional IT solutions, RPA can help the E&U industry to drive digital transformation and achieve results quickly with minimal effort. Plus, implementing RPA doesn’t affect or request changes in existing IT systems. As such, employees can use and accept RPA without having IT knowledge. The E&U industry has a wide spectrum of processes that can be automated. Today more than 50% of automation use-cases are found in the E&U industry and most of them are core processes. Even though there is still skeptic opinion about digitalization and automation in the E&U industry, automation front-runners and leading companies see benefits of implementing RPA just in few months, sometimes in a few weeks. Here are some of the real-world use-cases of implementing RPA in core and support functions14:  Energy Trading | British Petroleum (BP) is using automation in its trading function. Ayman Assaf, CIO for compliance, regulatory, risk and finance at BP Supply & Trading says,  Energy Automation Platform | Accuracy and safety are critical for energy utility providers. With the advancements in smart grids, companies seek to offer features like grid balancing and transactional energy solutions. Therefore, utility startups are advancing energy automation with “Automation is allowing us to consolidate data on the trading floor, using RPA to mimic repeated processes. This shifts the role of our analysts, increasingly freeing up their time to focus on higher-value tasks. So rather than collecting data sets, they can spend time interpreting and interrogating the meaning of that data.”