Uniper, a major German energy company, focuses on the production, trading, and supply of electricity, natural gas and other energy-related products. A diverse portfolio of power plants makes Uniper one of Europe's leading energy producers.
I recently had the opportunity to have an insightful conversation with @sneha_mascarenhas , Uniper’s head of process automation, where she shared the key factors have driven her company’s successful automation program for more than eight years. Early on, Uniper recognized the need to centralize the automation efforts and to serve as a single point of contact for stakeholders in the organization. Over time, she built a sizable team automation professionals who manage 80 SS&C Blue Prism digital workers.
Sneha told me that she feels a strong operating model is the most important element for building and scaling a successful intelligent automation (IA) program. She said, “this is where you define who does what and determine where the responsibilities lie — like who will be responsible process assessments, creating the backlog and finding the best technology. A clear process assessment is your starting point.”
As a result of this philosophy, Uniper has a robust and effective Center of Excellence (COE) that delivers an end-to-end service to their internal stakeholders for the full lifecycle of their automations. They conduct process assessment, ensuring each process automation is streamlined and a good fit for the technology. Additionally, the COE provides guidance, shares best practices and manages the automation infrastructure.
Sneha also gave a few examples of impactful use cases. One particularly innovative one combines SS&C Blue Prism digital workers with optical character recognition (OCR) and machine learning (ML). Before repair work can begin in a power plant, a PDF form must be filled out detailing the work order. Since the power plants are located in multiple different countries, these PDFs are filled out in the local language. Uniper’s team built an automation that uses OCR to extract the data from the PDF and ML to decipher the language for each work order. Once this is complete, the digital workers deposit the work order into SAP so that work can begin.
What to hear more advice from Sneha? Jump over to our on-demand webinar to listen to the full conversation.
