Data analytics isn’t new to the utility industry. But now the quantity and variety of different data sources have grown so dramatically that managing it all has become a daunting challenge. Asset, transmission, GIS, customer meter, financial, operational, call center, and many other types of data are streaming into utility networks. New techniques for using that data, like automation, orchestration, and machine learning, are providing valuable insights that can impact customer satisfaction and the bottom line.
The digital disruption that is transforming other industries and society at large is also transforming utilities. At the center of this transformation is data. Data is behind improved operational efficiencies, better customer experiences, more efficient utilization of energy, predictive maintenance, faster recovery from outages, and other use cases. The winners in the utility industry are putting data, analytics tools, and dynamic use cases to work to differentiate themselves. They’re using leading technologies like IoT and AI to compete successfully in a rapidly changing market environment.
The utilities that are succeeding in this manner are on the path to becoming intelligent enterprises. This can mean using data and analytics to reduce customer bills and equipment costs with more accurate long-term capacity planning. Or it can mean using blockchain to provide a distributed ledger with untampered certificates on green energy. Other uses of data analytics can empower every business department, partner, supplier, and customer with automated digital solutions, services, products, and actionable intelligence. Intelligent enterprises focus on improving the use of resources, fine-tuning processes, developing new business models, and anticipating future needs.
Strategic priorities for utilities include:
- Equipping personnel with real-time customer insights
- Operating more efficiently to lower costs
- Aligning energy production and consumption with market demand
- Using digital solutions to predict prevent and recover from outages
From our global experience working with the leading, most innovative utilities, here are three SAP “next practices”— capabilities and outcomes to help your company utilize data and analytics on a grand scale.
1. Integrate your diverse data sources
Data is the currency of digital transformation. Yet within most utility companies, data is scattered among multiple applications, files, data warehouses, data lakes, and public and private clouds.
Next practice #1: Integrate your data by combining data sets — including big data, process data, product data, analytical data, etc. — as needed, into a single data universe for much greater visibility.
2. Analyze your diverse data
Next practice #2: Integrate your data sources, using orchestration and governance solutions. Go from raw feed to intelligence with real-time analysis of vast data sets. How? With solutions to understand, integrate, cleanse, manage, associate, and archive data to optimize business processes and analytical insights.
3. Simplify your data landscape
Today, utilities often lack a 360-degree view of their data and data landscape. With different databases, apps, and clouds to support, no centralized solutions are being used to manage it all. Intelligent utility enterprises use process automation and a centralized, easy-to-use platform and interface to simplify access to data so line-of-business managers can participate with data specialists in the development of creative products and solutions. Stakeholders assigned to an architecture team within your company can collaborate through a user-friendly Web application in the planning, design, and governance of the architecture.
Next practice #3: Create and maintain a complete landscape architecture that is easy to share and understand. Open up this landscape to an array of company employees and managers to jointly manage your data environment as an agile, strategic tool.
A growing number of data analytics use cases for utility companies
Data analytics is being recognized as a vital tool for utilities that need to innovate faster than the competition, create new markets and design new products quickly, and attract and retain customers. The need for speed has grown — along with the diverse types and quantity of data. Becoming a truly intelligent enterprise requires a reliable, easy-to-use platform to capture, ingest, process, orchestrate, compute, and consume data at tremendous scale.
SAP customers in the utility industry that are intelligent enterprises are using data analytics fed by an increasing array of data sets for use cases that include:
- Short-term load forecasting for higher load utilization and less idle reserve capacity
- Asset data quality to make better use of data currently residing in silos and seamlessly process large data sets across highly distributed landscapes
- Long-term load capacity planning to extend the life of transformers by years and reduce time for forecasting and grid optimization
- Transformer survival analysis to identify needs for infrastructure investments earlier and improve compliance by generating auditable analyses
- Renewable energy distribution using blockchain to trade green energy and balance renewable supply and demand
These are just some of the many quickly evolving, creative ways that larger and diverse data sets are being put to work to guide utility companies today. Some use cases are relevant to every type of organization within the industry. Others are more suited to different types of businesses, geographies, markets, and other unique characteristics.
For more on how utilities around the world are transforming into intelligent enterprises, read the new SAP white paper “The Intelligent Enterprise for the Utilities Industry.”
And please listen to the replay of our “Pathways to the Intelligent Enterprise” Webinar, featuring Phil Carter, chief analyst at IDC, and SAP’s Dan Kearnan and Ginger Gatling.