Digitalization in the Energy & Utilities Sector

How Companies are Becoming More Data-Driven and Moving Faster to the Cloud

Every industry is going through digital transformation, and the energy and utilities market is no exception. These companies need to adopt various digital changes in their business models and processes in order to transform the way energy is produced, delivered, and consumed across the value chain. Businesses who find a way to successfully leverage data and provide more accurate information via predictive analytics can improve their operational performance, make better business decisions, and improve the customer experience.

The Drive for Energy & Utilities Analytics

According to the report from MarketsandMarkets, the global energy and utilities analytics market size is expected to grow from $2bn in 2020 to $4.3bn by 2025, at a CAGR of 16.3%. Adoption of smart meters, prioritization of power generation planning, and the need for accurate forecasting are expected to be the key factors driving the growth for the energy and utilities analytics market.

For utilities companies, big data and analytics are essential for gaining a deeper understanding of customer behavior, identifying how to improve solution performance, and gaining insights to better grow their business. With data analytics, energy providers can personalize their programs to maximize customer participation, as well as modernize these relationships to increase engagement.

The renewable energy market is another area that can benefit from big data analytics. According to the report from Mordor Intelligence, solar energy is expected to continue to dominate the renewable energy market, generating much more electricity than wind and hydropower over the next four years. With analytics solutions, utilities can optimize power generation and planning by providing accurate energy production forecasts. 

The Growth of Cloud-Based Analytics Solutions

In the energy and utilities analytics market, there have traditionally been two types of solution providers: software providers and service providers. 

Software vendors — such as TIBCO Software, Oracle, and Intel — offer platforms that deliver predictive analytics and maintenance capabilities, data visualizations for customer information, and power distribution. These platforms help to reduce costs and downtime, as well as improve customer retention by understanding customer consumption patterns and helping improve the customer experience3. Up until recently, software vendors have dominated the utilities analytics market. With the evolution of cloud technologies, however, service providers are gaining more market share.

Service providers — such as AWS, SAS, Google, and Microsoft — help utility companies migrate their analytics to the cloud in order to address issues such as infrastructure scalability, hardware/software costs, and personalized customer experiences. There is no software license or infrastructure to buy, so organizations can reach their efficiency goals by taking advantage of a cloud service’s performance, scale, and ease of use. Cloud solutions offer an elastic, cost-effective storage capacity in which businesses can run complex utility operations, including energy demand and distributed energy forecasting. In fact, MarketsandMarkets expects the adoption of cloud-based energy and utilities analytics solutions to grow significantly due to their numerous benefits (e.g., easy maintenance of data generated, cost-effectiveness, agility, flexibility, scalability, effective solution management).

Cloud-based, data-driven analytics systems are also becoming very important for managing the enormous amount of data being constantly generated by smart meters, IoT sensors, customers’ home energy devices, etc. They help streamline energy efficiency programs and enable utilities companies to deliver flexible power, provide scalability, maintain equipment more easily, and deliver better customer service through more powerful insights. World energy and utilities leaders are already moving their data analytics systems to cloud. For example:

• TC Energy is partnering with AWS to automate workflows, unlock data, and improve efficiency for its pipeline and power generation businesses.
• GE Power runs its key data analytics application on AWS, using Amazon Kinesis Data Streams and Amazon Elastic MapReduce.
• ExxonMobil is collaborating with IBM, Amazon, and other cloud leaders to gain real-time insights from data. This enables them to transform the customer experience by offering consumers new payment options at Exxon- and Mobil-branded service stations in the U.S.
• Exelon uses Oracle products, including Oracle Analytics Cloud, to access a comprehensive view of its customer engagement across all touchpoints at all utilities and offer multi-channel personalized experiences for its industrial customers. 

Case in Point: Smart Oil Condition Monitoring Service Development

GlobalLogic also works with many energy and utilities companies due to our deep domain expertise in big data and analytics. One of our clients, a leading multinational oil and gas company in Europe, provides an excellent example of how utilities companies can transform their operations through intelligent, cloud-based solutions.

The client approached us about developing a new service for their end customers: a cloud-based smart condition monitoring and predictive maintenance solution that would monitor oil conditions and deliver real-time data about an asset’s health. These insights would enable large industrial companies to prioritize assets that require attention, respond quickly to anomalies before failure occurs, and therefore reduce unplanned downtime. By moving away from time-based maintenance to condition-based maintenance, our client’s solution would improve asset utilization and increase productivity.

We initially started the engagement as a research and development project before moving on to evolve the service from a sensor trial phase to a fully-realized, digitally-enabled solution. The end result was a cloud-based solution that delivers real-time insights and enables users to optimize equipment health, lower maintenance costs, and increase operational efficiency. For our client, the solution is generating new revenue for existing and new customers and sectors, upselling lubricants, and being bundled with existing and future services.

Conclusion

By moving away from old legacy systems and using a data-driven, cloud-enabled approach, energy and utility companies are able to lower operating costs and increase efficiency. Big data and analytics also enable them to provide their customers with better service and design programs for more energy savings — thus ensuring customer loyalty.