Data analysis is a powerful capability that is helping utilities around the world build value in operations, planning and customer relations. As machine data pours in from smart meters and grid sensors, many utilities are deploying analytics that merge multiple data streams to derive awareness and insights and improve customer relationships.
Moving from data to insight is not easy. Recent surveys by the Utility Analytics Institute and Navigant Research indicate that many utilities are struggling to manage the terabytes of data they collect and derive meaningful business intelligence. Data integration is no easy task, but utilities that succeed in breaking down siloes and extracting the actionable intelligence can reap lucrative rewards.
Here is a quick look at some of the areas where utilities can leverage analytics to improve business outcomes.
Improved Grid Operations: By applying analytics to machine data from the grid, utilities can improve their awareness and foresight and operate with greater efficiency and reliability. Data from smart devices can be merged with customer data, weather reports and generation information to enable the use of user-friendly dashboards that improve decision making at all levels, from the field to the board room.
Reliability improves as a utility deploys visualization applications and gains real-time insight into grid and asset conditions. Shutdowns can be avoided when the utility can anticipate failures before they occur and proactively repair or replace assets.
Energy distribution becomes more cost-effective due to accurate predictions of consumption, anticipation of surges in demand and renewable energy generation, and efficient management of increasingly complex sets of generation assets.
Customer satisfaction and regulatory relationships improve when utilities recover from outages more quickly. Leaders can also improve the bottom line by optimizing workforce management and minimizing the loss of power sales.
Asset Management Enhancements: Analytics can leverage multiple data sets to help utilities gain comprehensive views of asset performance and health. Managers can reduce power plant cycling, predict asset failures, and make better decisions about maintenance and lifecycles — all leading to lower capital costs and higher availability.
Better Integration of DERs: Integrating distributed energy resources (DERs) into the grid can be a tremendous challenge. Utilities need to build a solid understanding of how DERs will integrate with other generation assets. Analytics can deliver real-time insights regarding grid conditions, consumption behavior patterns and energy flows. This opens the door to better forecasting and load balancing, while enabling effective management of potentially disruptive voltage swings. Analytics can also support better decisions on DER siting and sizing.
Effective Customer Segmentation: Analytics can help utilities take marketing to a new level by segmenting the customer base, optimizing interactions, and predicting customer behavior. By merging data from customer information systems, call centers, transaction systems and smart meters and applying powerful analysis, utilities can profile customers, identify up-sell and cross-sell opportunities, and predict their response to pricing and energy efficiency programs.
Analytics can also identify patterns in transactions and help utilities develop more effective business rules and processes that enhance customer satisfaction and reduce call center volumes.
Analysis of customer segments can also help utilities predict changes in customer behavior such as conservation and solar photovoltaic adoption and well as to anticipate customer response to new technologies and services.
Revenue Protection: Analytics can help utilities detect patterns in customer behavior and respond proactively to prevent financial losses. For example, correlation of customer payment histories with other data can help a utility spot customers who are at risk of falling behind on their bills. By reaching out proactively, they can reduce the instance of accounts going to collection. Analytics can also process Advanced Metering Infrastructure (AMI) data to detect anomalies that could indicate energy theft.
Stronger Customer Relationships: In locations where deregulation liberates customers to choose non-utility energy providers, it is critical for utilities to deliver a rich customer experience similar to that of a retailer or bank.
Data analysis can help utilities leverage existing relationships and forge deeper ties with customers around their energy consumption. Customers are accustomed to receiving helpful personalized data from other businesses, and they are more likely to value a utility relationship that delivers detailed information and affords them opportunities to tap into reduced energy rates.
Utilities can leverage smart meter data analysis to provide online visual representations of energy usage patterns and forecasts and help customers uncover opportunities to save. They can also use advanced algorithms to disaggregate a customer’s energy usage by appliance and identify energy-wasting appliances. Young customers are more likely to choose or retain a utility that delivers a customer experience similar to that provided by private enterprises.
—John MacKenna, Energy Writer