Utility Analytics

Better targeting, higher response rates and improved campaign ROI. Meaningful, satisfying customer interactions across channels. And cost-effective management of customer outreach programs, sites, products and rates. Our utility analytics solutions propel customer engagement with proven customer analytics capabilities that include:

• Segmentation. Develop highly granular customer segments and models. Understand customers better. And predict how they will act in the future.
  
• Campaign management. Connect the right offers to the right customers. Plan and manage your marketing programs – start to finish – more efficiently and effectively than ever before.
  
• Social media analytics. Understand customer sentiment about your brand, products and services across multiple channels – and its relationship to customer satisfaction.
• Demand-response program analytics. Know how to propel your energy efficiency efforts in collaboration with customer education, both today and tomorrow.

Capture detailed energy usage data from smart meters. Combine it with a well-rounded view of the customer relationship. Then design targeted, automated campaigns, and flexibly adjust your responses to customer, business and market conditions. Utility analytics solutions from SAS help you:

• Know your customers. Cleanse and integrate data from billing and operational systems and third parties. Use text analytics to reveal customer sentiment. And gain an accurate picture of the entire customer relationship across brands, channels and locations.
• Build faster, better models and campaigns. Build models to reflect each customer’s response propensity, attrition potential, cost of service, credit score and more. Model the impact of pricing programs on adoption and revenue. And streamline processes with automation.
• See how to adapt. Actually see how different customer segments consume energy – when, where and why – using data visualization. And predict how they’ll use it tomorrow so you’ll know when to change service offerings or adjust forecasted energy demand.

Optimized resource allocations. Improved planning and capital expense budgeting. And the ability to predict the volume, magnitude and location of demand. Our utility analytics solutions offer a broad, highly sophisticated set of algorithms for energy forecasting, which includes: 

• Load forecasting. Get trustworthy, repeatable and defensible load forecasts for short- to long-term planning horizons.
• Price forecasting. Predict future electricity prices with confidence, using mathematical models.
• Renewable energy forecasting. Know in advance how much wind power and solar energy will be available at any given time.

Harness new data streams to improve, minute-by-minute, how you respond to changing use conditions. Use a variety of advanced analytical tools to understand past trends, forecast the future and see clearly how your business functions. Then share your insights across all levels of the organization. With utility analytics solutions from SAS, you can:

• Build reliable forecasts, quickly. Capture usage information in 15- or 30-minute intervals, then develop models for small time increments. And forecast energy demand at any level of geographic or asset hierarchy, including meter level.
  
• Make better predictions. Convert transactional meter and operational systems data into a forecast-ready format. Use advanced data sets and data models to feed your forecasts and pricing.
• Improve decisions. Make better decisions about the power portfolio, and discover how climate, economic factors and other determinants will affect your forecast with multiple views of trends and correlations. Understand how changes to independent variables will affect demand load and revenue using predictive modeling.

Top-rated protection against revenue losses. Better regulatory relationships. And more effective collection techniques, along with higher revenue and customer satisfaction. Our utility analytics solutions deliver a framework of data management, analytics and reporting to improve:

• Fraud detection. Detect and prevent nontechnical loss, diversion and theft of service.
• Collections optimization. Determine the most effective collections program for every customer.
• Payment analytics. Match your rate programs with the payment plans that are best suited for each customer before a default condition occurs.

Identify fraud, diversion and theft of service quickly and accurately. Ensure that your collections techniques accommodate reasonable care regulations and individual situations. Then determine which collections program, rate or payment plan will work best for each customer. Utility analytics solutions from SAS enable you to:

• Stop revenue leaks. Spot fraud faster and avoid many types of losses using advanced analytics and autoregressive forecasting to identify fraudulent energy usage quickly and accurately.
  
• Optimize collections. Account for sensitive financial transactions and build risk scores for customers based on credit ratings, usage patterns and payment history. Then score payment propensity to determine which collections program will be most effective.
• Use the right resources at the right time. Increase the efficiency of fraud-related resources, including investigators and field assets. Build sustainable cost performance and increase debt recovery.
• Match the right rate and payment plans. Test and optimize treatment strategies using predictive analytics and what-if scenarios. Then decide which combination of rate and payment plans are best to help customers keep their accounts current.

Optimized management of the distribution grid with data-driven analytics. From micro-grids to electric vehicles, achieve better equipment efficiency and higher overall quality. And the ability to accurately predict outages before they occur, while running assets at peak performance. Our utility analytics solutions provide a broad scope of analytic and predictive capabilities to capitalize on investments in the internet of things and give you better results, using:

• Asset reliability analytics. Reduce the number of unplanned outages and optimize maintenance schedules.
• Optimal EV and DER integration. Forecast specific needs and time frames to leverage the right distributed energy resource at the right time, place and cost. 
• Storm analytics. Shrink outage duration by employing analytics before, during and after a storm to improve the effectiveness of your preparation and restoration efforts.
  
• Smart meter analytics. Optimize smart meter deployment and manage timely customer communications to get the most value from your investment.
• Visualize performance. Explore and analyze data from diverse connected grid assets through robust dashboards and interactive maps.
• Predictive maintenance. Integrate data from your historian, ERP and field notes to build predictive models for asset maintenance.
  

Capture and analyze data regardless of format or source to reveal the real triggers behind maintenance issues. Know the best corrective actions to take in each situation – and when to take them. Ensure peak performance by using monitoring, predictive models and alerts issued at predefined thresholds. With utility analytics from SAS you can:

• Accurately predict potential problems. Integrated data – from sensors, inspections, maintenance, inventory, history and warranties – combines with root-cause analysis to reveal the true reasons for performance problems out of hundreds or thousands of measures and conditions.
• Quantify the effects of maintenance plans. Simulate the impact of storms based on vegetation management and other maintenance schedules. Predict vulnerable assets and stage resources prior to adverse events in order to minimize the impact to customers.
• Boost uptime, performance and productivity. Get alerts so maintenance teams can make pending repairs as part of regularly scheduled maintenance. And select the most cost-effective way to replace degrading assets.
• Lower maintenance costs and the risk of revenue loss. Advanced optimization algorithms and solvers expand maintenance cycles without jeopardizing uptime or risking failures. Rapidly diagnose and repair issues with near-real-time insight into performance. And use advanced analytics to make better preparations and restoration efforts before and after storms.