Industry Insights
Resourcefulness Insight Report: Taking Operational Efficiency to the Next Level with Data Analytics
November 08, 2022
Every year, Itron’s Resourcefulness Insight Report outlines the impact current and future challenges will have on the grid and actions utilities can take to prepare. This year, the report examines the growing use of data analytics among cities and utilities in five countries, and how data-driven insights are helping them create more efficient services and unearth new opportunities.
The report outlines key use cases that demonstrate how real-time insights are driving transformation in the energy industry and enabling utilities to better manage energy and water resources for their communities. This includes improving operational efficiency, developing new revenue streams, supporting sustainability and renewables, providing personalized customer insights, managing extreme weather and enabling smart cities. We are excited to introduce our Resourcefulness Insights Report blog series that will explore each of these six use cases, assess the results we’re seeing and unpack how other cities and utilities can follow suit.
To kick off the series, let’s take a closer look at how cities and utilities are making the most of data to improve operational efficiency.
Itron’s 2022 Resourcefulness Insight Report lays out numerous applications of data and real-time analytics ranked by utilities and consumers. To no one’s surprise, the top-ranking application for utility executives is operational efficiency, with 56% ranking it among their top three priorities. According to a Zpryme survey on digital utilities, 56% of respondents want to increase operational efficiency at the business level, while the same percentage (58%) sees removing data silos as essential to achieving department-level operational efficiency.
What does increasing operational efficiency look like?
By gathering and leveraging intelligence from throughout the network, energy and water utilities can better understand consumption trends to enhance capacity planning, increase grid resilience and streamline operations. With an Advanced Metering Infrastructure (AMI) system in place, these benefits and more are in reach for cities and utilities everywhere.
AMI systems, a fundamental component of real-time data analytics, are utilities’ top investment priority today and will continue to be in five years when it comes to enhancing operational efficiency. Back-office analytics rank third today but will rank second in five years. Predictive analytics rank highly in Australia and highest in the U.K.
Virtually the entire list of utilities’ priority investments is directly tied to the larger effort to derive insights from real-time data. These solutions either generate insightful data or drive insights on their own.
Is the investment worth it?
To put it simply - yes. Although the investment upfront is significant, the savings in the long run are substantial and offset the initial investment.
Just ask Commonwealth Edison (ComEd). The utility anticipates saving $2 billion over the course of 20 years due to operational improvements and other outcomes resulting from a single smart grid that supports numerous applications. For example, ComEd deployed Itron’s Operations Optimizer analytics modules for AMI operations, grid operations and revenue assurance across more than 4 million smart meters, 6,300 critical distributed automation (DA) devices and 750 smart streetlights. ComEd saves $100 million annually through automation, analysis and process improvement and returns those savings directly to customers. The company also anticipates a 65% decrease in operating expenses for smart streetlight OpEx.
Maximizing operational efficiency is a key step in the process of creating more resilient grids and enables utilities to address the challenges of today while preparing for more to arise. Read the full 2022 Resourcefulness Insights Report visit www.itron.com/resourceful and stay tuned for more blogs in our series to learn how utilities and cities are making the most of data.
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