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8 Takeaways on the State of Observability for Energy and Utilities

Peter Pezaris
New Relic

In June, New Relic published the State of Observability for Energy and Utilities Report to share insights, analysis, and data on the impact of full-stack observability software in energy and utilities organizations' service capabilities.

  

Source: National Grid

Here are eight key takeaways from the report:

1. Outages Cost Energy and Utilities Companies More than Any Other Industry

The report found that high-impact-outages affect energy and utilities more than any other industry, with 40% experiencing outages at least once per week compared to 32% across all other industries surveyed. Consequently, the median annual downtime for energy and utility organizations was 37 hours, with 61% of respondents reporting that their mean time to resolve (MTTR) is at least 30 minutes to resolve outages. Each second during an outage comes with a price tag. More than half of energy and utilities organizations (52%) shared that critical business app outages cost at least $500,000 per hour, and 34% indicated that outages cost at least $1 million per hour.

2. Observability Increases Productivity

Since adopting observability solutions, energy and utilities companies have experienced substantial productivity improvements. Of those surveyed, 78% said their MTTR has somewhat improved. Further, organizations with full-stack observability noted even more significant MTTR progress, with 87% reporting improvements.

3. Increased Focus on Security, Governance, Risk, and Compliance is Driving Observability Adoption

For energy and utility organizations, the top technology trend driving the need for observability was an increased focus on security, governance, risk, and compliance (44%), followed by the adoption of Internet of Things (IoT) technologies (36%) and customer experience management (36%).

4. Observability Tooling Deployment is on the Rise

Organizations are prioritizing investment in observability tooling, which includes security monitoring (68%), network monitoring (66%), and infrastructure monitoring (60%). Notably, energy and utility organizations reported high levels of deployment for AIOps (AI for IT operations) capabilities, including anomaly detection, indecent intelligence, and root cause analysis (55%). In fact, by mid-2026, 89% of respondents plan to have deployed AIOps.

5. Energy and Utilities Companies are More Likely to Use Multiple Monitoring Tools

Energy and utilities organizations showed a higher tendency than average to utilize multiple monitoring tools across the 17 observability capabilities included in the study. In fact, three-fourths (75%) of respondents used four or more tools for observability, and 24% used eight or more tools. However, over the next year, 36% indicated that their organization is likely to consolidate tools.

6. Organizations are Maximizing the Value of Observability Spend

Out of all industries surveyed, energy and utilities organizations indicated the highest annual observability spend, with more than two-thirds (68%) spending at least $500,000 and 46% spending at least $1 million per year on observability tooling. In turn, organizations are planning to maximize the return on investment (ROI) on observability spending in the next year by training staff on how best to use their observability tools (48%), optimizing their engineering team size (42%), and consolidating tools (36%). Energy and utility companies stated that their organizations receive a significantly higher total annual value from observability than average, with 76% reporting receiving more than $500,000 from its observability investment per year, 66% stating $1 million or more, and 41% attaining $5 million or more per year in total value. The numbers reported around annual spending and annual value received reflect nearly a 3x median ROI, or 192%.

7. Observability Increases Business Value

Energy and utilities companies reported that observability improves their lives in several ways. Half of IT decision-makers (ITDMs) expressed that observability helps establish a technology strategy, and 46% said it enables data visualization from a single dashboard. Practitioners indicated that observability increases productivity so they can detect and resolve issues faster (43%) and allows less guesswork when managing complicated and distributed tech stacks (35%). Respondents also noted benefits enabled by observability, including increased operational efficiency (39%), improved system uptime and reliability (35%), security vulnerability management (35%), and improved real-user experience (29%). Ultimately, organizations concluded that observability provides numerous positive business outcomes, including improving collaboration across teams to make decisions related to the software stack (42%), creating revenue-generating use cases (35%), and quantifying the business impact of events and incidents with telemetry data (33%).

8. The Future is Bright for Observability Tooling Deployment

Energy and utilities companies are enthusiastic about their observability deployment plans over the next one to three years. By mid-2026, 99% of respondents expect to have deployed several monitoring tools, including security monitoring, database monitoring, and network monitoring, followed by 96% of organizations anticipating alerts and application performance monitoring. Methodology: New Relic's annual observability forecast offers insights into how observability influences organizations and their decision-makers. To gauge the current observability landscape, professionals from various industries and regions were surveyed. Among the 1,700 technology practitioners and decision-makers surveyed, 132 were associated with the energy and utilities sectors.

Peter Pezaris is Chief Design and Strategy Officer at New Relic

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8 Takeaways on the State of Observability for Energy and Utilities

Peter Pezaris
New Relic

In June, New Relic published the State of Observability for Energy and Utilities Report to share insights, analysis, and data on the impact of full-stack observability software in energy and utilities organizations' service capabilities.

  

Source: National Grid

Here are eight key takeaways from the report:

1. Outages Cost Energy and Utilities Companies More than Any Other Industry

The report found that high-impact-outages affect energy and utilities more than any other industry, with 40% experiencing outages at least once per week compared to 32% across all other industries surveyed. Consequently, the median annual downtime for energy and utility organizations was 37 hours, with 61% of respondents reporting that their mean time to resolve (MTTR) is at least 30 minutes to resolve outages. Each second during an outage comes with a price tag. More than half of energy and utilities organizations (52%) shared that critical business app outages cost at least $500,000 per hour, and 34% indicated that outages cost at least $1 million per hour.

2. Observability Increases Productivity

Since adopting observability solutions, energy and utilities companies have experienced substantial productivity improvements. Of those surveyed, 78% said their MTTR has somewhat improved. Further, organizations with full-stack observability noted even more significant MTTR progress, with 87% reporting improvements.

3. Increased Focus on Security, Governance, Risk, and Compliance is Driving Observability Adoption

For energy and utility organizations, the top technology trend driving the need for observability was an increased focus on security, governance, risk, and compliance (44%), followed by the adoption of Internet of Things (IoT) technologies (36%) and customer experience management (36%).

4. Observability Tooling Deployment is on the Rise

Organizations are prioritizing investment in observability tooling, which includes security monitoring (68%), network monitoring (66%), and infrastructure monitoring (60%). Notably, energy and utility organizations reported high levels of deployment for AIOps (AI for IT operations) capabilities, including anomaly detection, indecent intelligence, and root cause analysis (55%). In fact, by mid-2026, 89% of respondents plan to have deployed AIOps.

5. Energy and Utilities Companies are More Likely to Use Multiple Monitoring Tools

Energy and utilities organizations showed a higher tendency than average to utilize multiple monitoring tools across the 17 observability capabilities included in the study. In fact, three-fourths (75%) of respondents used four or more tools for observability, and 24% used eight or more tools. However, over the next year, 36% indicated that their organization is likely to consolidate tools.

6. Organizations are Maximizing the Value of Observability Spend

Out of all industries surveyed, energy and utilities organizations indicated the highest annual observability spend, with more than two-thirds (68%) spending at least $500,000 and 46% spending at least $1 million per year on observability tooling. In turn, organizations are planning to maximize the return on investment (ROI) on observability spending in the next year by training staff on how best to use their observability tools (48%), optimizing their engineering team size (42%), and consolidating tools (36%). Energy and utility companies stated that their organizations receive a significantly higher total annual value from observability than average, with 76% reporting receiving more than $500,000 from its observability investment per year, 66% stating $1 million or more, and 41% attaining $5 million or more per year in total value. The numbers reported around annual spending and annual value received reflect nearly a 3x median ROI, or 192%.

7. Observability Increases Business Value

Energy and utilities companies reported that observability improves their lives in several ways. Half of IT decision-makers (ITDMs) expressed that observability helps establish a technology strategy, and 46% said it enables data visualization from a single dashboard. Practitioners indicated that observability increases productivity so they can detect and resolve issues faster (43%) and allows less guesswork when managing complicated and distributed tech stacks (35%). Respondents also noted benefits enabled by observability, including increased operational efficiency (39%), improved system uptime and reliability (35%), security vulnerability management (35%), and improved real-user experience (29%). Ultimately, organizations concluded that observability provides numerous positive business outcomes, including improving collaboration across teams to make decisions related to the software stack (42%), creating revenue-generating use cases (35%), and quantifying the business impact of events and incidents with telemetry data (33%).

8. The Future is Bright for Observability Tooling Deployment

Energy and utilities companies are enthusiastic about their observability deployment plans over the next one to three years. By mid-2026, 99% of respondents expect to have deployed several monitoring tools, including security monitoring, database monitoring, and network monitoring, followed by 96% of organizations anticipating alerts and application performance monitoring. Methodology: New Relic's annual observability forecast offers insights into how observability influences organizations and their decision-makers. To gauge the current observability landscape, professionals from various industries and regions were surveyed. Among the 1,700 technology practitioners and decision-makers surveyed, 132 were associated with the energy and utilities sectors.

Peter Pezaris is Chief Design and Strategy Officer at New Relic

Hot Topics

The Latest

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

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