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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

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While 87% of manufacturing leaders and technical specialists report that ROI from their AIOps initiatives has met or exceeded expectations, only 37% say they are fully prepared to operationalize AI at scale, according to The Future of IT Operations in the AI Era, a report from Riverbed ...

Many organizations rely on cloud-first architectures to aggregate, analyze, and act on their operational data ... However, not all environments are conducive to cloud-first architectures ... There are limitations to cloud-first architectures that render them ineffective in mission-critical situations where responsiveness, cost control, and data sovereignty are non-negotiable; these limitations include ...

For years, cybersecurity was built around a simple assumption: protect the physical network and trust everything inside it. That model made sense when employees worked in offices, applications lived in data centers, and devices rarely left the building. Today's reality is fluid: people work from everywhere, applications run across multiple clouds, and AI-driven agents are beginning to act on behalf of users. But while the old perimeter dissolved, a new one quietly emerged ...

For years, infrastructure teams have treated compute as a relatively stable input. Capacity was provisioned, costs were forecasted, and performance expectations were set based on the assumption that identical resources behaved identically. That mental model is starting to break down. AI infrastructure is no longer behaving like static cloud capacity. It is increasingly behaving like a market ...

Resilience can no longer be defined by how quickly an organization recovers from an incident or disruption. The effectiveness of any resilience strategy is dependent on its ability to anticipate change, operate under continuous stress, and adapt confidently amid uncertainty ...

Mobile users are less tolerant of app instability than ever before. According to a new report from Luciq, No Margin for Error: What Mobile Users Expect and What Mobile Leaders Must Deliver in 2026, even minor performance issues now result in immediate abandonment, lost purchases, and long-term brand impact ...

Artificial intelligence (AI) has become the dominant force shaping enterprise data strategies. Boards expect progress. Executives expect returns. And data leaders are under pressure to prove that their organizations are "AI-ready" ...

Agentic AI is a major buzzword for 2026. Many tech companies are making bold promises about this technology, but many aren't grounded in reality, at least not yet. This coming year will likely be shaped by reality checks for IT teams, and progress will only come from a focus on strong foundations and disciplined execution ...

AI systems are still prone to hallucinations and misjudgments ... To build the trust needed for adoption, AI must be paired with human-in-the-loop (HITL) oversight, or checkpoints where humans verify, guide, and decide what actions are taken. The balance between autonomy and accountability is what will allow AI to deliver on its promise without sacrificing human trust ...

More data center leaders are reducing their reliance on utility grids by investing in onsite power for rapidly scaling data centers, according to the Data Center Power Report from Bloom Energy ...