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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

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The enterprises that will define the next decade are not the ones that deployed the most technology. They are the ones who understood what their technology was actually doing. That distinction is not a philosophical point. It is the central operational challenge facing every organization that has spent the last five years modernizing at speed ...

AI is becoming the operating system of the enterprise. It acts as an invisible coordination layer that understands intent, connects systems, and executes work across complex SaaS environments. Previously, employees had to click through multiple systems — CRM, ERP, support tools, collaboration platforms — to complete a single task. Now, instead of navigating each application manually, they can simply state what they need to accomplish ...

In 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become  more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs  for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...

Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...

Cloud spending is no longer viewed as a passthrough IT expense, but as a strategic financial lever that directly impacts innovation capacity, profitability and enterprise resilience, according to the CFO Cloud Cost Optimization Report from Azul ...

As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

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