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8 Takeaways from the State of Observability for Industrials, Materials and Manufacturing Report

Nic Benders
New Relic

New Relic's 2024 State of Observability for Industrials, Materials, and Manufacturing report outlines the adoption and business value of observability for the industrials, materials, and manufacturing industries.

Released in August, the report is based on insights from 285 technology professionals and was developed in association with the 2023 Observability Forecast. It reveals that manufacturers invest in observability to optimize uptime, improve productivity, and enable cross-team collaboration and strategic decision-making.

Here are 8 key takeaways from the report:

1. The Fifth Industrial Revolution is in effect

The manufacturing sector's shift into the Fifth Industrial Revolution, known as Industry 5.0, is defined by artificial intelligence (AI), sustainable product development, human and AI collaboration, and lean production practices. Usurping Industry 4.0's focus on the Industrial Internet of Things (IIoT), robotics, 3D printing (additive manufacturing), autonomous vehicles, digital twin simulation, touch interfaces, and virtual reality systems.

2. Observability is vital to reducing outages for manufacturers

Despite spending less on observability annually than most other industries, they had a higher proportion of observability capabilities currently deployed and more achieved full-stack observability than average. As a result, these industries experience outages less frequently, enjoy less annual downtime, and have lower outage costs than average. 30% reported outages at least once a week, compared to the average of 32%. Manufacturing organizations that had achieved full-stack observability saw a substantial improvement in their mean-time-to-respond (or MTTR), with 34% reporting an improvement of 25% or more since adopting observability. Additionally, just 12% of respondents estimated outages cost their organizations more than $1 million per hour compared to 21% across all industries.

3. Security is the biggest driver of observability adoption

The manufacturing industry must adhere to security, safety, and compliance requirements, standards, and guidelines set by governments and local and international organizations, such as the International Organization for Standardization (ISO), Society of Automotive Engineers (SAE), Defense Information Systems Agency (DISA), and Food and Drug Administration (FDA). As a result, the top technology strategy or trend driving the need for observability among industrials, materials, and manufacturing organizations was an increased focus on security, governance, risk, and compliance (50%). Regarding actual observability deployments, security monitoring was the most widely deployed capability and a higher proportion than average (78% in manufacturing compared to 75% for all industries).

4. AI is a core driver for observability

As a core pillar of Industry 5.0 in the manufacturing sector, organizations have already added AI solutions and capabilities to their tech stacks, a trend that will continue in the coming years.

The powerful combination of technologies like observability and AI creates more significant insights into telemetry data and is crucial to addressing the surmounting complexities of growing data sets. Observability is critical to the success of AI since it helps teams understand their telemetry data and how to improve MTTR and enables developers to easily apply fixes to code-level errors in their integrated development environment (IDE). It also increases automation for rapid alerts while improving incident detection and resolution. As a result, according to this year's report, 44% indicated that the adoption of new AI technologies in the manufacturing sector drove their need to onboard observability solutions. Just behind AI, 43% said IoT technologies contributed to the need for observability adoption.

5. They are moving toward tool consolidation

Industrials, materials, and manufacturing organizations continue to move toward tool consolidation to understand the different aspects of their business and avoid costly outages. This sector's low overall observability spending is likely due to the lack of tools. Industrials, materials, and manufacturing organizations were less likely than average to use multiple monitoring tools for the 17 observability capabilities included in this report. Three-fifths (61%) used four or more tools for observability compared to 63% overall. And 16% used eight or more tools compared to 19% overall.

The proportion of respondents using a single tool has increased since last year, growing from 3% to 4%. Additionally, the average number of tools has gone down by almost one tool, from an average of six tools in 2022 to five tools in 2023.

These figures indicate that industrial, materials, and manufacturing organizations are moving toward tool consolidation to understand the different aspects of their business and avoid costly outages.

6. Observability can prevent global supply chain disruptions

Critical outages can be particularly disruptive to carefully calibrated, intricate, and tightly scheduled global supply chains, putting business-to-business relationships and crucial revenue at risk. Yet, manufacturers are seeing improvements in their incident response timing, with 65% indicating their MTTR has improved since adopting an observability solution. Further, in the coming year, industrial, materials, and manufacturing organizations are expected to face an increase in supply chain disruptions, indicating that the time to tighten up and adjust their tech stacks to address vulnerabilities or make further deployments is now.

7. Observability improved job roles, performance, productivity, and team collaboration

Nearly half (43%) of IT decision-makers in the manufacturing sector said that observability made their jobs easier. Among IT practitioners, 47% said that it increases productivity since it allows them to find and resolve issues faster, and 31% said it enables less guesswork when managing complicated and distributed tech stacks. 45% indicated that observability improves collaboration across teams to make decisions related to the software stack — which was second highest across all other industries and 10% more overall.

8. Observability adoption in manufacturing will continue

Given their strong interest in deploying more capabilities in the next few years and a desire for a single platform for observability, this sector will likely continue to move from point solutions to robust observability platforms that provide end-to-end visibility. As technology transforms the industrial, materials, and manufacturing sectors to be ever more reliant on software and data, the need for observability will continue to grow.

Industrials, materials, and manufacturing organizations had ambitious observability deployment plans for the next one to three years. For example, by mid-2026, most are expected to have deployed security monitoring (96%), network monitoring (95%), and alerts (94%).

Nic Benders is Chief Technical Strategist at New Relic

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8 Takeaways from the State of Observability for Industrials, Materials and Manufacturing Report

Nic Benders
New Relic

New Relic's 2024 State of Observability for Industrials, Materials, and Manufacturing report outlines the adoption and business value of observability for the industrials, materials, and manufacturing industries.

Released in August, the report is based on insights from 285 technology professionals and was developed in association with the 2023 Observability Forecast. It reveals that manufacturers invest in observability to optimize uptime, improve productivity, and enable cross-team collaboration and strategic decision-making.

Here are 8 key takeaways from the report:

1. The Fifth Industrial Revolution is in effect

The manufacturing sector's shift into the Fifth Industrial Revolution, known as Industry 5.0, is defined by artificial intelligence (AI), sustainable product development, human and AI collaboration, and lean production practices. Usurping Industry 4.0's focus on the Industrial Internet of Things (IIoT), robotics, 3D printing (additive manufacturing), autonomous vehicles, digital twin simulation, touch interfaces, and virtual reality systems.

2. Observability is vital to reducing outages for manufacturers

Despite spending less on observability annually than most other industries, they had a higher proportion of observability capabilities currently deployed and more achieved full-stack observability than average. As a result, these industries experience outages less frequently, enjoy less annual downtime, and have lower outage costs than average. 30% reported outages at least once a week, compared to the average of 32%. Manufacturing organizations that had achieved full-stack observability saw a substantial improvement in their mean-time-to-respond (or MTTR), with 34% reporting an improvement of 25% or more since adopting observability. Additionally, just 12% of respondents estimated outages cost their organizations more than $1 million per hour compared to 21% across all industries.

3. Security is the biggest driver of observability adoption

The manufacturing industry must adhere to security, safety, and compliance requirements, standards, and guidelines set by governments and local and international organizations, such as the International Organization for Standardization (ISO), Society of Automotive Engineers (SAE), Defense Information Systems Agency (DISA), and Food and Drug Administration (FDA). As a result, the top technology strategy or trend driving the need for observability among industrials, materials, and manufacturing organizations was an increased focus on security, governance, risk, and compliance (50%). Regarding actual observability deployments, security monitoring was the most widely deployed capability and a higher proportion than average (78% in manufacturing compared to 75% for all industries).

4. AI is a core driver for observability

As a core pillar of Industry 5.0 in the manufacturing sector, organizations have already added AI solutions and capabilities to their tech stacks, a trend that will continue in the coming years.

The powerful combination of technologies like observability and AI creates more significant insights into telemetry data and is crucial to addressing the surmounting complexities of growing data sets. Observability is critical to the success of AI since it helps teams understand their telemetry data and how to improve MTTR and enables developers to easily apply fixes to code-level errors in their integrated development environment (IDE). It also increases automation for rapid alerts while improving incident detection and resolution. As a result, according to this year's report, 44% indicated that the adoption of new AI technologies in the manufacturing sector drove their need to onboard observability solutions. Just behind AI, 43% said IoT technologies contributed to the need for observability adoption.

5. They are moving toward tool consolidation

Industrials, materials, and manufacturing organizations continue to move toward tool consolidation to understand the different aspects of their business and avoid costly outages. This sector's low overall observability spending is likely due to the lack of tools. Industrials, materials, and manufacturing organizations were less likely than average to use multiple monitoring tools for the 17 observability capabilities included in this report. Three-fifths (61%) used four or more tools for observability compared to 63% overall. And 16% used eight or more tools compared to 19% overall.

The proportion of respondents using a single tool has increased since last year, growing from 3% to 4%. Additionally, the average number of tools has gone down by almost one tool, from an average of six tools in 2022 to five tools in 2023.

These figures indicate that industrial, materials, and manufacturing organizations are moving toward tool consolidation to understand the different aspects of their business and avoid costly outages.

6. Observability can prevent global supply chain disruptions

Critical outages can be particularly disruptive to carefully calibrated, intricate, and tightly scheduled global supply chains, putting business-to-business relationships and crucial revenue at risk. Yet, manufacturers are seeing improvements in their incident response timing, with 65% indicating their MTTR has improved since adopting an observability solution. Further, in the coming year, industrial, materials, and manufacturing organizations are expected to face an increase in supply chain disruptions, indicating that the time to tighten up and adjust their tech stacks to address vulnerabilities or make further deployments is now.

7. Observability improved job roles, performance, productivity, and team collaboration

Nearly half (43%) of IT decision-makers in the manufacturing sector said that observability made their jobs easier. Among IT practitioners, 47% said that it increases productivity since it allows them to find and resolve issues faster, and 31% said it enables less guesswork when managing complicated and distributed tech stacks. 45% indicated that observability improves collaboration across teams to make decisions related to the software stack — which was second highest across all other industries and 10% more overall.

8. Observability adoption in manufacturing will continue

Given their strong interest in deploying more capabilities in the next few years and a desire for a single platform for observability, this sector will likely continue to move from point solutions to robust observability platforms that provide end-to-end visibility. As technology transforms the industrial, materials, and manufacturing sectors to be ever more reliant on software and data, the need for observability will continue to grow.

Industrials, materials, and manufacturing organizations had ambitious observability deployment plans for the next one to three years. For example, by mid-2026, most are expected to have deployed security monitoring (96%), network monitoring (95%), and alerts (94%).

Nic Benders is Chief Technical Strategist at New Relic

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The Latest

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 ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

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