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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

Hot Topics

The Latest

AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...