Transforming Operations, and IT as a Whole, with the Right Technology Investments

Dennis Drogseth

In my last blog, I expressed my opinion that IT operations teams may be about to enjoy a renaissance rather than dismally fading away — but only if they adopt new ways of working, measuring themselves and interacting with business stakeholders.

Start with Is IT Operations Going Away or Is It Enjoying a Renaissance?

In this blog, I'd like to discuss how technology investments can help smooth the way toward operational transformation with a few examples from recent interviews. More specifically, I'd like to focus on three key areas of innovation, all in some way related to Advanced IT Analytics (what some in the industry call IT Operations Analytics or ITOA):

1. How Advanced IT Analytics (AIA) can pave the way

2. How next-generation ITSM promotes AIA-relevant process improvements

3. How AIA and service modeling can become a magic combination

These three areas of innovation are, admittedly, far from a complete list. But hopefully they will offer you a provocative place to start for seeking out transformative IT technologies.

How Advanced IT Analytics Can Pave the Way

Probably one of the hottest, most diverse and most misunderstood areas of technological innovation is AIA. There are a lot of reasons for this, but the most significant reason is that AIA is not a single market but a diverse landscape of options ranging from those bordering on traditional "big data" to those that are focused on real-time predictive insights with tiered approaches to data collection that typically include leveraging third-party tools. The variances here also embrace multiple use cases ranging from performance management to change and capacity optimization to financial optimization to integrated security concerns.

Here are just a few highlights from EMA's recent AIA research focusing on performance, change and capacity management:

■ AIA analytic heuristics range from anomaly detection to predictive trending to machine learning, to rule-based analytics to data mining — as just some examples. On average, our respondents wanted at least four different heuristics.

■ On average, respondents wanted their AIA investments to support 11 different roles (and many more stakeholders), including four domain-specific roles, four cross-domain roles (including executive IT), and three non-IT business roles.

■ The top three achieved benefits were with faster time to repair problems, faster time to deliver new services and more efficient use of cloud resources.

Quoting from a conversation earlier this year:

QUOTE #1: "The move [to advanced analytics] allowed us to unify our operations team with a single-pane-of-glass view and drill down so that we could share information more effectively. In the past, we caught only 3% of our problems proactively. Now that percentage went up to 88% … In effect, we are able to see everything we need to see to focus and resolve issues far more cohesively and dynamically than before."

How Next-Generation ITSM Promotes AIA-Relevant Process Improvements

Next-generation ITSM is in my view pivotal for both IT and IT operational transformation. So what are they? Next-generation ITSM teams are more progressively integrated with operations teams, more proactive, more likely to leverage and share analytics, more likely to provide workflows and automation that unify IT as a whole (as well as support enterprise business process needs), and more likely to provide meaningful metrics for IT efficiencies and governance than the more reactive ITSM teams of the past.

Following the AIA data path, we saw that 82% of our respondents indicated strong levels of ITSM/operations integration for shared advanced analytics!

Quoting from two other conversations earlier this year highlighting next-generation ITSM values:

QUOTE #2: "First and foremost we've been able to consolidate our processes for change, incident, and problem management across our entire operation by leveraging one single platform …"

QUOTE #3: "We've also enjoyed improved visibility into the impacts of changes on service performance and availability, so we can more quickly get to the root cause of many of the issues caused by changes and begin to automate fixes more consistently."

How AIA + Service Modeling Can Result in (at least a little) Magic

The AIA research showed that 96% of respondents wanted at least some level of modeled insight on interdependencies across the application infrastructure. Among the top three priorities were application-to-infrastructure, infrastructure-to-infrastructure, and application-to-application (application ecosystem) dependency insights.

Combining analytics with service modeling is a growth area in AIA, as analytics providers are becoming more effective in not only leveraging existing application dependency mapping solutions and even CMDB data, but also in creating their own unique approach to dependency modeling.

In another very recent dialog, I found some rather striking benefits when service modeling and analytics are combined:

QUOTE #4: "We estimate that we will be saving about $500,000 in the area of toolset consolidation … We were averaging 2.5 hours for MTTR … now it's about 38 minutes … You might say we never had eyes before. Now we have eyes."

In Summary

This is, admittedly, only a taste of what I've learned from research and conversations with IT about how technology can help to transform IT operations for the "brave new world" we live in. My focus on AIA, next-generation ITSM and service modeling was deliberate, as I see these as lying at the heart of the "operations renaissance." Also important are requirements for more advanced levels of automation and integrated support for security and operations. Superior digital experience management or end user experience management is also key.

The challenge in the market today is that while all these technologies are interdependent and mutually reinforcing, the innovations are coming from many different vendor sources. And true to form, many of these vendors are seeking to redefine the world around themselves in their marketing and messaging. Sorting through the pieces, and understanding where real value lies, takes time and patience and more than a little sober skepticism. But the innovations are real. And hopefully this blog can give you at least a hint — by category — of where to begin to look for them.

I deliberately kept the quotes anonymous on all fronts. If you'd like to see more information, then please check out our EMA library:

■ quote 1

■ quotes 2 and 3

■ quote 4

Image removed.

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Transforming Operations, and IT as a Whole, with the Right Technology Investments

Dennis Drogseth

In my last blog, I expressed my opinion that IT operations teams may be about to enjoy a renaissance rather than dismally fading away — but only if they adopt new ways of working, measuring themselves and interacting with business stakeholders.

Start with Is IT Operations Going Away or Is It Enjoying a Renaissance?

In this blog, I'd like to discuss how technology investments can help smooth the way toward operational transformation with a few examples from recent interviews. More specifically, I'd like to focus on three key areas of innovation, all in some way related to Advanced IT Analytics (what some in the industry call IT Operations Analytics or ITOA):

1. How Advanced IT Analytics (AIA) can pave the way

2. How next-generation ITSM promotes AIA-relevant process improvements

3. How AIA and service modeling can become a magic combination

These three areas of innovation are, admittedly, far from a complete list. But hopefully they will offer you a provocative place to start for seeking out transformative IT technologies.

How Advanced IT Analytics Can Pave the Way

Probably one of the hottest, most diverse and most misunderstood areas of technological innovation is AIA. There are a lot of reasons for this, but the most significant reason is that AIA is not a single market but a diverse landscape of options ranging from those bordering on traditional "big data" to those that are focused on real-time predictive insights with tiered approaches to data collection that typically include leveraging third-party tools. The variances here also embrace multiple use cases ranging from performance management to change and capacity optimization to financial optimization to integrated security concerns.

Here are just a few highlights from EMA's recent AIA research focusing on performance, change and capacity management:

■ AIA analytic heuristics range from anomaly detection to predictive trending to machine learning, to rule-based analytics to data mining — as just some examples. On average, our respondents wanted at least four different heuristics.

■ On average, respondents wanted their AIA investments to support 11 different roles (and many more stakeholders), including four domain-specific roles, four cross-domain roles (including executive IT), and three non-IT business roles.

■ The top three achieved benefits were with faster time to repair problems, faster time to deliver new services and more efficient use of cloud resources.

Quoting from a conversation earlier this year:

QUOTE #1: "The move [to advanced analytics] allowed us to unify our operations team with a single-pane-of-glass view and drill down so that we could share information more effectively. In the past, we caught only 3% of our problems proactively. Now that percentage went up to 88% … In effect, we are able to see everything we need to see to focus and resolve issues far more cohesively and dynamically than before."

How Next-Generation ITSM Promotes AIA-Relevant Process Improvements

Next-generation ITSM is in my view pivotal for both IT and IT operational transformation. So what are they? Next-generation ITSM teams are more progressively integrated with operations teams, more proactive, more likely to leverage and share analytics, more likely to provide workflows and automation that unify IT as a whole (as well as support enterprise business process needs), and more likely to provide meaningful metrics for IT efficiencies and governance than the more reactive ITSM teams of the past.

Following the AIA data path, we saw that 82% of our respondents indicated strong levels of ITSM/operations integration for shared advanced analytics!

Quoting from two other conversations earlier this year highlighting next-generation ITSM values:

QUOTE #2: "First and foremost we've been able to consolidate our processes for change, incident, and problem management across our entire operation by leveraging one single platform …"

QUOTE #3: "We've also enjoyed improved visibility into the impacts of changes on service performance and availability, so we can more quickly get to the root cause of many of the issues caused by changes and begin to automate fixes more consistently."

How AIA + Service Modeling Can Result in (at least a little) Magic

The AIA research showed that 96% of respondents wanted at least some level of modeled insight on interdependencies across the application infrastructure. Among the top three priorities were application-to-infrastructure, infrastructure-to-infrastructure, and application-to-application (application ecosystem) dependency insights.

Combining analytics with service modeling is a growth area in AIA, as analytics providers are becoming more effective in not only leveraging existing application dependency mapping solutions and even CMDB data, but also in creating their own unique approach to dependency modeling.

In another very recent dialog, I found some rather striking benefits when service modeling and analytics are combined:

QUOTE #4: "We estimate that we will be saving about $500,000 in the area of toolset consolidation … We were averaging 2.5 hours for MTTR … now it's about 38 minutes … You might say we never had eyes before. Now we have eyes."

In Summary

This is, admittedly, only a taste of what I've learned from research and conversations with IT about how technology can help to transform IT operations for the "brave new world" we live in. My focus on AIA, next-generation ITSM and service modeling was deliberate, as I see these as lying at the heart of the "operations renaissance." Also important are requirements for more advanced levels of automation and integrated support for security and operations. Superior digital experience management or end user experience management is also key.

The challenge in the market today is that while all these technologies are interdependent and mutually reinforcing, the innovations are coming from many different vendor sources. And true to form, many of these vendors are seeking to redefine the world around themselves in their marketing and messaging. Sorting through the pieces, and understanding where real value lies, takes time and patience and more than a little sober skepticism. But the innovations are real. And hopefully this blog can give you at least a hint — by category — of where to begin to look for them.

I deliberately kept the quotes anonymous on all fronts. If you'd like to see more information, then please check out our EMA library:

■ quote 1

■ quotes 2 and 3

■ quote 4

Image removed.

Related Links

Hot Topics

The Latest

The Real Enterprise AI Risk Isn't Hallucinations

Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

Beyond Buy vs. Build: The New Playbook for Data Pipelines

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

The Corporate Network Is Fading - Here's What Replaces It

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

IT Leaders Must Establish a Network Data Architecture Practice

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

Data Center Outages Are Decreasing but More Costly

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

Observability Has a Physical Layer Now: What AI Infrastructure Teaches IT Operations

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

TLS Certificate Expiration Is Becoming an Observability Problem

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprise Cloud Observability: Choosing the Right Starting Point

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

AI Is Making Incident Management More Complex - Bad Data Makes It Harder

Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...

MEAN TIME TO INSIGHT Podcast - Episode 26: Network Compliance

In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ...