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IT Cultural Transformation and the Elimination of Technology Silos

An Exercise in Efficiency or a Dream Turned Nightmare?
Dennis Drogseth

Cultural transformation and eliminating IT silos may sound like an impossible dream — and indeed, perhaps “eliminating” is too strong a word. But the reality is that IT organizations must change toward a more responsive, business-aligned culture, as well as toward a more service-aware (versus siloed) way of working.

So how do you begin? A lot depends, of course, on who you are — whether you’re a service desk manager, a vice president of service management or operations, a C-level exec looking across all of IT, or one of those lucky “catalysts” invited to take a transformative role in a matrix capacity.

It will also depend on your unique environment — both the vertical and business model you support and the distinctive characteristics of your IT organization as a human and technological aggregate.

So, there’s no generic answer, just as there’s no generic IT organization and no generic IT professional (or at least I have yet to meet one).

However, drawing from years of consulting and research, I believe I can make a few high-level suggestions to give you some basis for going forward — to accelerate the dream and minimize the nightmare:

Stand in the middle of the storm

"Stand in the middle of the storm." This is a phrase that Enterprise Management Associates (EMA) consultants use to explain the often-overlooked fact that IT organizations have various options to promote cultural transformation and cross-silo ways of working and these options are all interdependent. And they are technology, process, and organization. We don’t single out “people” because people — meaning their very human and sometimes siloed attitudes — are part of all three vectors in this storm of change.

Many in the industry still fail to recognize the need not only to understand each “stormy vector” separately, but also to understand how these vectors become a continuum. Just consider how many IT organizations pay considerable sums to process consultants, systems integrators, and organizational consultants — each group largely oblivious to the other and each group with its own terminology for describing objects, processes, and objectives. Each group has its own perspective on the “right” way to do things. In many instances, efforts to coordinate across these groups lead to a costly merry-go-round — with circular movement as opposed to actual forward progress — often with millions of dollars changing hands.

While the industry still treats the corners of the triangle as three separate worlds with different specialists attached to each, they are, in fact, fundamentally interdependent. The more you can bring these forces closer to the center, the more smoothly, more efficiently, and more effectively they will operate together. Technology can impact process and vice versa — for example, by making certain actions “automated” or “routine” that weren’t before. Process and organization are, of course, closely intertwined, and need to be understood as such. Effective process definitions should take into account your actual political environment, while your organizational structure may well have to evolve to support more cross-domain service awareness if you’re going to succeed in the long run.

Define your objectives

Cultural Transformation? Ask yourself “to do WHAT exactly?” While it’s all well and good to promote “cultural transformation” and “cross-siloed ways of working” I, personally, have never seen an initiative along these lines succeed that wasn’t a little more specific in nature. In defining specific objectives, you might also what to be clear why you feel cultural transformation is important to you, to your organization, and to the business. Then you can more meaningfully associate tangible objectives and metrics to the endeavor.

For instance, many initiatives are associated with technology deployments, such as a more automated capability for managing endpoints, a CMDB/CMS, or a truly cross-domain approach to managing service performance (including operations and the service desk). Other initiatives are framed at a higher level, such as the move to agile and DevOps, cross-domain IT asset optimization, or the move to assimilate internal and external cloud resources into service delivery. Others may be driven initially from non-IT requirements to optimize end-user and customer experience or support new business initiatives dependent on IT services. All these examples (and they are just a subset) represent tangible beginning points for driving IT cultural transformation and cross-silo ways of working.

Consider your resources

Once the initial catalyst for cultural transformation is clear, it’s time to begin to create a more tangible sense of what your resources are for achieving it. These resources may well include a core team (often part-time) of stakeholders, other relevant stakeholders across domains, existing or new management tools, and well-defined executive leadership. Like it or not, top-down leadership is key — a factor that’s been borne out again and again in our research and consulting.

Another lesson I’ve learned from multiple consulting engagements is: seek out the “enthusiasts.” Ask yourself, “Who are the true ‘catalysts for change’ and positive transformation?” And then try to center your initial phase program as much as possible with them.

Promote dialog and communication

No efforts at creating a truly cross-domain, service-aware way of working have succeeded, that I’m aware of, without effective dialog and communication that includes listening and documenting stakeholder concerns, as well as promoting new ways of working. It is a top-down, bottoms-up communication paradigm that — and here’s the good news — will bring strong benefits and insights in and of itself.

Once you start to create meaningful plans for moving into a true cross-domain way of working, ideally with measurable metrics including timeline objectives and business-impacting benefits, you may be surprised at how positive the benefits soon become. Benefits can range from vast improvements in efficiency as your organization finally begins to work together as a whole to increased business value and improved credibility with your service consumers.

But needless to say, cultural change in IT that resolves cross-silo issues isn’t a quick fix. It must evolve from multiple points of awareness and discussion as you, your IT organization, and the business it supports continue to change, adapt, and grow.

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Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

IT Cultural Transformation and the Elimination of Technology Silos

An Exercise in Efficiency or a Dream Turned Nightmare?
Dennis Drogseth

Cultural transformation and eliminating IT silos may sound like an impossible dream — and indeed, perhaps “eliminating” is too strong a word. But the reality is that IT organizations must change toward a more responsive, business-aligned culture, as well as toward a more service-aware (versus siloed) way of working.

So how do you begin? A lot depends, of course, on who you are — whether you’re a service desk manager, a vice president of service management or operations, a C-level exec looking across all of IT, or one of those lucky “catalysts” invited to take a transformative role in a matrix capacity.

It will also depend on your unique environment — both the vertical and business model you support and the distinctive characteristics of your IT organization as a human and technological aggregate.

So, there’s no generic answer, just as there’s no generic IT organization and no generic IT professional (or at least I have yet to meet one).

However, drawing from years of consulting and research, I believe I can make a few high-level suggestions to give you some basis for going forward — to accelerate the dream and minimize the nightmare:

Stand in the middle of the storm

"Stand in the middle of the storm." This is a phrase that Enterprise Management Associates (EMA) consultants use to explain the often-overlooked fact that IT organizations have various options to promote cultural transformation and cross-silo ways of working and these options are all interdependent. And they are technology, process, and organization. We don’t single out “people” because people — meaning their very human and sometimes siloed attitudes — are part of all three vectors in this storm of change.

Many in the industry still fail to recognize the need not only to understand each “stormy vector” separately, but also to understand how these vectors become a continuum. Just consider how many IT organizations pay considerable sums to process consultants, systems integrators, and organizational consultants — each group largely oblivious to the other and each group with its own terminology for describing objects, processes, and objectives. Each group has its own perspective on the “right” way to do things. In many instances, efforts to coordinate across these groups lead to a costly merry-go-round — with circular movement as opposed to actual forward progress — often with millions of dollars changing hands.

While the industry still treats the corners of the triangle as three separate worlds with different specialists attached to each, they are, in fact, fundamentally interdependent. The more you can bring these forces closer to the center, the more smoothly, more efficiently, and more effectively they will operate together. Technology can impact process and vice versa — for example, by making certain actions “automated” or “routine” that weren’t before. Process and organization are, of course, closely intertwined, and need to be understood as such. Effective process definitions should take into account your actual political environment, while your organizational structure may well have to evolve to support more cross-domain service awareness if you’re going to succeed in the long run.

Define your objectives

Cultural Transformation? Ask yourself “to do WHAT exactly?” While it’s all well and good to promote “cultural transformation” and “cross-siloed ways of working” I, personally, have never seen an initiative along these lines succeed that wasn’t a little more specific in nature. In defining specific objectives, you might also what to be clear why you feel cultural transformation is important to you, to your organization, and to the business. Then you can more meaningfully associate tangible objectives and metrics to the endeavor.

For instance, many initiatives are associated with technology deployments, such as a more automated capability for managing endpoints, a CMDB/CMS, or a truly cross-domain approach to managing service performance (including operations and the service desk). Other initiatives are framed at a higher level, such as the move to agile and DevOps, cross-domain IT asset optimization, or the move to assimilate internal and external cloud resources into service delivery. Others may be driven initially from non-IT requirements to optimize end-user and customer experience or support new business initiatives dependent on IT services. All these examples (and they are just a subset) represent tangible beginning points for driving IT cultural transformation and cross-silo ways of working.

Consider your resources

Once the initial catalyst for cultural transformation is clear, it’s time to begin to create a more tangible sense of what your resources are for achieving it. These resources may well include a core team (often part-time) of stakeholders, other relevant stakeholders across domains, existing or new management tools, and well-defined executive leadership. Like it or not, top-down leadership is key — a factor that’s been borne out again and again in our research and consulting.

Another lesson I’ve learned from multiple consulting engagements is: seek out the “enthusiasts.” Ask yourself, “Who are the true ‘catalysts for change’ and positive transformation?” And then try to center your initial phase program as much as possible with them.

Promote dialog and communication

No efforts at creating a truly cross-domain, service-aware way of working have succeeded, that I’m aware of, without effective dialog and communication that includes listening and documenting stakeholder concerns, as well as promoting new ways of working. It is a top-down, bottoms-up communication paradigm that — and here’s the good news — will bring strong benefits and insights in and of itself.

Once you start to create meaningful plans for moving into a true cross-domain way of working, ideally with measurable metrics including timeline objectives and business-impacting benefits, you may be surprised at how positive the benefits soon become. Benefits can range from vast improvements in efficiency as your organization finally begins to work together as a whole to increased business value and improved credibility with your service consumers.

But needless to say, cultural change in IT that resolves cross-silo issues isn’t a quick fix. It must evolve from multiple points of awareness and discussion as you, your IT organization, and the business it supports continue to change, adapt, and grow.

Hot Topics

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...