Skip to main content

Who Owns User and Customer Experience Management?

Dennis Drogseth

There is growing industry attention to user, customer, and digital experience management — often condensed by the acronym UEM for “user experience management.” This attention is more than justified, but most of the buzz leaves out critical questions like, “What is user experience management?”, “Who really runs (or who should run) the UEM show in the digital age?”, “What are its real benefits?”, and “What’s still missing from most UEM-related deployments?” In this blog I’m going to attempt to provide a few insights on each of these questions, leveraging my own industry dialogs as well as some EMA research.

The Importance of User Experience Management

In recent research about the future of IT service management, we found that the number one strategic priority was improved end-user experience internal to the business. Significantly, improved customer/supply-chain user experience also got high marks and was a top priority in some verticals.

In other EMA research from this year targeting digital and IT transformation, improved user experience management was the number one functional technology priority.

Perhaps even more impressive, when we looked at why IT organizations seeking to support transformative initiatives were slated for growth (and hence, were presumably valued), the two key technology initiatives cited were improved end-user experience internal to the business and improved customer/supply-chain user experience.

What Is User Experience Management, Actually?

Prior EMA research on User Experience Management addressed this very question in detail by looking at user and customer experience management as a single landscape in terms of the following five categories, ranked by priority:

1. Business impact – Optimizing the business outcomes of IT-delivered business services based on user interactions.

2. Performance – Monitoring and optimizing the effective delivery of business services to their end consumers in terms of performance and security concerns.

3. Service usage (neck and neck with performance) – Understanding the frequency and other usage patterns with which users (by type or group) leverage IT-delivered business services.

4. User productivity – Optimizing end-user interaction with business services — including the efficiency with which the service is utilized in support of business processes.

5. Design – Optimizing the effective design and content of business services for their end consumers in terms of navigation, relevance, etc.

So for those of you who think that UEM/customer experience management is simply a subset of Application Performance Management (APM), it’s long past time to think again. In fact, service desk and ITSM teams actually outscored (narrowly) application support teams as being in line for tracking UEM and customer experience issues.

So Who Really Owns User Experience Management?

As already indicated, it’s not just one group. User/customer experience management is, and should be, a shared investment across IT and between IT and business stakeholders. In many respects it is also shared between IT and the end-user community, which is becoming increasingly visible not just through incident-related communications but also through social media, mobile and other venues for improved customer dialog and outreach.

Here are a few highlights on the topic of user/customer experience management ownership:

■ Multiple EMA research projects have underscored the fact that UEM and customer experience management should be a 50/50 shared requirement between IT and business stakeholders.

■ A well-defined user/customer experience management team is an evolving requirement, and data consistently correlates such a team with improved results.

■ Executive IT tends to lead UEM and customer experience efforts because it touches different groups within IT and because UEM reflects directly on IT’s value to the business it serves. Within IT organizations, multiple stakeholders are involved in UEM — most notably groups within operations in collaboration with the service desk. That collaboration often includes improved workflows with increasing levels of automation, bidirectionally shared data, and sometimes shared analytics as well as feedback loops that often move through the service desk to operations and development with insights into service usage, value, and relevance.

■ Business stakeholders are increasingly playing a growing role, especially with the emergence of digital services and digital transformation priorities. These stakeholders generally fall into two categories:

- Line of business executives and service owners for internal users/consumers of IT services.

- Online operations and chief digital officers when external customers are the primary concern.

What Are the Benefits, and What’s Missing?

One of the reasons that user and customer experience management continue to rise in importance is that the benefits are manifold — reflecting backward on IT operational efficiencies on the one hand while radiating outward to support enhanced IT and business effectiveness as well as improved insights into service consumers’ priorities, wants, and needs. Data consistently shows that these insights can enhance a wide range of objectives, from customer loyalty and brand awareness to employee productivity and better business process optimization, just to name a few. On the other hand, if you want to reduce war room time, nothing beats meaningful UEM insights linked to business outcomes to set priorities and redefine some of the processes associated with incident management, problem management, availability management, and triage.

What’s missing? In most organizations user experience management is conducted on two fronts within IT that still remain isolated from each other — operations and the service desk. And in fact, in many cases operations is itself fragmented. Faced with this unfortunate situation, IT executives and business stakeholders often wrestle with SLAs that could have been written in the 90s in which IT effectiveness remains wedded primarily to cost rather than delivering value. Nothing, of course, could be further removed from the growing commitment to digital transformation.

Perhaps it’s not that surprising then that when it comes to roadblocks and complaints, the two chief categories consistently have a human face — better teaming between IT and the business and a richer understanding of real user needs and concerns. In both cases, this means dialog. Dialog on many levels. User experience management is, in the end, a persona-centric rather than a systems-centric set of disciplines — the beginning of a conversation that nearly a decade ago sent up a flare that first signaled the advent of the digital age.

The Latest

Pilots are everywhere, stakeholders are seeking results, businesses are pushing for new tools, and IT teams are being asked to make AI secure, reliable, and useful at scale. But as organizations move from testing AI to operationalizing it, many are discovering that the biggest barrier is not the model, the use case, or even the budget. It is the file data foundation within ...

Fast or cheap? For most of my career in engineering, speed and quality sat on opposite ends of a seesaw. The "OR" in "fast or cheap" was non-negotiable. It was expected that pushing for faster releases meant that something in quality would give way. Tightening quality controls meant the schedule slipped. Every engineering leader I know has lived some version of that tradeoff ... The seesaw is starting to level out ...

I have been building enterprise software for more than 20 years ... One thing stays true across all of it: You do not find out your foundation is wrong during the crisis. You find out when the debt comes due. For a lot of organizations, that bill is arriving now. New research ... puts hard numbers on something practitioners have been sensing for a while. The telemetry problem isn't coming. It's already here ...

The rapid growth of AI workloads is pushing traditional log management approaches to their limits, according to The State of Log Management 2026 report from Dynatrace. Modern logs have become critical to understanding, validating, and securing AI-driven decisions, helping organizations ensure reliability, compliance, and performance at scale. However, the volume and complexity of AI telemetry are overwhelming legacy tools ...

For years, secure connectivity has relied on a familiar pattern: route traffic back to centralized gateways, inspect it, and then allow access. This model worked when applications lived in a handful of data centers and users were largely confined to offices. That model is now under strain. Applications are distributed across clouds, users connect from everywhere, and real-time workloads demand performance that centralized inspection points struggle to deliver. As traffic volumes grow and latency expectations shrink, routing everything through a small number of control points has become both a performance bottleneck and a resilience risk. The future of secure connectivity requires a different approach ...

The AI experimentation phase is over, and the private cloud is where enterprise AI workloads are being deployed for security and scale, according to Private Cloud Outlook 2026, a new report from Broadcom ... 2026 marks an acceleration into a full AI tipping point. The shift is being shaped by three forces — costs, complexity, and control — that public cloud environments are increasingly failing to address for production AI at scale. Key findings from the report include ...

44% of organizations have reported an outage in the past year tied to suppressed or ignored alerts, and 78% had at least one incident where no alert was fired at all ... Engineers learned about failures from customers. That gap between what our tools report and what our customers experience is the problem DevOps teams have been quietly solving with GenAI tooling, even as most enterprises continue to run their NOCs on manual alert triage ...

Cloud outages are usually described as technical failures. When a service goes down, a dependency breaks, or a region has issues, the focus immediately shifts to infrastructure. But if you look closely at how these incidents actually unfold, the root cause is rarely the technology itself. It is almost always tied to decisions made earlier, during design, implementation, or day-to-day operations. The system behaves the way it was built. The real question is how it was built ...

77% of leaders say their teams need AI skills urgently. 64% say their organization plans to train current employees rather than hire new ones. So far, so reasonable. The part that surprised me is who's been put in charge: 34% of those leaders say IT and engineering own the AI skills mandate. Learning and Development or HR own it at 7% of organizations. That's roughly five-to-one in favor of the people who understand the tools, over the people whose actual job is teaching adults how to learn new ones ...

In the ever-evolving digital landscape, enterprises are increasingly focused on enhancing their observability stacks to gain deeper insights into their IT environments. Observability has become a cornerstone of modern IT operations, enabling organizations to monitor, diagnose, and optimize their systems with unprecedented precision. However, a critical piece of the puzzle often goes unnoticed in this transformation: IBM i ...

Who Owns User and Customer Experience Management?

Dennis Drogseth

There is growing industry attention to user, customer, and digital experience management — often condensed by the acronym UEM for “user experience management.” This attention is more than justified, but most of the buzz leaves out critical questions like, “What is user experience management?”, “Who really runs (or who should run) the UEM show in the digital age?”, “What are its real benefits?”, and “What’s still missing from most UEM-related deployments?” In this blog I’m going to attempt to provide a few insights on each of these questions, leveraging my own industry dialogs as well as some EMA research.

The Importance of User Experience Management

In recent research about the future of IT service management, we found that the number one strategic priority was improved end-user experience internal to the business. Significantly, improved customer/supply-chain user experience also got high marks and was a top priority in some verticals.

In other EMA research from this year targeting digital and IT transformation, improved user experience management was the number one functional technology priority.

Perhaps even more impressive, when we looked at why IT organizations seeking to support transformative initiatives were slated for growth (and hence, were presumably valued), the two key technology initiatives cited were improved end-user experience internal to the business and improved customer/supply-chain user experience.

What Is User Experience Management, Actually?

Prior EMA research on User Experience Management addressed this very question in detail by looking at user and customer experience management as a single landscape in terms of the following five categories, ranked by priority:

1. Business impact – Optimizing the business outcomes of IT-delivered business services based on user interactions.

2. Performance – Monitoring and optimizing the effective delivery of business services to their end consumers in terms of performance and security concerns.

3. Service usage (neck and neck with performance) – Understanding the frequency and other usage patterns with which users (by type or group) leverage IT-delivered business services.

4. User productivity – Optimizing end-user interaction with business services — including the efficiency with which the service is utilized in support of business processes.

5. Design – Optimizing the effective design and content of business services for their end consumers in terms of navigation, relevance, etc.

So for those of you who think that UEM/customer experience management is simply a subset of Application Performance Management (APM), it’s long past time to think again. In fact, service desk and ITSM teams actually outscored (narrowly) application support teams as being in line for tracking UEM and customer experience issues.

So Who Really Owns User Experience Management?

As already indicated, it’s not just one group. User/customer experience management is, and should be, a shared investment across IT and between IT and business stakeholders. In many respects it is also shared between IT and the end-user community, which is becoming increasingly visible not just through incident-related communications but also through social media, mobile and other venues for improved customer dialog and outreach.

Here are a few highlights on the topic of user/customer experience management ownership:

■ Multiple EMA research projects have underscored the fact that UEM and customer experience management should be a 50/50 shared requirement between IT and business stakeholders.

■ A well-defined user/customer experience management team is an evolving requirement, and data consistently correlates such a team with improved results.

■ Executive IT tends to lead UEM and customer experience efforts because it touches different groups within IT and because UEM reflects directly on IT’s value to the business it serves. Within IT organizations, multiple stakeholders are involved in UEM — most notably groups within operations in collaboration with the service desk. That collaboration often includes improved workflows with increasing levels of automation, bidirectionally shared data, and sometimes shared analytics as well as feedback loops that often move through the service desk to operations and development with insights into service usage, value, and relevance.

■ Business stakeholders are increasingly playing a growing role, especially with the emergence of digital services and digital transformation priorities. These stakeholders generally fall into two categories:

- Line of business executives and service owners for internal users/consumers of IT services.

- Online operations and chief digital officers when external customers are the primary concern.

What Are the Benefits, and What’s Missing?

One of the reasons that user and customer experience management continue to rise in importance is that the benefits are manifold — reflecting backward on IT operational efficiencies on the one hand while radiating outward to support enhanced IT and business effectiveness as well as improved insights into service consumers’ priorities, wants, and needs. Data consistently shows that these insights can enhance a wide range of objectives, from customer loyalty and brand awareness to employee productivity and better business process optimization, just to name a few. On the other hand, if you want to reduce war room time, nothing beats meaningful UEM insights linked to business outcomes to set priorities and redefine some of the processes associated with incident management, problem management, availability management, and triage.

What’s missing? In most organizations user experience management is conducted on two fronts within IT that still remain isolated from each other — operations and the service desk. And in fact, in many cases operations is itself fragmented. Faced with this unfortunate situation, IT executives and business stakeholders often wrestle with SLAs that could have been written in the 90s in which IT effectiveness remains wedded primarily to cost rather than delivering value. Nothing, of course, could be further removed from the growing commitment to digital transformation.

Perhaps it’s not that surprising then that when it comes to roadblocks and complaints, the two chief categories consistently have a human face — better teaming between IT and the business and a richer understanding of real user needs and concerns. In both cases, this means dialog. Dialog on many levels. User experience management is, in the end, a persona-centric rather than a systems-centric set of disciplines — the beginning of a conversation that nearly a decade ago sent up a flare that first signaled the advent of the digital age.

The Latest

Pilots are everywhere, stakeholders are seeking results, businesses are pushing for new tools, and IT teams are being asked to make AI secure, reliable, and useful at scale. But as organizations move from testing AI to operationalizing it, many are discovering that the biggest barrier is not the model, the use case, or even the budget. It is the file data foundation within ...

Fast or cheap? For most of my career in engineering, speed and quality sat on opposite ends of a seesaw. The "OR" in "fast or cheap" was non-negotiable. It was expected that pushing for faster releases meant that something in quality would give way. Tightening quality controls meant the schedule slipped. Every engineering leader I know has lived some version of that tradeoff ... The seesaw is starting to level out ...

I have been building enterprise software for more than 20 years ... One thing stays true across all of it: You do not find out your foundation is wrong during the crisis. You find out when the debt comes due. For a lot of organizations, that bill is arriving now. New research ... puts hard numbers on something practitioners have been sensing for a while. The telemetry problem isn't coming. It's already here ...

The rapid growth of AI workloads is pushing traditional log management approaches to their limits, according to The State of Log Management 2026 report from Dynatrace. Modern logs have become critical to understanding, validating, and securing AI-driven decisions, helping organizations ensure reliability, compliance, and performance at scale. However, the volume and complexity of AI telemetry are overwhelming legacy tools ...

For years, secure connectivity has relied on a familiar pattern: route traffic back to centralized gateways, inspect it, and then allow access. This model worked when applications lived in a handful of data centers and users were largely confined to offices. That model is now under strain. Applications are distributed across clouds, users connect from everywhere, and real-time workloads demand performance that centralized inspection points struggle to deliver. As traffic volumes grow and latency expectations shrink, routing everything through a small number of control points has become both a performance bottleneck and a resilience risk. The future of secure connectivity requires a different approach ...

The AI experimentation phase is over, and the private cloud is where enterprise AI workloads are being deployed for security and scale, according to Private Cloud Outlook 2026, a new report from Broadcom ... 2026 marks an acceleration into a full AI tipping point. The shift is being shaped by three forces — costs, complexity, and control — that public cloud environments are increasingly failing to address for production AI at scale. Key findings from the report include ...

44% of organizations have reported an outage in the past year tied to suppressed or ignored alerts, and 78% had at least one incident where no alert was fired at all ... Engineers learned about failures from customers. That gap between what our tools report and what our customers experience is the problem DevOps teams have been quietly solving with GenAI tooling, even as most enterprises continue to run their NOCs on manual alert triage ...

Cloud outages are usually described as technical failures. When a service goes down, a dependency breaks, or a region has issues, the focus immediately shifts to infrastructure. But if you look closely at how these incidents actually unfold, the root cause is rarely the technology itself. It is almost always tied to decisions made earlier, during design, implementation, or day-to-day operations. The system behaves the way it was built. The real question is how it was built ...

77% of leaders say their teams need AI skills urgently. 64% say their organization plans to train current employees rather than hire new ones. So far, so reasonable. The part that surprised me is who's been put in charge: 34% of those leaders say IT and engineering own the AI skills mandate. Learning and Development or HR own it at 7% of organizations. That's roughly five-to-one in favor of the people who understand the tools, over the people whose actual job is teaching adults how to learn new ones ...

In the ever-evolving digital landscape, enterprises are increasingly focused on enhancing their observability stacks to gain deeper insights into their IT environments. Observability has become a cornerstone of modern IT operations, enabling organizations to monitor, diagnose, and optimize their systems with unprecedented precision. However, a critical piece of the puzzle often goes unnoticed in this transformation: IBM i ...