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The Future of ITSM: How Are Roles (and Rules) Changing? Part 1

Dennis Drogseth

Both the “rules” and the “roles” governing IT Service Management (ITSM) are evolving to support a far-broader need for inclusiveness across IT, and between IT and its service consumers. Recent EMA research, What Is the Future of IT Service Management? (March 2015), exposed a number of shifting trends that might surprise many in the industry.

In our research, we approached ITSM not only as a set of service management processes, but we also viewed it in the context of recent trends in technology adoption and evolving organizational models. The research spanned 270 respondents in North America and Europe — in roles ranging from executives, to service desk professionals, to operations, and even development personnel — all of whom were actively engaged in ITSM in some way. Company/organizational size was a good mix, as well, ranging in size from 500 employees to more than 20,000 employees. Nearly 50% of those surveyed indicated that their ITSM teams were slated for growth. Another 35% were remaining the same, and only 15% were shrinking in size.

Probably the first thing that stood out in the survey responses was that there is a growing need to more fully integrate the service desk with operations beyond traditional trouble ticketing. This requirement is changing both the roles and the rules of ITSM, especially among the more successful ITSM teams, where dialog between service management professionals and core operations experts is becoming more multifaceted and more service-aware than in the past. In many cases, the more effective ITSM teams are increasingly helping to coordinate and focus operational experts in support of business needs.

Our data showed that the top three strategic priorities for ITSM teams were the following:

■ Improved user experience for internal service consumers (end users)

■ Improved operations-to–service desk integrations for incident and problem management

■ Improved operations-to–service desk integrations for configuration and change management

All three data points call out for stronger operations-to-ITSM integrations — in terms of workflow, analytics, and automation, as well as effective role-aware visualization. As an added confirmation, 55% of our respondents felt that “big data analytics for IT” belong equally to ITSM and operations, and 14% believed that big data was primarily the province of the ITSM team.

Another surprising finding that supports integrated operations was that, for the first time ever, “performance-related service impact” was the dominant use case for CMDB/CMS deployments — followed by asset and change management — once again emphasizing the need to optimize the delivery of critical IT application services and, hence, improve the end-user experience.

Read Part 2 of this blog

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The Future of ITSM: How Are Roles (and Rules) Changing? Part 1

Dennis Drogseth

Both the “rules” and the “roles” governing IT Service Management (ITSM) are evolving to support a far-broader need for inclusiveness across IT, and between IT and its service consumers. Recent EMA research, What Is the Future of IT Service Management? (March 2015), exposed a number of shifting trends that might surprise many in the industry.

In our research, we approached ITSM not only as a set of service management processes, but we also viewed it in the context of recent trends in technology adoption and evolving organizational models. The research spanned 270 respondents in North America and Europe — in roles ranging from executives, to service desk professionals, to operations, and even development personnel — all of whom were actively engaged in ITSM in some way. Company/organizational size was a good mix, as well, ranging in size from 500 employees to more than 20,000 employees. Nearly 50% of those surveyed indicated that their ITSM teams were slated for growth. Another 35% were remaining the same, and only 15% were shrinking in size.

Probably the first thing that stood out in the survey responses was that there is a growing need to more fully integrate the service desk with operations beyond traditional trouble ticketing. This requirement is changing both the roles and the rules of ITSM, especially among the more successful ITSM teams, where dialog between service management professionals and core operations experts is becoming more multifaceted and more service-aware than in the past. In many cases, the more effective ITSM teams are increasingly helping to coordinate and focus operational experts in support of business needs.

Our data showed that the top three strategic priorities for ITSM teams were the following:

■ Improved user experience for internal service consumers (end users)

■ Improved operations-to–service desk integrations for incident and problem management

■ Improved operations-to–service desk integrations for configuration and change management

All three data points call out for stronger operations-to-ITSM integrations — in terms of workflow, analytics, and automation, as well as effective role-aware visualization. As an added confirmation, 55% of our respondents felt that “big data analytics for IT” belong equally to ITSM and operations, and 14% believed that big data was primarily the province of the ITSM team.

Another surprising finding that supports integrated operations was that, for the first time ever, “performance-related service impact” was the dominant use case for CMDB/CMS deployments — followed by asset and change management — once again emphasizing the need to optimize the delivery of critical IT application services and, hence, improve the end-user experience.

Read Part 2 of this blog

Image removed.

Hot Topics

The Latest

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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 ...