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Introducing ITSM 2.0: A Cornerstone for Digital and IT Transformation

Dennis Drogseth

Over the course of numerous deployment dialogs and multiple research projects starting with last year’s work on ITSM futures, I have been tracking a still largely unheralded phenomenon: ITSM teams in many organizations are evolving to take a leadership role in helping all of IT become more efficient, more business aligned, and ever more relevant to business outcomes. Indeed, an ITSM 2.0 is emerging that’s radically different from its inherited, reactive past in ways that are sometimes predictable but more often surprising.

ITSM 1.0

OK, let’s start with what still seems to be the industry’s most common caricature of the “reactive service desk.” ITSM is potentially a great deal more than this, but frayed nerves on both sides of the IT/service-consumer divide have hardened suspicions, frustrations, and hands-up-in-the-air impatience levels with service desk operations.

When we first looked at progressive versus reactive ITSM in our ITSM futures research, we saw that those ITSM teams that were struggling the most had a number of predictable characteristics. These included:

■ Failure of credibility in supporting business requirements, which was directly correlated with being outsourced, as well as with losing staffing and other resources to Operations.

■ Inability to grapple with emerging (and in some cases, already well-established) requirements in adapting to cloud, agile process requirements, mobile, and endpoint awareness overall.

■ Failure to invest in more strategic and potentially transformative technologies ranging from classic ITSM investments, such as configuration management databases (CMDBs) and service catalogs, to broader shared investments, such as analytics, application discovery and dependency mapping (ADDM), and more advanced levels of automation for diagnostics and managing change.

■ Similar failure to invest in best practices, including, but in no way limited to, the IT Infrastructure Library (ITIL).

ITSM 2.0

The first thing to do here is take the ITSM 1.0 list and turn it on its head. We see then that, just for starters, ITSM 2.0 is:

■ More effective in supporting business requirements, and hence more likely to experience greater investment in terms of staffing and other resources.

■ More likely to play a role in shaping and optimizing IT operations efficiencies by helping to promote far more effective cross-silo (network/systems/applications) interaction and dialog.

■ Far more likely to participate in cloud, mobile, and even agile/DevOps initiatives.

■ Far more invested in strategic technologies ranging from CMDBs, service catalogs, and automation to even more advanced and shared levels of analytics, with often dramatic improvements in endpoint optimization for mobile and non-mobile devices, including lifecycle management and more effective customer/consumer experience.

■ Far more likely to address security requirements ranging from proactive support for incident and problem management (often through integrated technologies shared with operations), to endpoint compliance in patch and configuration management, to change management more broadly across the infrastructure.

■ Far more likely to play a role in promoting process efficiencies with best practices across all of IT.

In addition to this, ITSM 2.0 is beginning to take a growing role in supporting enterprise process efficiencies (for facilities, HR, etc.), as well as both Green IT and its successor, the Internet of Things (IoT).

Two Key ITSM 2.0 Differentiators: Integrated IT Operations and Endpoint Optimization

While each of these areas of differentiation deserves a more extensive discussion, in this blog I’d like to highlight two: integrated IT operations and endpoint optimization.

Integrated IT Operations

Bringing IT operations together with ITSM is one of the most poorly documented and yet most critical areas of advancement in the industry.

Here are some of the attributes of integrated IT operations that stand out in ongoing research and dialogs:

■ Sharing data for a far more integrated approach to availability and performance management, as combined with incident and problem management – This data can include event and time-series data, more advanced analytics including support for security, service modeling (CMDB, ADDM), shared knowledgebase access, and a growing role for social media and business data. Common mobile access can make this sharing of information even more compelling.

■ Sharing data for change management, and even agile or DevOps needs – This often requires increased insight into service modeling and automation in particular.

■ Improved workflow automation across IT operations and ITSM teams – As I mentioned, in many conversations I’m finding that it’s ITSM that is becoming the creative force in breaking through operations silos.

■ Project management governance.

■ Documented OpEx efficiencies to help IT operations and ITSM continue to improve in how they work, both collectively and individually.

■ Far more effective user experience management that places all the resources of ITSM teams and IT operations together on a common footing.

Endpoint Optimization

EMA is just concluding research on “Optimizing IT for Financial Performance.” And in that research ITSM once again plays a central role. Given the ascendant requirements to support mobile stakeholders, optimizing endpoints in terms of cost and value is a leading feature of ITSM 2.0. The top prioritized functional areas were the following:

■ Security

■ Software usage

■ License management

■ Software distribution

■ Power management

■ Hardware lifecycle management

■ Endpoint hardware usage

Endpoint optimization can also be greatly enhanced through service catalogs and app stores that integrate cost, SLAs, and usage insights into how end consumers access IT services.

In Conclusion

By implication at least, I hope you can see why I view ITSM 2.0 as a cornerstone of both IT and digital transformation, as it can be a unifier for IT, as well as for IT-to-business efficiencies and relevance. This unification stretches across process, data, technology, and dialog, with ITSM teams often forming a hub for all of these factors to come together.

But this isn’t actually the end of my discussion on ITSM 2.0. I’ll be following up with one more blog: ITSM 2.0 challenges. So stay tuned for more.

Image removed.

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Introducing ITSM 2.0: A Cornerstone for Digital and IT Transformation

Dennis Drogseth

Over the course of numerous deployment dialogs and multiple research projects starting with last year’s work on ITSM futures, I have been tracking a still largely unheralded phenomenon: ITSM teams in many organizations are evolving to take a leadership role in helping all of IT become more efficient, more business aligned, and ever more relevant to business outcomes. Indeed, an ITSM 2.0 is emerging that’s radically different from its inherited, reactive past in ways that are sometimes predictable but more often surprising.

ITSM 1.0

OK, let’s start with what still seems to be the industry’s most common caricature of the “reactive service desk.” ITSM is potentially a great deal more than this, but frayed nerves on both sides of the IT/service-consumer divide have hardened suspicions, frustrations, and hands-up-in-the-air impatience levels with service desk operations.

When we first looked at progressive versus reactive ITSM in our ITSM futures research, we saw that those ITSM teams that were struggling the most had a number of predictable characteristics. These included:

■ Failure of credibility in supporting business requirements, which was directly correlated with being outsourced, as well as with losing staffing and other resources to Operations.

■ Inability to grapple with emerging (and in some cases, already well-established) requirements in adapting to cloud, agile process requirements, mobile, and endpoint awareness overall.

■ Failure to invest in more strategic and potentially transformative technologies ranging from classic ITSM investments, such as configuration management databases (CMDBs) and service catalogs, to broader shared investments, such as analytics, application discovery and dependency mapping (ADDM), and more advanced levels of automation for diagnostics and managing change.

■ Similar failure to invest in best practices, including, but in no way limited to, the IT Infrastructure Library (ITIL).

ITSM 2.0

The first thing to do here is take the ITSM 1.0 list and turn it on its head. We see then that, just for starters, ITSM 2.0 is:

■ More effective in supporting business requirements, and hence more likely to experience greater investment in terms of staffing and other resources.

■ More likely to play a role in shaping and optimizing IT operations efficiencies by helping to promote far more effective cross-silo (network/systems/applications) interaction and dialog.

■ Far more likely to participate in cloud, mobile, and even agile/DevOps initiatives.

■ Far more invested in strategic technologies ranging from CMDBs, service catalogs, and automation to even more advanced and shared levels of analytics, with often dramatic improvements in endpoint optimization for mobile and non-mobile devices, including lifecycle management and more effective customer/consumer experience.

■ Far more likely to address security requirements ranging from proactive support for incident and problem management (often through integrated technologies shared with operations), to endpoint compliance in patch and configuration management, to change management more broadly across the infrastructure.

■ Far more likely to play a role in promoting process efficiencies with best practices across all of IT.

In addition to this, ITSM 2.0 is beginning to take a growing role in supporting enterprise process efficiencies (for facilities, HR, etc.), as well as both Green IT and its successor, the Internet of Things (IoT).

Two Key ITSM 2.0 Differentiators: Integrated IT Operations and Endpoint Optimization

While each of these areas of differentiation deserves a more extensive discussion, in this blog I’d like to highlight two: integrated IT operations and endpoint optimization.

Integrated IT Operations

Bringing IT operations together with ITSM is one of the most poorly documented and yet most critical areas of advancement in the industry.

Here are some of the attributes of integrated IT operations that stand out in ongoing research and dialogs:

■ Sharing data for a far more integrated approach to availability and performance management, as combined with incident and problem management – This data can include event and time-series data, more advanced analytics including support for security, service modeling (CMDB, ADDM), shared knowledgebase access, and a growing role for social media and business data. Common mobile access can make this sharing of information even more compelling.

■ Sharing data for change management, and even agile or DevOps needs – This often requires increased insight into service modeling and automation in particular.

■ Improved workflow automation across IT operations and ITSM teams – As I mentioned, in many conversations I’m finding that it’s ITSM that is becoming the creative force in breaking through operations silos.

■ Project management governance.

■ Documented OpEx efficiencies to help IT operations and ITSM continue to improve in how they work, both collectively and individually.

■ Far more effective user experience management that places all the resources of ITSM teams and IT operations together on a common footing.

Endpoint Optimization

EMA is just concluding research on “Optimizing IT for Financial Performance.” And in that research ITSM once again plays a central role. Given the ascendant requirements to support mobile stakeholders, optimizing endpoints in terms of cost and value is a leading feature of ITSM 2.0. The top prioritized functional areas were the following:

■ Security

■ Software usage

■ License management

■ Software distribution

■ Power management

■ Hardware lifecycle management

■ Endpoint hardware usage

Endpoint optimization can also be greatly enhanced through service catalogs and app stores that integrate cost, SLAs, and usage insights into how end consumers access IT services.

In Conclusion

By implication at least, I hope you can see why I view ITSM 2.0 as a cornerstone of both IT and digital transformation, as it can be a unifier for IT, as well as for IT-to-business efficiencies and relevance. This unification stretches across process, data, technology, and dialog, with ITSM teams often forming a hub for all of these factors to come together.

But this isn’t actually the end of my discussion on ITSM 2.0. I’ll be following up with one more blog: ITSM 2.0 challenges. So stay tuned for more.

Image removed.

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I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...