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Change Management Part 3: Optimizing Change Management for Cloud, Agile, and Mobile - How the Technologies Are Evolving

Dennis Drogseth

This is is Part 3 of a three-part series on change management. In Part 1, I examined both the processes and the use cases associated with managing change. In In Part 2, I looked at metrics, best practices, and pitfalls. In this third blog, I’ll look at how the technologies for service modeling, automation, visualization, and self-service are evolving to address the more dynamic demands of trends such as cloud, agile, and mobile.

Start with Change Management Part 1

Start with Change Management Part 2

Service Modeling

The place to start with any discussion of service modeling is still the configuration management database (CMDB) or configuration management system (CMS). However, service modeling is also important in service catalog capabilities for self-service, as well as application discovery and dependency mapping (ADDM) solutions.

In EMA research and consulting, we have seen increasingly close ties between service modeling and automation, as well as between service modeling and analytics. EMA has also documented a growing number of agile and DevOps initiatives leveraging CMS backbones for more timely provisioning and governance. Examples can be found in our book, CMDB Systems: Making Change Work in the Age of Cloud and Agile.

Image removed.All this may seem to go against the common wisdom, especially since the notion of service modeling, and the idea of deploying CMDBs in particular, is not infrequently thought of as “old hat.” But the truth is the CMDB/CMS/ADDM landscape is changing dramatically to support higher levels of dynamic currency, more advanced levels of automation, and more effective use of advanced analytics. EMA’s recent report What is the Future of IT Service Management? those respondents with CMDBs were twice as likely to be successful in their ITSM initiatives as those without, and those with ADDM capabilities were eight times more empowered. Similar trends emerged when EMA did research targeting effective service delivery over cloud in Q2 2013 and when we evaluated advanced operations analytics in Q4 2014.

One reason that CMBDs and ADDM tools can make such a difference is that while cloud and virtualization make capturing service interdependencies more difficult, they actually require more not less attention to optimizing service-to-infrastructure relationships across a broader and more eclectic mosaic of choices. Optimizing cloud, in all of its iterations (public/ private, SaaS, IaaS) is ultimately about visibility and control, not a cloudy faith in blind speed.

Automation

Not surprisingly, cloud also raises the bar for automation. In that same recent research on ITSM futures, we saw that “cloud ups the ante for increasing investments in automation in provisioning services” as a top choice (just after viewing cloud as a resource for growth). This choice was tied, not surprisingly, with “cloud is forcing us to pay more attention to DevOps.”

In our ITSM futures research, the top priorities for change-related automation were the following:

1. IT process automation (ITPA) – Also known as “runbook,” ITPA provides policy-based capabilities for integrating and unifying automation across everything from patch management to onboarding to service provisioning using a common set of automated workflows.

2. Systems configuration – This included automation in virtualized as well as non-virtualized environments.

3. Workflow between the service desk and operations – This priority reflects the pervasive need for better integration between service desk/operations that was seen in EMA’s ITSM futures research.

4. Storage and network configuration – Natural extensions of both cloud and traditional infrastructure, storage configuration and network configuration were each noted as automation priorities by 36% of respondents.

5. Automation for lifecycle asset management – This type of automation is made visibly more difficult in hybrid cloud environments. Although ranked fifth, this area was still a high priority overall and was selected by nearly one-third of respondents.

Visualization and Reporting

This may not sound new, but good visualization and reporting are more critical than ever for managing change. One way to address visualization is to ask which roles and use cases are supported. For more general change management, some of the roles to consider are domain specific (e.g., network, systems, desktop, mobile, security, service desk, applications, development). Cross-domain roles are also important, including engineering, architecture, service delivery, change management, asset management, financial planning, and user-experience management. Finally, to be truly aligned with business priorities, it’s often critical to include non-IT stakeholders, such as financial planning, non-IT executives, marketing, online operations, and partner management.

Service Catalog

Ideally, a service catalog, or even a service portal, should be a natural extension of the CMDB system, with consistent modeling and insight into relevant interdependencies. This is just as true for those catalogs that include cloud-based services as it is for those including in-house services as it’s becoming increasingly important to understand dependencies outside IT’s physical walls. Incorporating public-cloud, private-cloud, and non-cloud services in an integrated service catalog is more and more in demand, as is support for mobile access to corporate and other services.

Mobile and Self-Service

Managing mobile devices and support for self service, while separate, are linked in how they both support escalating consumer expectations surrounding the choice, availability and performance of IT services. Our ITSM futures research showed that mobile adoption has already become heterogeneous in most environments — including iPhones, Android, tablets and other devices. Moreover, 65% of our respondents offered mobile end consumers some level of access for corporate applications.

The top priority for self-service, the most consumer-driven form of change management, was, not surprisingly, automation for end-user access to services. Near the top were also self-service via a service catalog, and mobile access. Other prioritized self-service objectives, somewhat less directly related to change management, were self-service enabled knowledge management and automation for resolving end-user issues.

Changing Technologies in a Changing World

These are not the only technologies relevant to managing change. For instance, lifecycle asset management, usage analysis, and onboarding are all part of the picture. Moreover, analytics relevant to change management is increasingly part of the story as well — a topic I’ll address in October. But if there’s a net takeaway, it’s that change management technologies are themselves changing to address a changing world in the so-called “Digital Age.” This brave new world is neither “stable nor precise” according to the traditional IT canon. But it’s one of greater opportunity, greater dynamism, and greater dependency on IT services and their digital content than ever before.

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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 ...

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When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...

Change Management Part 3: Optimizing Change Management for Cloud, Agile, and Mobile - How the Technologies Are Evolving

Dennis Drogseth

This is is Part 3 of a three-part series on change management. In Part 1, I examined both the processes and the use cases associated with managing change. In In Part 2, I looked at metrics, best practices, and pitfalls. In this third blog, I’ll look at how the technologies for service modeling, automation, visualization, and self-service are evolving to address the more dynamic demands of trends such as cloud, agile, and mobile.

Start with Change Management Part 1

Start with Change Management Part 2

Service Modeling

The place to start with any discussion of service modeling is still the configuration management database (CMDB) or configuration management system (CMS). However, service modeling is also important in service catalog capabilities for self-service, as well as application discovery and dependency mapping (ADDM) solutions.

In EMA research and consulting, we have seen increasingly close ties between service modeling and automation, as well as between service modeling and analytics. EMA has also documented a growing number of agile and DevOps initiatives leveraging CMS backbones for more timely provisioning and governance. Examples can be found in our book, CMDB Systems: Making Change Work in the Age of Cloud and Agile.

Image removed.All this may seem to go against the common wisdom, especially since the notion of service modeling, and the idea of deploying CMDBs in particular, is not infrequently thought of as “old hat.” But the truth is the CMDB/CMS/ADDM landscape is changing dramatically to support higher levels of dynamic currency, more advanced levels of automation, and more effective use of advanced analytics. EMA’s recent report What is the Future of IT Service Management? those respondents with CMDBs were twice as likely to be successful in their ITSM initiatives as those without, and those with ADDM capabilities were eight times more empowered. Similar trends emerged when EMA did research targeting effective service delivery over cloud in Q2 2013 and when we evaluated advanced operations analytics in Q4 2014.

One reason that CMBDs and ADDM tools can make such a difference is that while cloud and virtualization make capturing service interdependencies more difficult, they actually require more not less attention to optimizing service-to-infrastructure relationships across a broader and more eclectic mosaic of choices. Optimizing cloud, in all of its iterations (public/ private, SaaS, IaaS) is ultimately about visibility and control, not a cloudy faith in blind speed.

Automation

Not surprisingly, cloud also raises the bar for automation. In that same recent research on ITSM futures, we saw that “cloud ups the ante for increasing investments in automation in provisioning services” as a top choice (just after viewing cloud as a resource for growth). This choice was tied, not surprisingly, with “cloud is forcing us to pay more attention to DevOps.”

In our ITSM futures research, the top priorities for change-related automation were the following:

1. IT process automation (ITPA) – Also known as “runbook,” ITPA provides policy-based capabilities for integrating and unifying automation across everything from patch management to onboarding to service provisioning using a common set of automated workflows.

2. Systems configuration – This included automation in virtualized as well as non-virtualized environments.

3. Workflow between the service desk and operations – This priority reflects the pervasive need for better integration between service desk/operations that was seen in EMA’s ITSM futures research.

4. Storage and network configuration – Natural extensions of both cloud and traditional infrastructure, storage configuration and network configuration were each noted as automation priorities by 36% of respondents.

5. Automation for lifecycle asset management – This type of automation is made visibly more difficult in hybrid cloud environments. Although ranked fifth, this area was still a high priority overall and was selected by nearly one-third of respondents.

Visualization and Reporting

This may not sound new, but good visualization and reporting are more critical than ever for managing change. One way to address visualization is to ask which roles and use cases are supported. For more general change management, some of the roles to consider are domain specific (e.g., network, systems, desktop, mobile, security, service desk, applications, development). Cross-domain roles are also important, including engineering, architecture, service delivery, change management, asset management, financial planning, and user-experience management. Finally, to be truly aligned with business priorities, it’s often critical to include non-IT stakeholders, such as financial planning, non-IT executives, marketing, online operations, and partner management.

Service Catalog

Ideally, a service catalog, or even a service portal, should be a natural extension of the CMDB system, with consistent modeling and insight into relevant interdependencies. This is just as true for those catalogs that include cloud-based services as it is for those including in-house services as it’s becoming increasingly important to understand dependencies outside IT’s physical walls. Incorporating public-cloud, private-cloud, and non-cloud services in an integrated service catalog is more and more in demand, as is support for mobile access to corporate and other services.

Mobile and Self-Service

Managing mobile devices and support for self service, while separate, are linked in how they both support escalating consumer expectations surrounding the choice, availability and performance of IT services. Our ITSM futures research showed that mobile adoption has already become heterogeneous in most environments — including iPhones, Android, tablets and other devices. Moreover, 65% of our respondents offered mobile end consumers some level of access for corporate applications.

The top priority for self-service, the most consumer-driven form of change management, was, not surprisingly, automation for end-user access to services. Near the top were also self-service via a service catalog, and mobile access. Other prioritized self-service objectives, somewhat less directly related to change management, were self-service enabled knowledge management and automation for resolving end-user issues.

Changing Technologies in a Changing World

These are not the only technologies relevant to managing change. For instance, lifecycle asset management, usage analysis, and onboarding are all part of the picture. Moreover, analytics relevant to change management is increasingly part of the story as well — a topic I’ll address in October. But if there’s a net takeaway, it’s that change management technologies are themselves changing to address a changing world in the so-called “Digital Age.” This brave new world is neither “stable nor precise” according to the traditional IT canon. But it’s one of greater opportunity, greater dynamism, and greater dependency on IT services and their digital content than ever before.

Hot Topics

The Latest

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 ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...