Reinventing ITSM? It's Not Going Away - Part 2
March 08, 2019

Dennis Drogseth
EMA

Share this

As some of you may know by now, one of my ongoing areas of focus is analytics, AIOps, and the intersection with AI and machine learning more broadly. Within this space, sad to say, semantic confusion surrounding just what these terms mean echoes the confusions surrounding ITSM.

Start with Reinventing ITSM? It's Not Going Away - Part 1

Analytics, AI and Automation

So we asked our respondents for a moment of "AI" free association, with a wide list of diverse terms to choose from. Spoiler alert, just to let you know now, the top choice was machine learning — which was the most logical single equivalent. But the longer list of priorities was yet more telling and more surprising, especially when you link "AI" definitions to IT and non-IT roles.

In addressing analytics and AI, we looked at the following technology initiatives, both in terms of prevalence and priority.

■ AIOps

■ Incident response analytics

■ Governance-related analytics (improving OpEx efficiencies)

■ Asset and cost optimization analysis

■ Big data

■ Analytics specific to business performance (e.g. revenue, business process efficiencies)

Then we mapped these, as well as priorities in automation (a list too long to go into here), to the following use cases:

■ Integrated operations (for superior availability, performance, and change management)

■ Integrated asset management/IT financial planning

■ Self-service capabilities for routine requests and services

■ Enterprise service management (ESM for HR, facilities, etc.)

■ DevOps/agile initiatives

■ Major Incident response

■ Integrated security and operations (SecOps)

■ Internet of Things (IoT)

The patterns we saw highlighted a lot of commonalities in terms of priorities for combining analytics and automation, integration needs, benefits and obstacles. But we also found some striking differences as we mapped the use-case-specific details across a wide range of variables from company size, to level of process and technology sophistication, to success rates, among many others.

If there was one common lesson, it was that those most progressed in use cases, were also most progressed in AI and analytics and most progressed in automation. Not surprisingly, they were also more willing to let automation be driven by analytic insights and AI.

Virtual Agents, AI Bots, ESM, and Wrapping Up

The first three topics in this header could easily be another blog in themselves, or two blogs, or actually a whole series of blogs. But to echo what I mentioned earlier, the overarching message turned out to be surprising commonality.

Even ESM, which reaches out to enable enterprise service workflows (and we examined how and why in-depth) showed strong synergies with AI/analytics and automation investments, as well as many other factors that turned out to characterize our "more progressive" groups.

To learn more about how and why, please join Valerie and me on April 11, as we discuss our findings in Automation, AI and Analytics: Reinventing ITSM.

Read Reinventing ITSM? It's Not Going Away - Part 3

In the meantime, I invite you to share your questions, perspectives, areas of interest, and concerns with us ...

Click here to email Dennis Drogseth with your comments

Dennis Drogseth is VP at Enterprise Management Associates (EMA)
Share this

The Latest

May 20, 2019

In today's competitive landscape, businesses must have the ability and process in place to face new challenges and find ways to successfully tackle them in a proactive manner. For years, this has been placed on the shoulders of DevOps teams within IT departments. But, as automation takes over manual intervention to increase speed and efficiency, these teams are facing what we know as IT digitization. How has this changed the way companies function over the years, and what do we have to look forward to in the coming years? ...

May 16, 2019

Although the vast majority of IT organizations have implemented a broad variety of systems and tools to modernize, simplify and streamline data center operations, many are still burdened by inefficiencies, security risks and performance gaps in their IT infrastructure as well as the excessive time it takes to manage legacy infrastructure, according to the State of IT Transformation, a report from Datrium ...

May 15, 2019

When it comes to network visibility, there are a lot of discussions about packet broker technology and the various features these solutions provide to network architects and IT managers. Packet brokers allow organizations to aggregate the data required for a variety of monitoring solutions including network performance monitoring and diagnostic (NPMD) platforms and unified threat management (UTM) appliances. But, when it comes to ensuring these solutions provide the insights required by NetOps and security teams, IT can spend an exorbitant amount of time dealing with issues around adds, moves and changes. This can have a dramatic impact on budgets and tool availability. Why does this happen? ...

May 14, 2019

Data may be pouring into enterprises but IT professionals still find most of it stuck in siloed departments and weeks away from being able to drive any valued action. Coupled with the ongoing concerns over security responsiveness, IT teams have to push aside other important performance-oriented data in order to ensure security data, at least, gets prominent attention. A new survey by Ivanti shows the disconnect between enterprise departments struggling to improve operations like automation while being challenged with a siloed structure and a data onslaught ...

May 13, 2019

A subtle, deliberate shift has occurred within the software industry which, at present, only the most innovative organizations have seized upon for competitive advantage. Although primarily driven by Artificial Intelligence (AI), this transformation strikes at the core of the most pervasive IT resources including cloud computing and predictive analytics ...