2021 Application Performance Management Predictions - Part 6

Industry experts — from analysts and consultants to users and the top vendors — offer thoughtful, insightful, and often controversial predictions on how APM and related technologies will evolve and impact business in 2021. Part 6, the final installment in the series, covers ITSM.

Start with: 2021 Application Performance Management Predictions - Part 1

Start with: 2021 Application Performance Management Predictions - Part 2

Start with: 2021 Application Performance Management Predictions - Part 3

Start with: 2021 Application Performance Management Predictions - Part 4

Start with: 2021 Application Performance Management Predictions - Part 5

FOCUS ON BUSINESS CONTINUITY

Business continuity and operational risk management interest takes precedence. It is not a question of "if," but rather "when" a disaster will strike. Responding to an incident in crisis mode without the benefit of planning, coordination, and testing can result in more downtime, higher recovery costs and times, a potential negative impact on brand and reputation, and business loss. In 2021, with the continued impact of COVID, we are likely to see even more interest from businesses, customers and investors regarding operational risk management, business continuity, and resiliency.
Anne Hardy
CISO, Talend

IMPROVED ITSM GUI AND DASHBOARDS

A common trend among IT Central Station ITSM reviews in 2020 was the lack of user-friendly interfaces. I therefore foresee vendors investing in the improvement of their GUIs and dashboards to enhance the user experience.
Russell Rothstein
Founder and CEO, IT Central Station

SELF-SERVICE ITSM

AI/ML assisted self-service whether through chat bots, virtual assistants, or purpose-built portals will become the channel of choice for offering or receiving help and information. On the enterprise side, the stunning cost savings make it a no-brainer. But customers and employees choose it as well. No surprise here. People like getting what they want or need, when they want or need it, in the way they want to seek it.
Valerie O'Connell
Research Director, Enterprise Management Associates (EMA)

In reaction to the pandemic, more and more organizations will bring in internal IT teams, and utilize self-service models and SaaS platforms to reduce the dependencies on external resources.
Ali Siddiqui
CPO, BMC Software

In 2021, chatbots powered with AI will begin to eliminate the "front-line" support analyst as the human ITSM analyst will be replaced with self-service portals and intelligent chatbots. Analysts will shift their focus to major incidents (one-to-many), problem management, and change management. Over the next 3-5 years, human involvement for most ITIL processes will be decreased because of improved machine learning and automation capabilities. We will see the traditional IT analysts become much more focused on business objectives versus IT tasks.
Marcel Shaw
Principal Federal Solutions Architect, Ivanti

Self-Serve Analytics will ramp up in 2021. As the pandemic continues in 2021, companies will look to further reduce dependencies on IT functions with self-serve analytics. This will help them turn data into valuable, shareable assets more quickly. Remote workforces and online expansions are draining IT resources. Automated data preparation, curation, stewardship, quality controls, and machine learning tools will help to stem the tide of IT demands.
Krishna Tamman
CTO, Talend

ENTERPRISE SERVICE MANAGEMENT

The use of ITSM people, processes, and products in support of non-IT functions such as HR and facilities will become the norm. In a world where people will complain about the mustard at a free lunch, EMA research yields an absolutely unambiguous endorsement of ESM. It has universally positive outcomes. C-level keepers of the budget will fund these initiatives without hesitation.
Valerie O'Connell
Research Director, Enterprise Management Associates (EMA)

As organizations have adjusted to the realities of remote work and adapting to manual tasks which result in decreased productivity, businesses are scaling and deploying ITSM solutions, leading to an increase in operational complexity to support the diverse needs of users and IT environments. To help reduce this complexity, and deliver an amazing employee experience organizations will look to enterprise service management solutions as a way to adopt processes that drive digital transformation. With AI service management, businesses can leverage hyper-automation and operations automation to increase productivity across the organization. Enterprise service management is the natural evolution to ITSM and will help businesses evolve into autonomous digital enterprises.
Ali Siddiqui
CPO, BMC Software

CMDB/CMS GETS NEW LIFE

It's back to the future as old ideas get new life in new use cases. CMDB/CMS will get a brand refresh for its critical role in delivering the service modeling that AIOps requires. With digital transformation in overdrive, service modeling and effective change management are center stage. CMDB/CMS in combination with discovery and dependency mapping (DDM) will be re-imagined and shaped to new use cases that power service excellence and cost-cutting initiatives.
Valerie O'Connell
Research Director, Enterprise Management Associates (EMA)

IOT PERFORMANCE IMPROVES

Adoption of IoT use cases under the umbrella of "edge computing" will accelerate standardization of operating system and application components, greatly improving performance, monitoring, and reliability of IoT solutions.
Jered Floyd
Technology Strategist, Office of the CTO, Red Hat

Check back after the Holidays for 2 more predictions series, covering NPM and the Cloud.

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Keys to Building a Partner Ecosystem That Scales

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 ...

How AI Agents Are Reshaping DataOps for the Always-On Enterprise

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 ...

AI Deepfakes: Rethinking Trust in the Workplace

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 ...

Nine in Ten Enterprises Plan Cloud Data Repatriation amid Rising Cloud Costs and Data Sovereignty Mandates

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 ...

Why ITOps Need Right-Sized AI, Not Bigger Models

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 ...

The End of Reactive DevOps: AI-Driven Observability for Zero-Defect Digital Systems

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 ...

5 Takeaways from the Observability Forecast for Media and Entertainment

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 ...

Why Moving Off the Cloud Is the Easy Part and What Comes Next Is Where Things Get Hard

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 ...

MEAN TIME TO INSIGHT Podcast - Episode 24: Network Observability Tool Sprawl

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Capacity Isn't a Guess: Observability-Driven Sizing for On-Prem Databases

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 ...

2021 Application Performance Management Predictions - Part 6

Industry experts — from analysts and consultants to users and the top vendors — offer thoughtful, insightful, and often controversial predictions on how APM and related technologies will evolve and impact business in 2021. Part 6, the final installment in the series, covers ITSM.

Start with: 2021 Application Performance Management Predictions - Part 1

Start with: 2021 Application Performance Management Predictions - Part 2

Start with: 2021 Application Performance Management Predictions - Part 3

Start with: 2021 Application Performance Management Predictions - Part 4

Start with: 2021 Application Performance Management Predictions - Part 5

FOCUS ON BUSINESS CONTINUITY

Business continuity and operational risk management interest takes precedence. It is not a question of "if," but rather "when" a disaster will strike. Responding to an incident in crisis mode without the benefit of planning, coordination, and testing can result in more downtime, higher recovery costs and times, a potential negative impact on brand and reputation, and business loss. In 2021, with the continued impact of COVID, we are likely to see even more interest from businesses, customers and investors regarding operational risk management, business continuity, and resiliency.
Anne Hardy
CISO, Talend

IMPROVED ITSM GUI AND DASHBOARDS

A common trend among IT Central Station ITSM reviews in 2020 was the lack of user-friendly interfaces. I therefore foresee vendors investing in the improvement of their GUIs and dashboards to enhance the user experience.
Russell Rothstein
Founder and CEO, IT Central Station

SELF-SERVICE ITSM

AI/ML assisted self-service whether through chat bots, virtual assistants, or purpose-built portals will become the channel of choice for offering or receiving help and information. On the enterprise side, the stunning cost savings make it a no-brainer. But customers and employees choose it as well. No surprise here. People like getting what they want or need, when they want or need it, in the way they want to seek it.
Valerie O'Connell
Research Director, Enterprise Management Associates (EMA)

In reaction to the pandemic, more and more organizations will bring in internal IT teams, and utilize self-service models and SaaS platforms to reduce the dependencies on external resources.
Ali Siddiqui
CPO, BMC Software

In 2021, chatbots powered with AI will begin to eliminate the "front-line" support analyst as the human ITSM analyst will be replaced with self-service portals and intelligent chatbots. Analysts will shift their focus to major incidents (one-to-many), problem management, and change management. Over the next 3-5 years, human involvement for most ITIL processes will be decreased because of improved machine learning and automation capabilities. We will see the traditional IT analysts become much more focused on business objectives versus IT tasks.
Marcel Shaw
Principal Federal Solutions Architect, Ivanti

Self-Serve Analytics will ramp up in 2021. As the pandemic continues in 2021, companies will look to further reduce dependencies on IT functions with self-serve analytics. This will help them turn data into valuable, shareable assets more quickly. Remote workforces and online expansions are draining IT resources. Automated data preparation, curation, stewardship, quality controls, and machine learning tools will help to stem the tide of IT demands.
Krishna Tamman
CTO, Talend

ENTERPRISE SERVICE MANAGEMENT

The use of ITSM people, processes, and products in support of non-IT functions such as HR and facilities will become the norm. In a world where people will complain about the mustard at a free lunch, EMA research yields an absolutely unambiguous endorsement of ESM. It has universally positive outcomes. C-level keepers of the budget will fund these initiatives without hesitation.
Valerie O'Connell
Research Director, Enterprise Management Associates (EMA)

As organizations have adjusted to the realities of remote work and adapting to manual tasks which result in decreased productivity, businesses are scaling and deploying ITSM solutions, leading to an increase in operational complexity to support the diverse needs of users and IT environments. To help reduce this complexity, and deliver an amazing employee experience organizations will look to enterprise service management solutions as a way to adopt processes that drive digital transformation. With AI service management, businesses can leverage hyper-automation and operations automation to increase productivity across the organization. Enterprise service management is the natural evolution to ITSM and will help businesses evolve into autonomous digital enterprises.
Ali Siddiqui
CPO, BMC Software

CMDB/CMS GETS NEW LIFE

It's back to the future as old ideas get new life in new use cases. CMDB/CMS will get a brand refresh for its critical role in delivering the service modeling that AIOps requires. With digital transformation in overdrive, service modeling and effective change management are center stage. CMDB/CMS in combination with discovery and dependency mapping (DDM) will be re-imagined and shaped to new use cases that power service excellence and cost-cutting initiatives.
Valerie O'Connell
Research Director, Enterprise Management Associates (EMA)

IOT PERFORMANCE IMPROVES

Adoption of IoT use cases under the umbrella of "edge computing" will accelerate standardization of operating system and application components, greatly improving performance, monitoring, and reliability of IoT solutions.
Jered Floyd
Technology Strategist, Office of the CTO, Red Hat

Check back after the Holidays for 2 more predictions series, covering NPM and the Cloud.

Related Links

Hot Topics

The Latest

Keys to Building a Partner Ecosystem That Scales

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 ...

How AI Agents Are Reshaping DataOps for the Always-On Enterprise

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 ...

AI Deepfakes: Rethinking Trust in the Workplace

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 ...

Nine in Ten Enterprises Plan Cloud Data Repatriation amid Rising Cloud Costs and Data Sovereignty Mandates

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 ...

Why ITOps Need Right-Sized AI, Not Bigger Models

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 ...

The End of Reactive DevOps: AI-Driven Observability for Zero-Defect Digital Systems

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 ...

5 Takeaways from the Observability Forecast for Media and Entertainment

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 ...

Why Moving Off the Cloud Is the Easy Part and What Comes Next Is Where Things Get Hard

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 ...

MEAN TIME TO INSIGHT Podcast - Episode 24: Network Observability Tool Sprawl

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

Capacity Isn't a Guess: Observability-Driven Sizing for On-Prem Databases

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 ...