Businesses Struggle to Enter New Digital Era

New survey reveals only 12% of today’s enterprises have fully transitioned to modern tools
Learn more about ScienceLogic

Enterprises depending exclusively on legacy monitoring tools are falling behind in business agility and operational efficiency, according to a new study, Prevalence of Legacy Tools Paralyzes Enterprises' Ability to Innovate, commissioned by Sciencelogic and conducted by Forrester Consulting.

The report says organizations with disjointed and outdated IT offerings that utilize legacy tools and strategies are trapped in a perpetual survival mode and unable to innovate.

Only 12% of respondents report having fully transitioned to modern monitoring tools, with 37% still relying exclusively on legacy tools keeping them stuck in a digital deadlock.

Respondents also revealed that legacy toolsets remain prevalent in their IT ecosystem, further relaying the negative implications of legacy IT vendors and tools that undermine service resilience, fast mean-time-to resolution, and the ability to automate to scale.

86% said they still use at least one legacy tool, which is actively exposing their business to negative impacts including high costs of IT support, service degradation, and increased security risks.

Top findings from the study include:

■ One third (33%) of companies are using 20 or more infrastructure and application monitoring tools that contribute to IT complexity

■ Legacy tools are causing long service disruptions and poor customer experience, while not supporting the shift to hybrid-cloud environments or new application architectures

■ End-to-end visibility into IT assets across hybrid architectures was named as a significant technical benefit of AIOps by 49% of respondents

■ 68% of decision-makers cite business agility as the top driver for changes in IT operations

The Opportunity Ahead

Mature enterprises are attempting to match their digital-native counterparts by adopting cloud-based architectures, but continue to fall short, as many modern tools are unable to manage outdated legacy systems.

To address IT visibility and remediation challenges, over two-thirds (68%) of companies surveyed have plans to invest in AIOps-enabled monitoring solutions over the next 12 months. These solutions apply AI/ML-driven analytics to business and operations data to make correlations and provide real-time insights that allow IT operations teams to resolve incidents faster–and avoid incidents altogether.

IT decision-makers reported that the major benefits of AIOps solutions include increased operational efficiency and business agility, as well as reduced cost of downtime.

"Enterprises that operate on dozens of legacy vendor tools are siloing the view of their IT environment, leading to prolonged service disruptions, issues with incident resolution, and ultimately, providing for a poor customer experience. These 'survival mode enterprises' have little chance of getting ahead of the agility curve and are in real danger of being left behind," said Dave Link, founder and CEO of ScienceLogic. "As the adoption of newer technologies like containers and microservices continues to rise, forward-thinking companies will drive extensive automation with artificial intelligence and machine learning algorithms. This study shows that companies will need to adopt innovations like AIOps to ensure a successful modernization and automation journey."

"These enterprises are starting to take the leap to modernize their IT environment, however, survival will require a cultural shift in how people and organizations understand the flow and impact of clean data as part of a broader strategy towards automation," Link added. "The reality is that those who have not started are already behind, but it is not too late to future-proof your IT systems and teams so they may focus on innovative advancements to propel your enterprise to market success."

Methodology: Survey respondents included IT decision makers and leaders from large organizations. Respondents have influence over or are the decision maker for their organization's infrastructure and application monitoring. The custom survey was completed in July 2019.

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Businesses Struggle to Enter New Digital Era

New survey reveals only 12% of today’s enterprises have fully transitioned to modern tools
Learn more about ScienceLogic

Enterprises depending exclusively on legacy monitoring tools are falling behind in business agility and operational efficiency, according to a new study, Prevalence of Legacy Tools Paralyzes Enterprises' Ability to Innovate, commissioned by Sciencelogic and conducted by Forrester Consulting.

The report says organizations with disjointed and outdated IT offerings that utilize legacy tools and strategies are trapped in a perpetual survival mode and unable to innovate.

Only 12% of respondents report having fully transitioned to modern monitoring tools, with 37% still relying exclusively on legacy tools keeping them stuck in a digital deadlock.

Respondents also revealed that legacy toolsets remain prevalent in their IT ecosystem, further relaying the negative implications of legacy IT vendors and tools that undermine service resilience, fast mean-time-to resolution, and the ability to automate to scale.

86% said they still use at least one legacy tool, which is actively exposing their business to negative impacts including high costs of IT support, service degradation, and increased security risks.

Top findings from the study include:

■ One third (33%) of companies are using 20 or more infrastructure and application monitoring tools that contribute to IT complexity

■ Legacy tools are causing long service disruptions and poor customer experience, while not supporting the shift to hybrid-cloud environments or new application architectures

■ End-to-end visibility into IT assets across hybrid architectures was named as a significant technical benefit of AIOps by 49% of respondents

■ 68% of decision-makers cite business agility as the top driver for changes in IT operations

The Opportunity Ahead

Mature enterprises are attempting to match their digital-native counterparts by adopting cloud-based architectures, but continue to fall short, as many modern tools are unable to manage outdated legacy systems.

To address IT visibility and remediation challenges, over two-thirds (68%) of companies surveyed have plans to invest in AIOps-enabled monitoring solutions over the next 12 months. These solutions apply AI/ML-driven analytics to business and operations data to make correlations and provide real-time insights that allow IT operations teams to resolve incidents faster–and avoid incidents altogether.

IT decision-makers reported that the major benefits of AIOps solutions include increased operational efficiency and business agility, as well as reduced cost of downtime.

"Enterprises that operate on dozens of legacy vendor tools are siloing the view of their IT environment, leading to prolonged service disruptions, issues with incident resolution, and ultimately, providing for a poor customer experience. These 'survival mode enterprises' have little chance of getting ahead of the agility curve and are in real danger of being left behind," said Dave Link, founder and CEO of ScienceLogic. "As the adoption of newer technologies like containers and microservices continues to rise, forward-thinking companies will drive extensive automation with artificial intelligence and machine learning algorithms. This study shows that companies will need to adopt innovations like AIOps to ensure a successful modernization and automation journey."

"These enterprises are starting to take the leap to modernize their IT environment, however, survival will require a cultural shift in how people and organizations understand the flow and impact of clean data as part of a broader strategy towards automation," Link added. "The reality is that those who have not started are already behind, but it is not too late to future-proof your IT systems and teams so they may focus on innovative advancements to propel your enterprise to market success."

Methodology: Survey respondents included IT decision makers and leaders from large organizations. Respondents have influence over or are the decision maker for their organization's infrastructure and application monitoring. The custom survey was completed in July 2019.

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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 ...

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 ...

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Why ITOps Need Right-Sized AI, Not Bigger Models

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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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