Top CIO Challenges: IT Complexity and Managing IT Performance

Learn more about Dynatrace

Digital transformation, migration to the enterprise cloud and increasing customer demands are creating a surge in IT complexity and the associated costs of managing it. Technical leaders around the world are concerned about the effect this has on IT performance and ultimately, their business according to a new report from Dynatrace, based on an independent global survey of 800 CIOs, Top Challenges for CIOs in a Software-Driven, Hybrid, Multi-Cloud World.

CIO responses to the survey indicate that lost revenue (49%) and reputational damage (52%) are among the biggest concerns as businesses transform into software businesses and move to the cloud.

And, as CIOs struggle to prevent these concerns from becoming reality, IT teams now spend 33% of their time dealing with digital performance problems, costing businesses an average of $3.3 million annually, compared to $2.5 million in 2018; an increase of 34%. To combat this, 88% of CIOs say AI will be critical to IT’s ability to master increasing complexity.

Software is Transforming Every Business

Every company, in every industry, is transforming into a software business. The way enterprises interact with customers, assure quality experiences and optimize revenues is driven by applications and the hybrid, multi-cloud environments underpinning them. Success or failure comes down to the software supporting these efforts. The pressure of this "run-the-business" software performing properly has significant ramifications for IT professionals.

According to the survey:

■ 44% of CIOs fear there could be a threat to the existence of their business if they are unable to manage IT performance.

■ As complexity continues to grow, 74% of CIOs say it could soon become extremely difficult to manage performance efficiently.


Enterprise "Cloud-First" Strategies Increase Complexity

Underpinning this software revolution is the enterprise cloud, allowing companies to innovate faster and better meet the needs of customers. The enterprise cloud is dynamic, hybrid, multi-cloud, and web-scale, containing hundreds of technologies, millions of lines of code and billions of dependencies. However, this transformation isn’t simply about lifting and shifting apps to the cloud, it’s a fundamental shift in how applications are built, deployed and operated.

According to the survey:

■ The majority of CIOs are already using or are planning to deploy microservices (88%), containers (86%), serverless computing (85%), PaaS (89%), SaaS (94%), IaaS (91%) and private cloud (95%) in the next 12 months.

■ The average mobile or web application transaction crosses 37 different technology systems or components. This brings an inherent increase in IT complexity, making it harder for organizations to manage performance.

The Age of the Customer Increases Pressure to Deliver Great Experiences

We are squarely in the age of the customer, where high quality service is paramount due to the ease with which customers will try competitive offerings and share their experiences instantly via social media.

The research highlights the extent to which businesses are struggling to combat IT complexity that threatens the customer experience, with CIOs revealing: on average, organizations have suffered 6 IT outages where user-experiences, business revenues or operations were impacted in the last 12 months.

IT Teams Are Feeling the Strain

Digital transformation, migration to the enterprise cloud and increasing customer demands are collectively putting pressure on IT teams, who continue to feel the strain, especially as it relates to performance. Revealing the extent of this dilemma, key findings of the research also show that:

■ More than three quarters of CIOs (76%) say they don’t have complete visibility into application performance in cloud-native architectures.

■ 78% of CIOs are frustrated that so much time is spent setting up monitoring for different cloud environments when deploying new services.

■ IT teams now spend around 33% of their time tackling performance problems.


Exploring the potential antidote to these challenges, the research further reveals that 88% of CIOs say that they believe AI will be critical to IT’s ability to master increasing complexity.

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Top CIO Challenges: IT Complexity and Managing IT Performance

Learn more about Dynatrace

Digital transformation, migration to the enterprise cloud and increasing customer demands are creating a surge in IT complexity and the associated costs of managing it. Technical leaders around the world are concerned about the effect this has on IT performance and ultimately, their business according to a new report from Dynatrace, based on an independent global survey of 800 CIOs, Top Challenges for CIOs in a Software-Driven, Hybrid, Multi-Cloud World.

CIO responses to the survey indicate that lost revenue (49%) and reputational damage (52%) are among the biggest concerns as businesses transform into software businesses and move to the cloud.

And, as CIOs struggle to prevent these concerns from becoming reality, IT teams now spend 33% of their time dealing with digital performance problems, costing businesses an average of $3.3 million annually, compared to $2.5 million in 2018; an increase of 34%. To combat this, 88% of CIOs say AI will be critical to IT’s ability to master increasing complexity.

Software is Transforming Every Business

Every company, in every industry, is transforming into a software business. The way enterprises interact with customers, assure quality experiences and optimize revenues is driven by applications and the hybrid, multi-cloud environments underpinning them. Success or failure comes down to the software supporting these efforts. The pressure of this "run-the-business" software performing properly has significant ramifications for IT professionals.

According to the survey:

■ 44% of CIOs fear there could be a threat to the existence of their business if they are unable to manage IT performance.

■ As complexity continues to grow, 74% of CIOs say it could soon become extremely difficult to manage performance efficiently.


Enterprise "Cloud-First" Strategies Increase Complexity

Underpinning this software revolution is the enterprise cloud, allowing companies to innovate faster and better meet the needs of customers. The enterprise cloud is dynamic, hybrid, multi-cloud, and web-scale, containing hundreds of technologies, millions of lines of code and billions of dependencies. However, this transformation isn’t simply about lifting and shifting apps to the cloud, it’s a fundamental shift in how applications are built, deployed and operated.

According to the survey:

■ The majority of CIOs are already using or are planning to deploy microservices (88%), containers (86%), serverless computing (85%), PaaS (89%), SaaS (94%), IaaS (91%) and private cloud (95%) in the next 12 months.

■ The average mobile or web application transaction crosses 37 different technology systems or components. This brings an inherent increase in IT complexity, making it harder for organizations to manage performance.

The Age of the Customer Increases Pressure to Deliver Great Experiences

We are squarely in the age of the customer, where high quality service is paramount due to the ease with which customers will try competitive offerings and share their experiences instantly via social media.

The research highlights the extent to which businesses are struggling to combat IT complexity that threatens the customer experience, with CIOs revealing: on average, organizations have suffered 6 IT outages where user-experiences, business revenues or operations were impacted in the last 12 months.

IT Teams Are Feeling the Strain

Digital transformation, migration to the enterprise cloud and increasing customer demands are collectively putting pressure on IT teams, who continue to feel the strain, especially as it relates to performance. Revealing the extent of this dilemma, key findings of the research also show that:

■ More than three quarters of CIOs (76%) say they don’t have complete visibility into application performance in cloud-native architectures.

■ 78% of CIOs are frustrated that so much time is spent setting up monitoring for different cloud environments when deploying new services.

■ IT teams now spend around 33% of their time tackling performance problems.


Exploring the potential antidote to these challenges, the research further reveals that 88% of CIOs say that they believe AI will be critical to IT’s ability to master increasing complexity.

Related Links

Hot Topics

The Latest

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 ...

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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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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 ...

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