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The Overconfidence Effect in Cloud Cost Management is Real (and Expensive)

Kash Shaikh
Virtana

"If I had asked people what they wanted, they would have said faster horses." - Henry Ford

In other words, do not try to make horses go incrementally faster, create the automobile (like the Ford Model T). Digital transformation, including its underpinning cloud infrastructure, is meant to deliver innovations that leapfrog the status quo.

The 21st century version uses digital technology and automation to overcome human limitations. Example: Performing calculations in the blink of an eye that would take a person lifetimes to complete. We are often blind to the ways our human limitations can creep into various systems and processes — and this overconfidence in the status quo can be limiting.

According to the results of a recent survey of 350 IT leaders at global organizations, we found evidence of the overconfidence effect in cloud migration.

The overconfidence effect is a well-established cognitive bias where a person's subjective confidence in their judgment is greater than the objective accuracy of those judgments. In short, it is when we systematically overestimate our knowledge and ability to predict on a massive scale.

Here is what we found: 85% of cloud decision makers surveyed feel confident managing their cloud bills, but 82% of respondents have incurred unnecessary cloud costs. Clearly, there is no guarantee that confidence in your cloud cost management capabilities, even among tech-savvy leaders, means you can avoid needless spending.

So, what does this mean for companies in the race to digital transformation?

Obviously, the pandemic accelerated organizations' journey to the cloud to enable agile, on-demand, flexible access to resources, helping them align with a digital business's dynamic needs. We heard from many of our customers at the start of lockdown last year, saying they had to shift to a remote work environment, seemingly overnight, and this effort was heavily cloud-reliant. However, blindly forging ahead can backfire.

This latest survey reveals that in addition to the overconfidence effect, enterprises are facing additional challenges across the hybrid cloud thanks to disjointed point tools, silos, lack of visibility, unexpected costs, lack of programmatic optimization, and the role risk plays in cloud cost management.

Cloud Waste is a Massive Problem

One of the biggest challenges is how to manage workloads operating in the cloud without incurring unexpected and unnecessary costs, which can eat into budgets needed for other areas of transformation. Over the many years we have been working with customers to optimize their cloud infrastructures, we have found that up to a third of their cloud spend is waste.

Clearly this is a rampant problem that continues to plague enterprises. It is important to note that the 82% from the survey represents unnecessary costs that respondents are aware of. It is highly likely that companies are spending far more than they need to without even knowing it.

For example, 56% of respondents lack programmatic cloud cost management capabilities. This can mean either that teams are spending too much time managing cloud costs or that the cloud waste is allowed to fester. Either way, time and money are being spent unwisely. Not only that, it is likely that there is waste that is not being uncovered. And the more the overconfidence effect is at play within an organization, the less likely it is that this waste will be identified.

The lack of visibility across hybrid and multi-cloud environments also blurs the issue. 86% of respondents said they cannot get a global view of cloud costs within minutes, creating delays and potentially reducing agility. 71% of respondents agreed that limited visibility across the hybrid cloud environment hinders their ability to maximize value, creates inefficiencies, and wastes time.

Disjointed tools also present a challenge. 72% of respondents said they are fed up with piecing together disparate management tools to monitor and manage everything from infrastructure performance to migration readiness to cloud cost, and 62% report that they have to cobble together multiple tools, systems, and custom scripts to get a global view of cloud costs. Again, these are the very same respondents who said they are confident in their ability to manage cloud costs.

What Leads to Waste also Impedes Transformation

Lack of programmatic management, limited visibility, and disparate tools affect more than just cloud costs. IT leaders are also grappling with issues that could hamper a successful digital transformation. 68% of survey respondents stated that their teams operate in silos, and 70% said that limited collaboration hinders their ability to adapt quickly and improve business outcomes.

Additionally, 66% of respondents stated that it is hard to understand if they are delivering the service levels the business needs, and 65% agreed that when there is an issue, they are hard-pressed to identify the business impact.

Finally, 77% cited increased performance issues as one of the reasons that pressure on cloud teams is on the rise.

The bottom line is that if you do not know what is going on across your entire infrastructure, you do not know if you are adequately serving the needs of the business and you cannot deliver performance levels that the business demands, which means that you have not met some of the foundational needs of digital transformation.

Clearing the way to cost-effective transformation

Wherever you have "seams" in your cloud monitoring and management — whether that is a result of multiple clouds, siloed teams, disparate tools, or time lags, for example — you have blind spots where unnecessary costs and other problems can hide. Combine that with the overconfidence effect and those risks only go up. A single modular platform can eliminate those seams and create appropriate levels of confidence rooted in data to de-risk cloud migrations; deliver deep precision observability into workloads before, during, and after a move; and optimize and manage efficiently once workloads are in the cloud.

This is underscored by Archana Vankatarman, Associate Research Director of Cloud Data Management at IDC Europe who said, "The duct-taped point tools and silos can make cloud cost management complex. The belief that they are wasting at least 15% of their public cloud spending will drive enterprises to actively invest in cloud cost management to halve cloud waste."

The bottom line is that cloud management is always changing. If you feel confident about your cloud costs based on your gut, think again. Have the right tools to know before you go forward with any initiative. In the end, you will not be upset that you took the time to get it right — and save money.

Methodology: Arlington Research, commissioned by Virtana, surveyed 350 cloud decision makers in April 2021 at US- and UK-based organizations with 250+ employees to better understand multi-cloud deployment experiences.

Kash Shaikh is CEO and President of Virtana

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The Overconfidence Effect in Cloud Cost Management is Real (and Expensive)

Kash Shaikh
Virtana

"If I had asked people what they wanted, they would have said faster horses." - Henry Ford

In other words, do not try to make horses go incrementally faster, create the automobile (like the Ford Model T). Digital transformation, including its underpinning cloud infrastructure, is meant to deliver innovations that leapfrog the status quo.

The 21st century version uses digital technology and automation to overcome human limitations. Example: Performing calculations in the blink of an eye that would take a person lifetimes to complete. We are often blind to the ways our human limitations can creep into various systems and processes — and this overconfidence in the status quo can be limiting.

According to the results of a recent survey of 350 IT leaders at global organizations, we found evidence of the overconfidence effect in cloud migration.

The overconfidence effect is a well-established cognitive bias where a person's subjective confidence in their judgment is greater than the objective accuracy of those judgments. In short, it is when we systematically overestimate our knowledge and ability to predict on a massive scale.

Here is what we found: 85% of cloud decision makers surveyed feel confident managing their cloud bills, but 82% of respondents have incurred unnecessary cloud costs. Clearly, there is no guarantee that confidence in your cloud cost management capabilities, even among tech-savvy leaders, means you can avoid needless spending.

So, what does this mean for companies in the race to digital transformation?

Obviously, the pandemic accelerated organizations' journey to the cloud to enable agile, on-demand, flexible access to resources, helping them align with a digital business's dynamic needs. We heard from many of our customers at the start of lockdown last year, saying they had to shift to a remote work environment, seemingly overnight, and this effort was heavily cloud-reliant. However, blindly forging ahead can backfire.

This latest survey reveals that in addition to the overconfidence effect, enterprises are facing additional challenges across the hybrid cloud thanks to disjointed point tools, silos, lack of visibility, unexpected costs, lack of programmatic optimization, and the role risk plays in cloud cost management.

Cloud Waste is a Massive Problem

One of the biggest challenges is how to manage workloads operating in the cloud without incurring unexpected and unnecessary costs, which can eat into budgets needed for other areas of transformation. Over the many years we have been working with customers to optimize their cloud infrastructures, we have found that up to a third of their cloud spend is waste.

Clearly this is a rampant problem that continues to plague enterprises. It is important to note that the 82% from the survey represents unnecessary costs that respondents are aware of. It is highly likely that companies are spending far more than they need to without even knowing it.

For example, 56% of respondents lack programmatic cloud cost management capabilities. This can mean either that teams are spending too much time managing cloud costs or that the cloud waste is allowed to fester. Either way, time and money are being spent unwisely. Not only that, it is likely that there is waste that is not being uncovered. And the more the overconfidence effect is at play within an organization, the less likely it is that this waste will be identified.

The lack of visibility across hybrid and multi-cloud environments also blurs the issue. 86% of respondents said they cannot get a global view of cloud costs within minutes, creating delays and potentially reducing agility. 71% of respondents agreed that limited visibility across the hybrid cloud environment hinders their ability to maximize value, creates inefficiencies, and wastes time.

Disjointed tools also present a challenge. 72% of respondents said they are fed up with piecing together disparate management tools to monitor and manage everything from infrastructure performance to migration readiness to cloud cost, and 62% report that they have to cobble together multiple tools, systems, and custom scripts to get a global view of cloud costs. Again, these are the very same respondents who said they are confident in their ability to manage cloud costs.

What Leads to Waste also Impedes Transformation

Lack of programmatic management, limited visibility, and disparate tools affect more than just cloud costs. IT leaders are also grappling with issues that could hamper a successful digital transformation. 68% of survey respondents stated that their teams operate in silos, and 70% said that limited collaboration hinders their ability to adapt quickly and improve business outcomes.

Additionally, 66% of respondents stated that it is hard to understand if they are delivering the service levels the business needs, and 65% agreed that when there is an issue, they are hard-pressed to identify the business impact.

Finally, 77% cited increased performance issues as one of the reasons that pressure on cloud teams is on the rise.

The bottom line is that if you do not know what is going on across your entire infrastructure, you do not know if you are adequately serving the needs of the business and you cannot deliver performance levels that the business demands, which means that you have not met some of the foundational needs of digital transformation.

Clearing the way to cost-effective transformation

Wherever you have "seams" in your cloud monitoring and management — whether that is a result of multiple clouds, siloed teams, disparate tools, or time lags, for example — you have blind spots where unnecessary costs and other problems can hide. Combine that with the overconfidence effect and those risks only go up. A single modular platform can eliminate those seams and create appropriate levels of confidence rooted in data to de-risk cloud migrations; deliver deep precision observability into workloads before, during, and after a move; and optimize and manage efficiently once workloads are in the cloud.

This is underscored by Archana Vankatarman, Associate Research Director of Cloud Data Management at IDC Europe who said, "The duct-taped point tools and silos can make cloud cost management complex. The belief that they are wasting at least 15% of their public cloud spending will drive enterprises to actively invest in cloud cost management to halve cloud waste."

The bottom line is that cloud management is always changing. If you feel confident about your cloud costs based on your gut, think again. Have the right tools to know before you go forward with any initiative. In the end, you will not be upset that you took the time to get it right — and save money.

Methodology: Arlington Research, commissioned by Virtana, surveyed 350 cloud decision makers in April 2021 at US- and UK-based organizations with 250+ employees to better understand multi-cloud deployment experiences.

Kash Shaikh is CEO and President of Virtana

Hot Topics

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

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Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...