Skip to main content

Enterprises Waste Over $2 Million Each Year on Data Availability Failures

Pete Goldin
APMdigest

Of those surveyed, 82 percent of CIOs admit that they are unable to meet their organization’s need for immediate, always-on access to IT services, according to the Veeam Data Center Availability Report 2014.

This availability gap has immediate costs: application failure costs enterprises more than $2 million a year in lost revenue, productivity, opportunities and data irretrievably lost through backups failing to recover. These costs will only increase as the global economy requires enterprises to work with partners, customers and stakeholders across time zones, pressuring data center assets to be always-on no matter the location. With emerging markets predicted to generate 40 percent of global growth within the next 15 years, missing global opportunities due to downtime can cause irrevocable damage.

“The availability of IT is more important than ever. Yet businesses globally are being failed by an IT industry that has led them to believe they have to accept downtime,” says Ratmir Timashev, CEO at Veeam. “This isn’t acceptable. Organizations can’t afford to lose millions of dollars from IT failures, nor can they continue to gamble with data availability. The good news is things are set to change. Organizations just need to throw away what they’ve been told for years about availability and demand better. If every organization does this, then in five years application availability will become a redundant topic as consumers and employees across the planet access what they want, when they want it.”

Key findings of the report include:

■ 82 percent of CIOs said they cannot meet the need of their business. More than 90 percent of CIOs are under pressure to both recover data faster, reducing the financial impact of unplanned downtime, and also back up data more often, reducing the risk of data loss.

■ The reasons CIOs are under pressure include more frequent, real-time interactions among customers, partners, suppliers and employees (65 percent of respondents); the need to access applications across time zones (56 percent); increased adoption of mobile devices (56 percent); employees working outside regular hours (54 percent); and an increasing level of automation for decision making and transactions (53 percent).

■ Unplanned application downtime occurs more than once per month (13 times per year).

■ Unplanned application downtime costs an organization between $1.4 million and $2.3 million annually in lost revenue, decreased productivity and missed opportunities.

■ One in six backup recoveries fails, meaning that with 13 incidents of application downtime per year, data will be permanently lost at least twice. This lost data costs enterprises a minimum of $682,000 annually.

■ Organizations are also risking between $4.4 million and $7.9 million of lost application data from downtime incidents each year.

Businesses are already calling for greater availability. However, IT departments are missing the recovery time objective (RTO) their businesses demand for mission-critical data by more than an hour and are more than 2.5 hours away from the always-on standards set by modern availability solutions. They are also missing the required recovery point objective (RPO); i.e., how often data is backed up, by 1.5 hours, and they are 4.5 hours away from modern always-on standards.

“Make no mistake, we are already in the era of the Always-On Business,” adds Timashev. “To keep pace, enterprises need entirely new types of solutions that enable 24/7 availability in a way that legacy data protection and backup products could never do. This means high-speed, guaranteed recovery of every file, application or virtual server when needed. It means leveraging backup data and environments to test the deployment of new applications, mitigating the risk of failure. And it means complete visibility, with proactive monitoring and alerting of issues before they affect operations. CIOs clearly recognize this, with 78 percent planning to change their data protection product in the next two years in order to get the availability that they need. As a result, the availability gap will start to become a thing of the past.”

Survey methodology: The Veeam Data Center Availability Report 2014 is based on a survey conducted online among 760 CIOs of companies with more than 1,000 employees across the United States, United Kingdom, Germany, France, Italy, the Netherlands, Switzerland, Brazil, Australia and Singapore. Vanson Bourne, an independent market research organization, directed the survey on behalf of Veeam.

Pete Goldin is Editor and Publisher of APMdigest

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 ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

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 ...

Enterprises Waste Over $2 Million Each Year on Data Availability Failures

Pete Goldin
APMdigest

Of those surveyed, 82 percent of CIOs admit that they are unable to meet their organization’s need for immediate, always-on access to IT services, according to the Veeam Data Center Availability Report 2014.

This availability gap has immediate costs: application failure costs enterprises more than $2 million a year in lost revenue, productivity, opportunities and data irretrievably lost through backups failing to recover. These costs will only increase as the global economy requires enterprises to work with partners, customers and stakeholders across time zones, pressuring data center assets to be always-on no matter the location. With emerging markets predicted to generate 40 percent of global growth within the next 15 years, missing global opportunities due to downtime can cause irrevocable damage.

“The availability of IT is more important than ever. Yet businesses globally are being failed by an IT industry that has led them to believe they have to accept downtime,” says Ratmir Timashev, CEO at Veeam. “This isn’t acceptable. Organizations can’t afford to lose millions of dollars from IT failures, nor can they continue to gamble with data availability. The good news is things are set to change. Organizations just need to throw away what they’ve been told for years about availability and demand better. If every organization does this, then in five years application availability will become a redundant topic as consumers and employees across the planet access what they want, when they want it.”

Key findings of the report include:

■ 82 percent of CIOs said they cannot meet the need of their business. More than 90 percent of CIOs are under pressure to both recover data faster, reducing the financial impact of unplanned downtime, and also back up data more often, reducing the risk of data loss.

■ The reasons CIOs are under pressure include more frequent, real-time interactions among customers, partners, suppliers and employees (65 percent of respondents); the need to access applications across time zones (56 percent); increased adoption of mobile devices (56 percent); employees working outside regular hours (54 percent); and an increasing level of automation for decision making and transactions (53 percent).

■ Unplanned application downtime occurs more than once per month (13 times per year).

■ Unplanned application downtime costs an organization between $1.4 million and $2.3 million annually in lost revenue, decreased productivity and missed opportunities.

■ One in six backup recoveries fails, meaning that with 13 incidents of application downtime per year, data will be permanently lost at least twice. This lost data costs enterprises a minimum of $682,000 annually.

■ Organizations are also risking between $4.4 million and $7.9 million of lost application data from downtime incidents each year.

Businesses are already calling for greater availability. However, IT departments are missing the recovery time objective (RTO) their businesses demand for mission-critical data by more than an hour and are more than 2.5 hours away from the always-on standards set by modern availability solutions. They are also missing the required recovery point objective (RPO); i.e., how often data is backed up, by 1.5 hours, and they are 4.5 hours away from modern always-on standards.

“Make no mistake, we are already in the era of the Always-On Business,” adds Timashev. “To keep pace, enterprises need entirely new types of solutions that enable 24/7 availability in a way that legacy data protection and backup products could never do. This means high-speed, guaranteed recovery of every file, application or virtual server when needed. It means leveraging backup data and environments to test the deployment of new applications, mitigating the risk of failure. And it means complete visibility, with proactive monitoring and alerting of issues before they affect operations. CIOs clearly recognize this, with 78 percent planning to change their data protection product in the next two years in order to get the availability that they need. As a result, the availability gap will start to become a thing of the past.”

Survey methodology: The Veeam Data Center Availability Report 2014 is based on a survey conducted online among 760 CIOs of companies with more than 1,000 employees across the United States, United Kingdom, Germany, France, Italy, the Netherlands, Switzerland, Brazil, Australia and Singapore. Vanson Bourne, an independent market research organization, directed the survey on behalf of Veeam.

Pete Goldin is Editor and Publisher of APMdigest

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 ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

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 ...