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Companies Suffer Crippling Business Damage During First 24 Hours of IT Outage

Most (83%) companies would suffer business damage during the first 24 hours of an outage and thereafter, according to Pivoting to Risk-Driven Security Operations, a report from Netenrich based on a global survey of IT and security professionals.


The survey also revealed interesting findings and contradictions when it comes to scaling security operations:

■ When looking to upgrade their security posture, 67% focused on tool upgrades yet organizations found that tool integrations (55%), lack of tool expertise (52%) and tool sprawl (41%) were their biggest pain points.

■ While security teams aspire to do more proactive and risk-driven operations, like risk management (37%), incident analysis (34%), threat modeling (29%), they spend most of their time doing foundational and reactive security tasks, like updating patches (43%), researching and analyzing critical incidents (41%) and removing false positives (40%).

Security teams are trapped doing the same thing they have been doing for years — reactive security. They're adding more tools, needing more resources and chasing thousands of alerts while lacking the contextual data and prioritization that's highly needed.

"Organizations fail to shift to a proactive approach that prioritizes security defenses around the most likely, highest business-impacting attack vectors," said John Bambenek, Primary Threat Researcher at Netenrich. "Security teams need to start evaluating business risk based on the likelihood of attack success and mapping that attack success to what it would actually cost the business. Focus on the critical issues that matter most to reduce the attack and outage impact."

The survey finds that companies want to do more threat modeling, incident analysis and risk management, however, very few employ it or even know how:

■ Less than 40% perform threat modeling.

■ Less than half conduct threat modeling on a daily (16%) or weekly basis (31%).

■ Only 30% practice external attack surface management.

"Our industry has taken an IT internal view to security rather than an attack external view of security," adds Bambenek. "Organizations need to shift mindsets, adopt a managed risk, not an IT-based approach. Security operations needs to be data-driven and predictive where continuous threat modeling runs at its core."

Other key findings from the report include:

■ 80% of companies have 30% or less of their IT budget dedicated to security.

■ Companies experienced minimal security budget increases despite growing IT demands as a result of remote work shifts and COVID impact: 19% reported no increases to security budgets, 29% received less than 10% budget and 8% received 50% or more budget increase.

■ Companies looked to MSPs to augment their security operations: 47% rely on managed services to run their ops entirely or in hybrid arrangements.

■ MSPs have an opportunity to expand their services by offering advanced, risk-based security and threat modeling services: only 17% of MSPs are offering threat modeling.

Methodology: Administered by Dimensional Research, a total of 333 qualified global IT and security professionals participated in the survey and carried enterprise security responsibilities at medium to enterprise-sized companies.

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Companies Suffer Crippling Business Damage During First 24 Hours of IT Outage

Most (83%) companies would suffer business damage during the first 24 hours of an outage and thereafter, according to Pivoting to Risk-Driven Security Operations, a report from Netenrich based on a global survey of IT and security professionals.


The survey also revealed interesting findings and contradictions when it comes to scaling security operations:

■ When looking to upgrade their security posture, 67% focused on tool upgrades yet organizations found that tool integrations (55%), lack of tool expertise (52%) and tool sprawl (41%) were their biggest pain points.

■ While security teams aspire to do more proactive and risk-driven operations, like risk management (37%), incident analysis (34%), threat modeling (29%), they spend most of their time doing foundational and reactive security tasks, like updating patches (43%), researching and analyzing critical incidents (41%) and removing false positives (40%).

Security teams are trapped doing the same thing they have been doing for years — reactive security. They're adding more tools, needing more resources and chasing thousands of alerts while lacking the contextual data and prioritization that's highly needed.

"Organizations fail to shift to a proactive approach that prioritizes security defenses around the most likely, highest business-impacting attack vectors," said John Bambenek, Primary Threat Researcher at Netenrich. "Security teams need to start evaluating business risk based on the likelihood of attack success and mapping that attack success to what it would actually cost the business. Focus on the critical issues that matter most to reduce the attack and outage impact."

The survey finds that companies want to do more threat modeling, incident analysis and risk management, however, very few employ it or even know how:

■ Less than 40% perform threat modeling.

■ Less than half conduct threat modeling on a daily (16%) or weekly basis (31%).

■ Only 30% practice external attack surface management.

"Our industry has taken an IT internal view to security rather than an attack external view of security," adds Bambenek. "Organizations need to shift mindsets, adopt a managed risk, not an IT-based approach. Security operations needs to be data-driven and predictive where continuous threat modeling runs at its core."

Other key findings from the report include:

■ 80% of companies have 30% or less of their IT budget dedicated to security.

■ Companies experienced minimal security budget increases despite growing IT demands as a result of remote work shifts and COVID impact: 19% reported no increases to security budgets, 29% received less than 10% budget and 8% received 50% or more budget increase.

■ Companies looked to MSPs to augment their security operations: 47% rely on managed services to run their ops entirely or in hybrid arrangements.

■ MSPs have an opportunity to expand their services by offering advanced, risk-based security and threat modeling services: only 17% of MSPs are offering threat modeling.

Methodology: Administered by Dimensional Research, a total of 333 qualified global IT and security professionals participated in the survey and carried enterprise security responsibilities at medium to enterprise-sized companies.

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 ... 

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 ...