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Lack of Network History Costs Large Enterprises Millions of Dollars Each Year, Survey Says

Large organizations have estimated the cost of network downtime ranges from hundreds of thousands to millions of dollars per hour, according to Endace's 2012 Network Visibility Survey.

The survey findings highlight the operational challenges being faced by IT teams as they come to terms with the latest high-speed, network-centric technologies such as cloud, unified communications and VDI.

Highlights from the survey, which is based on more than 100 interviews with senior network IT professionals from organizations with 5,000 to 200,000 employees, include the following about the current state of operational effectiveness:

- 23 percent of organizations experience serious service-affecting problems on a daily basis

- An additional 25 percent admit to experiencing serious network issues each month

- Organizations’ hardest network problems can take up to 30 days or more to rectify, making MAX-TTR (maximum time-to-resolution) an expensive issue for large, resource-constrained organizations

- Organizations can have up to 250 performance-related trouble tickets open at any given time, with half of respondents reporting that at least 50 percent of their trouble tickets stay open for more than 24 hours

- Nearly 40 percent of respondents noted that they do not know which applications are in use on their network, while 53 percent admit that employees use applications that violate IT policies

- Despite an abundance of monitoring tools, nearly 30 percent of organizations do not have a clear understanding of bandwidth utilization, which makes troubleshooting end-user issues extremely challenging

For obvious reasons, minimizing Time-to-Resolution on all types of service-affecting issues has become a top priority for organizations, putting IT operational teams squarely in the spotlight.

Comments from survey respondents confirmed that processes for diagnosing and remediating difficult issues are often ad-hoc.

“Most IT shops have invested heavily in detection technologies that alert on issues and correlation technologies that attempt to filter and triage the most important issues. But what we’ve learned from this study is that many shops still face long resolution times far too often,” said Spencer Greene, senior vice president of marketing and product management at Endace.

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Lack of Network History Costs Large Enterprises Millions of Dollars Each Year, Survey Says

Large organizations have estimated the cost of network downtime ranges from hundreds of thousands to millions of dollars per hour, according to Endace's 2012 Network Visibility Survey.

The survey findings highlight the operational challenges being faced by IT teams as they come to terms with the latest high-speed, network-centric technologies such as cloud, unified communications and VDI.

Highlights from the survey, which is based on more than 100 interviews with senior network IT professionals from organizations with 5,000 to 200,000 employees, include the following about the current state of operational effectiveness:

- 23 percent of organizations experience serious service-affecting problems on a daily basis

- An additional 25 percent admit to experiencing serious network issues each month

- Organizations’ hardest network problems can take up to 30 days or more to rectify, making MAX-TTR (maximum time-to-resolution) an expensive issue for large, resource-constrained organizations

- Organizations can have up to 250 performance-related trouble tickets open at any given time, with half of respondents reporting that at least 50 percent of their trouble tickets stay open for more than 24 hours

- Nearly 40 percent of respondents noted that they do not know which applications are in use on their network, while 53 percent admit that employees use applications that violate IT policies

- Despite an abundance of monitoring tools, nearly 30 percent of organizations do not have a clear understanding of bandwidth utilization, which makes troubleshooting end-user issues extremely challenging

For obvious reasons, minimizing Time-to-Resolution on all types of service-affecting issues has become a top priority for organizations, putting IT operational teams squarely in the spotlight.

Comments from survey respondents confirmed that processes for diagnosing and remediating difficult issues are often ad-hoc.

“Most IT shops have invested heavily in detection technologies that alert on issues and correlation technologies that attempt to filter and triage the most important issues. But what we’ve learned from this study is that many shops still face long resolution times far too often,” said Spencer Greene, senior vice president of marketing and product management at Endace.

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AI is becoming the operating system of the enterprise. It acts as an invisible coordination layer that understands intent, connects systems, and executes work across complex SaaS environments. Previously, employees had to click through multiple systems — CRM, ERP, support tools, collaboration platforms — to complete a single task. Now, instead of navigating each application manually, they can simply state what they need to accomplish ...

In 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become  more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs  for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...

Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...

Cloud spending is no longer viewed as a passthrough IT expense, but as a strategic financial lever that directly impacts innovation capacity, profitability and enterprise resilience, according to the CFO Cloud Cost Optimization Report from Azul ...

As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...

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 ...

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 ...

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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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 ...