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Why Government Agencies Aren't Ready to Return to the Office

Mike Marks
Riverbed

US government agencies are bringing more of their employees back into the office and implementing hybrid work schedules, but federal workers are worried that their agencies' IT architectures aren't built to handle the "new normal." They fear that the reactive, manual methods used by the current systems in dealing with user, IT architecture and application problems will degrade the user experience and negatively affect productivity.

In fact, according to a recent survey, many federal employees are concerned that they won't work as effectively back in the office as they did at home.

Employees Worry the User Experience Will Suffer

A Swish Data/Riverbed survey of federal IT workers, conducted in April and May by Market Connections, found that about half (47%) expect hybrid schedules that include teleworking two to four days a week to continue long-term, but that 52% think that the legacy IT and on-premises network architectures will struggle with the increased use of on-site collaboration tools such as Microsoft Teams and Zoom.

Those shortcomings manifest themselves in the user experience, the survey found. Forty-four percent of respondents are concerned that their user experience working in the office would fall short of their experience working from home. And a significant reason for the disconnect is the outdated methods agencies use to identify and quantify problems that arise with IT operations, and how those problems affect users.

A full 100% of survey respondents said it is at least somewhat important to measure the employees' user experience of productivity capabilities. But 87% said their agencies still rely — reactively — on waiting for help desk tickets to be generated before addressing problems. In fact, 51% rely on user phone calls as the primary means of quantifying problems.

The result, according to 59% of the feds surveyed, is that agencies aren't aware of the impact that changes in their IT environments are having. They're not measuring business-function productivity in terms of labor costs, latency or rates of success, all of which are tied to user experience. A majority of respondents said that although their organizations compare the business transaction productivity of teleworkers to that of in-office workers, they do so only partially. And measuring and comparing employee productivity is less likely to happen at civilian agencies than within the Department of Defense.

Unified Observability Takes a Proactive Approach

In light of the realities of hybrid work—with flexible home/office schedules, a greater reliance on collaboration tools and the shift toward greater use of digital workflows — federal employees are looking for a balance between collaborative tools and in-person needs.

A proactive approach that combines comprehensive network visibility and effective monitoring tools can provide a clear view of the user experience, which can enable both increased productivity and enhanced user satisfaction.

A Unified Observability platform can provide full-fidelity data from across the enterprise, capturing all transactions, packets and workflows. Using automated artificial intelligence and machine learning tools, it can prioritize actions to help enable cross-domain collaboration and coordination. While greatly improving the ability of IT teams to identify and remediate any problems (ranging from cyberattacks to workflow bottlenecks), Unified Observability enables IT teams to improve service delivery.

The higher quality of IT service will improve employee performance and the delivery of services to constituents and other stakeholders by allowing employees to more seamlessly perform their jobs, whether working from home or in the office. The visibility provided by a Unified Observability platform allows multiple teams across the enterprise to identify and analyze user issues while making use of automation to quickly resolve any problems.

"Government from Anywhere" as a Reality

The impact of the COVID-19 pandemic on top of digital transformations that were already underway has forever changed how agencies operate. The concept of "government from anywhere" is a widespread goal, but it requires a cultural change at most agencies. The survey recipients agreed, with 87% saying that their agency culture played a growing or significant role in driving change.

Abandoning inefficient, reactive methods of measuring the user experience in favor of enterprise-wide visibility with proactive monitoring and analysis will improve user experiences regardless of their location, while also boosting agency performance overall.

Mike Marks is VP of Product Marketing at Riverbed

The Latest

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...

In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ... 

Most production autonomous agents do not run in a vacuum. They run inside cloud infrastructure: virtual machines, containers, pods, managed clusters or private servers. That is where most operations teams start monitoring. Is the VM alive? Is the container running? Did the pod restart? Is memory stable? Is CPU too high? Did the health check pass? Those signals are useful. They tell you whether the shell around the agent is alive. They do not tell you whether the agent inside is actually operational ...

Enterprise IT environments have never been more observable ... Yet many organizations still grapple with outages, lengthy incident resolution cycles, and increasing complexity. Most teams do not suffer from a shortage of data. They struggle to determine what deserves attention and what action to take next ... Enterprise IT operations must move beyond monitoring and visibility. The next stage of maturity is decision operations, an approach that helps teams make faster, better-informed decisions ...

Why Government Agencies Aren't Ready to Return to the Office

Mike Marks
Riverbed

US government agencies are bringing more of their employees back into the office and implementing hybrid work schedules, but federal workers are worried that their agencies' IT architectures aren't built to handle the "new normal." They fear that the reactive, manual methods used by the current systems in dealing with user, IT architecture and application problems will degrade the user experience and negatively affect productivity.

In fact, according to a recent survey, many federal employees are concerned that they won't work as effectively back in the office as they did at home.

Employees Worry the User Experience Will Suffer

A Swish Data/Riverbed survey of federal IT workers, conducted in April and May by Market Connections, found that about half (47%) expect hybrid schedules that include teleworking two to four days a week to continue long-term, but that 52% think that the legacy IT and on-premises network architectures will struggle with the increased use of on-site collaboration tools such as Microsoft Teams and Zoom.

Those shortcomings manifest themselves in the user experience, the survey found. Forty-four percent of respondents are concerned that their user experience working in the office would fall short of their experience working from home. And a significant reason for the disconnect is the outdated methods agencies use to identify and quantify problems that arise with IT operations, and how those problems affect users.

A full 100% of survey respondents said it is at least somewhat important to measure the employees' user experience of productivity capabilities. But 87% said their agencies still rely — reactively — on waiting for help desk tickets to be generated before addressing problems. In fact, 51% rely on user phone calls as the primary means of quantifying problems.

The result, according to 59% of the feds surveyed, is that agencies aren't aware of the impact that changes in their IT environments are having. They're not measuring business-function productivity in terms of labor costs, latency or rates of success, all of which are tied to user experience. A majority of respondents said that although their organizations compare the business transaction productivity of teleworkers to that of in-office workers, they do so only partially. And measuring and comparing employee productivity is less likely to happen at civilian agencies than within the Department of Defense.

Unified Observability Takes a Proactive Approach

In light of the realities of hybrid work—with flexible home/office schedules, a greater reliance on collaboration tools and the shift toward greater use of digital workflows — federal employees are looking for a balance between collaborative tools and in-person needs.

A proactive approach that combines comprehensive network visibility and effective monitoring tools can provide a clear view of the user experience, which can enable both increased productivity and enhanced user satisfaction.

A Unified Observability platform can provide full-fidelity data from across the enterprise, capturing all transactions, packets and workflows. Using automated artificial intelligence and machine learning tools, it can prioritize actions to help enable cross-domain collaboration and coordination. While greatly improving the ability of IT teams to identify and remediate any problems (ranging from cyberattacks to workflow bottlenecks), Unified Observability enables IT teams to improve service delivery.

The higher quality of IT service will improve employee performance and the delivery of services to constituents and other stakeholders by allowing employees to more seamlessly perform their jobs, whether working from home or in the office. The visibility provided by a Unified Observability platform allows multiple teams across the enterprise to identify and analyze user issues while making use of automation to quickly resolve any problems.

"Government from Anywhere" as a Reality

The impact of the COVID-19 pandemic on top of digital transformations that were already underway has forever changed how agencies operate. The concept of "government from anywhere" is a widespread goal, but it requires a cultural change at most agencies. The survey recipients agreed, with 87% saying that their agency culture played a growing or significant role in driving change.

Abandoning inefficient, reactive methods of measuring the user experience in favor of enterprise-wide visibility with proactive monitoring and analysis will improve user experiences regardless of their location, while also boosting agency performance overall.

Mike Marks is VP of Product Marketing at Riverbed

The Latest

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...

In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ... 

Most production autonomous agents do not run in a vacuum. They run inside cloud infrastructure: virtual machines, containers, pods, managed clusters or private servers. That is where most operations teams start monitoring. Is the VM alive? Is the container running? Did the pod restart? Is memory stable? Is CPU too high? Did the health check pass? Those signals are useful. They tell you whether the shell around the agent is alive. They do not tell you whether the agent inside is actually operational ...

Enterprise IT environments have never been more observable ... Yet many organizations still grapple with outages, lengthy incident resolution cycles, and increasing complexity. Most teams do not suffer from a shortage of data. They struggle to determine what deserves attention and what action to take next ... Enterprise IT operations must move beyond monitoring and visibility. The next stage of maturity is decision operations, an approach that helps teams make faster, better-informed decisions ...