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4 Steps to Manage Remote Workers

A Gartner, Inc. survey of 229 HR leaders on April 2 revealed that nearly 50% of organizations reported 81% or more of their employees are working remotely during the coronavirus pandemic. Another 15% of those surveyed said 61-80% of employees are working remotely at this time. The Gartner survey showed that many workers are planning to work remotely more often in the future.

“While 30% of employees surveyed worked remotely at least part of the time before the pandemic, Gartner analysis reveals that post-pandemic, 41% of employees are likely to work remotely at least some of the time,” said Brian Kropp, Chief of Research for the Gartner HR practice. “Ultimately, the COVID-19 pandemic has many employees planning to work in a way that they hadn’t previously considered.”

In the current environment, many employees are working remotely for the first time and are now doing it full-time. In tandem, managers are having to direct remote employees and teams, and many of them have never managed remote workers.

To help organizations manage remote talent during the COVID-19 pandemic, Gartner recommends four steps:

Normalize Self-Direction

Gartner analysis finds that two-fifths of remote employees want more self-directed work. Managers must trust their employees and shift away from directing their work to coaching them to success. To do this, managers should focus on employees’ work product and outputs rather than processes.

Enable New Relationships

The Gartner ReimagineHR Employee Survey, fielded in 4Q19, revealed that 41% of respondents don’t feel connected to colleagues when working remotely and 26% of employees feel isolated when they work remotely. Managers must work with HR to learn signs of distress so that they can recognize them among their direct reports and colleagues.

“Organizations have been very pragmatic and have done well adapting to the new normal from a technology standpoint,” said James Atkinson, VP in the Gartner HR practice. “Now managers need to step in and help their employees build social and emotional connections to ensure individuals feel connected to their colleagues and the organizations, and to help teams continue to work together seamlessly.”

Accentuate the Positive

Employees working fully remotely are nearly twice as likely to receive corrective feedback — which focuses on behavior that was not successful — most often. To promote two-way communication, managers should focus on making discussions with remote employees open, evidence-based and forward-looking. Managers should also make sure to acknowledge what is going right while citing specific examples

Revamp Team Expectations

Many leaders have assumed the majority of people working remotely are individual contributors, however, Gartner analysis shows that fully remote employees are 3.5 times more likely to work across five or more teams. It is crucial for managers to set expectations with individual team members and the larger team to ensure effective individual contributions and team collaboration. Managers should also emphasize individual and team objectives in these conversations.

“While the majority of organizations are not currently hiring, nor are the majority of workers actively seeking new jobs, organizations do need to consider how they are managing their workforce,” said Mr. Kropp. “If companies are not thinking through the employee experience they are creating, they could face significant attrition when the labor market opens back up.”

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 ...

4 Steps to Manage Remote Workers

A Gartner, Inc. survey of 229 HR leaders on April 2 revealed that nearly 50% of organizations reported 81% or more of their employees are working remotely during the coronavirus pandemic. Another 15% of those surveyed said 61-80% of employees are working remotely at this time. The Gartner survey showed that many workers are planning to work remotely more often in the future.

“While 30% of employees surveyed worked remotely at least part of the time before the pandemic, Gartner analysis reveals that post-pandemic, 41% of employees are likely to work remotely at least some of the time,” said Brian Kropp, Chief of Research for the Gartner HR practice. “Ultimately, the COVID-19 pandemic has many employees planning to work in a way that they hadn’t previously considered.”

In the current environment, many employees are working remotely for the first time and are now doing it full-time. In tandem, managers are having to direct remote employees and teams, and many of them have never managed remote workers.

To help organizations manage remote talent during the COVID-19 pandemic, Gartner recommends four steps:

Normalize Self-Direction

Gartner analysis finds that two-fifths of remote employees want more self-directed work. Managers must trust their employees and shift away from directing their work to coaching them to success. To do this, managers should focus on employees’ work product and outputs rather than processes.

Enable New Relationships

The Gartner ReimagineHR Employee Survey, fielded in 4Q19, revealed that 41% of respondents don’t feel connected to colleagues when working remotely and 26% of employees feel isolated when they work remotely. Managers must work with HR to learn signs of distress so that they can recognize them among their direct reports and colleagues.

“Organizations have been very pragmatic and have done well adapting to the new normal from a technology standpoint,” said James Atkinson, VP in the Gartner HR practice. “Now managers need to step in and help their employees build social and emotional connections to ensure individuals feel connected to their colleagues and the organizations, and to help teams continue to work together seamlessly.”

Accentuate the Positive

Employees working fully remotely are nearly twice as likely to receive corrective feedback — which focuses on behavior that was not successful — most often. To promote two-way communication, managers should focus on making discussions with remote employees open, evidence-based and forward-looking. Managers should also make sure to acknowledge what is going right while citing specific examples

Revamp Team Expectations

Many leaders have assumed the majority of people working remotely are individual contributors, however, Gartner analysis shows that fully remote employees are 3.5 times more likely to work across five or more teams. It is crucial for managers to set expectations with individual team members and the larger team to ensure effective individual contributions and team collaboration. Managers should also emphasize individual and team objectives in these conversations.

“While the majority of organizations are not currently hiring, nor are the majority of workers actively seeking new jobs, organizations do need to consider how they are managing their workforce,” said Mr. Kropp. “If companies are not thinking through the employee experience they are creating, they could face significant attrition when the labor market opens back up.”

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 ...