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Why Work is Getting in the Way of ... Work

Steven ZoBell
Workfront

We're in the middle of a technology and connectivity revolution, giving us access to infinite digital tools and technologies. Is this multitude of technology solutions empowering us to do our best work, or getting in our way?

Workfront's 2020 State of Work report surveyed 3,750 knowledge workers globally to answer this question. Here's what I learned about technology's impact on modern work and what the highest-performing enterprises — work management pioneers — are doing to outpace the competition.


Legacy Technology is Getting in the Way of Work …

The good news: employees are engaged and want to make a strategic impact. 89% of the employees surveyed believe their role matters. 91% are proud of the work they do.

The bad news: they only spend 40% of their time doing the work they were hired to do.

What's impeding their productivity? Much of employees' time is spent trying to determine the specifics and details of what is most important, who they are to be coordinating with, and what the best next action is to move it forward.

But what about all the digital productivity tools that companies are buying to help employees? These tools — email, instant messaging, file storage, and so forth — are actually part of the problem as they have now created exabytes of siloed conversations and data for employees to navigate as they are trying to do their best work.

In addition, we are interrupted almost 14 times a day by digital tools. The Fast Company article, Worker, Interrupted: The Cost of Task Switching, claims that it takes us more than 20 minutes after each interruption to get back to our original task. That's 4.6 hours of wasted time — every day.

Technology can inhibit productivity, but it's also an important part of the employee experience (according to 88% of respondents).

... but Workers Still Crave the Right Solutions

Employees expect a workplace technology experience that delivers on multiple fronts: information access, user experience, personalization, and connection. They want the same consumer ease and simplicity at work that they get from Amazon, Instagram and Google.

Most workers surveyed (91%) crave these modern technology solutions, and 87% think their companies are missing opportunities by not adopting them. Included in the list of solutions that 71% of employees crave is a single place to understand and manage their work; 69% say they don't have that place today. Having one place to manage work is the next frontier of enterprise digital transformation, just as it happened for customer data, business financials, IT operations, and HR talent management.

On the one hand, technology is getting in the way of work. On the other hand, knowledge workers crave modern technology solutions. To navigate this technology paradox during this time of massive digital transformation, look at a fundamental attribute shared by companies that consistently outperform the competition: They deploy work management technology that helps people get the right work done.

High-Performing Companies Deploy Technology That Helps People Get Work Done

In this era of innumerable technologies (i.e., era of digital confusion), leading companies and teams that consistently outpace their rivals let their work management strategy drive their technology strategy.

They go beyond supporting their people with the digital applications and systems they crave, from product design tools to creative suites, by connecting these individual tools into an orchestrated whole, a digital platform for work that supports dynamic workflows and captures information that improves visibility and context.

These work management pioneers share three additional traits:

They start with visibility and context. People and teams understand the role they play in strategic company goals because strategy at all levels of the organization is well-defined, informed by data, and clearly communicated. Providing workers with visibility into how their work aligns with company goals drives powerful business outcomes.

They actively manage work. People and teams use data, not assumptions, to align and make decisions about status and performance of teams and projects.

They focus on agility as a core competency. People and teams work across departmental seams, changing more often, empowering new leaders, and redeploying themselves at the individual, team, or organizational level to drive new market opportunities.

We know that today's knowledge workers are engaged and want to be productive. We also know that they're frustrated with legacy tools that interfere with their productivity, yet still crave modern solutions that free them up to focus on the work they've been hired to accomplish.

To prevent work from getting in the way of work, IT leadership can stop buying tools that add to the digital confusion, and start taking significant steps to harmonize the messy digital landscape by prioritizing systems and best practices that enable the ongoing digital transformation across the enterprise.

Steven ZoBell is Chief Product & Technology Officer at Workfront

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 ...

Why Work is Getting in the Way of ... Work

Steven ZoBell
Workfront

We're in the middle of a technology and connectivity revolution, giving us access to infinite digital tools and technologies. Is this multitude of technology solutions empowering us to do our best work, or getting in our way?

Workfront's 2020 State of Work report surveyed 3,750 knowledge workers globally to answer this question. Here's what I learned about technology's impact on modern work and what the highest-performing enterprises — work management pioneers — are doing to outpace the competition.


Legacy Technology is Getting in the Way of Work …

The good news: employees are engaged and want to make a strategic impact. 89% of the employees surveyed believe their role matters. 91% are proud of the work they do.

The bad news: they only spend 40% of their time doing the work they were hired to do.

What's impeding their productivity? Much of employees' time is spent trying to determine the specifics and details of what is most important, who they are to be coordinating with, and what the best next action is to move it forward.

But what about all the digital productivity tools that companies are buying to help employees? These tools — email, instant messaging, file storage, and so forth — are actually part of the problem as they have now created exabytes of siloed conversations and data for employees to navigate as they are trying to do their best work.

In addition, we are interrupted almost 14 times a day by digital tools. The Fast Company article, Worker, Interrupted: The Cost of Task Switching, claims that it takes us more than 20 minutes after each interruption to get back to our original task. That's 4.6 hours of wasted time — every day.

Technology can inhibit productivity, but it's also an important part of the employee experience (according to 88% of respondents).

... but Workers Still Crave the Right Solutions

Employees expect a workplace technology experience that delivers on multiple fronts: information access, user experience, personalization, and connection. They want the same consumer ease and simplicity at work that they get from Amazon, Instagram and Google.

Most workers surveyed (91%) crave these modern technology solutions, and 87% think their companies are missing opportunities by not adopting them. Included in the list of solutions that 71% of employees crave is a single place to understand and manage their work; 69% say they don't have that place today. Having one place to manage work is the next frontier of enterprise digital transformation, just as it happened for customer data, business financials, IT operations, and HR talent management.

On the one hand, technology is getting in the way of work. On the other hand, knowledge workers crave modern technology solutions. To navigate this technology paradox during this time of massive digital transformation, look at a fundamental attribute shared by companies that consistently outperform the competition: They deploy work management technology that helps people get the right work done.

High-Performing Companies Deploy Technology That Helps People Get Work Done

In this era of innumerable technologies (i.e., era of digital confusion), leading companies and teams that consistently outpace their rivals let their work management strategy drive their technology strategy.

They go beyond supporting their people with the digital applications and systems they crave, from product design tools to creative suites, by connecting these individual tools into an orchestrated whole, a digital platform for work that supports dynamic workflows and captures information that improves visibility and context.

These work management pioneers share three additional traits:

They start with visibility and context. People and teams understand the role they play in strategic company goals because strategy at all levels of the organization is well-defined, informed by data, and clearly communicated. Providing workers with visibility into how their work aligns with company goals drives powerful business outcomes.

They actively manage work. People and teams use data, not assumptions, to align and make decisions about status and performance of teams and projects.

They focus on agility as a core competency. People and teams work across departmental seams, changing more often, empowering new leaders, and redeploying themselves at the individual, team, or organizational level to drive new market opportunities.

We know that today's knowledge workers are engaged and want to be productive. We also know that they're frustrated with legacy tools that interfere with their productivity, yet still crave modern solutions that free them up to focus on the work they've been hired to accomplish.

To prevent work from getting in the way of work, IT leadership can stop buying tools that add to the digital confusion, and start taking significant steps to harmonize the messy digital landscape by prioritizing systems and best practices that enable the ongoing digital transformation across the enterprise.

Steven ZoBell is Chief Product & Technology Officer at Workfront

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 ...