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IT Leadership: Measuring Employee Experience in a Post-COVID World

Nik Koutsoukos

I'm an old-school advocate for employee experience. For years, my colleagues and I have urged (and cajoled, and begged) business leaders to take the subject seriously. We've argued that engaged and well-supported workers are the cornerstone of business success — and that nothing kills productivity quicker than when people can't rely on the tools they need to do their jobs. That message has been getting through. It's been gratifying to see more and more C-suites prioritize measuring employee experience in recent years. And then … COVID-19 hit.

You can understand why many employee experience initiatives got put on the back burner. It's hard enough just to keep a business running during a pandemic. But when most of your workforce suddenly shifts to work-from-home, understanding employee experience becomes more important, not less. Not to mention that, for many businesses, large portions of the workforce will continue working remotely long after the COVID-19 crisis subsides.

Bottom line, "work" means something very different than it did a year ago. If we're going to give people the support they need to thrive in this new normal, we need to rethink employee experience: what we measure, how we measure it, and what we can ultimately do about it.

Accelerating Longstanding Trends

For many of the changes we've seen — like huge growth in remote work and digital collaboration — COVID-19 didn't so much create new models as kick pre-existing trends into high gear. The fact is, work has been growing more decentralized, and IT has been steadily losing control of business infrastructure, for years. Just look at the major IT trends of the last decade:

■ Core business applications moving from on-premises data centers to cloud-based software-as-a-service (SaaS)

■ Dominant connectivity models shifting from Ethernet to Wi-Fi

■ Explosive growth in mobile and remote work, often using devices outside IT control

Even if you care about deeply about employee experience, it's much harder to measure than it was back when everybody worked in the office, and all applications and networks and devices were controlled by IT. If employees are having issues, just figuring out where to look becomes much tougher. The challenge grows exponentially when most of your workforce shifts to full-time work-from-home, practically overnight.

At this point, businesses need to put aside the deep metrics about application performance and start from ground zero: Can my remote employees actually do their jobs? How are they feeling? Do they have the bare minimum they need to be productive?

Measuring the Right Things

If you're in human resources — or really, any executive leadership role in your organization — it's important to step back and look at employees holistically. We advocate measuring well-being across five broad categories:

■ The basics: When companies are scrambling to react to an unexpected crisis, it's easy to get caught by surprise. All of a sudden, you need to ask different kinds of questions:
- Do my employees have the equipment they need?
- Not just a working laptop, but a good monitor and keyboard?
- A comfortable chair?
- A place they can work that's free from noise and distractions?
- A fast and reliable network connection that can support video conferencing?

These aren't the kinds of things most companies have had to worry about before. But they're essential to employee well-being, so they need to be on your radar.

■ User experience: Assuring a quality digital experience is relatively easy when everyone works in the corporate office. But if COVID-19 has taught us anything, it's that we need our employees to be ready to work from anywhere, anytime. You're better off thinking proactively about assuring digital experience, rather than waiting to react to the next big disruption.

What are the core applications that each employee needs to do his or her job? Can they access those tools from home and use them as effectively as in the office? You'll need more granular monitoring tools to find out. It's not enough to know, for example, that a home user can connect to the Internet. Can they access all the apps they need reliably all day long? If not, why?

■ Connectivity: Traditionally, most businesses treated remote work connectivity as a "best-effort" scenario. When you're remote, you do the best you can. If you need business-class connectivity — guaranteed bandwidth under a service-level agreement (SLA), managed Wi-Fi, state-of-the-art performance monitoring — you come into the office. That's no longer an option for millions of workers.

So, it's more important than ever for IT to be able to look deeply into every user's connection and troubleshoot problems all the way into home networks. For many connectivity issues, the problem lies with the user's home network or local Internet service provider (ISP).

But, even if you can't fix the problem, you can tell users what's wrong and what they can do about it. Sometimes, that might be, "Your ISP is having issues and it could be a while. Focus on offline work for now" That's a lot better than hours of frustrated users and wasted IT effort trying to diagnose a problem they can't solve.

■ Device: Along those lines, it's more important than ever to understand what's happening on the employee's device. For many problems, the cause is just a lack of memory or CPU power in older hardware. The good news is that those are among the easiest problems for IT to solve. But, if you're not monitoring all the way to the device, it will take a lot longer to zero in on that.

■ Applications and services: Businesses need to be able to look outward when measuring employee experience, as well as inward. Yes, you need to know how employees' devices and network connections are performing. But, you should also be keeping tabs on your SaaS applications and cloud services. If, for example, Microsoft Office 365 is having slow performance across the southwestern United States, it sure would be useful for IT to know that before they spend hours trying to diagnose the problem.

Eliminating the Guesswork

The truth is, the list of issues outside IT's control keeps getting longer. But, that makes visibility even more important. When you have hard data about what your people are actually experiencing, you can:

■ Hold your SaaS and Internet providers accountable

■ Empower employees (and reduce their frustration) by quickly diagnosing problems in their own devices and home networks that they can fix themselves

■ Quickly identify problems beyond IT's control, so they can focus their time on tasks where they can make a real difference

We're all still adjusting to the challenges of a post-COVID world. But, when your business relies on a remote workforce every day, just knowing what's happening out there can be hugely beneficial.

The Latest

AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

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AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

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Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...

IT Leadership: Measuring Employee Experience in a Post-COVID World

Nik Koutsoukos

I'm an old-school advocate for employee experience. For years, my colleagues and I have urged (and cajoled, and begged) business leaders to take the subject seriously. We've argued that engaged and well-supported workers are the cornerstone of business success — and that nothing kills productivity quicker than when people can't rely on the tools they need to do their jobs. That message has been getting through. It's been gratifying to see more and more C-suites prioritize measuring employee experience in recent years. And then … COVID-19 hit.

You can understand why many employee experience initiatives got put on the back burner. It's hard enough just to keep a business running during a pandemic. But when most of your workforce suddenly shifts to work-from-home, understanding employee experience becomes more important, not less. Not to mention that, for many businesses, large portions of the workforce will continue working remotely long after the COVID-19 crisis subsides.

Bottom line, "work" means something very different than it did a year ago. If we're going to give people the support they need to thrive in this new normal, we need to rethink employee experience: what we measure, how we measure it, and what we can ultimately do about it.

Accelerating Longstanding Trends

For many of the changes we've seen — like huge growth in remote work and digital collaboration — COVID-19 didn't so much create new models as kick pre-existing trends into high gear. The fact is, work has been growing more decentralized, and IT has been steadily losing control of business infrastructure, for years. Just look at the major IT trends of the last decade:

■ Core business applications moving from on-premises data centers to cloud-based software-as-a-service (SaaS)

■ Dominant connectivity models shifting from Ethernet to Wi-Fi

■ Explosive growth in mobile and remote work, often using devices outside IT control

Even if you care about deeply about employee experience, it's much harder to measure than it was back when everybody worked in the office, and all applications and networks and devices were controlled by IT. If employees are having issues, just figuring out where to look becomes much tougher. The challenge grows exponentially when most of your workforce shifts to full-time work-from-home, practically overnight.

At this point, businesses need to put aside the deep metrics about application performance and start from ground zero: Can my remote employees actually do their jobs? How are they feeling? Do they have the bare minimum they need to be productive?

Measuring the Right Things

If you're in human resources — or really, any executive leadership role in your organization — it's important to step back and look at employees holistically. We advocate measuring well-being across five broad categories:

■ The basics: When companies are scrambling to react to an unexpected crisis, it's easy to get caught by surprise. All of a sudden, you need to ask different kinds of questions:
- Do my employees have the equipment they need?
- Not just a working laptop, but a good monitor and keyboard?
- A comfortable chair?
- A place they can work that's free from noise and distractions?
- A fast and reliable network connection that can support video conferencing?

These aren't the kinds of things most companies have had to worry about before. But they're essential to employee well-being, so they need to be on your radar.

■ User experience: Assuring a quality digital experience is relatively easy when everyone works in the corporate office. But if COVID-19 has taught us anything, it's that we need our employees to be ready to work from anywhere, anytime. You're better off thinking proactively about assuring digital experience, rather than waiting to react to the next big disruption.

What are the core applications that each employee needs to do his or her job? Can they access those tools from home and use them as effectively as in the office? You'll need more granular monitoring tools to find out. It's not enough to know, for example, that a home user can connect to the Internet. Can they access all the apps they need reliably all day long? If not, why?

■ Connectivity: Traditionally, most businesses treated remote work connectivity as a "best-effort" scenario. When you're remote, you do the best you can. If you need business-class connectivity — guaranteed bandwidth under a service-level agreement (SLA), managed Wi-Fi, state-of-the-art performance monitoring — you come into the office. That's no longer an option for millions of workers.

So, it's more important than ever for IT to be able to look deeply into every user's connection and troubleshoot problems all the way into home networks. For many connectivity issues, the problem lies with the user's home network or local Internet service provider (ISP).

But, even if you can't fix the problem, you can tell users what's wrong and what they can do about it. Sometimes, that might be, "Your ISP is having issues and it could be a while. Focus on offline work for now" That's a lot better than hours of frustrated users and wasted IT effort trying to diagnose a problem they can't solve.

■ Device: Along those lines, it's more important than ever to understand what's happening on the employee's device. For many problems, the cause is just a lack of memory or CPU power in older hardware. The good news is that those are among the easiest problems for IT to solve. But, if you're not monitoring all the way to the device, it will take a lot longer to zero in on that.

■ Applications and services: Businesses need to be able to look outward when measuring employee experience, as well as inward. Yes, you need to know how employees' devices and network connections are performing. But, you should also be keeping tabs on your SaaS applications and cloud services. If, for example, Microsoft Office 365 is having slow performance across the southwestern United States, it sure would be useful for IT to know that before they spend hours trying to diagnose the problem.

Eliminating the Guesswork

The truth is, the list of issues outside IT's control keeps getting longer. But, that makes visibility even more important. When you have hard data about what your people are actually experiencing, you can:

■ Hold your SaaS and Internet providers accountable

■ Empower employees (and reduce their frustration) by quickly diagnosing problems in their own devices and home networks that they can fix themselves

■ Quickly identify problems beyond IT's control, so they can focus their time on tasks where they can make a real difference

We're all still adjusting to the challenges of a post-COVID world. But, when your business relies on a remote workforce every day, just knowing what's happening out there can be hugely beneficial.

The Latest

AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...