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The Past, Present and Future of DEX

Tim Flower

Over the last 20 years Digital Employee Experience has become a necessity for companies committed to digital transformation and improving IT experiences. In fact, by 2025, more than 50% of IT organizations will use digital employee experience to prioritize and measure digital initiative success.

However, it is still often an unsung hero of IT with employees feeling its absence but not always appreciating its reach.

Let's take a look back at life before DEX, how we can define DEX and what the future of DEX looks like. A Look Back at the IT Horrors I started my career in technology in the late 80s — long before the idea of remote work or the availability of the internet right in your pocket. It was essentially the IT Dark Ages. Automation in EUC was in its infancy, and visibility into the technology being used was non-existent. This meant when something would break, IT wouldn't know, sometimes for weeks, until employees started calling into the helpdesk.

Technology projects would take months to complete out of fear of breaking machines. A product rolloutnwould be done in multiple, slow phases to ensure that there was built in time for the helpdesk to catch on to an issue. Of course, that also meant if a ticket wasn't created IT worked under the assumption thateverything was fine — something we know today is never the case.

Inevitably, there would be at least one wide scale outage that every team in IT would disavow knowledge of. Regardless, that team would be required to attend the lengthy escalation call while every service tower investigated "their stack" to verify that it wasn't their problem to solve. It was a time of trial-and-error troubleshooting, or looking at diagnostic tools that had no bearing on the problem. But more so, it was a period of wasted time — time that could have been used to push innovation forward, work on something to move business priorities forward or even just take a longer lunch. Before DEX, wespent so much time passing off blame to the network team, or server, Citrix, or SCCM teams. We did the best with what we had, but the world has changed so much since then. But think about your existing environment. If you don't have DEX capabilities, I could be describing your world TODAY, not 20 years ago!

Defining Digital Employee Experience

I've seen many definitions of DEX, but true Digital Employee Experience is the process and IT discipline that focuses on positive outcomes for employees rather than the mere success of provisioning technology. The best outcome of a DEX operation is that IT can finally disconnect the dependency on the employee to report issues, and can manage the environment based on facts, data, and reality — a more accurate portrayal of what is happening behind the scenes than what is received via ticketing system.

In addition, by focusing on improving speed and quality of services delivered with definitive measures and accuracy, costs can be controlled more precisely than just cutting line items from the budget.

DEX is still a fairly new discipline with different vendors taking liberties and infusing their own meaning into the definition to make sure their capabilities are part of the conversation, which can be very confusing to buyers.

For example, is the ability to manage the VDI environment to a deep technical level a requirement for DEX? The VDI management vendors believe so, but DEX is not a hypervisor platform management tool. From a technology consumer side, I also think there's a misunderstanding of the impact that employee sentiment can provide to augment IT's understanding of the business and employees they support. Many customers view employee feedback and sentiment as a nice-to-have and maybe something they'll look at "later", but those that have come to use it regularly see it as a must-have. 

The use of DEX, however, is up to the customer. I have seen many different case studies of how DEX was used to solve complex or elusive problems from improving collaboration with application teams to making acquisitions a bit easier.

The Next 20 Years of DEX

With AI more available than ever before, it is safe to say next gen AI models will propel DEX forward at a staggering rate. While AI has been in the background of some DEX solutions already, the innovations in the technology will bring in even deeper analysis and insights across even larger data sets faster than previously possible. This is a momentous time for technology as AI, linked with automation, is truly ready to change the game. Similar to the invention of the internet, the ubiquitousness of AI is both exciting and frightening. While some people fear it will take away jobs, others know it is about adapting not replacement. Of course, with any change to the way we work there is a learning curve and many enterprises today struggle to define how to adopt AI in a meaningful way.

Additionally, we can expect DEX to become more employee-facing, allowing employees to interact directly with technology to get information and insights that will likely even bypass the need for an application front end. And when you link it with augmented reality, the possibilities are endless.

We've come a long way since 2004. Work is what you do, not where you go. For many that work is now fully digital, and having a proactive IT organization no longer sets you apart. It isn't "a nice to have" but a must have, and if you haven't made the change yet you are falling behind. Coupled with AI, DEX's reach will only continue to grow with its impact being even more apparent. I've had the opportunity to witness these changes in real-time, experiencing the highs and lows of working in IT. And while as a customer I adopted DEX at a very early stage, it's something I wish I had been aware of even earlier. I often think of all the headaches and business impacting events we could have avoided. So, my advice to you is this: Embrace new technology and assess its viability for you as early as you can. Don't be afraid to push the limits of what is possible.

The Latest

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 ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

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 ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

The Past, Present and Future of DEX

Tim Flower

Over the last 20 years Digital Employee Experience has become a necessity for companies committed to digital transformation and improving IT experiences. In fact, by 2025, more than 50% of IT organizations will use digital employee experience to prioritize and measure digital initiative success.

However, it is still often an unsung hero of IT with employees feeling its absence but not always appreciating its reach.

Let's take a look back at life before DEX, how we can define DEX and what the future of DEX looks like. A Look Back at the IT Horrors I started my career in technology in the late 80s — long before the idea of remote work or the availability of the internet right in your pocket. It was essentially the IT Dark Ages. Automation in EUC was in its infancy, and visibility into the technology being used was non-existent. This meant when something would break, IT wouldn't know, sometimes for weeks, until employees started calling into the helpdesk.

Technology projects would take months to complete out of fear of breaking machines. A product rolloutnwould be done in multiple, slow phases to ensure that there was built in time for the helpdesk to catch on to an issue. Of course, that also meant if a ticket wasn't created IT worked under the assumption thateverything was fine — something we know today is never the case.

Inevitably, there would be at least one wide scale outage that every team in IT would disavow knowledge of. Regardless, that team would be required to attend the lengthy escalation call while every service tower investigated "their stack" to verify that it wasn't their problem to solve. It was a time of trial-and-error troubleshooting, or looking at diagnostic tools that had no bearing on the problem. But more so, it was a period of wasted time — time that could have been used to push innovation forward, work on something to move business priorities forward or even just take a longer lunch. Before DEX, wespent so much time passing off blame to the network team, or server, Citrix, or SCCM teams. We did the best with what we had, but the world has changed so much since then. But think about your existing environment. If you don't have DEX capabilities, I could be describing your world TODAY, not 20 years ago!

Defining Digital Employee Experience

I've seen many definitions of DEX, but true Digital Employee Experience is the process and IT discipline that focuses on positive outcomes for employees rather than the mere success of provisioning technology. The best outcome of a DEX operation is that IT can finally disconnect the dependency on the employee to report issues, and can manage the environment based on facts, data, and reality — a more accurate portrayal of what is happening behind the scenes than what is received via ticketing system.

In addition, by focusing on improving speed and quality of services delivered with definitive measures and accuracy, costs can be controlled more precisely than just cutting line items from the budget.

DEX is still a fairly new discipline with different vendors taking liberties and infusing their own meaning into the definition to make sure their capabilities are part of the conversation, which can be very confusing to buyers.

For example, is the ability to manage the VDI environment to a deep technical level a requirement for DEX? The VDI management vendors believe so, but DEX is not a hypervisor platform management tool. From a technology consumer side, I also think there's a misunderstanding of the impact that employee sentiment can provide to augment IT's understanding of the business and employees they support. Many customers view employee feedback and sentiment as a nice-to-have and maybe something they'll look at "later", but those that have come to use it regularly see it as a must-have. 

The use of DEX, however, is up to the customer. I have seen many different case studies of how DEX was used to solve complex or elusive problems from improving collaboration with application teams to making acquisitions a bit easier.

The Next 20 Years of DEX

With AI more available than ever before, it is safe to say next gen AI models will propel DEX forward at a staggering rate. While AI has been in the background of some DEX solutions already, the innovations in the technology will bring in even deeper analysis and insights across even larger data sets faster than previously possible. This is a momentous time for technology as AI, linked with automation, is truly ready to change the game. Similar to the invention of the internet, the ubiquitousness of AI is both exciting and frightening. While some people fear it will take away jobs, others know it is about adapting not replacement. Of course, with any change to the way we work there is a learning curve and many enterprises today struggle to define how to adopt AI in a meaningful way.

Additionally, we can expect DEX to become more employee-facing, allowing employees to interact directly with technology to get information and insights that will likely even bypass the need for an application front end. And when you link it with augmented reality, the possibilities are endless.

We've come a long way since 2004. Work is what you do, not where you go. For many that work is now fully digital, and having a proactive IT organization no longer sets you apart. It isn't "a nice to have" but a must have, and if you haven't made the change yet you are falling behind. Coupled with AI, DEX's reach will only continue to grow with its impact being even more apparent. I've had the opportunity to witness these changes in real-time, experiencing the highs and lows of working in IT. And while as a customer I adopted DEX at a very early stage, it's something I wish I had been aware of even earlier. I often think of all the headaches and business impacting events we could have avoided. So, my advice to you is this: Embrace new technology and assess its viability for you as early as you can. Don't be afraid to push the limits of what is possible.

The Latest

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 ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

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 ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...