Business and IT Transformation Starts with a "Frictionless" User Experience

Veronica Wolf
Learn more about Riverbed

Employee engagement, according to the latest Gartner Research, is a core element of the mobile and digital workspace. In other words, with the ever-changing business landscape, employees are more willing and able to evolve in their roles and lean into change if they are empowered with a positive, "frictionless" end user experience. During this period of business transformation, technology is seen primarily as an enabler for improved business and business change, therefore aligning IT with business goals and focusing on supporting business initiatives is now more critical than ever. But business transformation involves not only disruptive technologies such as cloud, virtualization and mobile, but also the people involved in the transformation, a.k.a. change management.

Your workforce, not the technology — according to Eric Klein, Director, Enterprise Mobility at VDC Research — is the most difficult element to any IT transformation initiative. In fact, based on a recent Forbes Survey conducted on behalf of Gartner, 45% of IT projects fail due to ineffective organizational change management.

Aternity's 2016 Business Transformation and User Experience Trends Survey sheds some light on how the End User Experience impacts the success of these critical enterprise initiatives. More than 200 IT executives weighed in on some of the key drivers and challenges they face as they shift from a technology-focused role to a more business-focused role.

Why Proactive End User Experience Management is Key to Business Transformation

Knowing just how IT transformation projects affect the End User Experience with critical LoB applications before the end users are impacted is key to a successful initiative. Despite the billion dollar a year market for System Management tools, analysts like Gartner and Forrester estimate that 70-80% of problems impacting the end users are never detected by IT. In fact, it's a rare occurrence if your users escalate the problem. So what about the majority of users who suffer in silence and don't complain to you? That's when the so-called "IT visibility gap" can become really painful.

What's more, it is estimated that when addressing an end user's complaint, between 80-90% of the effort is troubleshooting. In other words, IT is spending the vast majority of its support cycles on the back of their heels, reacting to an issue instead of preventing one. At the pace of transformational change, it's no longer enough for IT organizations to react to operational issues based on isolated incidents or gut instinct, as it can cost them and the businesses they serve far more than a few days of lost productivity.


With this need to bridge the visibility gap that exists now between the end user perception of performance received and IT's measurement of the performance delivered with traditional IT monitoring, it's not surprising nearly half of the survey respondents either selected "End User Experience Monitoring" (29%) or "Improving Workforce Productivity" (20%) as a capability they would like to have or improve in their monitoring toolset.

How a "Frictionless" End User Experience Translates to a Better Customer Experience

To deliver excellent customer service, you need to identify and resolve problems quickly.

No matter what industry you're in, if you do not have the insight into how long it takes your tech-dependent workforce to perform simple business transactions and activities as they interface with customers on the frontlines (POS, EHR, CRM, etc.), you cannot as effectively improve the customer experience.


So what does customer experience really mean, and how does this correlate with End User (workforce) Experience? Some of the best minds on this topic such as Esteban Kolsky, CEO of thinkJar believe that this translates to moving away from a focus on company-centric behavior to more of a customer-centric model, where the focus is on ongoing monitoring and correlation of the complexities and nuances of outside-in interactions with customers.

CIO Insight goes as far as to suggest CIOs and other business and IT leaders should re-examine just about everything relating to the customer experience. Omni-channel strategies enable your customers to do business with you as they wish, seamlessly via mobile, web, or in person. A similar seamless, client-centric approach with the tech-dependent workforce is needed in order to improve customer satisfaction and service.

To underline this point, the survey found "Customer Experience/Customer Intimacy" as the top initiative driving the need for improved visibility within organizations; outpacing by a factor of two (34%), major transformation initiatives including virtualization, cloud, mobile, GRC, and process automation (each at 15%).

The Bottom Line

If IT leadership is to be recognized as a strategic, business transformation "enabler" they need to be empowered with the tools to truly understand the internal and external customer experience.

This translates to having the visibility and actionable insights into how technologies impact your workforce, which in turn demonstrate the business value of IT initiatives and their effect on the ultimate customer.

Whether the budgeted transformational initiative is categorized under Improving Customer Satisfaction/Intimacy, or other initiatives such as GRC, Mobile/Cloud/VDI, Process Automation/Optimization, Agile/DevOps, or M&A/Change Management, managing enterprise change with visibility into how the initiative directly affects the end user is the first step to overcoming these barriers to success.

Veronica Wolf is Director of Content Marketing for Aternity.

Related Links

Hot Topics

Related Vendors

The Latest

Escaping Pilot Purgatory: How AI Becomes an Operational Advantage

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Closing the Gap in Modern Tech and the Tools Meant to Monitor Them

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 ...

MEAN TIME TO INSIGHT Podcast - Episode 23: NetOps Labor Shortage

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Why FinOps Rewrote Its Mission and What It Signals for Technology Management

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 ...

Clearing the Path to AI: Why Vendor Consolidation Matters Now

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 ...

Cold Data, Hot Problem: Why AI Is Rewriting Enterprise Storage Strategy

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 ...

Observability at a Crossroads: AI, Economics, Complexity and the Enduring Power of Open Source

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 ...

Explainability Is the New Battleground in AI-Powered Observability

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 ...

Empowering the Human Side of the Autonomous IT Age

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 Scale Is Outpacing Infrastructure - and IT Leaders Are Running Out of Time

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.

Business and IT Transformation Starts with a "Frictionless" User Experience

Veronica Wolf
Learn more about Riverbed

Employee engagement, according to the latest Gartner Research, is a core element of the mobile and digital workspace. In other words, with the ever-changing business landscape, employees are more willing and able to evolve in their roles and lean into change if they are empowered with a positive, "frictionless" end user experience. During this period of business transformation, technology is seen primarily as an enabler for improved business and business change, therefore aligning IT with business goals and focusing on supporting business initiatives is now more critical than ever. But business transformation involves not only disruptive technologies such as cloud, virtualization and mobile, but also the people involved in the transformation, a.k.a. change management.

Your workforce, not the technology — according to Eric Klein, Director, Enterprise Mobility at VDC Research — is the most difficult element to any IT transformation initiative. In fact, based on a recent Forbes Survey conducted on behalf of Gartner, 45% of IT projects fail due to ineffective organizational change management.

Aternity's 2016 Business Transformation and User Experience Trends Survey sheds some light on how the End User Experience impacts the success of these critical enterprise initiatives. More than 200 IT executives weighed in on some of the key drivers and challenges they face as they shift from a technology-focused role to a more business-focused role.

Why Proactive End User Experience Management is Key to Business Transformation

Knowing just how IT transformation projects affect the End User Experience with critical LoB applications before the end users are impacted is key to a successful initiative. Despite the billion dollar a year market for System Management tools, analysts like Gartner and Forrester estimate that 70-80% of problems impacting the end users are never detected by IT. In fact, it's a rare occurrence if your users escalate the problem. So what about the majority of users who suffer in silence and don't complain to you? That's when the so-called "IT visibility gap" can become really painful.

What's more, it is estimated that when addressing an end user's complaint, between 80-90% of the effort is troubleshooting. In other words, IT is spending the vast majority of its support cycles on the back of their heels, reacting to an issue instead of preventing one. At the pace of transformational change, it's no longer enough for IT organizations to react to operational issues based on isolated incidents or gut instinct, as it can cost them and the businesses they serve far more than a few days of lost productivity.


With this need to bridge the visibility gap that exists now between the end user perception of performance received and IT's measurement of the performance delivered with traditional IT monitoring, it's not surprising nearly half of the survey respondents either selected "End User Experience Monitoring" (29%) or "Improving Workforce Productivity" (20%) as a capability they would like to have or improve in their monitoring toolset.

How a "Frictionless" End User Experience Translates to a Better Customer Experience

To deliver excellent customer service, you need to identify and resolve problems quickly.

No matter what industry you're in, if you do not have the insight into how long it takes your tech-dependent workforce to perform simple business transactions and activities as they interface with customers on the frontlines (POS, EHR, CRM, etc.), you cannot as effectively improve the customer experience.


So what does customer experience really mean, and how does this correlate with End User (workforce) Experience? Some of the best minds on this topic such as Esteban Kolsky, CEO of thinkJar believe that this translates to moving away from a focus on company-centric behavior to more of a customer-centric model, where the focus is on ongoing monitoring and correlation of the complexities and nuances of outside-in interactions with customers.

CIO Insight goes as far as to suggest CIOs and other business and IT leaders should re-examine just about everything relating to the customer experience. Omni-channel strategies enable your customers to do business with you as they wish, seamlessly via mobile, web, or in person. A similar seamless, client-centric approach with the tech-dependent workforce is needed in order to improve customer satisfaction and service.

To underline this point, the survey found "Customer Experience/Customer Intimacy" as the top initiative driving the need for improved visibility within organizations; outpacing by a factor of two (34%), major transformation initiatives including virtualization, cloud, mobile, GRC, and process automation (each at 15%).

The Bottom Line

If IT leadership is to be recognized as a strategic, business transformation "enabler" they need to be empowered with the tools to truly understand the internal and external customer experience.

This translates to having the visibility and actionable insights into how technologies impact your workforce, which in turn demonstrate the business value of IT initiatives and their effect on the ultimate customer.

Whether the budgeted transformational initiative is categorized under Improving Customer Satisfaction/Intimacy, or other initiatives such as GRC, Mobile/Cloud/VDI, Process Automation/Optimization, Agile/DevOps, or M&A/Change Management, managing enterprise change with visibility into how the initiative directly affects the end user is the first step to overcoming these barriers to success.

Veronica Wolf is Director of Content Marketing for Aternity.

Related Links

Hot Topics

Related Vendors

The Latest

Escaping Pilot Purgatory: How AI Becomes an Operational Advantage

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Closing the Gap in Modern Tech and the Tools Meant to Monitor Them

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 ...

MEAN TIME TO INSIGHT Podcast - Episode 23: NetOps Labor Shortage

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Why FinOps Rewrote Its Mission and What It Signals for Technology Management

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 ...

Clearing the Path to AI: Why Vendor Consolidation Matters Now

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 ...

Cold Data, Hot Problem: Why AI Is Rewriting Enterprise Storage Strategy

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 ...

Observability at a Crossroads: AI, Economics, Complexity and the Enduring Power of Open Source

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 ...

Explainability Is the New Battleground in AI-Powered Observability

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 ...

Empowering the Human Side of the Autonomous IT Age

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 Scale Is Outpacing Infrastructure - and IT Leaders Are Running Out of Time

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.