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Making Digital Transformation Work for You – Part 1

Joshua Dobies

Today we think nothing of using our smartphones to access systems and share information with colleagues, partners and customers anytime, anywhere. It may be hard to believe, but ten years ago those capabilities were just wishful thinking. The decade-long (and still on-going) maturation of technologies like cloud computing, mobile, big data and social media platforms is fueling a digital transformation in how we get work done.

But the IT organization can do more than oversee the ad hoc adoption of these technologies. IT has the opportunity to drive an executive-led, enterprise-wide strategy that leverages technology to improve business processes. That means moving away from IT's traditional role of maintaining systems and troubleshooting users' problems to offering services that improve users' productivity levels and spur revenue growth. That's a significant change, so your first question is likely along the lines of, "What are the first steps to creating this digital transformation strategy?" This three-part series will answer that question.

Imagine if you asked an IT professional in 2005 to set up several servers and storage resources, install the various applications, ensure that users at all branch offices and other remote locations have seamless access on all their devices, and to have it all up and running within 24 hours. That IT pro would have laughed out loud. After all, that would have been before the 2006 introduction of Amazon Web Services (AWS), the 2007 unveiling of the first iPhone and other developments that served as the catalysts for the digital transformation.

Today, you can spin up servers, storage resources and applications in minutes. And users don't just ask for 24/7 access on all their devices, they demand it without suffering poor performance-related issues.

That's why it's so important to understand that digital transformation is a business strategy, not simply a technology trend. There is no automatic competitive advantage in adopting what everyone else is adopting. Mobile is a given in today's digital environment. Social is a business requirement. Big data and cloud are nearly universally used by businesses, as well, if they wish to remain competitive. To achieve competitive advantage from digital transformation, companies must move beyond the mere adoption of these digital technologies.

According to Capgemini Consulting and MIT Sloan Management, less-mature digital companies tend to take a tactical, piecemeal approach as they solve discrete business problems with individual digital technologies. As a result, they don't fully integrate digital technologies with their business operations, don't solve the underlying infrastructure problems that cause frequent application performance issues across the enterprise, and fail to deliver the required technical capabilities at scale.

These companies face mounting challenges down the road. IDC predicts that:

■ By 2017, 60% of digital transformation initiatives will be unable to scale due to a lack of a strategic architecture.

■ By 2018, 70% of siloed digital transformation initiatives will ultimately fail due to insufficient collaboration, integration, sourcing, or project management.

In contrast, maturing digital companies take a strategic approach, integrating digital technologies to transform how their businesses work. As a result, they are able to:

■ Generate 26% higher profits than less digitally mature competitors.

■ Generate 9% more revenue.

■ Achieve a 12% higher market valuation ratio.

These companies embrace and absorb cloud, mobile, social, and big data technologies. They create competitive advantage with the superior ability to orchestrate these technologies enterprise-wide to create and deliver digital services. Of course, that's easier said than done.

Today's globally distributed, hybrid application environments are more complex than ever. There are so many moving parts and operational dependencies that the weak links in the chain are bound frequently to get stressed to the breaking point.

The primary culprit is the network. Even as enterprises adopt new digital technologies, network operators still remotely maintain routers and push applications over the Web to each branch office.

As a result, users must contend with more instances of poor application performance. Their productivity suffers, and IT shoulders the blame. That should raise red flags in the executive suite considering the importance of the remote and branch office (ROBO). Application performance fails to meet the needs of the business not just some of the time but most of the time.

This is why a strategic approach to managing your organization's digital transformation is necessary. In parts two and three of this series, I will more closely examine the factors behind this "performance gap," and why it's time to move on from the traditional WAN architectures built on routers and switches.

Read Making Digital Transformation Work for You – Part 2: Bridging the Performance Gap

Joshua Dobies is VP of Product Marketing, Riverbed Technology.

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 ...

Making Digital Transformation Work for You – Part 1

Joshua Dobies

Today we think nothing of using our smartphones to access systems and share information with colleagues, partners and customers anytime, anywhere. It may be hard to believe, but ten years ago those capabilities were just wishful thinking. The decade-long (and still on-going) maturation of technologies like cloud computing, mobile, big data and social media platforms is fueling a digital transformation in how we get work done.

But the IT organization can do more than oversee the ad hoc adoption of these technologies. IT has the opportunity to drive an executive-led, enterprise-wide strategy that leverages technology to improve business processes. That means moving away from IT's traditional role of maintaining systems and troubleshooting users' problems to offering services that improve users' productivity levels and spur revenue growth. That's a significant change, so your first question is likely along the lines of, "What are the first steps to creating this digital transformation strategy?" This three-part series will answer that question.

Imagine if you asked an IT professional in 2005 to set up several servers and storage resources, install the various applications, ensure that users at all branch offices and other remote locations have seamless access on all their devices, and to have it all up and running within 24 hours. That IT pro would have laughed out loud. After all, that would have been before the 2006 introduction of Amazon Web Services (AWS), the 2007 unveiling of the first iPhone and other developments that served as the catalysts for the digital transformation.

Today, you can spin up servers, storage resources and applications in minutes. And users don't just ask for 24/7 access on all their devices, they demand it without suffering poor performance-related issues.

That's why it's so important to understand that digital transformation is a business strategy, not simply a technology trend. There is no automatic competitive advantage in adopting what everyone else is adopting. Mobile is a given in today's digital environment. Social is a business requirement. Big data and cloud are nearly universally used by businesses, as well, if they wish to remain competitive. To achieve competitive advantage from digital transformation, companies must move beyond the mere adoption of these digital technologies.

According to Capgemini Consulting and MIT Sloan Management, less-mature digital companies tend to take a tactical, piecemeal approach as they solve discrete business problems with individual digital technologies. As a result, they don't fully integrate digital technologies with their business operations, don't solve the underlying infrastructure problems that cause frequent application performance issues across the enterprise, and fail to deliver the required technical capabilities at scale.

These companies face mounting challenges down the road. IDC predicts that:

■ By 2017, 60% of digital transformation initiatives will be unable to scale due to a lack of a strategic architecture.

■ By 2018, 70% of siloed digital transformation initiatives will ultimately fail due to insufficient collaboration, integration, sourcing, or project management.

In contrast, maturing digital companies take a strategic approach, integrating digital technologies to transform how their businesses work. As a result, they are able to:

■ Generate 26% higher profits than less digitally mature competitors.

■ Generate 9% more revenue.

■ Achieve a 12% higher market valuation ratio.

These companies embrace and absorb cloud, mobile, social, and big data technologies. They create competitive advantage with the superior ability to orchestrate these technologies enterprise-wide to create and deliver digital services. Of course, that's easier said than done.

Today's globally distributed, hybrid application environments are more complex than ever. There are so many moving parts and operational dependencies that the weak links in the chain are bound frequently to get stressed to the breaking point.

The primary culprit is the network. Even as enterprises adopt new digital technologies, network operators still remotely maintain routers and push applications over the Web to each branch office.

As a result, users must contend with more instances of poor application performance. Their productivity suffers, and IT shoulders the blame. That should raise red flags in the executive suite considering the importance of the remote and branch office (ROBO). Application performance fails to meet the needs of the business not just some of the time but most of the time.

This is why a strategic approach to managing your organization's digital transformation is necessary. In parts two and three of this series, I will more closely examine the factors behind this "performance gap," and why it's time to move on from the traditional WAN architectures built on routers and switches.

Read Making Digital Transformation Work for You – Part 2: Bridging the Performance Gap

Joshua Dobies is VP of Product Marketing, Riverbed Technology.

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 ...