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Digital Transformation - Here for the Long Haul

Sydney Sloan

Once a catch-all buzzword, "digital transformation" is now an impossible-to-ignore strategic underpinning of leading businesses. In fact, APMdigest made digital transformation a "hot topic" for 2017, recognizing that its importance will continue to grow as more and more organizations embrace it.

A relevant research piece about digital transformation was recently released by Alfresco Software, The Great Rethink: How Digital Leaders Are Building Tomorrow's Organizations. The report is based on comprehensive interviews of more than 300 senior executives at companies with annual revenues exceeding $1 billion, and it identifies common characteristics of high-performance organizations as they seek to establish themselves as digital disruptors in their individual markets.

Alfresco's research aims to "separate the winners from the losers," concluding that three key levers are typically employed by business and IT leaders when determining the best way to leverage technology to drive successful digital transformation:

Design thinking — leveraging a relentless focus on optimizing user experience and customer experience to guide all business technology decisions

Open thinking — encouraging innovation from both inside and outside the organization to drive new initiatives

Platform thinking — building an ecosystem of partners and customers that exchange capabilities and data to create added value through systems and solution deployment

Alfresco's research notes that the path to digital success is best realized by activating all three of these levers simultaneously.

64 percent of the report's "best-in-class" firms, those that excel across all three categories, report significant annual growth (defined by exceeding 10 percent EBITDA growth over the past three years) versus 43 percent of those still developing their capabilities across one or two of the three key areas.

Leadership Is Key

The research determines that CEOs must lead corporate digital transformation, with close to half (49 percent) of the fast-growing companies' digital transformation efforts being led directly by the CEO, versus 20 percent for all others. Digital transformation starts at the top, ideally with the CEO driving change and ensuring that the whole company is moving in the right direction.

According to Alfresco, fast-growing companies also excel at customer- and user-first thinking, with 85 percent currently having dedicated user experience teams. In addition, they commit to an open approach to the flow of ideas and concepts in their organizations, with 85 percent saying a commitment to open standards is "important or very important."

Finally, high-performing companies re-imagine their business models to incorporate support for a shared economy and platform thinking; in fact, 67 percent of these companies plan to significantly increase the capability for customers and/or suppliers to connect to them in the next three years.

The report confirms that digital transformation has truly taken hold in the corporate world and illustrates that today's digital economy is a case of "disrupt or be disrupted." The financial performance of leading firms bears this out. Digital transformation is not just a critical stepping stone to success – it can be the key to an organization's very survival.

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 ...

Digital Transformation - Here for the Long Haul

Sydney Sloan

Once a catch-all buzzword, "digital transformation" is now an impossible-to-ignore strategic underpinning of leading businesses. In fact, APMdigest made digital transformation a "hot topic" for 2017, recognizing that its importance will continue to grow as more and more organizations embrace it.

A relevant research piece about digital transformation was recently released by Alfresco Software, The Great Rethink: How Digital Leaders Are Building Tomorrow's Organizations. The report is based on comprehensive interviews of more than 300 senior executives at companies with annual revenues exceeding $1 billion, and it identifies common characteristics of high-performance organizations as they seek to establish themselves as digital disruptors in their individual markets.

Alfresco's research aims to "separate the winners from the losers," concluding that three key levers are typically employed by business and IT leaders when determining the best way to leverage technology to drive successful digital transformation:

Design thinking — leveraging a relentless focus on optimizing user experience and customer experience to guide all business technology decisions

Open thinking — encouraging innovation from both inside and outside the organization to drive new initiatives

Platform thinking — building an ecosystem of partners and customers that exchange capabilities and data to create added value through systems and solution deployment

Alfresco's research notes that the path to digital success is best realized by activating all three of these levers simultaneously.

64 percent of the report's "best-in-class" firms, those that excel across all three categories, report significant annual growth (defined by exceeding 10 percent EBITDA growth over the past three years) versus 43 percent of those still developing their capabilities across one or two of the three key areas.

Leadership Is Key

The research determines that CEOs must lead corporate digital transformation, with close to half (49 percent) of the fast-growing companies' digital transformation efforts being led directly by the CEO, versus 20 percent for all others. Digital transformation starts at the top, ideally with the CEO driving change and ensuring that the whole company is moving in the right direction.

According to Alfresco, fast-growing companies also excel at customer- and user-first thinking, with 85 percent currently having dedicated user experience teams. In addition, they commit to an open approach to the flow of ideas and concepts in their organizations, with 85 percent saying a commitment to open standards is "important or very important."

Finally, high-performing companies re-imagine their business models to incorporate support for a shared economy and platform thinking; in fact, 67 percent of these companies plan to significantly increase the capability for customers and/or suppliers to connect to them in the next three years.

The report confirms that digital transformation has truly taken hold in the corporate world and illustrates that today's digital economy is a case of "disrupt or be disrupted." The financial performance of leading firms bears this out. Digital transformation is not just a critical stepping stone to success – it can be the key to an organization's very survival.

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 ...