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Continual Modernization Programs Are Key to IT Success

Modernization projects using an incremental and continuous improvement model achieve superior results when compared to other project-based approaches including the ripping and replacing of core business applications, according to the CHAOS2020 Report from Micro Focus and Standish Group.


The report indicates that this infinite flow method to modernizing core business applications has a number of benefits in regards to return of value, customer satisfaction, sustainable innovation and longer application lifespans.

"As we see in our latest research with Standish Group, a continuous and multi-phased modernization methodology delivers incremental value and reduces risk when compared to the alternatives of rewriting or replacing," said Neil Fowler, GM of Application Modernization and Connectivity at Micro Focus. "With application modernization typically being an important first step in an enterprise's larger digital transformation journey, an incremental flow-based model provides a methodology capable of matching the flexibility of today's business climate while ensuring continuous transformative activity."

Multi-decade Standish Group research of over 50,000 participants shows that an infinite flow model ensures ongoing modernization activity, while narrowing the gap between project management and delivery teams. This research is consistent with Micro Focus' own findings where 92 percent of core applications are strategic and 70 percent see modernization as their preferred option.

Key findings of the Endless Modernization research include:

Modernization Projects Yield Significantly Higher Success Rates

Companies replacing a software application and starting from scratch had a 26 percent success and 20 percent failure ratio as opposed to a 71 percent success and 1 percent failure ratio for teams choosing to modernize an existing application rather than fully replacing it.

Rip and Replace Projects Struggle

Only 27 percent of companies choosing a rip and replace strategy saw a high return, with 41 percent reporting a low or very low return on their investment. In comparison, a flow-based modernization methodology returned twice the value on average than other types of software development approaches.

Modernization is a Preferred Path over Ripping and Replacing

45 percent of enterprises ripping and replacing their application software were ultimately disappointed or not satisfied by their results as opposed to 55 percent of organizations choosing modernization responding as satisfied.

Incremental Flow-Based Modernization Approaches Have Numerous Benefits

Rather than running one large modernization project, research shows that enterprises incorporating a series of smaller, microservices or microprojects achieved much better outcomes.

"The demand is for more value, higher customer satisfaction, and lower costs," said Jim Johnson, founder, The Standish Group. "It is our opinion — based on our extensive research and observation of role models — that the move to infinite flow satisfies all three of these demands."

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 ...

Continual Modernization Programs Are Key to IT Success

Modernization projects using an incremental and continuous improvement model achieve superior results when compared to other project-based approaches including the ripping and replacing of core business applications, according to the CHAOS2020 Report from Micro Focus and Standish Group.


The report indicates that this infinite flow method to modernizing core business applications has a number of benefits in regards to return of value, customer satisfaction, sustainable innovation and longer application lifespans.

"As we see in our latest research with Standish Group, a continuous and multi-phased modernization methodology delivers incremental value and reduces risk when compared to the alternatives of rewriting or replacing," said Neil Fowler, GM of Application Modernization and Connectivity at Micro Focus. "With application modernization typically being an important first step in an enterprise's larger digital transformation journey, an incremental flow-based model provides a methodology capable of matching the flexibility of today's business climate while ensuring continuous transformative activity."

Multi-decade Standish Group research of over 50,000 participants shows that an infinite flow model ensures ongoing modernization activity, while narrowing the gap between project management and delivery teams. This research is consistent with Micro Focus' own findings where 92 percent of core applications are strategic and 70 percent see modernization as their preferred option.

Key findings of the Endless Modernization research include:

Modernization Projects Yield Significantly Higher Success Rates

Companies replacing a software application and starting from scratch had a 26 percent success and 20 percent failure ratio as opposed to a 71 percent success and 1 percent failure ratio for teams choosing to modernize an existing application rather than fully replacing it.

Rip and Replace Projects Struggle

Only 27 percent of companies choosing a rip and replace strategy saw a high return, with 41 percent reporting a low or very low return on their investment. In comparison, a flow-based modernization methodology returned twice the value on average than other types of software development approaches.

Modernization is a Preferred Path over Ripping and Replacing

45 percent of enterprises ripping and replacing their application software were ultimately disappointed or not satisfied by their results as opposed to 55 percent of organizations choosing modernization responding as satisfied.

Incremental Flow-Based Modernization Approaches Have Numerous Benefits

Rather than running one large modernization project, research shows that enterprises incorporating a series of smaller, microservices or microprojects achieved much better outcomes.

"The demand is for more value, higher customer satisfaction, and lower costs," said Jim Johnson, founder, The Standish Group. "It is our opinion — based on our extensive research and observation of role models — that the move to infinite flow satisfies all three of these demands."

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 ...