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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."

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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."

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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 ...

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Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...

Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

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