Composable ERP promised agility but created a sprawling tangle of disconnected apps. This Forbes article explores how ERP Lifecycle Optimization spanning change detection, impact analysis, automated testing, and AI-driven training helps enterprises finally regain control.
Five years ago, Gartner released a seminal paper that introduced the concept of a transformative world: composable ERP.
The paper promised enterprise software that would function like LEGO bricks: modular, buildable and easily reconfigurable. They called it “an adaptive technology strategy” that “enables…[you] to keep up with the pace of business change.” But the reality of ERP in 2025 has proved quite different. What was meant to be an agile, efficient software ecosystem is instead an unmanageable web of disconnected applications and fragmented data. The status quo today drives enterprise costs higher than they need to be. In a recent conversation I had with a CIO, they put it bluntly: “Composable ERP, without a proper lifecycle management strategy, is like building a race car with mismatched parts. Sure, it might look cool in the garage, but good luck winning any races.”
Five years ago, Gartner released a seminal paper that introduced the concept of a transformative world: composable ERP.
The paper promised enterprise software that would function like LEGO bricks: modular, buildable and easily reconfigurable. They called it “an adaptive technology strategy” that “enables…[you] to keep up with the pace of business change.” But the reality of ERP in 2025 has proved quite different. What was meant to be an agile, efficient software ecosystem is instead an unmanageable web of disconnected applications and fragmented data. The status quo today drives enterprise costs higher than they need to be. In a recent conversation I had with a CIO, they put it bluntly: “Composable ERP, without a proper lifecycle management strategy, is like building a race car with mismatched parts. Sure, it might look cool in the garage, but good luck winning any races.”
1. Change Detection: Know What’s Changing Before It Breaks
Sorting through your SaaS mess requires that you get ahead of issues. To do this, your IT team needs excellent system visibility. More specifically, they need real-time monitoring of configuration updates, API changes and metadata modifications to anticipate disruptions and avoid downtime. A misstep I’ve often observed—assuming manual alerts and ticketing systems are enough. Here’s why they fall short: By the time a problem shows up in a support ticket, it’s already customer-facing. I don’t know about you, but I want to catch issues before users ever feel them.
2. Impact Analysis: Understanding The Butterfly Effect
In an enterprise, no app is an island. A minor update in one SaaS app can completely derail another, causing a cascade of downstream issues across multiple workflows. With AI-enabled analysis, teams can visualize the impacts of cascading issues instantly. Manual methods of impact analysis are not wise, as teams often realize that they’ve missed critical cross-module impacts too late. My advice: Invest early in systems that surface and analyze these connections automatically and proactively. The hidden issues are usually the ones that hurt the most.
3. Automated Testing: Validate At Scale
Providers update the software frequently, which is viewed as one of the advantages of SaaS applications, but it is unsustainable if your testing methods are still manual. Enterprises need automated test frameworks to validate integrations and business processes in real time. Adopting robust test automation can mean 70% faster release cycles, with a 90% reduction in the occurrence of post-release defects. For this, I recommend agentic systems. They not only execute these tests but also decide which tests to run. They adapt testing based on what’s changing, so you can rest assured you’re covered.
4. Dynamic User Enablement: Adaptive Training In Real Time
With every update, employees need to be trained on how to adapt to each change, but too many training programs are static PDFs or outdated videos created manually. The most valuable enablement happens in the flow of work—giving users contextual help and guidance as they are navigating their tasks. For this, I recommend AI-driven training delivered through in-platform guidance. Agentic digital trainers can personalize training to specific user behaviors and adapt in real time, resulting in faster adoption, fewer errors, less workflow disruption and drastically fewer support tickets for your IT team to address.
5. AI-Enabled Observability: End-To-End Monitoring
To truly solve problems, IT teams need more than just error logs. AI-powered observability tools bring real-time visibility to your team across the ERP lifecycle. These tools can tell you not only where the fire is burning but also how it started and where it might spread. Agentic-powered observability tools allow your team to shift from putting out fires to preventing them in the first place.
A Smarter SaaS Strategy
Composable ERP is finally within reach. Enterprises that treat their ERP landscape as a unified whole will be the ones thriving in the Agentic AI era.
This is where ERP Lifecycle Optimization becomes essential. Instead of reacting to problems as they arise, enterprises can take a proactive approach to the core system of their IT ecosystem. ERP Lifecycle Optimization enables enterprises to orchestrate change, enhance existing systems and mitigate risks before they materialize.
