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Summary – The apparent stability of legacy software masks a gradual erosion of agility, exponential maintenance costs, dependence on scarce experts, and increasing vulnerability exposure.
After a targeted audit revealing technical debt, business bottlenecks, and compliance risks, we stabilize the foundation (patches, automated tests, CI/CD) then split the monolith into autonomous modules to shorten cycles and reduce TCO.
Solution: an iterative approach – diagnosis → quick wins → modular overhaul to restore agility, resilience, and readiness for data/AI use.
In many Swiss organizations, legacy software is viewed as an immutable asset: it “works,” it “runs,” so why invest? In reality, this inertia hides a gradual degradation of operational velocity and resilience, increasing onboarding times, complicating maintenance, and accumulating technical debt that’s difficult to curb.
Teams find themselves trapped in opaque code, dependent on a handful of experts and exposed to growing vulnerabilities. The issue isn’t just financial; it touches on innovation capacity, security, and competitiveness. It becomes essential to treat modernization not as a prohibitive cost, but as a strategic lever to restore agility and robustness.
Demystifying Legacy: When “It Still Runs” Equals a Roadblock
Leaving old software in place creates the illusion of immediate savings. This apparent stability hides an accumulation of invisible blockers that slow down every change.
Illusion of Continuity and Frozen Functionality
At first glance, a legacy system seems reliable because it has executed business processes for years without a major incident. This historical stability reinforces the belief that any intervention could create more problems than it solves.
Yet each new requirement or regulation forces you to dig into code that was often hastily rewritten without a long-term vision. Features are grafted on in an ad hoc manner, which severely limits the system’s adaptability.
Over time, teams spend more effort finding workarounds than developing true innovations. Inertia becomes a vicious cycle where every update brings unexpected hotfixes.
Accumulated Technical Debt and Unmaintainable Code
Legacy systems embody yesterday’s “quick wins”: modules added without refactoring, outdated dependencies left unpatched, and missing tests. Every compromise made under pressure shows up in the code’s complexity.
When components are neither tested nor documented, every change must be preceded by a laborious audit, multiplying delays and costs. Enhancements almost invariably risk causing regressions.
This spiral feeds technical debt, hindering digital transformation and increasing the effort needed to deliver new, market-relevant features.
Dependence on Internal Expertise and Knowledge Silos
An aging software estate often relies on the know-how of a few developers or administrators who understand the architecture end to end. Their departure can abruptly halt ongoing projects.
Knowledge transfer happens in dribs and drabs and is rarely formalized. Turnover, retirements, and internal mobility create gaps in documentation, making onboarding for newcomers interminable.
Without a shared vision and a foundation of best practices, every intervention risks worsening existing complexity rather than reducing it.
Example: A Swiss logistics services company maintained an in-house ERP for over ten years, supported by two key engineers. When one left, the other had to urgently document 200,000 lines of code, consuming three months of intensive work before even fixing the first bug. This cost the firm the equivalent of CHF 1.2 million in internal and external consultant fees, demonstrating that the “security” of the status quo can become a major liability.
The Hidden Impacts of Aging Applications
Beyond hosting and license costs, most legacy expenses hide in maintenance and recurring delays. These invisible burdens weigh heavily on overall company performance.
Innovation Throttling and Extended Delivery Times
Every request for change becomes a complex project: first, you must analyze the outdated code, document its interactions, and identify potential regression risks. This phase can account for up to 60 percent of total development time.
Teams lose responsiveness, ceding ground to more agile competitors who can launch new offerings or quickly improve the user experience.
Time-to-market stretches out, business opportunities are missed, and innovation stalls, harming competitiveness in fast-moving markets.
Exponential Maintenance Costs and Resource Drain
A monolithic, poorly documented codebase often requires multiple technical profiles (analysts, developers, testers) for the slightest fix. These teams are then diverted from high-value projects.
IT budgets are largely consumed by support tickets and debugging cycles, sometimes up to 80 percent of the total load. The remainder is insufficient to fund modernization or innovation efforts.
We frequently end up prioritizing urgent fixes over foundational projects, reinforcing the legacy vicious cycle.
Example: A Switzerland-based industrial machinery manufacturer allocated nearly 70 percent of its IT budget to corrective maintenance of its planning system. Teams reported five-month delays for new module deployments, delaying the market introduction of innovative products and limiting expected gains.
Security Vulnerabilities and Compliance Challenges
Unpatched dependencies accumulate vulnerabilities. Without automated testing and patch management, each new release exposes the system to critical attacks (XSS, SQL injection, remote code execution…).
In an increasingly strict regulatory context (GDPR, ISO 27001, fintech directives…), any unaddressed flaw can lead to heavy fines and irreversible reputational damage.
Legacy complexity often makes effective security audits impossible, isolating the company and weakening it against growing cyberthreats.
Edana: strategic digital partner in Switzerland
We support companies and organizations in their digital transformation
Progressive Modernization: From Analysis to Modular Redesign
Mitigating risks requires an iterative approach: diagnose, stabilize, and break the monolith into independent modules. This strategy ensures continuity while regaining control of the software estate.
Targeted Analysis and Diagnosis
The first step is to map the application landscape: inventory critical modules, dependencies, and measure risk exposure. A quick audit reveals priority technical debt areas. Consult our data governance guide to structure this phase.
This phase doesn’t aim to document everything immediately but to establish a scoring based on business impact and technical criticality. It focuses efforts on components that pose the greatest barriers to innovation.
The diagnosis also provides a clear roadmap with milestones and success indicators tailored to each project phase.
Stabilization and Quick Wins
Before any overhaul, it’s essential to establish a stable technical foundation: fix critical vulnerabilities, update major dependencies, and implement automated tests. Setting up a CI/CD pipeline ensures deployment quality and reliability.
These improvements deliver quick wins: fewer incidents, more reliable deployments, and reduced downtime. They build confidence among teams and stakeholders.
The CI/CD pipeline also guarantees that every future change meets a defined quality standard, limiting regressions and streamlining development cycles.
Modular Redesign and Independent Services
Gradually splitting the monolith into microservices vs modular monolith allows each component to be deployed and evolved independently. Each service then has its own codebase and dedicated tests. Learn how to choose between microservices vs modular monolith for your information system.
This granularity limits update impact, simplifies version management, and accelerates time-to-market. Teams can work in parallel on distinct functional domains.
Ultimately, the ecosystem becomes more resilient: an incident in one module no longer affects the entire platform, enhancing service continuity and operational security.
Anticipating the Future: ROI, AI, and Organizational Resilience
Modernizing a legacy system generates tangible gains: lower total cost of ownership (TCO), faster releases, reduced risks, and new data and AI use cases. It becomes a high-value investment.
Reducing Total Cost of Ownership (TCO)
By eliminating maintenance, support, and infrastructure overages, TCO contracts significantly. The share of IT budget devoted to corrective maintenance can drop from 70 percent to less than 30 percent. The savings can be reallocated to innovative projects, boosting competitiveness and reducing reliance on external funding.
Accelerating Time-to-Market and Enhanced Agility
A modular architecture and mature CI/CD enable continuous delivery of features without disrupting the system. Development cycles shrink from quarters to weeks or days.
Preparing for AI Integration and Data Utilization
A modern, well-structured, and documented codebase facilitates API exposure and data flow between systems. AI projects can then rely on robust, reliable, and secure pipelines.
Data consolidation and automated ingestion pipelines are greatly simplified by a modular architecture. The data lake becomes a concrete lever for advanced analytics.
Predictive capabilities and machine learning algorithms benefit from the flexibility of the new ecosystem, accelerating value creation without compromising the existing system.
Turning Your Legacy into a Competitive Advantage
Maintaining the status quo with legacy software is a false economy: technical debt, code opacity, and reliance on a few experts erode performance. Conversely, a progressive modernization—conducted in phases of analysis, stabilization, and modular partitioning—restores agility, secures operations, and frees up resources for innovation.
Return on investment is measured in reduced maintenance costs, accelerated delivery, and openness to data and AI applications. Each modernized module becomes a foundation for new, high-value features.
CIOs, CEOs, and business leaders gain visibility over their software estate and regain control of their digital roadmap. Our Edana experts are ready to support you in building a contextualized, progressive, and sustainable transformation, based on open source, modularity, and security.
