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Summary – When maintaining legacy software generates growing hidden costs, it strains the budget with time-consuming fixes, a complex codebase and critical reliance on a handful of experts, while exposing the business to delays, vulnerabilities and compliance issues. Each change can cost up to three times more, extend test cycles and siphon off over 15 % of the IT budget without warning. To reverse the trend, launch a comprehensive audit, map your critical assets, then opt for gradual modernization via microservices and short agile sprints, ensuring rapid TCO reduction and a scalable foundation.
Software that has been in place for decades may seem to run at no extra cost, but its operation and evolution incur expenses that are often invisible. The historical investment in its development masks a total cost of ownership (TCO) that rises every year, draining budget and resources. This article sheds light on these hidden charges, illustrates their impact in Swiss industry, and offers a pragmatic analysis to help you decide when it’s time to modernize.
Hidden Costs of Legacy Software
A system already in place is not a free asset—it generates hidden costs as soon as you start operating it. Every hour spent fixing or adapting it increases the total cost of ownership without ever alerting the budget.
Understanding a Code Monster
Diving into a codebase accumulated over several decades is a daunting task. Interdependent functions, disparate conventions, and outdated comments weigh down analysis speed. Every change carries a risk of regression that must be detected and tested manually, significantly extending delivery times and requiring teams to refactor code.
The time a developer spends identifying the impact of a simple bug fix on the entire system can be measured in dozens—or even hundreds—of hours. This bottleneck slows down all ongoing projects and systematically pushes new development to the back burner. Teams end up spending an increasing portion of their time understanding the old code rather than adding business value.
Within IT departments, this phenomenon is often perceived as inevitable and unbudgetable, reinforcing the notion that “everything is under control as long as nothing breaks.” Yet this illusion is costly for organizations in terms of both responsiveness and productivity.
Overruns from Recurring Changes
Adding a feature or fixing a bug in aging software becomes progressively more expensive. Every new request requires verifying infrastructure, checking dependency versions, and assessing impacts on related modules. Test cycles lengthen and multiply because legacy platforms often lack modular architectures and automated testing.
The principle of software obsolescence applies fully here: the longer updates are postponed, the more each hour of development costs. It’s not just the developer’s hourly rate that climbs—it’s also the time spent coordinating, documenting, and testing that blows budgets out of the water. In the long run, you end up spending more on maintenance than on new development.
Underestimating these overruns leads to overestimating an organization’s capacity to innovate and delays decision-making on the need to refactor or modernize the existing system.
Example from a Swiss Industry Group
In a large Swiss industrial group, a business application had accumulated nearly one million lines of code and about 20,000 development hours. No major incidents had occurred for years, which fed the belief that there was no problem. Yet each small enhancement took three times longer than a brand-new development.
This case shows that the absence of downtime is not an indicator of good technical health. Critical knowledge resided with two veteran developers, making every change risky. Lead times grew and human dependency stifled any automation strategy.
By quantifying these delays and identifying bottlenecks, the executive board ultimately measured annual hidden costs exceeding 15% of the IT budget—costs that never appeared as such in financial reports.
Annual Hidden Costs of Legacy Software
Beyond the historical investment, an old system incurs maintenance, hosting, and risk-management fees every year. These invisible costs weigh heavily on the operational budget.
Corrective and Evolutionary Maintenance
Every user-reported ticket leads to root-cause analysis, a correction phase, and then a battery of tests. In a poorly structured legacy system, a simple patch can require updating multiple old modules and revising their technical documentation.
The real cost of a simple fix often exceeds three times that of a clean implementation on a modern platform. Validation cycles trigger multiple back-and-forths between business units, QA, and development, degrading team efficiency and extending time to production.
These maintenance costs accumulate over twelve months and eventually represent a major portion of the IT budget—often without their root causes ever being clearly identified.
Dependence on Key Skills
The expertise required to evolve a legacy system frequently resides in a small number of people. When a key contributor is unavailable, projects stall. Onboarding newcomers can take hundreds of hours before they reach partial productivity.
This fragility heightens operational risk: a prolonged absence or unexpected departure can block strategic enhancements or delay security patches. Internal SLAs suffer, and business units experience slower delivery.
By relying on undocumented know-how, the company loses the ability to redistribute workloads and to build an agile IT roadmap.
Security, Hosting, and Compliance
An aging stack often includes obsolete or unmaintained components, opening the door to critical vulnerabilities. Security updates require extensive testing, sometimes incompatible with the existing architecture.
From a regulatory standpoint, compliance standards tighten every year. Audits demand proof of patch management, encryption, and access traceability. For a legacy system, meeting these requirements often means overprovisioning hosting or adding security layers—driving up cloud and hardware bills.
TCO calculations must therefore include these aspects to reveal an annual operational cost far higher than initial licenses or server charges alone.
Edana: strategic digital partner in Switzerland
We support companies and organizations in their digital transformation
When Modernization Becomes a Profitable Investment
Assessing the real value of legacy software—not based on its historical cost but on its future maintenance expense—shifts the perspective on modernization. A targeted refactor can be two to three times cheaper than the annual cumulative billing.
Diagnostic Phase and Asset Inventory
The first step is to map the application: list critical modules, evaluate test coverage, and identify technical debt. A focused audit highlights the most expensive areas to maintain and the biggest productivity gains.
Based on this diagnosis, components are ranked by business impact and operational risk. This prioritization focuses efforts on the most profitable modernization targets first, ensuring a rapid return on investment.
By producing a quantified inventory, the decision to modernize moves from a vague impression to a fact-based analysis—making modernization a strategic choice rather than a budgetary option.
Progressive Modernization Strategies
Refactoring doesn’t necessarily mean rebuilding from scratch. You can adopt a hybrid approach: extract 30% of the legacy code into a modular architecture while keeping the rest under supervision.
Microservices dedicated to critical features enable modern API integration, continuous deployment, and scalability based on real-world load and enable continuous deployment.
An agile project governance model—built on short sprints and regular demos to business stakeholders—ensures buy-in and continuous priority adjustments, maximizing the business impact of each iteration.
Measurable Gains and Future Outlook
A Swiss manufacturing company modernized 35% of its legacy system in under six months. It reduced its estimated annual TCO by 20%, doubled its capacity to deliver new features, and strengthened its security posture.
This example shows that an investment of CHF 1 million to 1.8 million—about one-third of the historical spend—can turn a technical drag into an innovation driver. Direct savings add to automation capabilities and AI exploitation on finally structured data.
In the long term, the modernized system serves as an evolving foundation, paving the way for new digital initiatives without restarting the technical-debt cycle.
Preparing for Modernization: Trade-Offs and Best Practices
Every modernization project must rest on clear governance, alignment between business units and IT, and context-appropriate technology choices. Contextual expertise always outweighs a one-size-fits-all recipe.
Business and Finance Alignment
Involving finance, business units, and IT from the scoping phase ensures visibility into costs and expected benefits. Building a clear business case grounds the decision in concrete figures rather than intuition.
It’s essential to quantify recurring savings, productivity gains, and reduced operational risks. This trade-off planning helps set priorities and secure multi-year budgets.
A shared roadmap avoids surprises and supports iterative funding, ensuring the project continues after each successful pilot phase.
Contextual Technology Choices
Opting for proven, modular open-source components limits vendor lock-in. Modern, non-blocking, typed frameworks ensure maintainability and high-load performance.
Choosing microservices versus modular monolith and an event-driven architecture offers fine-grained scalability and decoupled responsibilities. Teams retain the flexibility to absorb future business and technological changes.
Every choice should be validated by a proof of concept aligned with a real use case, ensuring the selected solution truly meets the organization’s needs.
Agile Governance and Continuous Steering
Implementing a monthly follow-up process that brings together IT, business stakeholders, and external parties allows you to re-evaluate priorities and adjust the roadmap. This iterative approach prevents budget overruns and delays decisions when necessary.
Integrating dashboards to track technical debt and modernization progress makes it possible to measure advances and demonstrate early benefits.
A culture of technical and business feedback fosters buy-in and ensures each modernization step remains focused on value creation.
Turn Your Legacy Software into an Innovation Lever
The true cost of legacy software is not what it cost to build, but what it costs to maintain and how it holds you back today. By quantifying its hidden charges and planning a phased modernization, you transform this asset into a solid foundation for automation and AI.
Our experts support every step, from diagnostic to CI/CD pipeline industrialization via our Data Pipeline Guide, as well as in choosing architectures and open-source technologies tailored to your context.
