Enterprise software that has grown over years or even decades fulfills its purpose – often surprisingly reliably. Production processes are controlled, data flows, workflows function. But behind this apparent stability lies a growing cost block that rarely appears transparently on the invoice. Technical debt, increasing maintenance efforts, dependency on individual knowledge carriers, and ever-longer development cycles make legacy systems one of the biggest underestimated cost factors in the company.

Those who honestly account for the total costs often come to a clear conclusion: A targeted modernization is not only cheaper than permanent continued operation – it is the prerequisite for remaining capable of action at all.

What exactly makes software "Legacy Software"?

The term legacy software describes applications that are based on outdated technologies, frameworks, or architectures but are still used productively. Typical characteristics are:

  • Outdated technology stack: Older programming languages, frameworks without active support, or proprietary runtime environments for which there are hardly any specialists left.
  • Grown architecture without clear structure: Over the years, features were added, interfaces adjusted, and workarounds built in – without an overarching architectural concept.
  • Missing or incomplete documentation: Business logic is in the code, not in comprehensible documents. New team members face a black box.
  • Monolithic structure: Individual modules are so tightly interwoven that a change in one place can have unpredictable effects in another.

Such systems are not bad per se. At the time of their creation, they were often the best possible solution. But technologies evolve, requirements change – and what was once forward-looking becomes a bottleneck.

The hidden costs: Why "it still works" is deceptive

The obvious costs of software – license fees, hosting, occasional bug fixes – are just the tip of the iceberg. The real cost drivers of legacy systems are more subtle, but significantly more serious in total.

Onboarding effort and knowledge loss

The older and more complex an application, the longer it takes new developers to get acquainted. With grown systems of hundreds of thousands or even millions of lines of code, several hundred hours of onboarding time is not uncommon – before any productive work can be done at all.

The problem is exacerbated when key knowledge carriers leave the company. If knowledge about business logic, data structures, and historical decisions is not documented, it is irretrievably lost. The costs of rebuilding this knowledge often exceed any estimate.

Technical debt as silent compound interest

Technical debt arises when pragmatic decisions – quick fixes, postponed refactorings, missing tests – accumulate over years. Each of these decisions may have been understandable at the time. But in total, they lead to:

  • Every change takes longer because side effects must be checked manually,
  • The error rate increases because automated tests are missing or no longer work,
  • Innovations are blocked because the architecture simply doesn't support new requirements.

Studies quantify the share of technical debt in the total costs of IT portfolios at up to 40 percent. For legacy systems, this share is empirically significantly higher.

Rising risk and compliance costs

Outdated technologies eventually no longer receive security updates. Operating such systems becomes a calculated risk – with increasing costs for protection, monitoring, and emergency measures. At the same time, regulatory requirements are growing: data protection, IT security standards, and industry-specific compliance requirements demand technical measures that can only be implemented on outdated platforms with disproportionately high effort.

Opportunity costs: What doesn't happen

Perhaps the biggest cost factor is invisible: Every hour spent maintaining a legacy system is missing for innovation. New business models, improved customer experiences, more efficient processes, or the integration of modern technologies like AI-supported automation – all of this moves into the distant future when the development team is primarily occupied with keeping the status quo running.

What modernization really costs – and what it saves

A common misconception is: "A new development costs at least as much as the previous total investment." This is usually not true. Because with modernization, you don't start from zero. Business logic, proven processes, and existing expertise form a solid foundation to build on.

Why modernization is cheaper than expected

Typically, the productive core functions of a grown application make up only about 20 to 35 percent of the total code. The rest consists of historical baggage: features no longer used, redundant logic, outdated integrations, and workarounds. A thorough analysis separates the valuable from the superfluous – and significantly reduces the actual modernization scope.

In addition, there are efficiency gains through modern development tools, frameworks, and methods. What took weeks ten or twenty years ago can be implemented in a fraction of the time with current technologies and proven architectural patterns. With a conservative estimate, the modernization budget is often one-third to half of the historical total investment – including safety reserves.

Comparison: Continued operation vs. modernization

Dimension Continued Legacy System Operation After Modernization
Maintenance costs Increasing, difficult to plan Significantly reduced, plannable
Change speed Weeks to months per feature Days to a few weeks
Error rate High, difficult to trace Low through automated tests
Knowledge distribution Dependent on individuals Documented, team-capable
Security level Declining, difficult to secure Current, patchable
Scalability Severely limited Modularly expandable
Innovation capability Blocked Open to AI, APIs, new channels

Modernize step by step instead of replacing everything at once

One of the most common mistakes in software modernization projects is the so-called big-bang approach: shut down everything, rebuild everything, introduce everything simultaneously. This approach carries enormous risks – from data loss to operational disruptions to overwhelming everyone involved.

We at mindtwo therefore rely on a modular, phased approach that ensures operational continuity while delivering measurable progress.

Phase 1: Analysis and inventory

Before a single line of code is written, there is a thorough analysis. Code quality, architecture, data structures, interfaces, and especially the business logic of the existing application are recorded. The goal is to gain a clear picture:

  • Which functions are business-critical and must be retained?
  • Which areas are technically particularly fragile?
  • Where are the greatest efficiency potentials?
  • Which external systems and interfaces must be considered?

This phase creates the foundation for a realistic effort estimate and comprehensible prioritization.

Phase 2: Stabilization of the existing system

Parallel to planning the modernization, the existing system is stabilized. Monitoring is set up or improved, critical error sources are fixed, backup strategies are reviewed. The goal: Secure ongoing operations while modernization is being prepared.

Phase 3: Module-by-module renewal

The actual modernization takes place in clearly defined stages. Individual modules or functional areas are successively transferred to a modern architecture – with a clean API layer, automated tests, and documented code. Old and new system parts run in parallel during the transition phase, so that business operations are never endangered.

Phase 4: Operation, monitoring, and further development

After the rollout of individual modules, the phase of continuous improvement begins. Performance monitoring, regular updates, and planned further development ensure that the system doesn't fall into the trap of technical debt again. Professional maintenance and care is not a downstream topic, but an integral part of the operating model from the start.

What matters in technology selection

Modernization is always also a technology decision. It's not about following the latest trend, but about creating a future-proof, maintainable, and scalable foundation. From our experience, the following principles are crucial:

  • Modular architecture: Individual system components must be able to be developed, tested, and deployed independently of each other. This reduces complexity and accelerates release cycles.
  • API-first approach: Clean interfaces enable integration with third-party systems, mobile applications, or future AI services – without having to touch the core system.
  • Established frameworks with active community: Technologies like Laravel or comparable, proven frameworks provide a solid foundation with long-term support, extensive documentation, and a large talent pool.
  • Automation from the start: CI/CD pipelines, automated tests, and infrastructure-as-code are not optional extras, but the foundation for sustainable operation.
  • Clear data architecture: A well-thought-out database structure with a clean data model is the basis for reporting, evaluations, and in the future also for AI-supported analyses.

When is the right time for modernization?

The question "When should we modernize?" can often be answered more precisely than expected. Clear indicators that speak for imminent modernization are:

  • Maintenance costs exceed 15–20% of the original development value per year – and the trend is rising.
  • Release cycles are getting longer and longer: What used to be done in days now takes weeks or months.
  • Frequent, difficult-to-trace errors after actually small changes.
  • Key persons are about to leave – and their knowledge is not documented.
  • New business requirements (integration of partner systems, new digital services, automation) cannot be implemented with the existing system or only with disproportionate effort.
  • Security or compliance requirements can no longer be met with current technology.

If even just some of these points apply, a structured assessment of the current state is worthwhile – before the pressure to act becomes so great that there is no more time for a well-considered approach.

Modernization as investment, not as cost factor

The crucial change of perspective in software modernization is this: It's not about spending money to repair something that supposedly still works. It's about transforming a growing, difficult-to-control cost block into a controllable investment asset.

Companies that take this step benefit on multiple levels:

  • Plannable budgets instead of unpredictable maintenance costs
  • Faster market response through shorter development cycles
  • Lower personnel risk through documented, team-capable code
  • Higher security through current technologies and regular updates
  • Innovation capability as the foundation for new digital services, process automation, and AI integration

How we approach modernization projects at mindtwo

We accompany companies from different industries – from industry to healthcare to media and retail – in modernizing business-critical applications. Our approach combines strategic consulting with sound technical implementation: from the first analysis through architecture conception and UX design to productive operation.

In doing so, we don't think in projects that are "finished" at some point, but in high-performance web applications that grow with a company's requirements. Modularly built, cleanly documented, and designed so that further development is not a struggle but part of normal operations.

Those who want to take the first step should start with an honest inventory. What does the existing system really cost – not just in direct expenses, but in speed, flexibility, and risk? The answer to this question is often the most convincing business case for modernization.