IT Legacy in Practice
From crown jewel to millstone
Many systems that are technically outdated are still in use. Often at high cost, with significant risks and mounting frustration. And yet, few dare to let go. What if the replacement fails? What if critical knowledge is lost? And how do you build a business case for a replacement that offers little to no functional gain?
That’s precisely what makes legacy one of the most persistent challenges in the boardroom. The good news: there is a way forward for existing and potentially future legacy. But it requires courage, patience and a clear roadmap. Here’s a starting point.
Be critical of
the devil you know
It’s tempting to stick with what you know. The systems may be clunky and outdated, but they work. Everyone knows where the buttons are and what the limitations are. It feels safe. But that safety is deceptive. Risks are growing: security vulnerabilities that can no longer be patched, escalating licence costs, and specialists heading into retirement. The longer you wait, the more exposed you become.
A common pitfall is the sunk cost fallacy: the tendency to defend past investments. Millions may have been poured into the system, so letting go feels like throwing away value. But those costs are already sunk and won’t come back. Holding on often leads organisations to migrate everything one-to-one—including redundant features, outdated processes and design flaws. The result? An expensive replica of the past, wrapped in modern technology—functional legacy.
Make it tangible: map out what it costs to keep your legacy running: in money, risk and missed opportunities. Then ask: what do we truly need to move our organisation forward? Often, that’s when it becomes clear that “just keeping things going” is more costly and dangerous than renewal.
The type of legacy determines its impact on operations. A legacy ERP system or outdated database, for instance, has far greater business implications than obsolete support software. Something to keep in mind.
Kill your
darlings
This may be the hardest lesson. Every organisation has features or processes that were once valuable but now mainly get in the way.
You’ll often hear: “We’ve always done it this way.” Or: “We’ve used that functionality for twenty years, it has to stay.” Many organisations don’t even realise they’re dealing with legacy. The system seems to work fine, while processes are inefficient and risks only surface when no one knows how the system actually functions. Many of these darlings are best left behind. The more you carry over to a new system, the more complex, costly and risky your migration becomes.
Talk to end users. Ask what they need and actually use. You’ll be surprised how much is redundant. See migration as an opportunity to clean up your data, your processes and your application landscape.
Building the future,
step by step
A big bang migration may sound appealing (“done in one go!”), but in practice it’s rarely feasible. The risks are enormous, and the shop needs to stay open in the meantime.
A smarter approach: take it step by step. Use the strangler pattern: build new functionality alongside the old system and gradually shift more processes over. This way, you stay in control and can adjust course when needed.
Different
by design
The biggest mistake you can make is building new legacy. And it happens faster than you think. Without clear choices, you end up with custom solutions, dependencies and technical debt all over again.
Be explicit in your design principles and architectural decisions. Decide which systems to buy, what to build in-house, and how to standardise technology and data integration. Document, safeguard and periodically review all decisions. And always start with the end in mind: how long do we want this system to run? And how do we ensure it remains flexible and valuable over that period?
Different:
functionality over technology
A classic approach to legacy is technical: take the existing code and translate it line by line into a modern language or platform. It seems logical and safe, but in practice you end up with a one-to-one copy of the old system. The only thing that changes is the underlying technology. For the organisation, it often feels like “high cost, low gain”.
At Conclusion, we take a different approach. And that starts with functionality. What does the system actually do today? Which processes does it support, which features are essential, and which are barely used? These insights come from technical analysis—such as observability data—but also from user interviews and direct observation. AI helps us understand the vast amount of logic and data in old systems more quickly, by analysing screens, tests, documentation and designs. We use these functional insights to generate new system components.
This functional analysis is a relatively new approach, supported by AI. The result is a clearly defined set of core functionalities that form the basis for rebuilding. It’s a logical step—and thanks to AI, it’s now realistic and achievable.
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