Skip to main content
Bonsai Software
All field notes
Our approach31 July 20268 min read

Redeveloping software: when it pays off and when it doesn't

Software redevelopment is the right choice when the existing system is fundamentally no longer usable or adaptable, but in most cases that is not the situation. Many organisations consider a full rebuild while the real problem is far smaller: a missing integration, a process that keeps breaking down, or manual data entry consuming too much time. Those problems call for a different conversation than "let's throw it out and start over."

By Yeslin Beljaars

Why the reflex to redevelop is understandable but rarely correct

A system that creaks, causes delays, or no longer fits current ways of working: the urge to throw it out and start again comes quickly. That is understandable. But the reason a system breaks down is almost never the code itself. It is the point where two systems do not communicate, a process that was never properly defined, or data that is defined differently in multiple places. If those problems are not resolved before redevelopment begins, they will simply be built in again. The result is a new system with the same flaws.

When is software redevelopment the right choice?

There are situations where redevelopment is the most honest option. That is the case when technical debt has accumulated to the point where every change breaks more than it fixes. Or when the vendor of the existing system is gone, the licence is expiring, and no viable migration path exists. Also when the system was never properly built around the organisation's actual processes and that cannot be corrected structurally without rewriting everything. In those cases, continuing is a sustained drain on resources. But even then, it is rarely the entire system that needs to be rebuilt at once. Almost always it is a specific module, an integration, or a subprocess that needs redoing, not the complete landscape.

Which signs tell you that redevelopment pays off?

Redevelopment pays off when the system steers the workflow instead of supporting it. That is easy to recognise: people adapt the way they work to the system rather than the other way round. They export data to Excel to be able to use it, keep a shadow administration because the system does not show information in the right place, or wait for reports that arrive too late. The blockages are often not in the complex steps but in simple hand-offs: an order is ready but the next department does not know, or a document has been approved while the system still shows 'in progress' because the status has to be updated by hand. At a hundred orders a day, those small hitches add up.

When is redevelopment the wrong answer to the right problem?

The most common situation: a system does its job, but slowly, cumbersomely, or with too much manual work in between. People export lists to Excel, copy and paste information from one system to another, or wait on approvals that circulate by email. That is not a reason to replace the core system. It is a reason to build targeted automation that eliminates the manual steps and moves data to the right place automatically. An AI Workers approach around an existing ERP, TMS, or WMS resolves this faster and cheaper, with less risk. You only discard what works when it is genuinely no longer usable.

What are the hidden costs of a full rebuild?

Redevelopment almost always takes longer than the initial estimate. Not because builders are slow, but because knowledge of the old system is never fully documented. Halfway through, you discover edge cases, client-specific agreements, and manual corrections that appear nowhere in a specification but are needed every single day. Meanwhile, operations do not stand still. You are building a new system while people continue working in the old one, with all the double entry and synchronisation problems that brings. That is justifiable when it is truly necessary. But when it is not, you pay a high price for a problem that could have been solved with a narrower approach.

How do you choose between rebuilding and an AI Workers approach?

Ask yourself this question: does the problem resolve itself if data reaches the right place and the manual steps in between are removed? If the answer is yes, redevelopment is almost certainly too heavy an intervention. An AI Workers approach or targeted document processing is the better option. If the answer is no, because the system is genuinely no longer adaptable, no longer supported, or structurally contains the wrong logic, then rebuilding is worth discussing. But start small: rebuild the most critical subprocess, bring it into production, and learn from that process before scaling further. Rebuilding everything in one go is almost always a mistake, even when you have a good reason to start.

Rebuilding custom or choosing a standard package: is there a third option?

Yes. When an organisation chooses to redevelop, that does not have to mean falling back on a generic standard package. The choice is not binary. A custom-built core system designed from the ground up around the organisation's own processes, with AI built in rather than added as a separate layer around it, is a realistic option. This delivers a system that genuinely follows operations, without the compromises of a package built for a hundred sectors at once. It does require a structured approach: clear milestones, go/no-go decision points, and ownership of code and data with the client. That is how you avoid trading one vendor dependency for another.

Why start with the real workflow, not the code?

Every company has a documented process and a real process, and the two drift apart. The real process lives in the heads of the people who work with it every day: which fields they ignore, which workarounds they use, which links to outside parties appear on no diagram at all. Redevelop without bringing that to the surface and you rebuild the inefficiency, just more neatly. So always plan a discovery phase before you build: talk to the users, not only the managers, and have them show their actions screen by screen. Do not ask what goes wrong; ask what people do when the system does not give them what they need. After that phase, a go/no-go moment tests whether the picture is right and whether building is the right next step.

Seeing this in your own operations?

Book a call

Frequently asked questions

When should you actually redevelop software?

When technical debt is so high that every change breaks more than it fixes, when the vendor disappears without a migration path, or when the system is structurally built on the wrong process logic. In all other cases, a targeted adjustment or AI layer is almost always the more sensible choice.

What is the difference between redeveloping software and building an AI layer?

Redevelopment means rebuilding the core system from the ground up. An AI layer or Workers approach leaves the existing system intact and removes the manual work in between: retrieving data, processing it, and placing it in the right location. The second option is faster and cheaper when the core system itself is still functional.

How long does software redevelopment typically take?

It varies considerably by scope, but in practice it almost always takes longer than the initial estimate. The main reason is that knowledge of the old system is incompletely documented. Edge cases and manual corrections only surface halfway through. A phased approach with go/no-go decision points per subprocess limits this risk.

Is building custom more expensive than a standard package when redeveloping?

In the short term, often yes, but total costs over multiple years are by no means always higher. Standard packages bring licence costs, customisation costs, and an ongoing dependency on the vendor. Custom software owned by the client does not carry those recurring costs. The trade-off depends on the complexity of the processes and how far they deviate from what a standard package supports.

Which signs show that a system needs to be redeveloped?

When people adapt the way they work to the system rather than the other way round, and workarounds such as shadow administrations and Excel exports have become the norm. The system is then steering the operation instead of supporting it, and a system that follows the real workflow pays off straight away.