The system your business runs on was probably built for a different version of your business. It has never been fully documented. The person who understood it best left three years ago. Every change takes three times as long as it should and introduces a bug you won't find for six months. This is not technical debt. It is operational risk with a ticking clock.
What it actually costs
Finance teams budget for visible legacy costs: licencing, support contracts, the occasional consultant. What doesn't make the budget: the developer time spent understanding a system before being able to change it — typically 60 to 70% of every ticket on a legacy codebase. The business opportunities declined because the system can't support the feature. The compliance exposure when the system can't produce the audit trail the regulator wants. And the bus factor: the number of people whose departure would create a genuine operational crisis. On most legacy systems, that number is one.
Why big-bang rewrites fail
The failure modes are well documented: scope creep driven by discovered complexity, underestimation of the undocumented business logic built into the old system over years of patches, the difficulty of rebuilding a system while the business continues running on it, and the collapse of stakeholder confidence when delivery slips. 70% of major IT rewrites fail to deliver on their original scope, timeline, and budget. The ones that succeed generally look less like replacement and more like transplant.
The parallel migration method
Build the new system beside the old one. Run both. Prove the new system against live production data in shadow mode — processing every real transaction, comparing outputs to the legacy system — before moving any traffic. Cut over when the data says it's ready: when the new system agrees with the legacy on 99.5% of transactions and outperforms it on the metrics that matter. Then retire the old system with the confidence of evidence, not the optimism of a delivery timeline.
The method
How we structure a parallel migration
Phase 1 (weeks 1–4): Build the new system's core data model and primary workflows independently. Both systems run. Phase 2 (weeks 4–8): Shadow mode. The new system processes every production transaction. We compare outputs. Phase 3 (weeks 8–12): Cutover. New system becomes primary. Legacy runs as read-only fallback for 30 days, then is retired. Production risk at cutover: near zero.
When to act
Three signals that your system has crossed from technical debt into operational liability. First: a change that should take a week consistently takes a month. Second: you cannot answer basic compliance or data questions without manual investigation. Third: your best engineers spend more time understanding the system than improving it. If two of those three are true today, you are living inside the liability, not managing it from the outside.
The board conversation
How to frame the risk to leadership
'Our core system was built in [year]. [X] years of changes have accumulated, most undocumented. We currently cannot [specific capability]. The risk of a forced migration — triggered by a compliance event, a key departure, or vendor end-of-life — is [specific scenario with cost estimate]. A planned parallel migration costs [range]. An unplanned one historically costs three to five times more.' We can help you build that conversation.