Why do data migration projects fail?

On paper, data migration sounds simple: Move data from the legacy system to the target system. Test it. Go live. Done.

In reality, data migration is one of the most complex, high-risk parts of any digital transformation programme. It’s where strategy runs into legacy systems, assumptions get tested (and aren't always correct!), and small mistakes quietly turn into big problems at go-live.

If you’ve ever wondered why data migration feels harder than it should be, the short answer is this: It’s rarely a technical problem.

It’s a people, planning, and decision-making problem, with technology caught in the middle!

Let’s break down why data migration is so hard, and what successful projects do differently.

Data migration isn’t just technical work.

One of the biggest misconceptions about data migration is that it’s purely an IT task. Something that happens “behind the scenes” once the new system is chosen.

In practice, data migration sits at the intersection of:

• Business processes

• Data quality

• Organisational culture

• Governance and decision-making

• Technology

Every data field represents a business decision that was made at some point in the past. Often, many years ago. Sometimes by people who are no longer in the organisation.

When you migrate data, you’re not just shifting records from one system to another. You’re dealing with inconsistent definitions, years of built-up workarounds, unclear ownership, and data that doesn’t quite agree with itself. These things don’t usually look like big problems at first but they add up fast and often end up driving some of the biggest decisions in the project.

That’s why data migration projects give issues that teams didn’t even realise existed. If migration is treated as a late-stage technical task, these issues emerge far too late - usually during testing, or worse, after go-live.

The power of planning.

Data migration rewards preparation. Projects that struggle almost always rush past the planning phase in favour of getting started.

What does a strong data migration plan look like?

• Understanding what data actually exists -

  You'd be surprised how much data still exists on spreadsheets, in drawers and on different databases the CIO never knew existed!

  
  

• Agreeing on what should move, not just what can move -

  Just because data can be migrated doesn’t mean it should be. A strong plan forces the hard conversations early: what still delivers value, what’s legally required, and what can finally be left behind.

  
  

• Defining ownership for decisions and sign-off -

  Data issues don’t resolve themselves. Strong migration plans make ownership explicit, who decides, who signs off, and who takes accountability when trade-offs are needed.

  
  

• Aligning migration timelines with business readiness -

  You can have the cleanest data in the world, but if the business isn’t ready to validate, test, or change processes, migration will stall.

  
  

Skipping this work doesn’t save time. It simply defers risk. And deferred risk tends to show up at the worst possible moment. At binary10, planning isn’t treated as overhead; it’s treated as risk reduction.

Why are no two data migration Projects ever the same?

Templates are useful. Assumptions are dangerous.

One of the most common reasons data migration fails is the belief that we did this last time or that this worked for another company.

Every migration is shaped by:

• The legacy systems involved

• The quality and consistency of legacy data

• The organisation’s operating model

• Regulatory requirements

• Internal capability and resourcing

Successful teams reuse methodology, not shortcuts.

People and culture shape delivery.

• Who owns the data?

Data migration quickly exposes whether ownership is clear or assumed. When no one truly owns the data, decisions can't be made, or even, issues don't get resolved.

• Who can make decisions?

Migration surfaces how empowered teams really are. If every decision needs multiple layers of approval, even small data issues can turn into major delays.

• How comfortable are teams with change?

Moving data means changing processes, reports, and ways of working. Teams that struggle with change often cling to legacy structures, even when they no longer make sense.

• How willing are people to challenge “how it’s always been done”?

Legacy data is full of historical choices that no one remembers making. Strong migrations happen when teams are willing to question old rules instead of blindly carrying them forward.

These cultural factors have a direct impact on migration outcomes.

For example:

↳ If data ownership is unclear, decisions stall.

↳ If teams are afraid to flag issues, problems stay hidden.

↳ If leadership treats migration as a checkbox, corners get cut.

The technical challenges are solvable. The cultural ones require trust, communication, and leadership support.

So, we have noticed a pattern in successful projects.

• Clear accountability

Successful projects make it obvious who owns decisions, data quality, and sign-off. When accountability is clear, issues get resolved quickly instead of circling endlessly in meetings.

• Psychological safety for raising concerns

The best migrations are the ones where people feel safe flagging problems early. When teams can say “this doesn’t look right” without fear, risks surface sooner, while there’s still time to fix them.

• Understanding of why migration quality matters

When everyone understands the downstream impact of poor data - on payroll, reporting, compliance, and trust, quality stops being just a data problem and becomes a business priority.

Without these, even the best technical solution will struggle.

Communication gaps that can mess up a go-live.

Most data migration failures aren’t caused by a single big mistake. They’re caused by dozens of small misunderstandings that compound over time.

Common communication gaps mean:

• Business teams assuming IT is handling data decisions

• IT assuming the business has validated requirements

• System integrators focusing on build, not data readiness

• Migration risks being under-communicated to senior stakeholders

Strong migration teams communicate well, especially when things are uncomfortable.

Why do you need data migration specialists from day one?

Bringing data migration specialists in late is going to be expensive.

When migration expertise is missing early on:

• Data requirements are poorly defined

• System design decisions create migration complexity

• Testing cycles become longer and more painful

• Fixes are reactive, not preventative

However, involving data migration specialists from the start makes a real difference. It allows system design to be shaped around real data constraints, risks to be identified early — before they turn into blockers — and rework and late-stage surprises to be avoided. The result is a smoother programme overall, with timelines and budgets far better protected.

Migration done well saves time, money, and stress, especially during the most critical phase of a programme.

Data migration doesn't have to be painful.

Data migration will probably never be easy. But it doesn’t have to be painful.

The ultimate points you need to remember are:

• Planning before pressure

• Experience over assumptions

• Communication over confidence

• People over processes

This article is based on one of our podcast episodes.

If you’d like to hear the full conversation, you can listen to Episode 2 of the Data Migration Podcast here: LINK