What is data migration, and why do so many projects go wrong?
Key points
- Data migration means moving data between systems while keeping it accurate and usable.
- Most failures come from poor planning, unclear scope, or the client not knowing their own data well enough.
- At least 80% of data issues stem from missing or poor client data, not the migration itself.
- Success means going live with the data that matters, correctly placed and working as intended.
George Tye
CEO & Founder
The Data Migration Trap
Data migration usually gets one line on a project plan, then quietly becomes the reason the go-live date slips. On paper it looks simple: move the data from the old system to the new one.
In practice, it’s where all the assumptions about “the data” meet what’s actually sitting in the source system.
This article covers what data migration actually involves, why projects run into trouble, and what a good migration looks like when it goes right.
What is Data Migration?
Data migration is the process of moving data from one system to another, usually as part of a platform change or system upgrade. The data needs to come out cleanly, get mapped to fit the new system, and go back in a state people can actually trust and use. It’s rarely a straight copy job.
Migration types:
| Migration type | What it involves |
|---|---|
| System-to-system | Moving data from a legacy platform into a new CRM or line-of-business system |
| Consolidation | Merging data from multiple sources into one system, often after a merger or acquisition |
| Cloud migration | Moving on-premise data into a cloud platform such as Salesforce |
| Upgrade migration | Moving data between versions of the same platform, often with structural changes |
Why do so many data migration projects go wrong?
These are the reasons we see most often on real projects, not the generic list you’d find in a textbook.
Poor Planning
Data migration is often treated as an afterthought rather than a core part of the project. Timelines get built around the main system implementation first, and migration gets squeezed into whatever time is left. By the time the gap shows up, there’s no room to fix it properly.
Clients not understanding their own data
Every migration needs someone on the client side who understands the data and can make decisions about it. Without that person, decisions stall or fall to the wrong people, and problems that should have been caught early get missed.
No agreement on scope
Scope changes are common, and they tend to land later than they should. New data sources, extra fields, “can we also bring across…” requests. Without a clear scope agreed from the start, these push out timelines and cause problems elsewhere.
At least 80% of data-related issues we see come down to missing or inadequate client data, not technical problems with the migration itself. This is almost always resolved through a proper Data Quality Review (DQR).
What does a successful migration actually look like?
Going live with all the data the client sees value in, sitting in the right place, and working in the new system as intended. It’s not about moving every record from the old system, it’s about moving what matters, in a state the client can trust.
In practice, that means:
- The data people actually use day to day is present and easy to find, not buried or missing.
- Records map cleanly to the new system’s structure, so nothing looks wrong or out of place once the team starts using it.
- Known gaps or issues have been flagged and dealt with before go-live, not discovered after.
- The client has been involved in the key decisions along the way, so there are no surprises when they log in for the first time.
A migration can move every single record from the old system and still fail, if the data doesn’t behave the way people expect once it’s live. Equally, a migration can deliberately leave some historic or low-value data behind and still be a complete success, as long as that was a decision made on purpose rather than something that just happened.
How our approach prevents the most common failures
From the start, we ask the questions that actually matter: what data matters to the client, where the data can be improved if needed, and where the gaps are between the source and target systems. We involve the client throughout, because it’s their data.
If you’re moving to Salesforce specifically, this approach sits behind everything we do on that platform. Learn more about our Salesforce Data Migration service
Frequently Asked Questions
What is data migration?
Moving data from one system to another, for example from a legacy platform to a new CRM, while keeping it accurate and usable once it’s in the new system.
Why do data migration projects fail?
Usually poor planning, the client not understanding their own data well enough, testing happening too late, or scope changing without proper agreement.
What is a Data Quality Review (DQR)?
The process of finding and fixing issues in the source data before or during migration. It’s how most data-related issues get resolved.
What does a successful data migration look like?
Going live with the data the client values, correctly placed and working as intended, rather than simply moving everything from the old system regardless of whether it’s still needed.
How can I reduce the risk of my migration failing?
Plan the migration alongside the wider project from day one, agree scope early, involve someone who understands the data, and leave real time for testing before go-live.
Do you handle data migration into Salesforce?
Yes, it’s one of our core areas of work. More on our Salesforce Data Migration page.
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