PIPELINEGuide
Is data migration worth it for small businesses?
Not every business needs data migration. When it pays off, when it doesn't, and how to calculate that beforehand instead of finding out afterwards.
Whether data migration is worth it comes down to a simple calculation: how often a process occurs, how long it takes and what an hour costs at your business. Only when these numbers are available can you seriously say whether it pays off — we check this before every quote.
01 — Fit
When it's worth it
- The process in question occurs at least weekly.
- It follows rules you can write down — even if there are exceptions.
- Today it's manual work that no one enjoys doing.
- There's one person who decides, not three who need to coordinate.
- You can name what would tell you it worked.
02 — Boundaries
When we advise against it
- The process is still changing. As long as you're adjusting the process itself, manual work is more flexible and cheaper.
- Exceptions outweigh standard cases. Then you're automating exceptions, and that gets expensive.
- There's no data foundation. Without digitally available source data, the basis is missing.
- Volume is too low. With five transactions a month, no system pays off — not even an affordable one.
- The real bottleneck lies elsewhere. If you don't have enough inquiries, you don't need faster processing.
03 — Calculation
How to calculate it
Four numbers are enough: How often does the process occur? How long does it take? What does an hour cost internally? And what does the solution cost — one-time plus operation over three years?
An example: A process that occurs twice a week and takes 40 minutes each time ties up around 69 hours per year. At an internal hourly rate of 45 euros, that's roughly 3,100 euros per year locked in there. If a solution reduces this effort by two-thirds, it often pays for itself — depending on the actual quote — within one to two years. We'll give you the exact figure for your case after the initial meeting.
This calculation is deliberately conservative: it only accounts for the time saved, not the errors avoided or the orders that come through due to faster response. In practice, the benefit is usually higher — but you shouldn't count on it before you've measured it.
04 — Classification
What experience shows
The effort of migration lies almost entirely in data quality — not in transferring.
05 — Questions
Frequently asked questions
What happens to attachments and documents on the record?
They are transferred along, provided the target system supports them. Where the format doesn't fit, it's clarified beforehand whether conversion is necessary or external storage remains more practical.
What if something is missing after the switchover?
That's why count protocol and fallback option: the legacy inventory remains untouched until acceptance is complete. Subsequent additions of individual areas are possible.
How do we ensure nothing gets lost?
Through the count protocol: number of records before and after is compared, samples are checked for content. Only after this acceptance is the migration considered complete.
Can we keep working in parallel?
For short transitions yes, with a cutoff date. For longer migrations, you typically continue working in the legacy system until the switchover and transfer the additions at the end.
How long does a migration take?
The transfer itself usually hours. The time goes into analysis, rules, and trial runs — typically two to six weeks, depending on the condition of the legacy data.
Do we need access to both systems simultaneously for the migration?
Yes, at least for the period of trial runs and the actual switchover. After that, access to the legacy system can be restricted or terminated.
Do we take everything?
Rarely makes sense. Dead records, test datasets, and ten-year-old transactions burden the new system. We recommend migrating the active inventory and keeping the rest archived and accessible.
06 — Next
Related pages
- Data Migration — Overview
- Data migration — alternatives
- Data migration — practical examples
- Data Migration — Common Mistakes
- Data migration — pros and cons
- Data Migration — Provider Comparison
- Data Migration — Data Protection
- Data migration — introduction
- CRM integration
- Custom software
- API Interfaces
- All guides
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