In almost every organisation, someone sits between two systems. Orders from the webshop get typed into the accounts package by hand, customer details get copied across via an Excel export, and every Monday morning someone retypes last week’s figures into a report. Each instance looks trivial: a quarter of an hour here, half an hour there.
Because the work arrives in such small portions, nobody adds it up. The cost of copying data by hand has three layers: the hours themselves, the errors that inevitably come with them, and everything that doesn’t get done while your people are busy retyping. Only the first layer is visible.
The hours are the visible part
Work it out for your own situation. Someone who spends half an hour every working day moving data across ends up above a hundred hours a year: almost three full working weeks spent moving information that already exists somewhere. If three colleagues do similar work, you’re talking about months of labour time. And those hours cost more than gross salary alone; employer costs and workplace overheads count too.
Errors make the bill unpredictable
Retyping goes wrong sooner or later, however carefully someone works. The awkward part isn’t the typo itself but the moment it surfaces: the invoice that doesn’t add up, the delivery sent to an old address, stock levels that don’t match the webshop. Fixing it then costs a multiple of the original input time, because you have to trace where it went wrong and correct it in every system the error has since reached. You can read how these errors arise and spread in our article on errors in manual data transfer between systems.
The biggest cost never appears on an invoice
The most expensive consequences are the things that don’t happen. Hours spent on copying don’t go to customers, sales or improvement. Reports are only current once someone has updated them, so decisions wait, or rely on last week’s figures. And growth makes this challenge bigger rather than smaller: more orders means more retyping, until you take someone on for work an integration could have done.
Four steps to a concrete figure
You don’t need external research to work this out for yourself. Measuring for a week is enough:
- Have everyone who moves data across track how much time it takes over a week, and scale that up to a year.
- Multiply those hours by the fully loaded hourly rate: salary plus employer costs and overheads.
- Add in the fixing work from the past quarter, including the time spent tracing errors and handling complaints.
- Estimate what those same hours would have delivered if they’d gone to customers or improvement instead; that’s usually the biggest item.
Put the outcome next to the cost of an integration and the conversation changes character: from something the team quietly does on the side to an ordinary business case.
An integration turns a recurring cost into a one-off investment
The alternative is to remove the manual step: an integration that lets your systems exchange data directly, through the APIs most modern packages already offer. An order that comes in through the webshop then lands in the accounts without anyone touching it, in the right format and without a typo. The work that currently comes back every week is done for good.
It’s also fair to say that not every bit of copying justifies an integration. If it’s a few minutes a month, leave it as it is. But once retyping is a fixed part of someone’s week, an integration usually pays for itself many times over. We build data integrations for organisations that want their systems to work together instead of their people retyping between them. Tell us about your situation and we’ll work out together whether it’s worth it.