The real cost of hunting missing data
A senior analyst on a typical European salary costs around sixty euros an hour fully loaded. If they spend an hour a day chasing missing data in normal weeks and three hours a day during the four close weeks of the year, that is 300 hours, or about 18,000 euros, from one person.
| Period | Hours per day | Working days | Hours |
|---|---|---|---|
| Normal weeks | 1 | 240 | 240 |
| Close weeks | 3 | 20 | 60 |
| Total | 300 |
Multiply across a finance team of four. Add a controller signing adjustments. Add the IT person who keeps getting pulled in to explain why the ETL failed last night. A mid-sized company tends to land somewhere between 80,000 and 150,000 euros a year on this, with no line on any budget calling it out.
Estimate the cost for your team
Adjust the sliders. Numbers update as you type. Defaults are rough averages, not a recommendation.
Reduction percentage varies by team. We have seen anywhere from 40% to 80% depending on how much of the work was repeat hunting versus genuinely new mapping decisions. Treat this as a rough order of magnitude, not a quote.
The work itself is detective work without a closed case. The codes that broke this month will break next month, in a different way, and the analyst has no way to fix the underlying cause. It exhausts people first and then loses them.
The cost concentrates at three boundaries.
Between systems. The ERP knows your customers as one set of codes, the CRM as another, the reporting layer joins on a third. Any incomplete mapping does not disappear. It shows up as a blank line in a report, or a total that does not match, and somebody has to chase it. The chase costs more than the original mapping would have.
Between time periods. A code is added in week one of the quarter but the mapping table refreshes in week three. Transactions in those two weeks are unmapped. Nobody notices until quarterly review, when the number is wrong by exactly the new product line. Patching it backwards is several times the work of maintaining it correctly.
Between departments. Marketing renames a campaign. Finance still has the old name in their attribution map. Reporting picks one, and the two reports disagree. The argument that follows is not about data. It is about whose version is canonical, and that is the most expensive conversation in the building.
A real registry does not eliminate the work. New codes still appear, mappings still need review. What changes is the feedback loop. An unmapped value becomes a notification, not a discovery in a report two weeks later. Each list has a named owner who gets pinged when something is missing. The fix takes seconds because the access path and the editing path are the same.
Teams that have made this move typically cut close periods by three to five days. Not because anyone got faster at typing. Because nobody was hunting anymore.
If your team spends more time finding data than analysing it, the registry pays back in months. The exact payback depends on which boundary above hurts most.