Finance and Operations quote different figures for the same monthly number and both insist they are right. How do you settle it?

Start from the assumption that both are right

The framing you are handed — which number is correct — is nearly always the wrong question, and answering it as asked is how these investigations run for three weeks. Two competent teams counting the same business event rarely have a bug. They have two definitions, each of which is correct for the purpose it was built for, and the disagreement is only visible because both got put on the same slide.

So the question to work on is what question each figure answers. Operations counts what it dispatched, because that drives warehouse and courier decisions. Finance counts what it can recognise as revenue under an accounting policy, which excludes things Operations legitimately counts and applies a different date. Both numbers are needed. Neither is a mistake. Saying this out loud early also de-escalates the meeting, because nobody has to be wrong for you to make progress.

That said, do not assume it: prove it. A genuine defect does occasionally hide in here — a join that duplicates rows, a filter dropping records with a null branch code, a timezone conversion applied twice — and the reconciliation below is what distinguishes the two cases.

Decompose instead of comparing totals

Comparing two monthly figures tells you nothing except that they differ. The technique is to shrink the problem until you can see individual records, along four axes at once.

Narrow the window to a single day, ideally a quiet one. Narrow the population to one branch or one product line. Get both sides to the same grain, which usually means asking each owner for a record listing rather than a total. Then match the two lists on a business key and look at what is in one and not the other. The first divergence you find explains far more than the aggregate difference does, because the same cause repeats thousands of times over a month.

Five causes account for most of these, and it is worth checking each explicitly. Population, where one side includes cancellations, internal transfers, test accounts or zero-value records. Timing, where one uses the event date and the other the posting date, or the month cut-off falls at midnight in different timezones. Filters, where a status list on one side has drifted out of step with the other. Source, where one reads the transactional system and the other a warehouse loaded overnight with a day's lag. And calculation, where currency is converted at a different rate date or a deduplication rule differs.

Publish a bridge, not a verdict

The deliverable that ends the argument is a reconciliation that walks from one figure to the other in named steps. Once the gap is fully explained, the disagreement stops being about trust.

Step	Records
Operations dispatched count for March	12,480
Less orders cancelled after dispatch, excluded by Finance	−402
Less intercompany transfers, not revenue	−173
Less dispatched 31 March, invoiced 1 April	−246
Plus dispatched 28 February, invoiced in March	+190
Finance recognised count for March	11,849

Every line is a business rule somebody can agree or dispute on its own, which is what makes the table useful — a stakeholder who rejects the whole 631-record gap will happily accept or challenge the 173 intercompany transfers. That bridge happens to close exactly, which is the comfortable case. More often it does not, and the aim is then to drive the difference down to a residual you can name and size. Suppose thirty records were left over out of 12,480: that is not a rounding tolerance to be waved away; it is a small pile of specific records, and it is where the actual defect lives if there is one.

Fix the governance or you will be back

Reconciling the month is the easy half. If both reports keep running with both definitions, the same meeting happens in April with different numbers, so the analysis has to end in a decision about definitions rather than about March.

That decision has three parts. One metric gets a written definition — population, date basis, inclusions, exclusions, source, and the calculation — recorded in a glossary that is referenced by the reports themselves. One named person owns it, meaning they approve changes to it and are asked before a new report reuses the name. And the other figure is either retired or explicitly renamed so it stops competing: "dispatched volume" and "recognised order volume" can coexist forever without an argument, whereas two things both called "March orders" cannot.

The failure mode to avoid is settling it by rank. If the number that wins is the one belonging to the more senior stakeholder, the losing team keeps their own spreadsheet, keeps using it to run their part of the business, and you have added a shadow report to the problem you were asked to solve.