You ask your ops lead for last month's revenue number. She sends you one. You ask your bookkeeper. He sends you a different one. Both are confident. Neither is wrong, exactly — they're just pulling from different places.
That's not a data problem. That's a location problem.
The distinction matters because the fix is different. A data problem means your data is incomplete, inaccurate, or missing. A location problem means your data is fine — it's just living in three places at once, with no clear rule about which one counts. Most small companies are swimming in data. What they're missing is a single authoritative source for each thing that matters.
How It Happens
Nobody decides to create a location problem. It accumulates.
Year one, you run everything out of QuickBooks. Year two, your sales lead starts keeping a tracker in Sheets because QuickBooks doesn't surface the pipeline view she needs. Year three, your ops manager is maintaining his own version because the Sheets tracker doesn't reflect returns. By year four, you have three sources and a standing argument about which one is right.
Each version made sense when it was created. The problem isn't that anyone did something wrong. The problem is that the sources were never rationalized — nobody ever said, out loud and in writing, which one is the canonical source and what happens to the others.
What "Canonical" Actually Means
Canonical means: when this number and any other number disagree, this one wins. Not because it's newer, not because someone you trust maintains it, but because it has been designated as the source of record and the others have been explicitly subordinated to it.
This is a decision, not a technical state. You can't automate your way to a canonical source. You have to name it.
For every piece of data your business runs on — revenue, headcount, pipeline, inventory, customer records, whatever is load-bearing in your specific operation — there is either a named canonical source, or there isn't. If there isn't, every report, every meeting, and every decision downstream of that data is contaminated by the ambiguity, even when nobody notices.
The Audit You Can Do Right Now
Take the five numbers that matter most to how you run the business. For each one, answer three questions:
Where does this number come from? Not where you check it — where it originates. If you're not sure, that's already data.
Who else has a version of this number? List every place a version of it exists: tools, spreadsheets, email threads, people's heads.
If your version and someone else's version disagree, what happens? If the answer is "we have a conversation," you don't have a canonical source. You have a recurring argument with intermittent resolution.
For most companies running between fifteen and seventy-five people, this exercise surfaces two or three places where the answer to question three is "we have a conversation." Those are your location problems. They are also, almost always, the places where operational drag is highest — because every decision that depends on that data requires a synchronization step before it can move forward.
What You Do With What You Find
The goal isn't to pick the fanciest tool or migrate everything into a single system. The goal is to make a decision and document it.
For each contested source: name the winner. Write it down. Tell the people who maintain the other versions what changed and why. Then — and this is the part that doesn't happen often enough — deprecate the losers. Not archive. Deprecate. Make them unavailable as decision inputs, or at minimum label them clearly as non-authoritative.
The canonical source doesn't have to be the most sophisticated one. It has to be the one everyone agrees counts. A spreadsheet that everyone treats as the source of record is better than a purpose-built tool that half the team ignores.
The Second-Order Problem
There's a reason this matters beyond operational tidiness.
When your data sources are contested, you can't trust your own reporting. When you can't trust your reporting, you make decisions based on feel. When you make decisions based on feel, you can't learn from them — because you can't reconstruct what you actually knew at the time.
Small companies often blame their tools when this happens. The data is messy, the system is wrong, they need a better platform. Sometimes that's true. More often, they need to make a decision they've been deferring: which source counts, and what do we do with the rest.
That decision is free. It doesn't require new software. It requires about an afternoon and someone with the authority to make it stick.
Start there.