Sam was a star. The iceman, the closer. He shut deals faster than anyone, and closed 20% more than the rest of the team. Management loved him. He got the bonuses, the praise, and the pick of the leads.
There was just one problem. Nobody could see what those wins were actually costing.
The company measured net sales. That was the number on the board, the number everyone chased. What it never recorded was the gross price and the discounts handed out to get each deal over the line.
And Sam was handing out plenty.
He was not closing because he was brilliant. He was closing because he was the cheapest option in the room, quietly giving away margin on every deal to keep his numbers up.
On paper he was the hero. In reality he was the most expensive person in the building.
Nobody saw it, because the data was never built to show it.
This is a trap many owners walk into.
You make your decisions on the numbers in front of you, and you assume those numbers are telling you the truth. But if the data is incomplete, or it measures the wrong thing, then every decision you stack on top of it is wrong too.
You reward the wrong people and you double down on the wrong wins.
Garbage in and garbage out.
It gets worse the moment AI enters the picture.
Everyone is racing to bolt AI onto their business, but AI does not fix bad data, it trusts it.
Feed it a flattering lie and it will repeat that lie faster, with more confidence, and at a far bigger scale.
Feed it clean, well kept numbers and it compounds good decisions instead.
It is the same story when you go to sell. A buyer digs into your figures, and the moment they find the data does not hold up, they stop trusting all of it. Then they discount hard, or they walk.
Clean data and clear documentation are not admin.
They are what let you, a buyer, and one day your own AI, see what is actually true.
So how good is yours, really?
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P.S. If you would like a snapshot of what other traps might be lurking in your business, take the Buyer’s Verdict. Twenty questions, a quick score on the four things buyers pay for, and a straight answer back. Free.
Business value advisor George Sotiropoulos tells the story of Sam, a star salesman who closed twenty percent more than anyone else and was celebrated for it, while the company only measured net sales and never recorded the discounts he gave away. Sam was not the hero the numbers made him look, he was the most expensive person in the building, and nobody saw it because the data was never built to show it. The lesson is that decisions made on incomplete or wrong data are wrong decisions, AI only amplifies the problem because it trusts bad data rather than fixing it, and clean data and documentation are what let an owner, a buyer, and eventually AI see what is actually true.