One untested assumption was setting the price of their growth.
A ten-person Texas title-data company assumed growth meant hiring more people to hand-key historical records, until we tested that assumption.
The Situation
The company sold digital title-plant data to title companies on a subscription, and had done well at it for more than a decade. Growing meant adding counties, and adding a county meant turning thousands of historical property documents into usable, indexed data. These records go back to the 1800s. Poor scans, handwriting, inconsistent formats, misspelled names, references that point off at other documents. The whole industry took it as given that this work needed people, and a lot of them. So the math looked fixed. More counties, more documents, more data-entry staff, and thinner margins on every expansion. They'd looked at hiring. They'd looked at traditional OCR, which had always choked on records like these. Neither one moved the numbers.
What We Found
Before we talked about technology at all, we spent time understanding how the business actually ran, where the money went, and where people spent their hours. When we looked at where the time and money really went, the answer was the hand work. Turning those messy records into usable data took five to ten minutes of concentrated effort per document, and that was the true cost of every new county. And the belief holding up the whole cost structure, that only a person could read these records, had never actually been tested against current tools.
What Changed
Rather than argue about whether it could work, we ran a small experiment against the real, messy historical documents.
What Followed
The assumption didn't survive contact with the test, and the economics of expanding into a new county changed completely.
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