Document data capture is the step after imaging: reading the fields the firm actually uses from each page, the client, the date, the amount, the reference, checking them against the record, and filing them against the numbered page so the document is found by what it says rather than by what it was named. For a small firm the value is in three or four fields captured reliably, not in forty captured badly. The free document capture worksheet on this site sizes the pages a year that would pass through capture and the retrieval hours the captured fields replace; Batesio Pro holds the fields against each page and finds the page by them.
The fields worth capturing
Client, matter or period, date, amount and reference cover most of what a small firm searches for. Capturing forty fields from every page produces forty fields nobody trusts; four fields checked are what make the search work.
The check
A captured field is compared with the record it is filed against: the client name matches the client, the period matches the matter, the amount matches the invoice. A field that fails the check is flagged for a person rather than filed wrong. The worksheet's daily load, a hundred and fifty pages on the default, is the number of checks a day the rule must handle.
Where the fields live
Against the Bates-numbered page, in the client's record, searchable and exportable. Fields captured into a spreadsheet beside the scans are a second system to reconcile. Dropbox, cited below, prices a Standard team plan at $15 per user per month for storage that captures nothing; the fields are what find the page.
Questions people ask about document data capture
Is document data capture the same as OCR?
OCR reads the text; data capture picks the fields out of it, checks them and files them against the record.
How accurate does capture need to be?
Accurate enough on the four fields the firm searches by, with every failed check going to a person. The check is what makes the accuracy honest.
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