Last year I wrote about real issues to be found in the MLC’s dataset- an exploration of what was really sitting inside the industry's most transparent copyright dataset. The headline then: the MLC reported around 90% of royalty value matched, while our analysis showed only 22% of ISRCs had been attributed to any work- some 170 million of 217 million recordings sitting unlinked, with the long tail holding more recoverable money than the industry's hits-first workflows were eve

Every catalog acquisition starts in the same place. A data room opens, and inside sits the familiar furniture: a stack of royalty statements, some contract summaries, perhaps a seller-commissioned earnings report with a decay curve that always seems to flatten out at exactly the right moment (funny that). And at the centre of it all, the schedule of works- the document that defines what is actually for sale.

Most catalog cleanup projects begin in a familiar place- are the right recordings attached to the right works. Are all the ISRCs present? Are they linked to the correct compositions? The difficulty is that recording-work matching relies on a much deeper assumption: that the list of works being matched to is itself clean.