In the 1970s it took an average of 1.7 songwriters to write a hit, today it takes around 4.5. That's a 165% increase, and the number is still climbing- Beyoncé's ‘Heated' carries eighteen credited writers alone. Since the 90s there has been a slowly increasing trend to sample and interpolate, and it is quietly doing something to publishing data that the industry's registration systems were always unlikely to be able to absorb.

Last week we followed a single stream from a listener in Hamburg to a songwriter's bank account, and found it splitting into multiple royalty chains before it had travelled anywhere at all. There was one element we touched upon, but only at a high level: why the same song, streamed in the same place, can be processed through entirely different machinery depending on who wrote it.

The gap between the play and the payment is where the music industry lives, and it is almost completely invisible, including to plenty of people who work in music. This week let's follow one stream all the way through, and look at every place it can go wrong.

Dancing Queen is literally, T-000.000.001-0. So let's do something anyone reading this can replicate, and take a look at the databases- The MLC's public search, PRS's works search, ASCAP's and BMI's repertoire tools- and look up Dancing Queen to see how the ISWC has fared in its 30+ years of history.

The Leakage Ledger is a recurring edition where I’ll publish actual numbers from actual catalog work. Anonymised (obviously) and stripped of anything identifying- but real. One catalog, the findings, and what they were worth. No thesis to defend, just the pure maths. Tangible numbers- those that you can see, touch and feel, change that conversation. A publisher can't benchmark themselves against a sentiment, but they can absolutely benchmark themselves against a percentage.

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.