Data in Music

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.

If publishers want to use AI meaningfully, they first need to know whether their own data is in a fit state to support it. Publishing data is not a neat database of facts waiting to be queried. It is a living, fragmented, territory-specific web of claims, registrations and human judgement. Anyone who has spent any length of time inside the operational machinery of publishing knows this instinctively- this is the world AI is entering.

There’s a predictable moment in the life of a growing business as operations, departments and processes mature and become engrained. More data, more stakeholders, more decisions. What once felt intuitive begins to feel fragmented, with questions taking longer to answer and conversations starting to loop. Teams begin to operate with slightly different assumptions and understandings about the same reality. Photo by Ricardo Gomez Angel It is a natural evolution in the growth cyc

Since The MLC’s inception in 2018 through to the start of its start of distributions in 2021 and beyond it has been closely watched- by the market at large, by key stake holding publishers and by compatriot CMOs the world over. from next year there is to be a material change in how monies are distributed- Pro-rata payouts

As we all know, the conversation around music catalog investments has become increasingly sophisticated as the asset class has matured. The ability to identify, administer, and ultimately collect the income attached to rights is a deep specialism- and one that cannot be synthesized or sidestepped by AI.

There was a moment, not that long ago, when music rights acquisitions felt almost mechanical- streaming growth was steady, capital was abundant. The underwriting conversation revolved around a small set of variables: historical cashflow, growth assumptions, discount rate, and multiple. If you believed in the long-term durability and expansion of streaming, the rest followed.

Music rights are nuanced, and always have been. Creative collaboration, shared ownership, territorial differences, long tails of value, and cultural context are all part of what makes music operationally distinct from many other industries. There is, however, an important distinction to be made between nuance and friction.

“We are a defacto data company. We don’t work in the music industry- we work in the data industry.” This quote from Caroline Champarnaud of SACEM speaks deeply to the operational reality of a modern collecting society- though it resonates far beyond that context, into the very fabric of music publishing and copyright administration in the modern age. The more I’ve thought about it since, the more it feels like an accurate description of the publishing ecosystem.

Top songs are what attract capital. Music, and entertainment at large, is a hits driven business. This may be true, as most of the value magnetises to the ‘head’ of catalogs, but it doesn’t mean that everything else has no value. In fact- the truth is far from it. Large catalogs can offered history, predictability, and a level of institutional comfort that made underwriting easier- let alone the base level of recognizability and ‘icon’ status that marketing departments dream

Competitive advantage in music is often framed around ownership, but data provides an equally powerful advantage. Serious operators across the music ecosystem are all looking at broadly the same raw data inputs (keeping in mind last week’s look at how data is no longer a scarce resource)- with cloud infrastructure and AI flattening the technical barriers to entry. Data is no longer the differentiator it once was.

For years, conversations around music data have revolved around access- to global copyright databases, better royalty data, deeper DSP reporting (+ the terms of DSP licenses). Data in this framing is treated as a scarce resource- something hoarded, guarded, and used to justify competitive advantage. The great news is the tide has shifted in recent years, meaning this framing no longer holds.

There’s a recurring dichotomy in how music publishing ‘value’ is discussed. The media conversation clusters around the headline acquisition of iconic catalogs and blockbuster songwriters- the “big deals” naturally command attention. They are tangible, easy to explain, and fit the narrative that music IP behaves like a financial asset. However there is also a real engine of value outside those deals that make the music headlines. There is still material revenue to be found ac

The music industry runs on identifiers. Without them, the complex ecosystem of recordings, compositions, rights, and royalties would quickly collapse into chaos (... more so than it already is). The two most critical identifiers are ISRC and ISWC- the codes that uniquely define distinct audio recordings and song compositions respectively. Their existence looks simple on the surface, but they represent both different philosophies and underpin key workflows and challenges in at

Imagine trying to value a ring in a jewellery store, but wearing a blindfold. You can sense the outlines, feel the cut of the stone and setting, but the fine detail- the information that actually determines whether you’re about to buy a diamond or a dud- is obscured. That’s where many funds still find themselves today. Investment decisions are often made with incomplete or unreliable data. Acquisition packs are full of disparate (and static) spreadsheets

The conversation around “independence” in the modern music industry has come to the fore in recent weeks, and is getting harder to define. The major music companies have always built to consolidate power and position- not just through powerful content ownership, but via distribution and now through data.

After data (which, have no fear, is going to feature) the economic landscape for music publishing in a digital world is one of my favourite topics to explore. Well… alongside licensing frameworks, systemic politics, global society pipelines- which are all, of course, different facets of the same dynamic. Whichever way you look at it, songs don’t receive value on par with what’s shared by the rest of the industry. And even when value is ascribed, it’s struggling to get through