royalties | Digital Music Observatory

New Indicators for Royalty Pricing and Music Antitrust

Wed, 02 Jun 2021 17:00:00 +0200

As Chief Legal Counsel in a music organization, what type of data do you usually use in your work and/or projects?

I work with copyright in artistic works, which is a decentralized system by nature. Unfortunately, works do not have a central registry in Europe. Protection takes place “ipso iure”, and there are various licensing solutions and actors. Although a lot of the data exists, it is not collected, stored or analyzed in a unified way.

For my daily tasks, however, data would be needed for setting the price of the different licenses and, or identifying the works that were used, exploited, to properly manage the payouts to the rights holders. Price-setting should be based on revenues arising from these exploitation of works. It must take into consideration the income structure of any industry using protected material. And often these requirements are very special, like in the case of the telecom sector as a user of work, and the different business models applied in on-demand services, just to mention the most difficult aspects of my work. Because of the trade secrets and business confidentiality requirements, often it is only possible to have a top-down view of industry data and have insights into trends, but not into the details.

The other area I work with is the identification of content, e.g. music and various types of audiovisual content with regard to the music included.

In an ideal data world, what would be the ultimate dataset or datasets that you would like to see in the Digital Music Observatory?

Sometimes data is available for the US or Western European countries but not for the Central and Eastern European region and I suppose even less in countries that are not members of the European Union. Another concern is that analysis is more available for valuable mass repertoires than the small language niche ones – this is a real problem in the CEE region. As this addresses several cultural diversity and competition issues, I would like to help the creation of datasets that address these aspects, allow comparisons and factual identification of market problems or failures.

Our Digital Music Observatory grew out of the CEEMID project, which brought some data-poor CEE countries to the level of advanced music markets, particularly for pricing reasons.

What type of data breakthrough do you see being a game changer for researchers and/or policymakers in your field of work?

I think a data breakthrough is just happening and following the recent evolution of data science, new and fascinating approaches are appearing. I believe that this is a great field to show human creativity matched with computing capacity and technology. From a practical and business point of view, it would be a real breakthrough if the proprietary data use of those multinational ‘big tech’ online services that reshape the world not only in the cultural industries of film and music, but also politics and freedom of speech, would be open for scrutiny and analysis by various independent actors.

Our Feasibility Study for promoting a small language repertoire in radio and streaming.

I particularly find the trustworthy AI element of the data observatory, i.e. the analysis of recommendation system and other autonomous system data to understand potential negative (and positive) outcomes the most prospective part of the Digital Music Observatory.

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Valuing Music

Thu, 12 Nov 2020 11:00:00 +0100

The copyright and neighboring right royalty is the wage-like earning of the music performer, the composer and producer. In popular music performers usually play their own composition and sing their own lyrics. If the musician is self-published, all the three royalties directly pay the artist’s work. If a professional publisher is helping the artist as a composer, or a record producer as a recorded performer, they usually share the respective royalty revenues. In emerging markets fewer, in mature markets more composers are represented by publishers and performers by record labels.

International Comparisons

The CEEMID international comparison models are based on the implicit econometric model set out in the AKKA/LAA vs Konkurences padome case which goes far beyond the regional comparison suggested by the earlier Czech Léčebné lázně Mariánské Lázně v OSA case for comparing royalty tariffs in the European Union.

The EUCJ declared that “it is appropriate to compare its rates with those applicable in neighbouring Member States as well as with those applicable in other Member States adjusted in accordance with the PPP index, provided that the reference Member States have been selected in accordance with objective, appropriate and verifiable criteria and that the comparisons are made on a consistent basis.”

In our view, setting a royalty tariff, especially when comparison of other market prices is taken into consideration, should follow the principles of the IFRS 13 Fair Value Measurement international accounting standard. This accounting standard was endorsed as an official interpretation of accounting principles by the EU Commission Regulation 1255/2012, which is in turn a binding interpretation in the light of the directly applicable 1126/2008 EC Regulation. This document gives a practical guidance on how to use objective data in valuations. Although the language of the standard is mainly aimed at large corporation with heterogeneous balance sheets, as a canonical, cross-country reading of sound accounting principles it is applicable for establishing the fair value of an assets or liabilities, including intangible assets such as royalty-earning copyright and neighboring rights.

On the top level of the hierarchy we find publicly observable prices in frequently traded assets, which is not applicable in our case. The second level of the hierarchy contains more reliable, publicly verifiable data sources and the third level of the hierarchy non-public information that is objective. Whenever possible, publicly available and verified information should be used.

The structure of the music and audiovisual industries makes the use of Level 1 input data almost impossible in a European context, because the vast majority of the industry players are microenterprises and sole solicitors, and even larger entities such as collective management societies and TV stations usually fall in the scope of the EU small- and medium size enterprise category. With few exceptions, this is the case with HORECA tariff payers, i.e. restaurants, pensions, hotels and other similar establishments. Micro-, small and medium sized enterprises are usually subject to simplified and limited financial reporting, tax reporting rules and mandatory official statistical reporting rules. Most of the EU economic statistics are created from tax and financial reports, and in other cases from mandatory statistical reports. Because creative and cultural enterprises usually do not fall into the threshold set for most enterprise statistics data collection, and because of the simplified tax and accounting reports, less official statistics can be created.

In the absence of high-level valuation input data, we must use level 2 (public) and level 3 (private) data sources that are by nature subject to interpretation. Such interpretation is subjective in the language of the standard because it is personally made by an objective analyst. The reliability of the valuation depends not only on the quality of the data, which is the case with level 1 data, but on the sound analysis of a competent analyst.

CEEMID made a large effort in the last 5 years to use high quality, publicly observable data and private data to create meaningful and objective social, economic and cultural indicators as set out in the EUCJ preliminary decision.

Market Comparators

The best models are based on market data and use information on prices and quantities agreed by independent, arms-length contractual partners. Our market comparator models process all collectively managed and estimated individually licensed uses of music and audiovisual content in a country. It is than possible to compare private copying values, value transfer to media platforms, or individual uses such as radio or television to the total market value of music listening per hour or film watching per hour. These models require the most data input.

We used such estimates in the Slovak Music Industry Report, in the calculation of private copying benefits to consumers and value transfer to YouTube in Hungary and Croatia.

Direct Estimates & Hypothetical Evaluations

Direct estimates are measuring quantities of unknown uses and they relate them to known market prices. Hypothetical evaluations ask the willingness of users to pay for uses. These models are easier to create, require less information, but they can be more easily challenged by regulators, licensees or auditors, because they do not rely only on independent and arms-length transaction data.

Hedonic Pricing

Hedonic price models are econometric price models that establish the residua value of music in complex services like hotel or restaurant services. We have used hedonic price modelling to establish the value of music use in the HORECA sector. Technically these models could be used to evaluate the use in television or radio but the data requirements are extensive.

Why Did We Start The Demo Music Observatory?

Tue, 27 Oct 2020 10:00:00 +0200

I was contacted during the consultation period of the Feasibility Study of the European Music Observatory. That led to an uneasy series of conversations with the consultants of this project, and a very enlightening series of conversations with European civil servants, music industry organizations, music managers and artists. My main pitch was that every single assumption of this project is wrong.

They started from the assumption that there is hardly any data available on the European music scene – whereas we found while building up CEEMID, errr, a pan-European music data observatory, is that music is one of the most data-driven industries in the world, it is choking in numbers, and the reason why this data is not visible is very different. They were talking about lack of data in fields where we already had about 2000 pan-European indicators ready. (See Introducing the CEEMID Observatory, 9/28/2019 large self-contained html file, takes time to load into browser)

Big data creates injustice

The music industry is scattered: it has the author’s or publishing side, the recording side, a large live music business and usually a very environment for classical (art) music. Within these segments there are hundreds of organizations in each EU country, and each have their own small or large datasets. The music industry has plenty of data, but it is not integrated, and it is often hidden from organizations that may have a conflicting agenda.

The fragmentation of data makes these players easy prey in the era of big data. Companies who monopolise big datasets first and create weapons of math destruction in the forms of algorithms that work for them, can take an unusually large share of the money created throughout the value chain. Proprietary, uncontrolled, big data trained algorithms reinforce inequality — this makes Google’s YouTube, Spotify, but also Netflix in films or Amazon in books so powerful against its competitors, but also against competition regulators or suppliers — in this case songwriters, video producers, filmmakers, book publishers and authors. If their algorithm works against a creator, the creator is doomed, because half of the global sales are driven by secret algorithms.

Big Data vs Small Datasets, Research Automation

The problem of the music industry is not too little, but too much data. Music is drowning in numbers, and it has too little resources to turn much data into valuable information.

Our concept of the European Music Observatory is to pool enough resources to create value for rightsholders, talent managers, venues, festivals and the entire music ecosystem. Most music organization employ 1-5 people, and even the largest national organization, like collective management organizations, fall under the EU definition of small- and medium sized enterprises. They do not have data scientists, market researchers, forecasters. They are small organizations with small research budgets and very little time for researching. Nevertheless, with more than 60 partners in 12 countries we have shown that this is possible:

we turned 700 million royalty statements into meaningful indicators about the price and volume growth in 20 European streaming markets;
calculated the value gap and the value of private copying in Hungary and Croatia;
helped closing the royalty gap in Hungary and Slovakia by helping collective management to significantly increase their royalty collection;

helped granting agencies to make more relevant grant calls and designed indicators to measure the impact of their grants;
started the creation of local recommendation engines that help the circulation of the small nation repertoires or city scenes in Europe or beyond.

Music Has Data, But You Need A Map

Scattered industries tend to be riddled with conflicts of interests. While working with royalty collection management societies in the last 7 years I often saw that songwriters, producers and performers are often fighting each other for slices of the pie that is just too small. That means that national members of CISAC (GESAC in Europe), IFPI, and AEPO-ARTIS often do not share data with each other, although their income is below any legally acceptable threshold. They have individually very rich datasets that in many jurisdictions just never meet. Labels, small publishers are so little organizations that they do not have a data scientist, let alone a dedicated IT person, or even an HR professional to hire the services of data scientists.

We were able to collect at least 70% of the information content of the planned European Music Observatory, and far more, than most of the 50 data observatories we examined in Europe, because we took an approach inspired in open source software development: continuous opt-in, opt-out data integration, focusing on the synergies that partners can achieve, instead of aiming at endless discussions and compromises on sharing data. We never take away proprietary data from anybody, we just connect data among partners, and enrich it with open data. We would like to guide the industry from hierarchical database planning to the philosophy of open collaboration.

We automated most of the research tasks, to make it less costly, less error-prone, and require less labour input. We can automate most of the data collection, data processing, imputation, validation, documentation, reporting, even some modelling.
We invested into harvesting the vast open data of the European Union and its member states. In the EU, most taxpayer funded research data is freely available, but at a cost of significant data reprocessing cost. If the data was originally collected to calculate to inflation or monitor tax revenues, it needs to be significantly altered for the music industry to be useful.
We have found a way to connect many small data sources and open data. We can create big data from much small data, and deploy analytics, algorithms on collective datasets.

Granting And Policy Evaluation For Musicians In Hungary

Thu, 12 Nov 2015 19:00:00 +0100

The data and intelligence of CEEMID was used in Hungary to create an ex ante evaluation of the new Cseh Tamás Program to support popular music development in Hungary. Our mandate was to create concrete granting proposals that have a high chance of making a change in terms of the later royalty earning capabilities of artists.

In the first phase of the project, we made two workshops with the eight fields development method to understand the challenges and existing working practices that result in a low level of royalties paid out in Hungary. This methodology requires a groupwork of all stakeholders and professionals of the industry. In this case, we worked in groups of 30-40, covering various artists, stage, light, sound technicians, producers, managers and even band transporters. One group predominantly was Budapest-based and one in Eastern Hungary, to have a different view on working and market conditions in the metropolitan city and in the countryside. While royalties are not applicable for live music, it was well understood by the granting authority and the music industry that royalties cannot grow without a healthy live music sector in the country.

In the workshop, the consultant with several aides facilitates a very structured conversation that starts with a desired state of the industry which is not described by slogans but by actual characterizations of a desired working environment. Instead of envisioning that “everybody gets a grant”, we describe the ideal project planning and management cycle of a new tour or record to see how a granting can fit into this workflow and what type of grants add effective assistance to realize goals. For each goal and change we envision how that effects the work of the performing artists, her manager, the technician crew, even the schedule of the tour bus driver. We discuss if the change makes any material change in the way we can prepare for a new album release.

In the latter stages what sort of changes we envision in day practices, programmers, institutions and what concrete steps are needed to be made to get there. As a controlling step, we assign indicators that can be objectively judged, and which can show the degree of change if recommended actions are taken.

The advantage of the eight-fields methodology, which was originally developed to support EU and global aid program design is that it allows conflicting viewpoints, finding consensus, and display very highly detailed policy and program scenarios already in a day. It is generally a very enjoyable experience for artists and professionals. If the workshop takes place over 2 days, a first draft program is already presented on the second morning and by the end of the day participants usually have a detailed program. In this case, we came up with dozens of concrete proposals, many of which could be addressed to the stakeholders themselves without any action taken from the granting authority.

In the next stage we carried out the annual CEEMID Music Professional Survey with additional questions where artists, managers and technicians could rate the proposals. They could also optionally give their next year development priorities in the fields of live performances, recordings and composition, in the context of their current work, pre-existing financing and professional assistance of financial assistance needs. In Hungary, more than 1000 music professionals filled out the survey in 2015.

At the end of the workshop and the survey, we could present a very comprehensive policy and granting program, with preliminary estimates on granting needs, ideal and minimum grant sizes, and grant contractual conditions to avoid grant calls that cannot be contracted out to winners due to unrealistic prerequisites.

These results, with suggested cultural policy indicators, program indicators and budgetary outlines were presented to the granting authority of the Cseh Tamás Program (currently named: Hangfoglaló Popular Music Support Program)