How the music industry could benefit from data technology convergence

At JAAK, we have been working with the music and media industries over the past couple of years to develop a blockchain-based solution for the registration, assignment and management of intellectual property. A project that we call KORD.

We have been collaborating with the largest organisations in our target areas of the creative industries to both understand their needs, and design potential solutions to address them. As a result, our work has afforded us a unique position to assess the current state of play and the potential impact that developments in technology may provide.

This article is intended to provide a narrative around some of the issues that stakeholders face in the creative process whilst setting out the new tools that they will have available to them. The focus here is music because it’s within our industry that the issues are currently most obvious, but everything is translatable across all industries that have a heavy reliance on intellectual property. Music, due to its ubiquity and universality, just tends to lead the way with these things.

The music industry context

Laying out the dynamics of the industry

The marketplace for music today is balanced between: (i) supply — fuelled by creators represented by labels and publishers; and (ii) demand — listeners and in turn the platforms providing access (broadcasters like BBC Radio, Digital Service Providers like Spotify).

Prior to the internet revolution, recorded music was a scarce resource, a high value product with distribution channels controlled to extract maximum value. Since then, it has gradually slipped from being considered a product, to a service, to a utility. Recorded music is now ubiquitous and access to it taken for granted. It is more often in the background, part of the scenery.

The fragmentation of the album and the movement from an ownership model to an access model with the proliferation of all-you-can-eat streaming has allowed Digital Service Platforms (DSPs) to aggregate the listener base. This has pulled the impetus of licensing negotiation away from rightsholders, driving consolidation as market share becomes increasingly important, and created a translucent barrier between creator and consumer, where each can see the other as much as the platform allows them to do so.

Currently, major streaming platforms are not profitable as stand-alone services, primarily due to customer acquisition costs and the high cost of royalties that they must pay out; up to 85% cost of revenue.

Inefficiencies in the fragmented nature of rights and the reporting hurdles that this presents are a challenge. As is extracting revenue from users as platforms grow.

Spotify’s recently released F-1 accompanying its announcement of intention to IPO (through a private placement) noted declining ARPU and increasing content consumed per user. Cost of revenue has declined in the last year, though, in its own words: “This decrease in cost of revenue as a percentage of revenue was driven largely by a reduction in content costs pursuant to new licensing agreements”.

The success of major rightsholders is now directly twinned with the success of streaming.

The volume of data in the music industry has grown exponentially since the rise of streaming, due to the potential to track every single play. The impact of the Internet of Things, through “smart speakers”, among other devices, will drive an explosion of ‘contextual data collection’, providing near-boundless additional data points for every single play.

The music industry’s current infrastructure cannot cope with its appetite and requirements for data, relying on thresholds and censi for payment attribution.

“Ba”: a foundation for knowledge creation

Building on the SECI model for knowledge management:

• Socialization (tacit to tacit) “is the process of converting new tacit knowledge through shared experiences in day-to-day social interaction.”
• Externalization (tacit to explicit) is a process whereby “tacit knowledge is articulated into explicit knowledge…so that it can be shared by others to become the basis of new knowledge.”
• Combination (explicit to explicit) is a process whereby “explicit knowledge is collected from inside or outside the organization and then combined, edited, or processed to form more complex and systematic explicit knowledge…The new explicit knowledge is then disseminated among the members of the organization.”
• Internalization (explicit to tacit) is a process whereby “explicit knowledge created and shared throughout an organization is then converted into tacit knowledge by individuals…This stage can be understood as praxis, where knowledge is applied and used in practical situations and becomes the base for new routines.”

Ba creates spaces to spiral from tacit to explicit knowledge, between individuals and collectives, to create new knowledge.

“Ba can be thought of as a shared space for emerging relationships. This space can be physical (eg. office, dispersed business space), virtual (e.g., email, teleconference), mental (eg. shared experiences, ideas, ideals) or any combination of them. Ba provides a platform for advancing individual and/or collective knowledge.” Source

The creative ideation process

Taking this idea of a continuous evolution of knowledge creation and communication, we can build out an analogous “create-communicate-capture-combine” feedback loop to underlay the creative ideation process, and then consider the platforms that we provide to facilitate this journey:

• Create: making something new
• Communicate: sharing that something with others
• Capture: getting feedback
• Combine: consider the feedback to make improvements; repeat

Music creation, in fact any creation, starts with a spark; an idea. An idea that is influenced by past sensory triggers that have been stored to memory. This idea starts small and then builds momentum as our brain starts to perform whatif/howabout analysis.

Then the idea is tested with other people, tyre-kicked. And sometimes the other people have useful feedback, information and experience. Morphing the idea into an even stronger idea. This process is an example of the first “create-communicate-capture-combine” feedback loop.

Once the idea has been around the loop enough times, and it is in its final form, it is ready to be communicated to the general public. In music, traditionally, from this point on the creator will effectively lose control of their creation and rely on third parties to relay information and statistics back as to its success.

The process will then start again, with an additional series of influences from the previous work. The flow of information driving each step along the way.

Strengthening the loop

Creation is a function of all the influence, information, experience, feedback and relationships that are available and relevant, yet it’s no secret that the music industry is currently disjointed, unconnected, and its capacity to handle relatively modest levels of data is unevenly distributed, concentrated around the Majors. A number of the links in the create-communicate-collect-combine cycle are not working to their full potential.

Two examples:

1. input attribution and access to data — the internet has made a great difference to the types of people that we can communicate with; however, long-distance trust can make co-creation a challenge — a broken create-communicate link;
2. the post-release process leaves the majority of data relating to a piece of music confined in silos, inaccessible to the creator, and thus not considered as part of the next creation cycle — a broken capture-combine link.

There is an opportunity to do better. There is the potential to use new technologies to develop a global creation Ba. A “shared space for emerging relationships”, a “platform for advancing individual and/or collective knowledge”. An environment to nurture the next era of creativity.

The new tools; turbocharging the process

There are three pieces of incoming data technology that are going to be at the heart of connecting a fragmented digital music landscape and strengthening the links in the create-communicate-collect-combine cycle:

(i) Internet of Things;

(ii) Machine Learning; and

(iii) Blockchain Technology.

In this section I will argue why each is important and why they are all interdependent.

Before we begin though, it is worth noting that we are not alone in this exploration. These three technologies are set to impact every single avenue of modern life, and there are plenty of clever people flying in a million different directions trying to work out just how.

For example, Outlier Ventures have their ‘convergence thesis’, which has inspired them to take positions in companies across the emerging ‘data economy’. Our friends at BigchainDB have recently launched their project ‘Ocean protocol’, which aims to create an incentivised substrate for the sharing of data and development of artificial intelligence.

It’s also worth noting that there has never been a more important time for us to understand the value chain of data. Web 2.0 was built by growth hacking customer aggregation with the provision of free services, while obfuscating the true value. As a society we had made our peace with this, while the super-aggregators maintained their outward perception of being t-shirt wearing, “don’t be evil” mantra chanting, scrappy (multi-billion dollar) ‘startups’.

However it feels like the tide is turning. The recent Cambridge Analytica controversy has honed the public consciousness towards the unfortunate fact that the cost of our hyper-connected social web driven life is that the companies providing these services now know everything about us. And so, the search for another way, decentralisation, which has been bubbling away in the forums and conversations of groups of the more security-conscious extremities of the population for a long time, is starting to be taken seriously, both in terms of capital and societal support. Maybe the end is in sight for Aggregation Theory.

The alignment of Internet of Things, Machine Learning, and Blockchain Technology is coming, so let’s see what this might mean for the creative industries, and especially music.

Internet of Things

Customer preference and behaviour is currently analysed through relatively simple means: track play counts, playlist popularity, hours listened per day, possibly geolocation and activity estimation. There are a limited number of data points that a platform can capture to understand the listener.

This will all change, however, with the potential of Smart Speakers and Virtual Assistants, such as the Amazon Echo (Alexa), and the Apple Home Pod (Siri). Suddenly, rather than needing to know the track name, a user can search for “that one that starts with a sad acoustic guitar but has a happy chorus”, or request “something minimal to help me concentrate”. The use of natural language for vocal search will have serious ramifications on how we think about music, how we think about discovering music, and how we value the relative substitutability of music.

There will also be serious implications as to how we communicate music within the supply chain as the metadata for a song grows exponentially due to all of these new data points made available by IoT devices. DDEX’s Electronic Release Notification (ERN) working group has been discussing the additions of data fields in relation to voice smart speakers for some time.

From a slightly more sci-fi angle, developments in other Internet of Things devices such as wearables could allow artists to get a much better understanding of their fan’s emotional responses to their music. And as a result, the capture and create stages in the creative cycle could be enhanced in ways that were previously impossible.

Platforms will be able to beat match to heart rates, analyse and direct changes in mood through rising or falling bpm, coordinate with other wearables and services, to build up an overall picture of the situation and environment that the listener is operating in.

The data that can be captured around each and every song will explode exponentially, creating so many more touch points from creator to fan.

Machine Learning

Machine Leaning algorithms feed on data. An explosion in the volume of data that can be collected will drive an explosion in the insights and services that can be built on the back of it.

The below are three ideas for music… there are many, many more being worked on out there:

1. Administrative functions and creative suggestions will become far more intelligent and processes will be automated, which will free up more time for creators to work on the ‘value-add’ rather than the mundane and repetitive.
2. Machine Learning algorithms will lower the barriers to access, acting as a crutch to allow many new creators to develop works that would currently not have the required skills to do so. This could be as simple as suggesting lyrics and chords, or even extend to automatically playing instruments based on basic cues and requests. Innovation can and will come from all areas of society.
3. In a live setting, an algorithm could assess the data coming through to it from the dancefloor to suggest to the DJ the next track that they should play. It could even create variations to the track that is currently playing based on feedback that it gets.

Of course, machine learning could also be used to replace the creative process altogether. [warning: this section is slightly controversial]

Streaming services are being forced to divert their reliance away from high royalty music. Whilst, arguably, a section of the general public is increasingly blasé about the source of the music that it is listening to, attaching value to convenience and availability over quality and the integrity of the creative source. If music has become a utility for the masses, then potentially the next step is for it to become a machine-made utility.

Rightshodlers will attempt to limit this, for a while, but, arguably, they have been aggregated away from the customer. Streaming platforms are currently restricted from competing at the record label level, but this feels like a short-term solution, and it is already being tested in a number of cases. Even if streaming platforms are kept out of the machine-made composition game, then there are any number of hungry start-ups ready to take the mantle on.

That said, I believe that there will always be room for ‘human-made’ music, and one outcome of this series of trends could be an even greater importance being placed on live music.

It could also act as a catalyst for the creation of new music experiences. Streaming was introduced over ten years ago. We got comfortable and it could be argued that we have stagnated ever since.

Blockchain Technology

The industry has struggled to create an environment for the effective sharing of information, which could severely lessen the potential impact of advancements in both Internet of Things and Machine Learning. Fortunately, though, this is one of the problems that Blockchain Technology, decentralised databases, storage and computation are really well suited to solve.

There has been so much hype around blockchain over the past couple of years that it’s easy to get lost in the hyperbole. So let’s just remind ourselves about what it can actually do — blockchain’s great promise is in incentivising competing parties to collaborate on a shared output, working towards a mutual goal by pairing individual gain with the common aim, while maintaining sovereignty and provenance of data.

We’ve already done some previous writing on some of impact that we expect to come.

Our previous blog, AVOCs: unlocking the next phase of the music industry, details our plans with KORD to create a SSOT (Single Source of Truth) of data in the music industry. Then, utilising identity and authority, to transform this SSOT into an AVOC (Authoritative View of Claims), enabling competing stakeholders to settle on single, aggregated view of rights ownership.

As described in The KORD Network: Lowering the barriers for developers in the music industry, we believe that decentralisation could lower the barriers to innovation by opening up access to data and allowing for the point of competition to be around the best service (algorithm), and shifting the focus towards value adding innovation. Kick-starting a marketplace for buyers and sellers of information and services.

All of this can be underpinned by a tokenised system, which would provide contributors with the opportunity to earn ownership of the network as they add value to it and participate in the reward as the system grows.

This the killer mechanic that really separates Blockchain Technology apart from previous attempts with regards to bootstrapping stakeholders into a new way of thinking. Instead of relying on goodwill for early adoption support, we can directly incentivise participation through the reward of tokens, which would provide utility within the network. See our piece, Everything has a price: Announcing the KORD Token, for more information.

Fitting it all together: The Data Technology Tripartite

Internet of Things, Machine Learning, and Blockchain Technology, the Data Technology Tripartite, will shape the future of one corner of our industry. A blockchain enabled network provides the link between the inputs (Internet of Things receivers) and the processing (Machine Learning), acting as a substrate for communication of data, while maintaining provenance and control. As we see each of the technologies grow in use and adoption, we will see how they act as a catalyst to each other.

I would argue that the system is unlikely to develop to its full potential without the success of each constituent part. Equally, the success of each individual technology strengthens the case for the other two.

Summary

The creative ideation process is driven by information flowing between each phase. Current technical and business challenges can cause a disconnect. Disrupting the cycle.

New data technologies will grant us the opportunity to construct a global creation Ba. A shared space for advancing individual and collective creative output.

At its heart will be the development of Internet of Things, Machine Learning, and Blockchain Technology. A tripartite of technology that will catalyse its own growth.

There are likely to be additional impacts to the creative process, which will require proactive efforts to understand and preempt.

We are continuing our efforts with the widest possible range of stakeholders to build the Blockchain Technology piece of this puzzle, through our project called KORD. Find out more about our progress to date here.

Thanks to Henriette Heimdal, Andrew Clark, Lawrence Lundy-Bryan, Alex Kennedy, Vaughn McKenzie, Lewis Marshall, Fred Tibbles and everyone else for their input and feedback while writing this piece.