PRS for Music

Effective Data Management through Machine Learning

PRS for Music is the home of the Performing Right Society (PRS) and the Mechanical-Copyright Protection Society (MCPS). PRS pays royalties to its members when their works are broadcast on TV or radio, performed or played in public, whether live or through a recording, streamed or downloaded.

MCPS pays royalties to its members when music is copied as a physical product such as CDs and DVDs, streamed or downloaded, used in TV, film or radio.

The Challenge

In early 2020, PRS engaged Leading Resolutions to conduct a high level review of its data capability and develop a plan to carry out a more detailed analysis in order to build a full data strategy.

PRS wanted to create a Data Strategy to ensure they were:

Brilliant at the basics
Innovating and able, through deeper analysis, to support a longer-term business strategy

Whilst supporting the five key imperatives:

Deliver excellent core services and support to members, and implement and evolve the segmented member offering

Increase member income by delivering significant growth in 2020, and by identifying and prioritising opportunities for revenue growth

Stabilise and scale the current distribution platform, and define future distributions offering

Optimise governance and management of joint ventures (JV), and update longer-term JV and partnerships strategy

Build a high performing and engaged team

The Solution

The first step was to engage key stakeholders and knowledge holders across PRS to baseline the current position, so that a clear improvement plan could be created with agreed business objectives. Through a series of structured interviews and workshops, we captured detailed comments, observations and requirements.

The results were mapped onto three key themes:

1. Improve the data tooling for delivery and operations

2. Put a formal data governance framework in place

3. Improve the data management to maximise opportunity for PRS and their customers.

However, conscious that fast track initiatives were also needed, we recommended the implementation of automation tools to realise immediate business benefit. This enabled instant improvement across the data catalogue as well as contract analysis, with automated unification of data, using machine learning tools, removing the semi-automated processes that existed.

We ran proof of concepts and prototypes in these areas using real business scenarios.

The Results

We delivered a comprehensive data governance, strategy and policy framework which created immediate benefit to PRS within programmes such as the end-to-end distribution review and CRM.

In addition, the Data Cataloguing PoV clearly demonstrated that machine learning could quickly and accurately catalogue poorly identified data from multiple sources using both data column names and the data contents itself.

Likewise, the Data Unification PoV showed that by using human-guided machine learning, automated matches could be produced for usage data rivalling current processes, even with foreign character sets. This process also challenged current human assumptions within the business and improved the matching of data immediately.

PRS now has an embedded data governance strategy enabling them to mobilise the governance groups and focus on data and process ownership, data stewardship and detailed business processes. Data pipelines are able to provide real time operational metadata and, in parallel, continue to explore opportunities to innovate and enhance capability.

There were clear benefits for our client that included a clear, fit for purpose data governance process. All their projects and programmes now capture data requirements at an early stage in the process, preventing later rework and additional costs.

In addition, future storage needs are identified and impact analysis across multiple systems is completed in good time through reliable reporting systems.