Over the past several months, researcher Caitlin McDonald has been working with researchers at the Creative Research and Innovation Centre at University Loughborough London (Jennie Jordan and Graham Hitchen) and with data specialists at The Data City (Fatima Garcia and Harini Nagesh) to explore challenges of data-driven decision making in the creative industries.

This is the fifth Creative Horizon project supported by Creative Informatics, interdisciplinary partnerships between academia and industry designed to break new ground in how data-driven technologies can benefit the creative industries in the future. This project focuses on moving towards better, more ethical economic analysis frameworks to support creative industries research and development. Core questions the research attempts to answer are:

• What are the data, and data adoption, barriers to innovation in the creative industries?
• How can we make data collection, processing & analysis more useful for data consumers (like policymakers and funders) and for data producers (like businesses and individual creatives)?

To find out more about where the biggest challenges were, we conducted 28 individual interviews and ran five interactive research workshops with stakeholders interested in various aspects of creative industries data, including creative practitioners and organizations, trade bodies, NGOs, government departments, policymakers, and market and academic researchers. This culminated in a highly collaborative ‘Policy Hack Day’ where we invited participants to view our early conclusions from the research and to work together to identify potential solutions to challenges for data barriers to innovation in the creative industries.

Elspeth Murray, a facilitator and live-scribe artist, worked with us to translate the most evocative phrases arising from the research into relatable imagery encapsulating the three major themes emerging from the research. These are:

Innovation Ecosystems

Strategy, Policy and Programme Development

Data Capture & Management for Decision Support

By bringing together stakeholders with varying perspectives on the challenges through the Hack Day, we were able to identify a few core recommendations for the future of policymaking for the creative industries:

• A common data standard allowing interoperability across different technology platforms would benefit policymakers and those who are economically active in the creative industries by facilitating a more complete picture of creative industries activity.
• All industries are now grappling with the need to evaluate their impact beyond purely economic output, and the creative industries have the potential to lead the way in developing novel frameworks for evaluating broader societal, environmental and purpose-driven impacts given that many creative projects and organisations already describe their work in these broader terms.
• Given that the creative industries have a much higher proportion of sole traders than other industries, particularly in sub-sectors like craft, there is ‘dark matter’ missing from but implied in the data that skews the figures most commonly used for econometric analysis of the sector: we can’t see data on sole traders directly using data from Companies House or many other common data sources, but we know they have a massive presence within the sector’s real activities and impacts. Finding a commonly accepted means for evaluating or estimating this impact within economic models would be of high value in creating more effective policy decisions for the sector. Related to this challenge, Creative Informatics partners Creative Edinburgh recently launched their report Connecting, Collaborating, Creating: The Experiences of Creative Freelancers in Edinburgh in 2022. Also check out our prior work mapping freelancers in the Creative Industries in our cachement area.
• The real value of data is as a tool that supports decision-making: finding ways to incorporate data into continuous learning cycles instead of traditional end-of-programme evaluation mechanisms allows for snarfblat. This may include identifying the ‘minimum viable data’ required for a decision—and stopping data collection that isn’t in support of a decision-making process.

Elspeth created a moving (in all senses of the word) overview of her drawings throughout the day, encapsulating some of the key insights attendees shared. Watch below:

We will be writing up our findings in more detail in a white paper forthcoming in the next few months. If these findings have piqued your curiosity and you’d like a more detailed briefing on our research outcomes, reach out to caitlin.mcdonald@ed.ac.uk.