This piece was originally written for and published on Native, the journal of the Digital R&D Fund for the Arts. It is part of the Making Digital Work: Data guide, available to download here.
Even if we do recognise the worth of our data and make the time to gather and analyse it, if we’re a freelancer or a small organisation — as much of the sector is — it can feel like our contribution is insignificant since the data can only tell a little story. So perhaps it’s unsurprising that the cultural sector is data-shy. We don’t generally spend money to generate datasets in order to inform our decision making, certainly no more than just enough to satisfy minimum reporting requirements.
Cultural policy consultant John Knell believes that the secret to cracking the data conundrum is to avoid the D-word entirely. Instead, he suggests we focus in on the idea of insights. We need to embrace the idea of initiating enriching conversations, both internally with colleagues and more outwardly facing with peers and of course audiences.
We’re fetishising the wrong bit of the equation. According to Knell, the assumption that organisations care about data, want to gather data and then want to do something with that data is flawed. In fact, many arts organisations have serious hurdles to leap over in the form of both expertise and resource shortages. In his opinion, 80% of us are data shy, 15% are data driven and 5% are data ready. It just doesn’t make sense to ask people to jump straight in the data deep end.
Knell says we can all embark on a big data revolution, but only if we focus on generating insights that can act as a starting point for conversation. We need to give ourselves the opportunity to focus on results rather than data per se. We’re all interested in critical and peer review, and if we create the appropriate platforms we can then use data in a way that reflects our critical practice.
Knell is currently working with a consortium of Manchester cultural organisations to develop
a new approach to measuring the quality and value of cultural activity. Culture Counts is supported by the Digital R&D Fund for the Arts and plans to be the first system
in the world to draw together comprehensive public value metrics within an electronically automated data collection platform.
Culture Counts is dubbed a Big Data project. But initially the team were simply trying to answer this question: what is a quality cultural experience? Their quest led them towards developing indicative outcomes, and subsequently a series of metrics.
The platform uses these metrics to gather real-time data from artists, their peers and the public. It then combines this with more traditional data relating to attendance, funding, and box office. Taken together, these two types of data allow the platform to deliver comprehensive value analysis and reporting on a continuous basis. This in turn enables data-driven decision-making.
Culture Counts uses a standard language across all of its surveys. By standardising measurements, it can benchmark across a number of organisations and over time. Reports are produced in real- time, so organisations can see feedback as it’s actually being fed back. The platform builds beautiful and useful graphs illustrating exactly what you want and need to measure. You can easily share the reports and export the graphs and data. You can even share your saved templates with others.
This is where the magic starts to happen. Suddenly we in the cultural sector are working together to create big datasets rather than working in small individual silos. Moreover, we’re working together to define appropriate metrics for evaluating quality. There’s also a network effect, with Culture Counts becoming a sector- wide tool that enables reflection. We become part of a community with the potential for self-reflection.
Data is now not just an advocacy tool, it’s not just about audit. It becomes a useful driver of critical review, it allows us to understand how our work will be accepted by our peers and audiences. We become a live community, working with our sector-wide data to evaluate our worth. The importance of data isn’t the data by itself. It’s the possibility of self-awareness and self-reflection that it brings to bear to make us better.