Over the past six years, data hackathons have changed from involving groups of data specialists coming together to address challenges set by organisations, to much more collaborative affairs where data and non-data specialists work together to solve a collective challenge. Cat Drew explores how a design approach involving prototyping helps people work through sometimes nebulous and complex concepts like data in a staged and reflective way.
A couple of weeks ago, we ran a data challenge day to create an online patient verification system for Digital North West London. It’s made me think back to my first hackathon 6 years ago with the Met police whereby we used data to create apps to support victims of domestic abuse or help neighbourhood police remember which law to arrest people under.
Since then, a lot has changed. Back then, hackathons had mostly been a method for gathering a load of (mostly male) data geeks together to resolve a particular challenge, feeding them beer and pizza and getting them to come up with a digital prototype at the end.
Now, they are a much more human-centred and multidisciplinary endeavour, with different people of varying levels of data knowledge working together in the room, and the outcome being a wider range of end products.
I’ve taken part in a quite few of them recently, ranging from an experimental data studio hosted by Dr Lucy Kimbell on food banks, a Design Jam in Berlin on increasing people’s trust, transparency and control over their data, to a hackathon on using data to prevent homelessness to a workshop on using data to show cancer survivorship routes.
While the topic area and length of time (3 hours to 3 days) has varied, these events have all taken a data and design approach; bringing together data and non-data experts to co-design ideas, working in an iterative, human-centred and reflective way.
Conversations about data can often be difficult. Data as a ‘thing’ is challenging to conceptualise. People’s opinions around data privacy are often far more stringent than their actions; a complex issue that requires both a fair amount of technical knowledge and ethical considerations. Discussions can end up being quite high level and often conclude with ‘there is more to do’.
Prototyping however gets people focused on solving just part of a problem. It allows them to ‘come down’ from these strategic conversations, to push their thinking forward in a tangible way, and then reflect back on what this means for the wider system. Usefully it breaks a big problem down into bite-sized chunks.
Prototyping is a purposeful way of pushing forward with complex and (often) nebulous subjects like data – by making and sharing something that is tangible.
As an example at the workshop for online patient verification, the participants got into quite a high-level discussion about the challenges involved and I was worried about how we were going to get them to the idea phase. But by breaking down these ‘lofty’ challenges into more specific ones, we generated three viable ideas. It wasn’t easy as the topics are complex but we made sure we had facilitators on each table who were quick to digest what people were saying, visualise it and share it back with the group so they could see their ideas evolving. Our brains were pretty fried at the end of the day but the output was very worthwhile!
The space of the co-design workshop – prototyping included –is as much about the process of learning and knowledge generation during the day, as the ideas that are produced.
This was my biggest takeaway from the Design Jam around trust, transparency and control – as it was expertly facilitated by Alex Lawrence and Marcus Hormeß from Work Play Experience.. They host hundreds of ‘jams’ around the world, and during the one I attended they shared their techniques which chimed with our experience at Uscreates.
Prototyping can take many forms, and early stage ones created by non-data experts need not be digital. At the challenge day for online patient verification, we were left with sketches and a video (see below). At the hackathon to prevent homelessness, we used dummy data to create some predictive models. At the Berlin Design Jam, we used Marvelapp to come up with a series of click-through wireframes. They don’t need to be perfect. As Adam says, they just need to be ‘good enough to push your thinking forward’.
Cat Drew is Uscreates’ Delivery Director. She oversees delivery and direction of projects by using data and design techniques, ensuring that they link to the client’s wider strategic objectives and deliver impact. Previously Cat was a senior policy advisor at Policy Lab, working with government departments to promote design-based techniques in policymaking, and Head of Policy IT & Digitisation Policy at the Home Office. She was responsible for supporting police forces to digitally transform their services and processes by working with tech experts and other forces to co-design digital capabilities that set out what a digital force looks like. Prior to that Cat was Head of Neighbourhood Policing at the Home Office, and a researcher at IPPR.