Over the past 18 months, the Trussell Trust, the UK’s biggest foodbank, has been exploring its data in new ways. Working with researchers from Hull University Business School, data science firm Coppelia and social innovation agency AAM Associates, the project honed in on new insights and ways of viewing its network, which has undergone rapid growth in the past five years.
As well as producing analytical assessments of food bank usage, a mapping tool was also developed to show how the trust’s users are distributed geographically. Heat maps showing usage – the darker the colour, the greater the demand – allowed the visualization of regional patterns of need.
Open data added further richness by building a predictive model. Census data (e.g. unemployment levels and other deprivation indices) were aligned to the wards where food bank usage was most prevalent, to suggest where the Trust’s resources may be needed elsewhere in the country. This helps the charity to take a strategic review of UK need, as well as responding to community-led requests for new food banks.
So far, so good in proving the strategic and operational gains to be drawn from existing datasets. But there is so much more to do.
Introducing the Data Studio
In early July University of the Arts London (UAL) is bringing together a group of people from different backgrounds to combine their ways of analyzing and visualizing data and to explore what new insights and methods might come from doing this. We aim to build new connections between two kinds of expertise – design thinking and data science – through a small experimental project we are calling the Data Studio which will take place on 11-12 July at Central Saint Martins in London.
The premise behind the Data Studio is that designers and artists have approaches that help with the gathering, organising, presenting and interpreting of data to shape idea generation, decision making and action. While there are some data science specialists who recognize the importance of visualizing data to people being able to interpreting it, much of the discussion about data science can be disconnected from some of the other competences associated with design – starting with end user perspectives, reframing issues, turning insights into ideas, prototyping solutions and involving people in co-design.
Over the past decade design thinking and service design have become increasingly visible as capabilities that commercial, public and third sector organisations building into their teams. A book by Tim Brown, head of the design consultancy IDEO published in 2009, introduced the term design thinking to the business world. A recent book with the title Sprint shows how Google Ventures brings together collaborative teams to explore issues and generate and prototype solutions in intense five-day bursts.
Funded by UAL, the Data Studio builds on and extends a project funded by the ‘New Economic Models in the Digital Economy’ group (NEMODE, part of RCUK) and managed by the University of Hull. In that project data produced by the Trussell Trust, a network of over 400 food banks, was analysed to produce a visualization of usage.
A conventional ‘design thinking’ approach would start with exploring an issue by generating insights into the lived experiences of stakeholders, for example users of food banks and their families, as well as donors, volunteers and others in the ecosystem. The kinds of data typically generated are ethnographically-informed, nuanced pictures of people’s lives as they engage with services. This approach is interventionist and aims to use insights to generate or shape new service or product concepts.
A typical data science approach would start with exploring a problem by combining digital data from one or more data sets and identifying patterns to inform decision making. For example the prototype application created with the Trussell Trust uses anonymised postcode data taken from foodbank vouchers to map foodbank use per head of the population down to electoral ward level in combination with census data. It produced a visualisation that gives the Trust and local food bank managers a detailed understanding of how their users are distributed geographically.
By combining both these approaches in the Data Studio, we aim to generate insights and prototype concepts that are oriented towards action by combining big data with ‘thick’ data and perspectives from different parts of the ecosystem. These insights will, we believe, open up ways of thinking about food bank usage and result in new directions for strategic decision making, data gathering and digital engagement.
The Data Studio will bring together about 20-25 people from different backgrounds to work together experimentally to combine different approaches to combining data, generating insights, identifying opportunities and proposing new service concepts. Participants come from academia, policy, the voluntary sector and small business with a wide range of specialist knowledge in design, data science, sociology, organizational change, textiles and fine art.
Please get in touch if you would like to apply to be involved in the Data Studio. We are aware that the London Datastore is used by professionals from a range of disciplines and we are especially interested in hearing from those with a specific interest in food security and community poverty and those who may already be working with datasets (open or closed) that could add extra value to this investigation. But anyone with an interest in data science or design thinking is welcome to apply.
Our hunch is that the mix of these perspectives and ways of thinking about and using data will result in new insights about the Trussell Trust’s data but also for data scientists more broadly. The outputs will include an illustrated report for the Trust and a more public summary of the insights, methods and implications for people working in data science and design thinking.
|Lucy Kimbell,||Andy Hamflett|
|Director, Innovation Insights Hub,||Co-Founder and Director,|
|University of the Arts London.||AAM Associates|