Emotion, empathy and ethnography in policy-making
The last decade has been marked by a significant shift in the debate about the relationship between the citizen and the state. Around the world, in order to remain relevant, organisations have undertaken significant transformation to become more ‘human-centred’.
But what does this mean for policy-making? Beyond the headlines of populism, long after election campaigns are over, how might policymakers better understand citizens’ perspectives when designing policy? Put another way, how should we improve and innovate the way policy is made to ensure it becomes more human-centred?
Over the last four years the Policy Lab has been exploring the use of ethnography as a tool for policy-making. Ethnography offers an approach to deeply understand peoples’ lives. This can contribute to a body of evidence that informs future policies, which can be tested at a later stage. This blog looks at how to best involve citizens’ ‘lived-experiences’ in the policy-making process and how to combine it with other forms of data.
Ethnography in policy-making
The term ethnography comes from latin, with ‘ethno’ meaning people and ‘graphy’ meaning writing. In the early days of the field, anthropologists would visit communities and write down their observations in journals, spending months and sometimes years in a place to become deeply connected to its people and their ways of life. Historically, the most important methodological principle of ethnography is participant-observation fieldwork. This means our Policy Lab ethnographers spend a lot of time out around the country with the people affected by government policies.
Since the 1980s, the corporate world has embraced ethnographic techniques and adapted them to their practical objectives. Companies like Red Associates in Copenhagen and Ipsos MORI in the UK use ethnography with large corporations to help them better understand customers. However, governments around the world have been slower to integrate these techniques into their policy-making toolkit.
Kyna Gourley joined the Policy Lab as the UK Government’s first in-house film ethnographer in 2015 and since then has spent hundreds of hours with different people documenting and sharing their experiences. She’s attended job centres in partnership with DWP and visited national parks for our work on Defra’s Independent Landscapes Review. This kind of data, using rich visual film, helps policy-makers understand individual human behaviours, revealing not just what is happening but also why it is happening.
Ethnographic research also helps individuals and communities have more agency when sharing their experience of a policy issue, because ‘ethnographic interviews’ are by definition open and offer research participants the platform to say what is important to them, in their own words. Through the ethnographer’s camera, they can show policy-makers the reality they live in, deciding what policy-makers should know about them or their experience.
Over time the Lab has expanded its ethnography team and now regularly involves the public in shaping future government policies using a variety of techniques. We have found ethnography to be particularly valuable when working with under-represented groups, but it also adds value to many others - even policies that don’t have obvious services or traditional ‘user needs’.
How is ethnography different to other qualitative research methods?
As a tool for policy-making, ethnography is different to traditional qualitative research techniques like consultation. It generally involves smaller numbers of people and provides much deeper insights in a way that is more open-ended and doesn’t have to preempt particular lines of enquiry. Our participatory policy design ladder (below) shows how ethnography fits into the shifting power dynamics towards the citizen.
Big data and ‘thick’ data
Compared with quantitative data, ethnography creates different forms of data - what anthropologists call ‘thick data’. Complex social problems benefit from insights beyond linear, standardised evidence and this is where thick data shows its worth. In Policy Lab we have generated ethnographic films and analysis to sit alongside quantitative data, helping policy-makers to build a rich picture of current circumstances.
On the other hand, much has been written about big data - data generated through digital interactions - whether it be traditional ledgers and spreadsheets or emerging use of artificial intelligence and the internet of things. The ever-growing zettabytes of data can reveal a lot, providing a (sometimes real time) digital trail capturing and aggregating our individual choices, preferences, behaviours and actions.
Much hyped, this quantitative data has great potential to inform future policy, but must be handled ethically, and also requires careful preparation and analysis to avoid biases and false assumptions creeping in. Three issues we have seen in our projects relate to:
- partial data, for example not having data on people who are not digitally active, biasing the sample
- the time-consuming challenge of cleaning up data, in a political context where time is often of the essence
- the lack of data interoperability, where different localities/organisations capture different metrics
Through a number of Policy Lab projects we have used big data to see the big picture before then using thick data to zoom in to the detail of people’s lived experience. Whereas big data can give us cumulative evidence at a macro, often systemic level, thick data provides insights at an individual or group level. We have found the blending of ‘big data’ and ‘thick data’ - to be the sweet spot.
Policy Lab's work develops data and insights into ideas for potential policy intervention which we can start to test as prototypes with real people. These operate at the ‘meso’ level (in the middle of the diagram above), informed by both the thick data from individual experiences and the big data at a population or national level. We have written a lot about prototyping for policy and are continuing to explore how you prototype a policy compared to say a digital service.
Emotion as a source of evidence
Having gathered ‘thick data’, how might policy-makers handle the emotional perspectives captured in data from individuals? How for example, can policy-makers be sure this isn’t just anecdotal?
In each project, Policy Lab’s ethnographers review the existing evidence and then use ethnography to understand the more complex narrative behind the big data and statistics. It is the job of the ethnographers to guide policy-makers through the analysis stage so that they too are included in this process. To do this, our ethnographers use storytelling techniques to summarise often complex research findings into thematic films. These can be shared easily with the policy team and are available to be shown again within the department and with ministers.
Our project on the future of rail is one example where including emotional responses in the research narrative revealed a fresh perspective to policy team and service providers, beyond the usual performance data such as train punctuality. By shadowing rail passengers, we revealed individual's anxieties about travelling, for example getting pushchairs on and off trains in a short time. To many people, this experiential approach is simply common sense. However, finding effective ways to marry this data with the rigorous, objective standards of evidence needed to inform policy requires careful consideration.
Future policy-making will continue to require strong quantitative evidence (including big data). This will become more readily available at scale and in real time, but we think there is also a really important role for qualitative insights (thick data) from ethnography to add into the mix. And whilst it is early days for the application of ethnography in policy-making the early signs from the Policy Lab are positive. We are therefore reaching out across government to share experience though a recently established anthropologist network. If you are interested in learning more do get in touch by emailing us: email@example.com.