Three examples of data empowerment
It was a humid December afternoon in Banda Aceh, a bustling city in north Indonesia. Two women members of an education reform advocacy group were busy preparing infographics on how the city government was spending its education budget and its impact on service delivery quality in schools. The room was abuzz with questions and apprehension because the next day, the group would present its analysis on the data that they were able to access for the first time to education department officials. The analyses uncovered inefficiencies, poor school performance, ineffective allocation of resources, among others.
While worried about how the officials would react, almost everyone in the room was cheerful. One advocate told me she found the whole process liberating. She found it exhilarating to use government-published data to ask civil servants why the state of education in some schools was disappointing. “Armed with data, I am no longer afraid to speak my mind,” she said.
This was five years ago, but the memory has stuck with me. It was one of many experiences that inspired me to continue advocating for governments to publish data proactively, and searching for ways to use data to strengthen people’s voice on matters that are important to them.
Globally, there are many examples of how data has enabled people to advocate for their rights, demand better public services or hold governments to account. This blog post shares a few examples, focusing largely on how people are able to access and use data that shape their lives — the first dimension of how we characterize data empowerment.
Poverty Stoplight: People use their own data to improve their lives
One of my favorite examples is the Paraguayan NGO Poverty Stoplight, which treats people as more than just data providers. Instead, people take an active role in defining and diagnosing their well-being and charting a path out of poverty for themselves and their families based on their skills and assets. While Poverty Stoplight collects people’s data, it also allows, and even supports them, to use their own data to assess themselves and improve their well-being.
Development organizations and practitioners, myself included, often treat people as mere research subjects, in order to provide input about their condition so that program designers can come up with ways to lift them out of poverty. Poverty Stoplight changed that paradigm and recognizes individuals’ agency in their own data, lives and future.
Data Zetu: Giving borrowed data back to citizens
Among the many initiatives of Data Zetu, a nonprofit organization based in Tanzania, I find the Shareback Session particularly powerful. The program has collected a tremendous amount of data about people and their communities and decided to “share this data back” with the very people who produced it. The Shareback Sessions provide people with the opportunity to discuss what the data says, collectively define problems and strategically find ways to address those problems. Like Poverty Stoplight, it recognizes individual agency, and solemnly respects each individual’s local knowledge.
Although it is an ethical research practice for researchers to communicate their findings to participants, in many instances, researchers but also NGOs that collect data from people fail to go back to the field to inform research participants about the findings, and how their data was used to arrive at these findings. When it does happen, it is often a one-way conversation informing people about conclusions drawn about them and their lives, rather than Data Zetu’s impactful collective discussions, problem-solving and implementation of solutions.
Check My School: Data-based community action to improve school performance
Check My School is a participatory and community-based monitoring and school-improvement approach in the Philippines. It starts by working with community stakeholders to collectively access and analyze school performance data. Based on the data, parents, students and other stakeholders openly discuss the problems and potential solutions with government service providers to improve the quality of instruction, facilities and support school services.
In this case, people are not just sources of complaints, but also solutions. They actively participate in school governance processes. Check My School also provides citizens with the opportunity to monitor the performance of government-run schools, from procuring chairs and textbooks, to completing construction of new schools and buildings.
How we treat people and their data: the main difference
The key unifying thread of these examples is how people and their communities are viewed in designing and implementing development projects. People are not treated as data farms; they are regarded as the active producers of data, with the capacity to use it for their own, and their communities’, wellbeing. People are not treated only as data providers, but as data users with the contextual knowledge and information to help solve the very problems they are confronted with. Finally, people are not treated as recipients of a development intervention; they are partners in co-creating solutions aimed to improve their lives and societies.
This, I would argue, is the fundamental and foundational standpoint of data empowerment advocates. This paradigm asks more of those designing and implementing development programs. In our next post, we will explain how to embed this frame of thinking in designing data innovation projects, as well as framing how we need to do development differently.
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