This post was co-written by Nonso Jideofor and Kate Vang, Data Scientist at ONE. ONE advocates for ending extreme poverty and preventable disease, in part through data-driven policy change.
Earlier this year, The Engine Room and ONE partnered to better understand how civil society in Sub-Saharan Africa is using data to achieve policy reform. Our joint research focused on actors already working with data in their policy reform efforts, and we looked at the role that data already plays in their initiatives. We conducted semi-structured interviews and design workshops with advocacy actors, policy experts, data specialists and journalists in Nigeria and Ghana. Together, we explored how they define and approach policy reform; when they collect, analyse and disseminate data; and how they coordinate with other actors to achieve their goals.
Our findings have implications for how the international data community supplies data to local actors, expects data to be used, and supports further work with data. We would love to chat with you if you have any thoughts on the research, want to share related work, or want to ask questions!
What we learned
The international open data community asks regional, national and sub-national actors to use existing data, but many of these actors prioritise collecting new data instead.
(Here, we use the term ‘existing data’ to include official and unofficial data typically in the form of international indices, reports, official statistics, national budgets or contracts.)
We found three common reasons for why the actors we spoke with prioritise firsthand collection over using existing data sources:
- One, they don’t see a clear application for this existing data to their work. They understand the data, but find it unrelated to their activities and goals.
- Two, they don’t trust the data. Actors are unsure about who collected it, what their methodology was, and if they manipulated the data for their own needs or not.
- Three, they receive praise and recognition for collecting new data. One reason for this is that civil society actors often compete for funding and funders ask them for new knowledge.
- Finally, respondents also noted that at times it’s easier to collect data than ask for, or interpret, existing data. For example, engaging with governments to get official sources is time consuming and doesn’t always result in requested, credible or easy-to-interpret data.
In the end, we concluded that the perceived benefits of working with existing data do not outweigh the perceived costs.
International actors often view policy reform as one long, continuous process, whereas data-savvy actors in sub-saharan Africa approach it as having two fairly distinct phases.
The first phase they perceive is marked by short-term, intense advocacy around broader issues – including service delivery, human rights, transparency and more. The phase second is a long-term, slow, incremental transition from advocacy around an issue to policy reform. When focused on the first, they are not necessarily thinking about the second. We found two reasons as to why it is difficult to connect these short- and long-term goals.
- One, data actors don’t focus on the long-term goals of the second phase because achieving them often depend on factors outside their control, such as political will.
- Two, data collection is useful for achieving short-term outcomes, but long-term goals require the difficult tasks of coordinating with other actors and working with diverse datasets.
Overall, we observed that issues can garner strong momentum – on their own – that would move them from the first to the second phase. This momentum is often sparked by a complex set of influences that can be difficult to disentangle. In this context, we found that strategically working with data in the first phase is critical to sparking momentum and moving into the second, longer-term phase.
International actors are aware of success stories about working with data for policy reform, but actors involved in these successes haven’t reflected on them.
Though actors we spoke with were aware of successful uses of data for policy reform, they did not frequently reflect on them to extract their methods and tactics or to share them for replication. We found the following reasons for this:
- One, actors using data do not prioritise or invest time into unpacking how they are using data. In many cases, they may not see the benefit to this.
- Two, data-savvy actors primarily share stories about their successes to promote their work, inspire others, or to find collaborators to do raise funds. They more rarely – and perhaps forget to – share stories in order to encourage peers to adopt successful techniques that were used to achieve their goals.
Our research illuminated that sharing successful data efforts is common practice but that the reasons for sharing may be missing an important point. Sharing success stories with an emphasis on how to replicate good processes (instead of just sharing interesting stories) can lead to more effective work at-scale.
Our research gave us a lot of things to think about. In particular, we’ve started to ask ourselves these three questions:
- How do we raise the value of working with existing data and not just make it easier to access and use?
- How do we encourage a stronger link between short-term advocacy activities and longer term strategies for policy change?
- How do we move beyond just promoting data-driven work more generally and towards promoting specific and effective tactics for working with data?
Moving forward, we aim to design ways of working that help us answer these questions. We hope that you will be inspired to do so as well. And if you do, let’s stay in touch to exchange notes! You can reach Nonso at email@example.com and Kate at firstname.lastname@example.org.