How Can We Translate Data Science into Policy?

“Consulting researchers for evidence is not in the culture of African leaders but it is our role to make them appreciate this approach.” A participant at a Data Science Africa event - 2023 - in Kigali

Data Science Africa (DSA) has built a strong foundation of data literacy through its various programs and training events and continues to nurture a community of African data scientists. At a recent event in Kigali, the community sought to take the impact of DSA to another level by exploring the potential of research and projects to support effective data-driven policy-making in Africa.

I was interested in this, having experienced firsthand the need to link data science with decision-making while working as a data analyst at UN Global Pulse Kampala. Last year, I worked with DSA to curate a series of talks, one-on-one conversations, and open discussions, all of which proved very enlightening. The aim was to empower participants to think beyond developing data-centric solutions and consider how data science might affect policy-making.

At the Kigali event, the highlight was an open discussion in which we examined challenges, explored our role as data scientists, and spotted opportunities for research on how data science can support policy.

In a room full of data-driven solution developers, with only a handful of decision-makers, participants had a lively discussion that showed diverse perspectives. Yet a notable consensus was evident – a shared recognition of the role data scientists can play.

Participants were asked what challenges they had experienced in translating data science solutions into pointers for practical policy.
“It’s challenging to explain the data science solutions to policymakers,” said one.
“The needs of decision-makers are ever-changing, making it hard to find or generate relevant and timely evidence,” said another.
A third noted: “There are many other things that influence policy, e.g., politics, which hinder data use.”

The discussion showed data scientists feel responsible for communicating their findings in ways that make sense to policymakers.
“We need to begin projects with an end in mind,” said one. “We are not doing data-driven projects for the sake of it but so that the solutions can be utilized.”
“We need to produce impact-oriented research, which takes time and probably more resources but increases the chances of it being used to inform decision-making,” said another.

A number of speakers noted the need for data scientists to try to understand policymakers and engage in conversations that can influence policies. Some went as far as to suggest that data scientists should start looking at playing other roles, “not just coding”, to increase the chances of influencing policy.
“Consulting researchers for evidence is not in the culture of African leaders but it is our role to make them appreciate this approach,” said one bold thinker.

As our keynote speaker, we were lucky to have Diasmer Bloe, a strategy and evaluation professional from Data for Policy, a global forum for knowledge-sharing and collaboration on evidence-based practices. (Diasmer is the researcher on the Africa Engagement Project, which aims to boost African academic, industry, and policy participation in the Data for Policy community.)

Diasmer enlightened us with valuable insights into data-driven policy-making and shed some light on how well it was going in Africa. She highlighted challenges in this area, which resonated with our concerns. For example, we learned that policymakers are increasingly interested in making use of data science but are still limited by their access to data, capacity to make sense of it, and financial resources.

My own involvement in facilitating these sessions has taught me that both data scientists and policymakers must bridge the gap between scientific findings and policy decisions.

According to Data for Policy, policymakers need to learn how to be both consumers and producers of evidence. This requires them to learn about different data sources and data-driven methods. From our side, we data scientists need a better understanding of policymakers’ challenges in order to raise their confidence in data-driven projects.

Among prevailing issues, DSA recognizes the challenges with data discoverability, sharing, and interoperability; the limitations of human and technical capacities; and the legitimacy of public concerns. But the DSA community sees these challenges as opportunities, driving our work to strengthen policy with hard evidence.

After the event, I was left pondering a question from the DSA chairperson, who asked: “Are there solid examples of use and impact that justify the need for data integration into policymaking?” In other words, is data science credible? What do we need to do to raise public trust? And how can we create a data-driven culture in public institutions? For community members, these are potential research questions.

Indeed, the journey ahead is exciting as we empower the community to innovate solutions and build policymakers’ trust. An interdisciplinary community with a shared interest in the potential and effect of data science on policy is only the first step. DSA wants members to explore more avenues and opportunities.

We welcome your stories of successful data-centric solutions. If you would like to get in touch, you can contact DSA here: info@datascienceafrica.org