By Noel Schroeder–
In the clamber for more, better, and bigger development data in the era of the Sustainable Development Goals, the spotlight is most often on large, national-level sets of information. “Big Data” is regularly prioritized by governments, donors, and businesses as the most efficient and effective means to inform and therefore achieve successful, sustainable development policy making.
The problem is that this probably won’t work.
Agenda 2030, the declaration of the 17 Sustainable Development Goals (SDGs) states that “quality, accessible, timely and reliable disaggregated data will be needed to help with the measurement of progress and to ensure that no one is left behind. Such data is key to decision-making.” Data is undeniably important: we need to understand who is more marginalized and what solutions work to ensure the full achievement of social, political, and economic rights. But the emphasis on Big Data in service of sustainable development outcomes excludes the contributions of grassroots organizations, who have extensive on-the-ground evidence of what works best in development because their data sets are too small or methodologies not rigorous enough. This does a disservice to the evidence-based development that the SDGs are trying to achieve, and risks leaving behind those who are already systematically excluded from decision-making and power.
It also ignores the way that development policies actually get made.
We like to think that government officials pore over pages and pages of statistics, consult experts, and come to a policy decision based on a careful analysis of the evidence. That’s not quite accurate, unfortunately. A recent study demonstrated that government officials “lacked capacity to analyze or interpret data” and “that they had to make decisions too quickly to consult evidence.” While this study was conducted with civil servants only in India and Pakistan, we have heard from grassroots groups across the Global South of similar challenges in getting decision-makers to read, understand, and utilize their data.
Part of this challenge has to do with the kind of data being presented to decision-makers. Large, complex data sets may be comprehensive, but they are not always the most persuasive. Bureaucratic constraints, deadlines, and a lack of sophisticated understanding of statistics lead government officials (and all humans, really) to more often than not use mental shortcuts and prior knowledge to make complex decisions about development policies.
There is a way to overcome these challenges and help government officials to make informed decisions: we must foster and amplify the evidence from grassroots advocates. The study authors explain that “in cases where the policymaker holds strong beliefs and is inclined to discount evidence, an intervention to soften the policymaker’s priors may be more useful than generating rigorous evidence.” This is especially important for grassroots advocates working towards gender equality, an issue with very strongly held beliefs on all sides.
Stories, case studies, anecdotes, and reports from grassroots gender equality advocates are as much true evidence as Big Data. This kind of qualitative evidence (sometimes denigrated as ‘soft’) is crucial: it provides context, demonstrates an effect, and helps decision-makers (again, who are fellow humans) to understand the personal impact of development policies and programs.
When Women Thrive Alliance works with advocates to create impactful advocacy strategies, we stress the importance of coupling easy-to-understand quantitative data with persuasive stories that showcase authentic voices of women and girls. Rita from Women Thrive Alliance member organization Women For a Change Cameroon recognized the importance of grassroots data and shared with others during a Raise Your Visibility online course, “one of the best ways we can persuade someone to act is through storytelling.”
In an era in which we are attempting to create monumental, transformative change in development, we cannot afford to leave the data contributions of grassroots advocates behind. The data revolution for the SDGs needs to focus less on accumulating Big Data and more on tapping int0 the already-existing immense stores of data that grassroots civil society holds. Grassroots advocates need access to the funding that is currently being funneled to generators of big data. With greater support, they can leverage and amplify their evidence in a way that will actually influence development policy making.