Advising in an Imperfect World – Expert Reflexivity and the Limits of Data

Article by Justyna Bandola-Gill, Marlee Tichenor and Sotiria Grek: “Producing and making use of data and metrics in policy making have important limitations – from practical issues with missing or incomplete data to political challenges of navigating both the intended and unintended consequences of implementing monitoring and evaluation programmes. But how do experts producing quantified evidence make sense of these challenges and how do they navigate working in imperfect statistical environments? In our recent study, drawing on over 80 interviews with experts working in key International Organisations, we explored these questions by looking at the concept of expert reflexivity.

We soon discovered that experts working with data and statistics approach reflexivity not only as a thought process but also as an important strategic resource they use to work effectively – to negotiate with different actors and their agendas, build consensus and support diverse groups of stakeholders. What is even more important, reflexivity is a complex and multifaceted process and one that is often not discussed explicitly in expert work. We aimed to capture this diversity by categorising experts’ actions and perceptions into three types of reflexivity: epistemic, care-ful and instrumental. Experts mix and match these different modes, depending on their goals, preferences, strategic goals or even personal characteristics.

Epistemic reflexivity regards the quality of data and measurement and allows for a reflection on how well (or how ineffectively) metrics represent real-life problems. Here, the experts discussed how they negotiate the necessary limits to data and metrics with the awareness of the far-reaching implications of publishing official numbers.  They recognised that data and metrics do not mirror reality and critically reflected on what aspects of measured problems – such as health, poverty or education – get misrepresented in the process of measurement. And sometimes, it actually meant advising against measurement to avoid producing and reproducing uncertainty.

Care-ful reflexivity allows for imbuing quantified practices with values and care for the populations affected by the measurement. Experts positioned themselves as active participants in the process of solving challenges and advocating for disadvantaged groups (and did so via numbers). This type of reflexivity was also mobilised to make sense of the key challenge of expertise, one that would be familiar to anyone advocating for evidence-informed decision-making:  our interviewees acknowledged that the production of numbers very rarely leads to change. The key motivator to keep going despite this, was the duty of care for the populations on whose behalf the numbers spoke. Experts believed that being ‘care-ful’ required them to monitor levels of different forms of inequalities, even if it was just to acknowledge the problem and expose it rather than solve it…(More)”.