In the early 1990s, a revolutionary movement emerged in the international development research community using collaborative methods and bottom-up approaches to not only create knowledge through qualitative inquiry but also to define criteria and indicators to quantitatively measure key concepts, program results, and impact (Holland 2013, 1). Proponents argued that collaborative methods often provide a more accurate and complete picture of the reality on the ground. In addition, including local people in the process of designing measurement tools allows their perceptions and priorities to be communicated to policy makers even in a quantitative format (Chambers 2010; Firchow 2018; Holland 2013). Thus, international development researchers have used quantitative collaborative methods to develop participatory statistics— sometimes called participatory numbers—to design, monitor, and assess the impact of projects, programs, and policies (Gaillard et al. 2016). This article explores the use of one collaborative methodology applicable to the field of political science, with particular emphasis on scaling it for use at higher levels of analysis.