Systems Learning™
Born of our positionality, rooted in systems thinking, and optimized for equity and learning, Systems Learning™ is based on the premise and belief that stories are not merely enhancements to evaluation, but rather that all of evaluation is the act of storytelling. Equitable evaluation is about producing truer stories based on a credible body of evidence – credibility not from numbers, but from the testimony of witnesses closest to the ground.
Systems Learning™ is a systematic approach for building a body of evidence that inextricably links data with a diversity of perspectives, prioritizing those closest to the work and those most affected by the work. We see positionality not merely in terms of the sometimes problematic “identity” categories we often use to define it – such as race, ethnicity, sexuality, gender, poor, immigrant. Rather, we believe Edgar Villanueva says it best in Decolonizing Wealth, “Those most excluded and exploited by today’s broken system possess exactly the perspective and wisdom needed to fix it.” That is how we see positionality and its value – and we humbly count ourselves in that group.
Systems Learning™ is a storytelling approach that elevates perspectives to scrutinize numbers because, as Deborah Stone states in her book, Counting, “Every number is born of subjective judgments, points of view, and cultural assumptions. Numbers are filled with bias through and through…” Ultimately, numbers are stories, as Brené Brown suggests in her adage that “stories are just data with a soul.” Numbers are always in service of a purpose and agenda. Scrutinizing numbers is particularly important when the work at hand intersects the trifecta of wicked problems: poverty/income inequality, health/education disparities, and racism/discrimination. These involve many interacting variables that are evolving in dynamic social systems and contexts with factors that are often incomplete, in flux, and difficult to define.
Wicked problems are associated with fast thinking, which Daniel Kahneman in Thinking Fast and Slow calls our “jumping-to-conclusions machine,” where assumptions and biases go unchecked. Fast thinking has no time for context or perspective, which is where, according to David Epstein in Range, we are most likely to find solutions to wicked problems. Slow thinking, conversely, is where we are explicit and intentional about challenging assumptions, exposing biases, and revealing new stories that give context and meaning to data. Systems Learning™ is designed to facilitate slower thinking for emergent learning about wicked problems. Slower thinking informed by a diversity of perspectives surfaces breakthrough solutions.
Reach out today to discover how Systems Learning™ can transform evaluation for your organization.