Shared Measurement and Big Data For Good
Traditional tools for evaluation and measurement fail to take into account the complexity of an interconnected and digitized world. Emerging techniques, such as developmental evaluation, improve on traditional linear, cause-and-effect models, while shared measurement increases the capacity of cross-sector collaboration. In this panel discussion, experts offer a case study-rich overview of three emerging tools: developmental evaluation, shared measurement, and big data. Kathy Brennan describes how developmental evaluation adopts a systems-learning approach absent from formative and summative designs, making it more favorable to evaluating complex, non-linear, and dynamic social realities. Patricia Bowie discusses the importance of shared measurement as a catalyst for collective learning. Researcher Lucy Bernholz warns that data collection offers as much peril as potential, and implores the nonprofit sector to think critically about how digital data is driving actions and whose voices it excludes. Presented in partnership with FSG, this panel discussion was part of the Next Generation Evaluation conference.