At Living Cities, we think of the use of data for collective impact as a continuous “feedback loop” that helps you change behavior and create systemic change in communities. The goal of this data-driven feedback loop is learning and improvement.
Developing a strong data-driven feedback loop requires discussing assumptions with your collective impact partners. Your partners may hold assumptions (correct or not) about any number of things, and you should make sure any conversation about data involves a conversation about root causes of problems. If you don’t understand why certain problems exist, it’s unlikely that you can determine effective strategies for solving those problems.
Our Prepare Learning Circle sites, which are a part of the StriveTogether network, have gone through a factor analysis process to determine root causes that influence their ultimate shared result. The attached resource contains a factor analysis example from All Hand Raised for their work of increasing post-secondary training. You can use this example as a template for facilitating your own factor analysis discussions.