Data driven decision making at non-profit social impact organizations: A case study of Amnesty International

Abstract: Decision making is deemed one of the most influential and impactful activities in an organization. Yet, it is often based solemnly on the decision makers knowledge, experience, and instinct, disregarding the quantitative evidence which can be obtained from data generated in the organizations processes. This thesis aimed to investigate how data and data analysis may support decision making in non-profit social impact organizations. It does so by studying the Swedish Section of Amnesty International. Through interviews with employees and reviews of data, the study explores what data is generated in the organizations processes, what tasks and decisions need additional information as decision basis, what analysis can be made to obtain such information, and lastly what technical and organizational process that must be in place for implementing continuous data analysis measures. The study found that Amnesty mainly collect data of two categories, namely member- and donor related data, and data related to communication efforts. Identified information needs concern member- and donor behavior, as well as the performance of communication efforts. Categorizing communication material and segmentations of people that engage with Amnesty has been identified as valuable measures for aiding decision making. Furthermore, major changes in supporting infrastructure and activities are considered necessary for enabling data driven decision making. Lastly, the thesis discusses the degree to which findings are general. Many of the projects’ conclusions stem from that Amnesty is member-based and have a large focus on communication with the public, just as many other non-profit social impact organizations. The thesis is thus considered valuable and applicable also for other organizations in the same space.