This paper presents findings from an analysis of data driven decision-making in nonprofit organizations that house social enterprises, or businesses that have both social and financial goals. The findings constitute one key component of a mixed-methods evaluation that includes an implementation study and outcomes evaluation of workers in California-based social enterprises receiving support from REDF, a San Francisco-based venture philanthropy organization. Organizations selected for the study were those that serve individuals facing the greatest barriers to work (for example, over 85 percent of workers have a criminal history and over 80 percent have been homeless in the past year).

 The potential of data to support effective decisions might be especially important in organizations that incorporate both business and social concerns into their mission. Such organizations frequently face conflicting objectives created by an attempt to maximize a double bottom line of both fiscal performance and positive social impact. As such, organizations that engage in socially responsible businesses, but in a manner that provides a return on their investment, might benefit from using data both to make decisions about financial viability and to increase the welfare of the populations they seek to serve (the “double bottom line”). Their need to collect, analyze, and use data might be greater as they must track information on business operations, finances, customers and the social return on investment. Indeed, the potential of data to support effective decision-making related to meeting the needs of target groups has led some foundations, including REDF, to require the organizations they support to use data to inform and improve practice. The question of using data to support organizations seeking to maximize a double bottom line is not, however, well researched. Yet, evidence suggests that data driven decision making might not be emphasized. A recent survey of about 400 non-profits, however, suggests that while 89 percent tracked data about their finances, only about 50 percent consistently tracked data on how their work affected the people it was designed to help. In order to explore the potential of data to support social enterprises, this paper will focus on analyses designed to address the research question, How do social enterprises use data to make decisions about target populations and business operations? We will present analyses of both qualitative and quantitative (survey) data about the types, analysis, and uses of data as well as resources for and attitudes toward data driven decision making in the nine social enterprises as they attempt to meet a double bottom line and provide both a social and economic return on investment.