Does Data Matter? Exploring how nonprofits working with abuse victims in Edmonton utilize data to inform service delivery

  • Author / Creator
    Draga, Solomiya
  • This study explores data collection and utilization at four non-profit service organizations in Edmonton, Alberta. Participating organizations work with female victims of violence, abuse and exploitation. Through in-depth, semi-structured interviews, I explore the types of data collected at each organization, the reasons behind data collection, and how information is utilized in decision-making. I also analyze organizations’ client paperwork, data management software, and annual reports. Finally, I supplement this study by conducting a statistical analysis of a quantitative dataset obtained from one of the participating organizations. The results of this study are contextualized via Resource Dependence and Rational Choice Theories. The findings suggest that non-profit organizations in Edmonton allocate significant resources to collecting, documenting, analyzing and storing client data. This includes demographic information, information about service provision, qualitative feedback, wellness assessments, and historical narratives. Data is collected to help organizations manage daily activities, inform their practice, satisfy funder requirements and obtain additional funding. However, I argue that organizations face significant barriers to collecting and managing their data. Organizations lack the financial and human resources required to effectively manage client data. As a result, organizations are restricted in their ability to utilize client data in decision-making. Therefore, organizations predominantly rely on easily-accessible sources of information such as staff observations, client feedback, and anecdotal evidence. They are largely unable to make full use of their quantitative data. Yet quantitative data can be greatly beneficial to organizations’ decision-making practices. This research suggests several solutions to addressing organizations’ current barriers related to incorporating quantitative data into decision-making.

  • Subjects / Keywords
  • Graduation date
    Fall 2018
  • Type of Item
  • Degree
    Master of Arts
  • DOI
  • License
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