Data-driven decision making in the community college context

This case study explored how data-driven decision making occurred within institutional planning activities at a California community college. The problem statement for this research was that the practice of data-driven decision making for program effectiveness within community colleges has not been clearly defined and understood within the literature. The research question asked, "What enables data-driven decision making within a variety of routine planning activities, including how do practitioners employ data-driven decision making and what processes are utilized in data-driven decision making?" This study utilized a descriptive case study methodology. A descriptive case study is an empirical inquiry that investigates a case in depth and within its real-world context (Yin, 2014). Using a combination of one-on-one interviews, document review, and observations, this study gathered data on organizational routines and processes, the people involved in planning, and the process and tools used within planning. Three major findings were that (a) data-driven decision making is enabled by organizational structure, dialogue, the availability of data reports, and support and guidance by institutional research professionals; (b) practitioners employ data-driven decision making by tracking various metrics, detecting barriers to goals, identifying needs, and adjusting practices accordingly; and (c) stakeholders within a college approach institutional planning with certain expectations and assumptions that reflect the college's broader culture. The findings indicated: (a) the design of the college's institutional planning structure and processes impacts how data-driven decision making is employed at a college; (b) stakeholders tend to form meaning together and dialogue about data is one avenue that facilitates the meaning-making process; (c) data collection is key, thus the research questions guiding data collection are also key; (d) the data-driven decision-making process includes using data to reach a decision as well as acting on or responding to the information or newly created knowledge; and (e) the practice of data-driven decision making is influenced by organizational culture. The recommendations suggest ways that community colleges, leaders, and practitioners can support or facilitate data-driven decision making within institutional planning activities.