As the data cycle nears its end, and the data has been systematically collected, analyzed, and visualized, it will be important to make sure that all the work was not done for nothing. In fact, all the work that the program has done leads to this critical step in the data cycle, which is often and unfortunately missed. The deliberate use of data in ways that contribute to continuous improvement efforts. This does not diminish other decision-making strategies, but it does promote informed decision-making, is more relatively unbiased, and is structured in a way that is often agreed upon by a diverse set of stakeholders. Using data to drive program enhancements or individual candidate feedback is the best mechanism for creating a structure for continuous improvement. 

Data use should occur at multiple levels throughout the program on both a scheduled and ad hoc basis. In other words, using data can be embedded into the program in formal and informal environments. Formal data use can occur at scheduled meetings where data is systematically reviewed and an established protocol is employed to review and discuss data. In these settings, conclusions for improvements can be reached and strategies developed for implementing those improvements. In informal settings, data is accessed in the context of discussions that are driven by other priorities. In these settings, data can still aid in decision-making but are more applicable to subsidize other processes.