Data-driven decision making is a policy trend that purports to make funding decisions fair and effective by evaluating programs based on objective performance criteria. Disadvantages experienced by competitors for funding that serve specialized populations, such as youth homelessness organizations competing for HUD Continuum of Care (CoC) funds, can undermine the goal of promoting effective programs. Youth homelessness is an important social issue impacting 1.87 million young adults across the span of a year (Moulton et a., 2018), and prior research suggests that youth are most interested in seeking services from youth-specific providers. The purpose of this research is to determine the extent of HUD’s investment in youth homelessness programs, the composition of the organizations that are funded to provide these services, and the utility of HUD’s data-driven funding mechanisms in promoting access to HUD funding for youth-specific providers. Compiling an administrative dataset of public HUD data and other sources revealed that HUD funding to address youth homelessness has doubled during the study period of 2014 to 2018, but outside of a large influx of funds with the Youth Homelessness Demonstration Program (YHDP) that was awarded to just 21 out of over 400 CoCs during the study period, funding stagnated from 2016 to 2018. While most jurisdictions (75 percent of CoCs) had at least one youth-targeted program, fewer than half (40 percent of CoCs) funded any youth programs. The composition of organizations that provided youth homelessness programs were mixed with about 30 percent each being operated from within homeless-specific and youth-specific organizations. The strongest predictor of a youth program receiving funding is if the organization is an incumbent in the field, having received multiple HUD grants over the study period, indicating that there is a barrier to entry that favors larger organizations and homeless-specific organizations to receive funding for youth homelessness programs. Finally, there are several issues with HUD’s data-driven decision-making rules that undermine the overall effectiveness of HUD’s data use, including poor data quality, data burden experienced by providers, and a mismatch between HUDs “objective” criteria and the realities of service provision with the specialized population of youth experiencing homelessness. Policy proposals that would address these issues would be to expand HUD funding for programs for homeless youth, reduce barriers to access by providing technical assistance to providers seeking HUD CoC funds, develop alternative criteria on which to assess youth homelessness programs, and improve overall data quality.