Learning technologies are now commonplace in education, and generate large volumes of educational data. Scholars have argued that analytics can and should be employed to optimize learning and learning environments. This article explores what is really meant by "analytics", describes the current best-known examples of institutional analytics in higher education, and reviews the many systemic challenges to implementation of educational analytics at scale. While many schools are currently gripped by analytics panic, this article argues that large-scale implementation may not be achievable for most. Instead, it proposes that small grassroots pragmatic analytics programs may achievably offer administrators, educators, and learners targeted and customized insights into localized and specific teaching and learning challenges--meeting immediate needs with available skills and resources, making meaning with data in ways that specific local audiences can access and understand, and growing a culture of evidence-based educational planning from the bottom up.