Effective teaching and learning depend on decisions made at different levels. To explore the link between learning design and the process of managing the risk of student failure in e-learning courses, we have found that both fields focus on decision-making aspects aimed at enhancing teaching and learning. Learning analytics play a mediating role between the two domains, helping to strengthen the endeavor. Managing the risk of failure is mainly determined by data-driven approaches to make evidence-based decisions. At the same time, investigating links between learning design and learning analytics is of increased research interest. In this paper, we present an original algorithmic approach that captures parts of existing knowledge and literature from the fields of learning design, learning analytics, and risk management to examine connections and establish initial synergistic foundations for enhancing learning design decisions. As part of an ongoing project, we aim to articulate a unified design system that supports risk management and quality assurance strategies in technology-enhanced learning environments.