Critically examines Simple Additive Scoring (SAS) and Simple Multiplicative Scoring (SMS) as decision-making aggregation methods across four domains: GPA in education, the SOFA score in healthcare, landslide susceptibility mapping in GIS, and the UN Human Development Index. SAS allows high scores to compensate for critical failures (e.g. a flat surface scoring 74% landslide susceptibility), while SMS improves on this with mandatory requirements but applies them uniformly. The paper argues for more expressive aggregation frameworks like Dujmovic’s Logic Scoring of Preference (LSP) that can represent nuanced factor relationships while remaining explainable.