High-resolution mass spectrometry (HRMS) has become the cornerstone of non-target analysis (NTA) workflows, enabling molecular formula assignment from accurate mass and isotopic patterns. Yet even sub-ppm mass accuracy and tandem MS/MS fragmentation remain fundamentally one-dimensional constraints, insufficient to resolve structural isomers or eliminate candidate ambiguity in complex matrices. We draw an analogy to the history of maritime navigation to demonstrate that increasing measurement dimensionality — not marginal precision gains — is the decisive factor for unambiguous molecular identification. A formal mathematical framework is developed in which the identification uncertainty volume in N-dimensional observable space scales multiplicatively with each added dimension, while precision improvements yield only linear reductions in candidate count. This principle is formalised as the "Bounty Rule": analytical identification confidence scales with the number of independent measurement dimensions, not with precision within any single dimension alone. Ion mobility spectrometry (IMS), which provides collision cross section (CCS) values encoding molecular size and shape, is introduced as the orthogonal "longitude" to the mass spectrometric "latitude." Using cyclic IMS-HRMS data on structurally challenging isomeric flavonoids in Passiflora extracts, we demonstrate resolution enhancement from a resolving power of ≈65 to ≈145 over five cyclic passes, enabling complete isomer separation at identical exact mass. We further discuss the instrument acquisition paradox in which continued investment in ever-higher mass resolution yields diminishing analytical returns compared with adoption of IMS as a complementary dimension. The term heterohyperspectral is proposed to describe this class of physically heterogeneous, high-dimensional molecular datasets.