Collective cell migration is ubiquitous in biology, from development to cancer; it is influenced by heterogeneous cell types, signals and matrix properties, and requires large scale regulation in space and time. Understanding how cells achieve organized collective motility is crucial to addressing cellular and tissue function and disease progression. While current two-dimensional model systems recapitulate the dynamic properties of collective cell migration, quantitative three-dimensional equivalent model systems have proved elusive. The overarching hypothesis of this work is that cell collectives are heterogeneous in nature; and that the influence of biochemical, physical, and mechanical factors combined leads to diverse physical behaviors. The central goal of this work is to establish standard tools for the understanding of 3D collective cell motility by treating individual cell-collectives as independent entities. An experimental model studies cell collectives by tracking individual cells within cell cohorts embedded in three dimensional collagen scaffolding. A computational model of 3-dimensional multi-scale self-propelled particles recreates experimental data and accounts for intercellular adhesion dynamics. A custom algorithm identifies cellular cohorts from experimental and simulated data so these may be treated as independent entities. A second custom algorithm quantifies the temporal and spatial heterogeneity of motion in cell cohorts during ‘motility events’ observed in experiments and simulations. The results show that cell-cohorts in 3D are dynamic with spatial and temporal heterogeneity; cohesive motility events can emerge without an external driving agent. Simulated cohorts are able to recreate experimental motility event signatures. Together these model systems and analytical techniques are some of the first to address collective motility of adhesive cellular cohorts in 3-dimensions.