As work becomes more fluid and less predictable, there has been a much-needed shift in organizing and planning work beyond the limitations of jobs and roles. While this transition remains imperative, it’s important to recognize that many organizations still use at least a segment of jobs and roles as the basis for talent practices, such as workforce planning and succession planning. Rather than abandoning jobs and roles completely, many organizations are more likely to adopt a combination of approaches—encompassing jobs, skills, tasks, etc.—to facilitate diverse planning needs. With regard to jobs, this new article introduces two strategies for identifying an organization’s critical roles. The first method employs a data-driven, bottom-up analysis, while the second adopts a top-down approach through inference. The article exemplifies how data can unveil overlooked roles and guide strategic choices. From my experience, organizations often stumble into common pitfalls while identifying critical roles, namely a) pegging role significance solely to job level (e.g., exclusive focus on executive roles), b) gauging criticality based on how difficult a role is to fill, and c) tethering role criticality to incumbents rather than the role’s value generation for the organization and its stakeholders. A data-based approach can help to overcome these common challenges to critical role identification.