Disaggregating Talent Data
Examining Selection Data for Equity
Many organizations collect talent data across recruitment, engagement, performance, development, and promotion—but far fewer disaggregate it in ways that reveal how systems actually operate for different groups. When data is only reviewed in aggregate, it can mask differences in who is represented, how people progress, and how experiences vary across the talent lifecycle.
This tool offers a practical example of how disaggregating talent data can surface meaningful insights, using selection as a starting point. In a simple, Google Sheets–based format, it shows how organizations can examine representation, stage-by-stage progression, and candidate experience by race and gender. The goal is not to provide definitive answers, but to demonstrate how disaggregated data can help teams focus attention where it will matter most.