The world of talent management is undergoing significant changes, driven by the shift towards more agile and networked organizational structures. The rise of the "network of teams" challenges traditional top-down management structures and leadership development, succession planning, and talent retention. To address these challenges, companies are increasingly relying on people analytics models that use data from existing HR, talent, and performance management applications to produce valuable insights into what makes people tick and how to attract top talent. However, most of these concepts are not new, and the key issue lies in deriving insights from the vast amount of available people data in a way that is efficient, cost-effective, and intuitive. The solution lies in recognizing the wealth of relationships that exist naturally within the data, organizing it as a graph, and making relationships first-class citizens. This approach enables companies to find hidden potential, retain talent, and differentiate themselves from competitors by extracting valuable insights from connected data.