Paper Contents
Abstract
The paper probes the subject matter on key performance indicators in reporting on talent acquisition, further demonstrating that data analytics and machine learning greatly influence recruitment and hiring procedures. It establishes the presence of various performance parameters; notably these are time-to-hire, quality of hire, cost to hire, and acceptance rate. Such key performance measures reveal insights toward an efficient recruitment practice and process completion. These metrics allow companies to make informed decisions about enhancing their hiring procedures and eventually aligning them with their overall business objectives. Data-driven approaches in talent acquisition are important in effectively competing within the competitive job market and to attract top talent.
Copyright
Copyright © 2025 MARTHALA CHETANA REDDY . This is an open access article distributed under the Creative Commons Attribution License.
