Analytics for Improving Talent Acquisition Processes

Abstract

Talent Acquisition (TA) is an important function within HR, responsible for recruiting high quality people for given job positions through various sources under stringent deadlines and cost constraints. Given the importance of TA in the overall successful operations and growth of any organization, in this paper we identify specific “business questions” focused on analyzing various aspects of the TA processes, analyze past TA data using statistical analysis techniques and to discover novel patterns/insights and actionable knowledge which can help in improving the cost, efficiency and quality of recruitment. Our predictive analytic is mainly related to various duration and delays in TA, candidate selection or rejection, offer acceptance by selected candidates, root cause analysis for offer decline. We also use the data-mining technique of subgroup discovery to identify interesting patterns (e.g., candidate subgroups having unusually high decline ratios). We illustrate the approaches through a real-life data-set.