Talent Management and HR Analytics
Programme Overview
This course is designed to give participants a deeper understanding of current talent management practices and how people analytic techniques are used to influence the decisions that impact them. People, places, and processes are leveraged to create value within companies, yet decisions on how to influence and shape these decisions are often made by gut instinct, company politics, or individual bias at an extreme cost to both the individual and organization at large. This course will focus on a philosophical understanding of current talent management practices, as well as critical thinking about opportunities for future improvement in the field of talent/HR analytics. Learning objectives include:
- Review of statistical and business intelligence tools/processes.
- A deeper understanding of how people analytics practices are being used to influence current talent management practices/policies.
- Advancing critical thought on how to evolve current talent management practices/policies with talent/HR analytics.
Instructor
Stephen Smith leads the people analytics, client solutions, and product development areas as part of the global WPA team. Stephen also teaches Talent Management and HR Analytics courses at Drake University and is a VP of People Analytics at the Iowa chapter of Society of Human Resource Management (SHRM).
HR practitioners looking to improve talent management decisions. Analysts, consultants, directors, and executives alike will learn more about leveraging people data to improve business outcomes.
This course will focus on the main talent management areas (hiring, total rewards, performance management, leadership development, culture and engagement, and training & development) and how data can improve decisions and business outcomes.
Proficient understanding of common biases, statistics, and business intelligence methods.
A deeper understanding of how people analytics practices are being used to influence current talent management practices/policies.