Data-Driven Talent Management: Using Analytics to Improve Employee Experience - Hardcover

Saling, Kristin

Hardcover

ISBN 10: 139861629X ISBN 13: 9781398616295

Publisher: Kogan Page, 2024

Synopsis

DISTINGUISHED FAVORITE: NYC Big Book Award 2025 - Business: General

How can I use insights from people data to develop an inclusive, engaged, high-performing workforce? What data is available and how do I collect it ethically?

Data-Driven Talent Management is a practical guide for HR professionals which answers these questions. It outlines effective data collection and analysis methods as well as showing how to develop metrics and key performance indicators to support employee experience. It also provides guidance on how to build a comprehensive talent database by understanding different employee experiences, attributes, skills and journeys. In addition, there is also essential advice on how to leverage data to improve motivation and employee engagement, use data to assess different thought and work styles in the workforce and use the results to build a diverse and inclusive organization that allows all employees and the business to thrive.

Full of tools, tips and frameworks and written by a professional who is implementing a data-driven approach to talent management for the US Army, the world's largest employer, this is essential reading for all mid-level and senior HR practitioners.

About this title

About the Author

Kristin Saling is Director at the Innovation Cell for the United States Army Human Resources Command where she enables the command to capitalize on the latest HR business practices and technologies. Prior to this, she was Deputy Director of People Analytics for the Assistant Secretary of the Army for Manpower and Reserve Affairs (ASA (M&RA)) and Chief Analytics Officer for the Army Talent Management Task Force. She is based in Orlando, Florida.

Edition details

• Publisher: Kogan Page
• Publication date: 2024
• Language: English
• ISBN 10: 139861629X
• ISBN 13: 9781398616295
• Binding: Hardcover
• Edition number: 1
• Number of pages: 248