Buch, Englisch, 258 Seiten, Format (B × H): 245 mm x 174 mm, Gewicht: 468 g
Reihe: Global HRM
A Global Perspective
Buch, Englisch, 258 Seiten, Format (B × H): 245 mm x 174 mm, Gewicht: 468 g
Reihe: Global HRM
ISBN: 978-1-032-02900-9
Verlag: Taylor & Francis Ltd
Workforce Analytics: A Global Perspective provides a comprehensive sweep of key issues facing the evolving discipline of workforce analytics. The editors, all globally recognized in this field, have curated a collection of unique pieces that introduce workforce analytics, discuss its place in the HR sphere, and systematically address the key practical challenges faced by analytics experts working in and with organizations. Drawing on the combined expertise of the editors and a range of practicing expert contributors, the book provides a current, cutting-edge, and multi-perspective survey of workforce analytics. The contributions examine why workforce analytics is important, how it can help contribute to business success, and the considerations businesses need to address to maximize the benefit of this important HR expertise. A breakthrough text in a game-changing emerging discipline, the book is an essential resource for practitioners, students, and researchers in workforce analytics, people analytics, and human resource management more broadly.
Zielgruppe
Postgraduate and Undergraduate
Autoren/Hrsg.
Fachgebiete
- Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Wirtschaftsprognose
- Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Personalwesen, Human Resource Management
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering
Weitere Infos & Material
PART 1: WORK FORCE ANALYTICS (WFA)
1 Introduction and book overview
2 Theoretical frameworks for workforce analytics
3 Data collection and analysis
PART 2: ANALYTIC TECHNIQUES
4.0 Considering techniques in workforce analytics
4.1 Causal inference in HR analytics with Directed Acyclic Graphs
4.2 Latent Class and Latent Profile Analysis
4.3 Efficient ways to leverage untapped data sources: Using natural language processing to assess work attitudes and perceptions
4.4 Decision trees and HR analytics: An example
4.5 Organizational network analysis (ONA) at the Broad Institute
4.6 Machine learning tools to support strategic HR decision-making
4.7 Connecting employee survey data to organizational performance indicators using micro-macro multilevel regression
4.8 Key takeaways
PART 3: WFA APPLICATIONS AND FUTURE
5 Implementation and change management
6 Ethics and workforce analytics
7 Building the workforce analytics function
8 The future of workforce analytics