Applying Advanced Analytics to HR Management Decisions: Methods for Selection, Developing Incentives, and Improving Collaboration (Paperback)

By James C. Sesil

Dramatically improve human capital management decisions by applying advanced analytics and Big Data technologies and processes! Pioneering HR technology expert James Sesil identifies widespread flaws in today's HR decision-making processes, and reveals how advanced analytics can help organizations make far more robust decisions about employee selection, performance management, strategy alignment, collaboration, and more. In this book he shows how to integrate Business Intelligence, ERP, Strategy Maps, Talent Management Suites, and advanced analytics -- and use them together to make far better decisions. You'll learn how to measure and improve the value of HCM decision-making in workforce/succession planning, talent acquisition, career development, corporate learning, and beyond. Sesil teaches key lessons from sources ranging from online dating services to Moneyball-style sports player selection processes. He shows how to systematically improve decision-making through more complete and sophisticated collaboration and new Collective Intelligence approaches. You'll learn how to use both internal and external data sources more effectively, and review a wide variety of advanced tools now available from vendors such as OrcaEyes, Vemo, Aruspex, Peoplefluent, Infor/Lawson, DecisionLens, Oracle, Ultimate, Cogniti, IBM, SAP, and Microsoft. Sesil concludes by demonstrating how to build data driven cultures and organizations that truly want to bring objectivity to decision-making, and will actually use these remarkable new tools. This book will be an invaluable resource for every HR executive, manager, analyst, and IT professional seeking new opportunities for competitive advantage through human capital and technological innovation.

• Format: Paperback
• Language: English
• ISBN: 0134770943
• ISBN13: 9780134770949
• Release Date: June 2017
• Publisher: Pearson FT Press
• Length: 224 Pages
• Weight: 0.60 lbs.
• Dimensions: 0.4" x 5.9" x 8.9"