Big data are changing the way we work. This book conveys a theoretical understanding of big data and the related interactions on a socio-technological level as well as on the organizational level. Big data challenge the human resource department to take a new role. An organization's new competitive advantage is its employees augmented by big data.

Fundamentals of Human Resource Management: People, Data, and Analytics provides a current, succinct, and interesting introduction to the world of HRM with a special emphasis on how data can help managers make better decisions about the people in their organizations. Authors Talya Bauer, Berrin Erdogan, David Caughlin, and Donald Truxillo use cutting-edge case studies and contemporary examples to illustrate key concepts and trends. A variety of exercises give students hands-on opportunities to practice their problem-solving, ethical decision-making, and data literacy skills. Non-HR majors and HR majors alike will learn best practices for managing talent in today’s ever-evolving workplace.

FINALIST: Business Book Awards 2019 - HR and Management Category Traditionally seen as a purely people function unconcerned with numbers, HR is now uniquely placed to use company data to drive performance, both of the people in the organization and the organization as a whole. Data-Driven HR is a practical guide which enables HR professionals to leverage the value of the vast amount of data available at their fingertips. Covering how to identify the most useful sources of data, collect information in a transparent way that is in line with data protection requirements and turn this data into tangible insights, this book marks a turning point for the HR profession. Covering all the key elements of HR including recruitment, employee engagement, performance management, wellbeing and training, Data-Driven HR examines the ways data can contribute to organizational success by, among other things, optimizing processes, driving performance and improving HR decision making. Packed with case studies and real-life examples, this is essential reading for all HR professionals looking to make a measurable difference in their organizations.

The new edition of this SAGE Handbook builds on the success of the first by providing a fully updated and expanded overview of the field of human resource management. Bringing together contributions from leading international scholars - and with brand new chapters on key emerging topics such as talent management, engagement , e-HRM and big data - the Handbook focuses on familiarising the reader with the fundamentals of applied human resource management, while contextualizing practice within wider theoretical considerations. Internationally minded chapters combine a critical overview with discussion of key debates and research, as well as comprehensively dealing with important emerging interests. The second edition of this Handbook remains an indispensable resource for advanced students and researchers in the field. PART 01: Context of Human Resource Management PART 02: Fundamentals of Human Resource Management PART 03: Contemporary Issues

As a field, human resources has been slow to evolve, despite a great need and opportunity for change. Human Resource Excellence delivers the newest findings about what makes HR successful and how it can add value to today's organizations. Tracing changes in a global sample of firms across the US, Europe, and Asia, this landmark volume provides an international benchmark against which to measure a company's HR practice. For over twenty years, USC's Center for Effective Organizations has conducted the definitive longitudinal study of the human resource management function. Analyzing new data every three years, the Center charts changes in HR and offers guidance on how human resource professionals can drive firm performance. In this latest survey, Edward E. Lawler III and John W. Boudreau conclude that HR is most powerful when it plays a strategic role, makes use of information technology, and has tangible metrics and analytics. Their insights offer an essential understanding of HR's changing role in strategy, big data, social and knowledge networks, and the gig economy.

"This volume is a step by step guide to implementing predictive data analytics in human resource management (HRM). It demonstrates how to apply and predict various HR outcomes which have an organizational impact, to aid in strategizing and better decision making. The book: Presents key concepts and expands on the need and role of HR analytics in business management; Utilises popular analytical tools like Artificial Neural Networks (ANN) and K-Nearest Neighbour (KNN) to provide practical demonstrations through R scripts for predicting turnover and applicant screening; Discusses real world corporate examples and employee data collected first-hand by the authors; Includes chapter-wise problem exercises and case studies for students and teachers. Comprehensive and accessible, this guide will be useful for students, teachers and researchers of data analytics, big data, human resource management, statistics, and economics. It will also be of interest to general readers unfamiliar with statistics or programming"--

This book analyzes the effects of the latest technological advances in blockchain and artificial intelligence (AI) on business operations and strategies. Adopting an interdisciplinary approach, the contributions examine new developments that change the rules of traditional management. The chapters focus mainly on blockchain technologies and digital business in the "Industry 4.0" context, covering such topics as accounting, digitalization and use of AI in business operations and cybercrime. Intended for academics, blockchain experts, students and practitioners, the book helps business strategists design a path for future opportunities.

This book draws on recent debate surrounding the emergence of cognitive intelligence in organizations, exploring the redefinition of the labor market and consequently, employment. With a particular focus on Human Resource Management (HRM), the authors analyse the socio-cultural transformation of traditional practices and methodologies that are ocurring in the workforce. Digital HR presents detailed case studies and interviews with HR managers of large multinational companies, providing comprehensive empirical evidence for academics and students interested in the development of HRM in today’s digital landscape. The book will also be valuable to practitioners and managers looking to adapt the role of HR in their own companies or organizations.

The world is witnessing the growth of a global movement facilitated by technology and social media. Fueled by information, this movement contains enormous potential to create more accountable, efficient, responsive, and effective governments and businesses, as well as spurring economic growth. Big Data Governance and Perspectives in Knowledge Management is a collection of innovative research on the methods and applications of applying robust processes around data, and aligning organizations and skillsets around those processes. Highlighting a range of topics including data analytics, prediction analysis, and software development, this book is ideally designed for academicians, researchers, information science professionals, software developers, computer engineers, graduate-level computer science students, policymakers, and managers seeking current research on the convergence of big data and information governance as two major trends in information management.

This book directly addresses the explosion of literature about leveraging analytics with employee data and how organizational psychologists and practitioners can harness new information to help guide positive change in the workplace. In order for today’s organizational psychologists to successfully work with their partners they must go beyond behavioral science into the realms of computing and business acumen. Similarly, today’s data scientists must appreciate the unique aspects of behavioral data and the special circumstances which surround HR data and HR systems. Finally, traditional HR professionals must become familiar with research methods, statistics, and data systems in order to collaborate with these new specialized partners and teams. Despite the increasing importance of this diversity of skill, many organizations are still unprepared to build teams with the comprehensive skills necessary to have high performing HR Analytics functions. And importantly, all these considerations are magnified by the introduction and acceleration of machine learning in HR. This book will serve as an introduction to these areas and provide guidance on building the connectivity across domains required to establish well-rounded skills for individuals and best practices for organizations when beginning to apply advanced analytics to workforce data. It will also introduce machine learning and where it fits within the larger HR Analytics framework by explaining many of its basic tenets and methodologies. By the end of the book, readers will understand the skills required to do advanced HR analytics well, as well as how to begin designing and applying machine learning within a larger human capital strategy.