Confidently analyse your organization's HR data using R and R Studio to gain insights that improve people strategy and business decision-making. Effective use of HR data has the power to transform a business. However, this is only possible if HR practitioners have the knowledge, skills and confidence to analyse the data and to draw evidence-based insights from it. This book is the practical guide that HR professionals need. Through worked examples, this book shows readers how to carry out and interpret analyses of HR data in areas such as recruitment, performance, employee engagement and diversity. People professionals are then shown how to use the results to develop robust people strategies and to support more effective evidence-based decision-making. Using R in HR Analytics provides a thorough grounding in the differences between descriptive reporting and predictive analytics as well as the methods and measures used to identify the validity of results. There is also expert guidance on the role of artificial intelligence, machine learning and large language modelling on HR analytics. Written for HR professionals at any level, there is essential coverage of data privacy and the ethical considerations of using people data. Online resources include sample datasets to allow readers to practice analysing HR data.

"HR Analytics for Business Excellence" explores the transformative power of data-driven decision-making in human resource management. This book provides comprehensive insights into leveraging analytics to enhance employee performance, optimize talent acquisition, and improve overall organizational effectiveness. It delves into key metrics, analytical tools, and case studies, illustrating how HR analytics can drive strategic initiatives, foster a culture of continuous improvement, and ultimately contribute to business success. By integrating analytics into HR practices, organizations can make informed decisions that align with their goals and enhance their competitive advantage.

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Human Resources (HR) departments often have significant data sets related to employees and positions within their organizations, but optimizing use of this data can present challenges. As the business world rapidly transforms due to technological advancements, experts within the HR domain must learn to effectively use data to improve workforce performance and assist with strategic decisions. A comprehensive understanding of HR analytics and its multiple levels, ranging from descriptive to perspective, can emphasize how the data can support, track, and monitor employee performance, culture, turnover rate, and absenteeism. HR Analytics in an Era of Rapid Automation is a valuable guide for academics, researchers, and practitioners interested in the latest developments in HR analytics. It covers relevant theories and conceptual models based on quantitative and qualitative findings and emphasizes the importance of utilizing HR analytics for sustainable decision making. With a focus on recruitment analytics, talent acquisition, employee performance analytics, and more, this book provides practical solutions to the challenges facing HR professionals in the rapidly changing business world. By highlighting the value of people and HR analytics for business success, this book offers several solutions for the analysis of challenges facing HR professionals today.

HR metrics and organizational people-related data are an invaluable source of information from which to identify trends and patterns in order to make effective business decisions. But HR practitioners often lack the statistical and analytical know-how to fully harness the potential of this data. Predictive HR Analytics provides a clear, accessible framework for understanding and working with people analytics and advanced statistical techniques. Using the statistical package SPSS (with R syntax included), it takes readers step by step through worked examples, showing them how to carry out and interpret analyses of HR data in areas such as employee engagement, performance and turnover. Readers are shown how to use the results to enable them to develop effective evidence-based HR strategies. This second edition has been updated to include the latest material on machine learning, biased algorithms, data protection and GDPR considerations, a new example using survival analyses, and up-to-the-minute screenshots and examples with SPSS version 25. It is supported by a new appendix showing main R coding, and online resources consisting of SPSS and Excel data sets and R syntax with worked case study examples.

Modern research goes beyond disciplinary horizons for devising solutions to the society’s most pressing unsolved issues. Within the disciplinary framework, the ability to solve problems through the generation of knowledge is no more addressed from discipline-specific points of view only. However, it has become apparent that the research needed to address today’s complex problems requires the expertise of many disciplines. Multidisciplinary approach incorporates a combination of concepts and knowledge from various disciplines. These contributions enable the exchange of knowledge and experiences from diverse groups of people that can promote a holistic vision of a subject, as well as new explanatory theories. Being multidisciplinary does not mean giving up skills—it means moving into new scientific directions using one’s own special set of skills. Rather than being an end in itself, this kind of research is a way of achieving innovative goals, enriched understanding, and a synergy of new methods. The book highlights, the diverse perspectives of the researchers across disciplines from sustainable urban development to renewable energy strategies, from biodiversity conservation to equitable machine learning, internet of things, deep learning and Artificial Intelligence (AI) models, eco-friendly methods, individualized education plans, and social policies that can contribute to more comprehensive and effective solutions to some of the world’s most pressing issues, while acknowledging that sustainability challenges are inherently interconnected hence the importance of inclusivity in research.

This book provides a comprehensive overview of various aspects of HR analytics. It delves into important definitions, the significance of HR analytics, methods of data collection and management, as well as specific areas such as recruitment analytics, performance management analytics, employee engagement analytics, and diversity, equity and inclusion (DEI) analytics. The book also explores ethical considerations, implementation strategies, and the role of HR analytics in workforce planning, succession planning, and employee wellness. Additionally, it discusses monitoring the impact of interventions and offers insights into the future of HR analytics. Besides, it offers a range of practical tools and templates for various applications. KEY FEATURES • Comprehensive coverage: Covers a wide range of topics related to HR analytics from the basics to more specialized areas. • Diverse tools and techniques: Includes discussions on various data analysis techniques, such as predictive analytics, machine learning, and statistical modelling. • Practical templates and forms: Inclusion of templates and forms, such as employee attitude surveys and KPI dashboards, make this book more hands-on and practical. • Ethical and legal considerations: Focusses on ethics and compliance/legal considerations for the evolving landscape of HR analytics. • Future-oriented content: Discusses on the future of HR analytics and emerging trends is a dimension of forward-looking. • Agile HR analytics: Includes Agile HR Analytics as an emerging trend. • Staying updated: Acknowledges the importance of staying updated on HR analytics trends. • Clarity and accessibility: Presents a clear, accessible, and engaging text making the book reader-friendly. • The book primarily intended to the students of business schools is equally valuable to the professionals in the field. For instructor’s resources, visit https://www.phindia.com/HR_ analytics_deepa_mukul_partha TARGET AUDIENCE • MBA — HR • Data Analytics and HR Professionals