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| data science in hr: Introducing HR Analytics with Machine Learning Christopher M. Rosett, Austin Hagerty, 2021-06-14 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. |
| data science in hr: Data-Driven HR Bernard Marr, 2018-04-03 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. |
| data science in hr: The Practical Guide to HR Analytics Shonna D. Waters, Rachael Johnson-Murray, Valerie N. Streets, Lindsay McFarlane, 2018 The need for HR professionals to understand and apply data analytics is greater than ever. Today's successful HR professionals must ask insightful questions, understand key terms, and intelligently apply data, but may lack a clear understanding of the many forms, types, applications, interpretations, and capabilities of HR analytics. HR Analytics provides a practical approach to using data to solve real HR challenges in organizations and demystifies analytics with clear guidelines and recommendations for making the business case, starting an HR analytics function, avoiding common pitfalls, presenting data through visualization and storytelling, and much more. |
| data science in hr: Predictive HR Analytics Dr Martin R. Edwards, Kirsten Edwards, 2019-03-03 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. |
| data science in hr: Introduction to People Analytics Nadeem Khan, Dave Millner, 2020-04-03 An understanding of people analytics is a crucial skill for all HR professionals. No longer limited to employees in data teams or those with analyst in their job titles, people analytics is now an integral part of every HR job. Introduction to People Analytics allows all HR professionals to get to grips with analytics, feel confident in their ability to handle employee and organizational data and use analytics to move from opinions to insights. From where to find data in an organization, how to collect it and analyse it through to how to use these findings to add business value, Introduction to People Analytics is essential reading for all HR professionals. With case studies and thought leadership insights from companies who have leveraged people analytics to improve culture and employee engagement, increase performance and reduce costs including NHS, Brompton Bikes, British Heart Foundation, King, Experian and AstraZeneca, FIS and Swarovski, this book shows how and where HR analytics can make a tangible difference to organizations. There is also expert guidance and practical advice on how to embed analytics into HR processes and adopt a data-driven approach to all workplace activities. |
| data science in hr: The Power of People Nigel Guenole, Jonathan Ferrar, Sheri Feinzig, 2017-05-19 Learn from Today’s Most Successful Workforce Analytics Leaders Transforming the immense potential of workforce analytics into reality isn’t easy. Pioneering practitioners have learned crucial lessons that can help you succeed. The Power of People shares their journeys—and their indispensable insights. Drawing on incisive case studies and vignettes, three experts help you bring purpose and clarity to any workforce analytics project, with robust research design and analysis to get reliable insights. They reveal where to start, where to find stakeholder support, and how to earn “quick wins” to build upon. You’ll learn how to sustain success through best-practice data management, technology usage, partnering, and skill building. Finally, you’ll discover how to earn even more value by establishing an analytical mindset throughout HR, and building two key skills: storytelling and visualization. The Power of People will be invaluable to HR executives establishing or leading analytics functions; HR professionals planning analytics projects; and any business executive who wants more value from HR. |
| data science in hr: People Analytics in the Era of Big Data Jean Paul Isson, Jesse S. Harriott, 2016-04-21 Apply predictive analytics throughout all stages of workforce management People Analytics in the Era of Big Data provides a blueprint for leveraging your talent pool through the use of data analytics. Written by the Global Vice President of Business Intelligence and Predictive Analytics at Monster Worldwide, this book is packed full of actionable insights to help you source, recruit, acquire, engage, retain, promote, and manage the exceptional talent your organization needs. With a unique approach that applies analytics to every stage of the hiring process and the entire workforce planning and management cycle, this informative guide provides the key perspective that brings analytics into HR in a truly useful way. You're already inundated with disparate employee data, so why not mine that data for insights that add value to your organization and strengthen your workforce? This book presents a practical framework for real-world talent analytics, backed by groundbreaking examples of workforce analytics in action across the U.S., Canada, Europe, Asia, and Australia. Leverage predictive analytics throughout the hiring process Utilize analytics techniques for more effective workforce management Learn how people analytics benefits organizations of all sizes in various industries Integrate analytics into HR practices seamlessly and thoroughly Corporate executives need fact-based insights into what will happen with their talent. Who should you hire? Who should you promote? Who are the top or bottom performers, and why? Who is at risk to quit, and why? Analytics can provide these answers, and give you insights based on quantifiable data instead of gut feeling and subjective assessment. People Analytics in the Era of Big Data is the essential guide to optimizing your workforce with the tools already at your disposal. |
| data science in hr: Fundamentals of HR Analytics Fermin Diez, Mark Bussin, Venessa Lee, 2019-11-11 Providing practical, hands-on approaches to connect data to HR policies and practices to help influence overall business performance, this book is an essential resource for aspiring, new and experienced HR professionals across a wide range of industrial contexts. |
| data science in hr: Excellence in People Analytics Jonathan Ferrar, David Green, 2021-07-03 Effectively and ethically leveraging people data to deliver real business value is what sets the best HR leaders and teams apart. Excellence in People Analytics provides business and human resources leaders with everything they need to know about creating value from people analytics. Written by two leading experts in the field, this practical guide outlines how to create sustainable business value with people analytics and develop a data-driven culture in HR. Most importantly, it allows HR professionals and business executives to translate their data into tangible actions to improve business performance. while navigating the rapidly evolving world of work. Full of practical tools and advice assembled around the Insight222 Nine Dimensions in People Analytics® model, this book demonstrates how to use people data to increase profits, improve staff retention and workplace productivity as well as develop individual employee experience. Featuring case studies from leading companies including Microsoft, HSBC, Syngenta, Capital One, Novartis, Bosch, Uber, Santander Brasil and American Eagle Outfitters®, Excellence in People Analytics is essential reading for all HR professionals needing to unlock the potential in their people data and gain competitive advantage |
| data science in hr: Work Rules! Laszlo Bock, 2015-04-07 From the visionary head of Google's innovative People Operations comes a groundbreaking inquiry into the philosophy of work -- and a blueprint for attracting the most spectacular talent to your business and ensuring that they succeed. We spend more time working than doing anything else in life. It's not right that the experience of work should be so demotivating and dehumanizing. So says Laszlo Bock, former head of People Operations at the company that transformed how the world interacts with knowledge. This insight is the heart of Work Rules!, a compelling and surprisingly playful manifesto that offers lessons including: Take away managers' power over employees Learn from your best employees-and your worst Hire only people who are smarter than you are, no matter how long it takes to find them Pay unfairly (it's more fair!) Don't trust your gut: Use data to predict and shape the future Default to open-be transparent and welcome feedback If you're comfortable with the amount of freedom you've given your employees, you haven't gone far enough. Drawing on the latest research in behavioral economics and a profound grasp of human psychology, Work Rules! also provides teaching examples from a range of industries-including lauded companies that happen to be hideous places to work and little-known companies that achieve spectacular results by valuing and listening to their employees. Bock takes us inside one of history's most explosively successful businesses to reveal why Google is consistently rated one of the best places to work in the world, distilling 15 years of intensive worker R&D into principles that are easy to put into action, whether you're a team of one or a team of thousands. Work Rules! shows how to strike a balance between creativity and structure, leading to success you can measure in quality of life as well as market share. Read it to build a better company from within rather than from above; read it to reawaken your joy in what you do. |
| data science in hr: The Training Measurement Book Josh Bersin, 2008-04-22 The Training Measurement Book offers managers, executives, and training and human resource professionals a method for measuring their investments in a way that provides information that is both actionable, credible, and meaningful to corporate leaders. Using the methods outlined in this important resource, you can free yourself from traditional, often cumbersome measurement models and put in place pragmatic, useful, and easy-to-implement approaches for measuring training activities. |
| data science in hr: People Analytics For Dummies Mike West, 2019-03-19 Maximize performance with better data Developing a successful workforce requires more than a gut check. Data can help guide your decisions on everything from where to seat a team to optimizing production processes to engaging with your employees in ways that ring true to them. People analytics is the study of your number one business asset—your people—and this book shows you how to collect data, analyze that data, and then apply your findings to create a happier and more engaged workforce. Start a people analytics project Work with qualitative data Collect data via communications Find the right tools and approach for analyzing data If your organization is ready to better understand why high performers leave, why one department has more personnel issues than another, and why employees violate, People Analytics For Dummies makes it easier. |
| data science in hr: Human Resource Management Talya Bauer, Berrin Erdogan, David Caughlin, Donald Truxillo, 2019-01-02 Winner of the 2020 Most Promising New Textbook Award from the Textbook & Academic Authors Association (TAA) Human resources is rapidly evolving into a data-rich field but with big data comes big decisions. The best companies understand how to use data to make strategic workforce decisions and gain significant competitive advantage. Human Resource Management: People, Data, and Analytics introduces students to the fundamentals of talent management with integrated coverage of data analytics. Features tied to SHRM competencies and data exercises give students hands-on opportunities to practice the analytical and decision-making skills they need to excel in today’s job market. Engaging examples illustrate key HRM concepts and theories, which brings many traditional HRM topics to life. Whether your students are future managers or future HR professionals, they will learn best practices for managing talent in the changing workplace. A Complete Teaching & Learning Package SAGE Premium Video Included in the Interactive eBook! SAGE Premium Video tools and resources boost comprehension and bolster analysis. Videos featured include Inside HR interviews where students can hear how real companies are using HR to gain competitive advantage, as well as SHRM and TedTalk videos. Interactive eBook Includes access to SAGE Premium Video, multimedia tools, and much more! Save when you bundle the interactive eBook with the print version. Order using bundle ISBN: 978-1-5443-6572-5. SAGE coursepacks FREE! Easily import our quality instructor and student resource content into your school’s learning management system (LMS) and save time. SAGE edge FREE online resources for students that make learning easier. |
| data science in hr: The New HR Analytics Jac FITZ-ENZ, 2010-05-12 Using Fitz-enz’s proprietary analytic model, you will be equipped to measure and evaluate past and current returns and apply the information to make predictions about the future value of human capital investments. In his landmark book, The ROI of Human Capital, Jac Fitz-enz presented a system of powerful metrics for quantifying the contributions of individual employees to a company’s bottom line. Now, in The New HR Analytics, he reveals how human resources professionals can apply this expense-based knowledge to make the most strategic staffing decisions for their companies. You’ll learn how to: evaluate and prioritize the skills needed to sustain performance; build an agile workforce through flexible Capability Planning; determine how the organization can stimulate and reward behaviors that matter; apply a proven succession planning strategy that leverages employee engagement and drives top-line revenue growth; and recognize risks and formulate responses that avoid surprises. Brimming with real-world examples and input from thirty top HR practitioners and thought leaders as well as exclusive analytical tools, The New HR Analytics ushers in a new era in human resources and human capital management. |
| data science in hr: Beyond HR John W. Boudreau, Peter M. Ramstad, 2007 In Beyond HR: The New Science of Human capital, John Boudreau and Peter Ramstad show you how to do this through a new decisions science-talentship. Through talentship, you move far beyond merely reactive mind-set of planning and budgeting for headcount and hiring and retaining talent. |
| data science in hr: Data-Driven HR Irma Doze, Toine Al, 2019-09-10 Many organizations wrestle with questions, even as they sit atop a treasure trove of valuable information collected by their HR information systems and other business software. This book, a best seller in the Netherlands (Dutch version), shows how you can answer those questions and how you can create value using HR metrics and HR analytics. |
| data science in hr: The Decision Maker's Handbook to Data Science Stylianos Kampakis, 2019-11-26 Data science is expanding across industries at a rapid pace, and the companies first to adopt best practices will gain a significant advantage. To reap the benefits, decision makers need to have a confident understanding of data science and its application in their organization. It is easy for novices to the subject to feel paralyzed by intimidating buzzwords, but what many don’t realize is that data science is in fact quite multidisciplinary—useful in the hands of business analysts, communications strategists, designers, and more. With the second edition of The Decision Maker’s Handbook to Data Science, you will learn how to think like a veteran data scientist and approach solutions to business problems in an entirely new way. Author Stylianos Kampakis provides you with the expertise and tools required to develop a solid data strategy that is continuously effective. Ethics and legal issues surrounding data collection and algorithmic bias are some common pitfalls that Kampakis helps you avoid, while guiding you on the path to build a thriving data science culture at your organization. This updated and revised second edition, includes plenty of case studies, tools for project assessment, and expanded content for hiring and managing data scientists Data science is a language that everyone at a modern company should understand across departments. Friction in communication arises most often when management does not connect with what a data scientist is doing or how impactful data collection and storage can be for their organization. The Decision Maker’s Handbook to Data Science bridges this gap and readies you for both the present and future of your workplace in this engaging, comprehensive guide. What You Will Learn Understand how data science can be used within your business. Recognize the differences between AI, machine learning, and statistics.Become skilled at thinking like a data scientist, without being one.Discover how to hire and manage data scientists.Comprehend how to build the right environment in order to make your organization data-driven. Who This Book Is For Startup founders, product managers, higher level managers, and any other non-technical decision makers who are thinking to implement data science in their organization and hire data scientists. A secondary audience includes people looking for a soft introduction into the subject of data science. |
| data science in hr: Hr Analytics Essentials You Always Wanted To Know Vibrant Publishers, Dr. Michael Walsh, 2021-04-06 After reading this book, you will be able to: ● Define what HR Analytics can do for an organization ● Determine the best HR analytics role for you ● Assess the readiness of your organization for undergoing a study using HR analytics ● Apply HR Analytics in various HR disciplines, including recruiting and staffing, labor negotiations, incentives, and training ● Use Excel to efficiently manage data for your HR analytics Have you ever wondered if there is a science behind the people decisions businesses make? If you have ever been curious about the methods employed by human resources professionals, then HR Analytics Essentials You Always Wanted to Know is the resource guide you need! Part overview of the field, part handbook for getting started in HR Analytics yourself, HR Analytics Essentials You Always Wanted to Know walks readers through the many benefits of using analytics to make better people decisions. HR Analytics requires more than just strong gut instincts and a talent for talking with people. As this guide shows, HR Analytics is both an art and a science that can help your organization make informed decisions that benefit all stakeholders, including employees. Through a blend of theory and practice, you will learn how to think like an HR Analytics professional and apply your expertise in real-world scenarios. With case studies and online tutorials, including a step-by-step guide for using Excel to efficiently work with your data, HR Analytics Essentials You Always Wanted to Know will be the handbook you need to help steer your organization to success. About the Author Dr. Michael Walsh is an industrial and organizational psychologist with over 15 years of human resources and people analytics experience. Michael currently leads Global Talent Management and Organizational Effectiveness for Eaton Corporation’s Vehicle Group. He also teaches a Human Resources Analytics course for master’s level students at the University of Illinois and Wayne State University. Previously, Michael’s passion for People Analytics landed him at Bloomberg and Fiat Chrysler Automobiles where he started and led the Global People Strategy and Analytics and People Analytics and Insights functions, respectively. Michael began his professional career as a client facing consultant for Mercer’s Human Capital practice focused on HR Strategy, Organizational Design/Development and Human Capital Analytics. Michael worked for Mercer in Chicago, Dubai and New York. His master’s degree is in Human Resources and Industrial Relations from the University of Illinois and his PhD is in Industrial and Organizational Psychology. About Vibrant Publishers Vibrant Publishers is focused on presenting the best texts for learning about technology and business as well as books for test preparation. Categories include programming, operating systems and other texts focused on IT. In addition, a series of books helps professionals in their own disciplines learn the business skills needed in their professional growth. Vibrant Publishers has a standardized test preparation series covering the GMAT, GRE and SAT, providing ample study and practice material in a simple and well organized format, helping students get closer to their dream universities. |
| data science in hr: The Future of Management in an AI World Jordi Canals, Franz Heukamp, 2019-10-07 Artificial Intelligence (AI) is redefining the nature and principles of general management. The technological revolution is reshaping industries, disrupting existing business models, making traditional companies obsolete and creating social change. In response, the role of the manager needs to urgently evolve and adjust. Companies need to rethink their purpose, strategy, organisational design and decision-making rules. Crucially they will also need to consider how to nurture and develop the business leaders of the future and develop new ways to interact with society on issues such as privacy and trust. Containing international insights from leading figures from the world of management and technology, this book addresses the big challenges facing organisations, including: · Decision-making · Corporate strategy · People management and leadership · Organisational design Taking a holistic approach, this collection of expert voices provides valuable insight into how firms will discover and commit to what makes them unique in this new big data world, empowering them to create and sustain competitive advantage. |
| data science in hr: Introduction to Employment Law Kathy Daniels, 2019-01-03 Understand the theory and practical application of UK employment law without the need for any prior legal knowledge. Written specifically for HR and Business students, Introduction to Employment Law is a clear and accessible guide to employment law and how it applies in practice. Covering everything from employment tribunals and discrimination to redundancy and termination of employment, this textbook doesn't assume any prior knowledge of the UK legal system and equips students with all the knowledge and skills that they need to take forward into the workplace. Fully revised with all the latest cases and legal developments, this new edition includes coverage of hot topics such as defining employment status in the gig economy, gender pay reporting, the General Data Protection Regulation (GDPR) and the legal implications to be considered with Britain's withdrawal from the European Union. Packed with pedagogical features to consolidate learning including chapter objectives, tasks, 'explore further' sections, key learning points and examples to work through, as well as a dedicated study skills chapter, Introduction to Employment Law is essential reading for all students studying the CIPD Level 5 Intermediate module in employment law as well as being a useful resource for those studying at level 3 and an accessible introduction for level 7 and those on undergraduate and postgraduate courses needing a thorough grounding in employment law. Online resources include lecture slides, case studies, multiple choice questions, annotated weblinks and an instructor's manual. |
| data science in hr: Big Data in Organizations and the Role of Human Resource Management Tobias M. Scholz, 2017 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. |
| data science in hr: Statistical Tools and Analysis in Human Resources Management Bhattacharyya, Dipak Kumar, 2018-01-12 Recently, the use of statistical tools, methodologies, and models in human resource management (HRM) has increased because of human resources (HR) analytics and predictive HR decision making. To utilize these technological tools, HR managers and students must increase their knowledge of the resources’ optimum application. Statistical Tools and Analysis in Human Resources Management is a critical scholarly resource that presents in-depth details on the application of statistics in every sphere of HR functions for optimal decision-making and analytical solutions. Featuring coverage on a broad range of topics such as leadership, industrial relations, training and development, and diversity management, this book is geared towards managers, professionals, upper-level students, administrators, and researchers seeking current information on the integration of HRM technologies. |
| data science in hr: R for Data Science Hadley Wickham, Garrett Grolemund, 2016-12-12 Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true signals in your dataset Communicate—learn R Markdown for integrating prose, code, and results |
| data science in hr: bookdown Yihui Xie, 2016-12-12 bookdown: Authoring Books and Technical Documents with R Markdown presents a much easier way to write books and technical publications than traditional tools such as LaTeX and Word. The bookdown package inherits the simplicity of syntax and flexibility for data analysis from R Markdown, and extends R Markdown for technical writing, so that you can make better use of document elements such as figures, tables, equations, theorems, citations, and references. Similar to LaTeX, you can number and cross-reference these elements with bookdown. Your document can even include live examples so readers can interact with them while reading the book. The book can be rendered to multiple output formats, including LaTeX/PDF, HTML, EPUB, and Word, thus making it easy to put your documents online. The style and theme of these output formats can be customized. We used books and R primarily for examples in this book, but bookdown is not only for books or R. Most features introduced in this book also apply to other types of publications: journal papers, reports, dissertations, course handouts, study notes, and even novels. You do not have to use R, either. Other choices of computing languages include Python, C, C++, SQL, Bash, Stan, JavaScript, and so on, although R is best supported. You can also leave out computing, for example, to write a fiction. This book itself is an example of publishing with bookdown and R Markdown, and its source is fully available on GitHub. |
| data science in hr: The HR Scorecard Brian E. Becker, David Ulrich, Mark A. Huselid, 2001-04-11 Three experts in Human Resources introduce a measurement system that convincingly showcases how HR impacts business performance. Drawing from the authors' ongoing study of nearly 3,000 firms, this book describes a seven-step process for embedding HR systems within the firm's overall strategy—what the authors describe as an HR Scorecard—and measuring its activities in terms that line managers and CEOs will find compelling. Analyzing how each element of the HR system can be designed to enhance firm performance and maximize the overall quality of human capital, this important book heralds the emergence of HR as a strategic powerhouse in today's organizations. |
| data science in hr: Learning Statistics with R Daniel Navarro, 2013-01-13 Learning Statistics with R covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com |
| data science in hr: Reinventing Jobs Ravin Jesuthasan, John Boudreau, 2018-09-18 How to Optimize Human-Machine Work Combinations Your organization has made the decision to adopt automation and artificial intelligence technologies. Now, you face difficult and stubborn questions about how to implement that decision: How, when, and where should we apply automation in our organization? Is it a stark choice between humans versus machines? How do we stay on top of these technological trends as work and automation continue to evolve? Work and human capital experts Ravin Jesuthasan and John Boudreau present leaders with a new set of tools to answer these daunting questions. Transcending the endless debate about humans being replaced by machines, Jesuthasan and Boudreau show how smart leaders instead are optimizing human-automation combinations that are not only more efficient but also generate higher returns on improved performance. Based on groundbreaking primary research, Reinventing Jobs provides an original, structured approach of four distinct steps--deconstruct, optimize, automate, and reconfigure--to help leaders reinvent how work gets bundled into jobs and create optimal human-machine combinations. Jesuthasan and Boudreau show leaders how to continuously reexamine what a job really is, and they provide the tools for identifying the pivotal performance value of tasks within jobs and how these tasks should be reconstructed into new, more optimal combinations. With numerous examples and practical advice for applying the four-step process, Reinventing Jobs gives leaders a more precise, planful, and actionable way to decide how, when, and where to apply and optimize work automation. |
| data science in hr: The Basic Principles of People Analytics Erik Van Vulpen, 2019-05-08 People analytics (also known as HR analytics) is revolutionizing Human Resource Management. Get ready for the future of HR and discover how you can leverage the power of data to drive better outcomes for your business and employees. We set out to write an inspiring book for (HR) professionals, managers, and directors who want to get a feel for the scope of HR analytics and learn how it can help both the employees and the business. In this book, we combined our experiences with lots of inspiring examples. It's concise, easy to read and teaches you all the basic principles of people analytics. After reading this book, you will: - have a solid understanding of what HR analytics is - know the difference between HR analytics and HR reporting - have a clear picture of the scope and the added value of HR analytics - understand the capabilities needed to build an HR analytics team - have plenty of ideas for applying HR analytics to your organization - know which pitfalls to avoid to prevent failure Who should read this book? If you're new to HR analytics and want to learn all the basics without having to plow through pages full of jargon, this book is for you. It's concise and easy to read, especially for people without a background in statistics or IT. Also if you're not working in human resource management yet and want to explore this exciting new field, this book provides you the foundation you are looking If you already have a career in HR analytics and are looking for in-depth knowledge and information, this book is NOT for you. It's definitely interesting and inspiring for those who have already started but don't expect in-depth (statistical) information. |
| data science in hr: Will College Pay Off? Peter Cappelli, 2015-06-09 The decision of whether to go to college, or where, is hampered by poor information and inadequate understanding of the financial risk involved. Adding to the confusion, the same degree can cost dramatically different amounts for different people. A barrage of advertising offers new degrees designed to lead to specific jobs, but we see no information on whether graduates ever get those jobs. Mix in a frenzied applications process, and pressure from politicians for relevant programs, and there is an urgent need to separate myth from reality. Peter Cappelli, an acclaimed expert in employment trends, the workforce, and education, provides hard evidence that counters conventional wisdom and helps us make cost-effective choices. Among the issues Cappelli analyzes are: What is the real link between a college degree and a job that enables you to pay off the cost of college, especially in a market that is in constant change? Why it may be a mistake to pursue degrees that will land you the hottest jobs because what is hot today is unlikely to be so by the time you graduate. Why the most expensive colleges may actually be the cheapest because of their ability to graduate students on time. How parents and students can find out what different colleges actually deliver to students and whether it is something that employers really want. College is the biggest expense for many families, larger even than the cost of the family home, and one that can bankrupt students and their parents if it works out poorly. Peter Cappelli offers vital insight for parents and students to make decisions that both make sense financially and provide the foundation that will help students make their way in the world. |
| data science in hr: New Paradigm in Decision Science and Management Srikanta Patnaik, Andrew W. H. Ip, Madjid Tavana, Vipul Jain, 2019-09-20 This book discusses an emerging area in computer science, IT and management, i.e., decision sciences and management. It includes studies that employ various computing techniques like machine learning to generate insights from huge amounts of available data; and which explore decision-making for cross-platforms that contain heterogeneous data associated with complex assets; leadership; and team coordination. It also reveals the advantages of using decision sciences with management-oriented problems. The book includes a selection of the best papers presented at the International Conference on Decision Science and Management 2018 (ICDSM 2018), held at the Interscience Institute of Management and Technology (IIMT), Bhubaneswar, India. |
| data science in hr: HR Analytics Dipak Kumar Bhattacharyya, 2017-05-26 How can predictive analytics help HR personnel to make more informed decisions? How has analytics extended a new perspective to express HR activities in measurable and objective terms? The introduction of analytics has induced a shift in the traditional HR function-from human resource management (HRM) to human capital management (HCM). HR Analytics reflects on this crucial role of analytics and predictive modelling in human resource settings within modern-day organizations. Keeping in view the emerging need among HR professionals and analysts, this textbook offers interesting insights into the use of analytics to aid strategic decision making. Key Features • Goes beyond traditional HR metrics and scorecard, and discusses the major advances and application of big data in HR decision making • Special focus on measurement of value propositions, data collection and visualization among others • Chapter opening cases, industry insights and caselets throughout the book to give real-life perspectives • Engaging exercises and assignments for students • Ancillary teaching materials for instructors on the dedicated companion website |
| data science in hr: Cognitive Analytics: Concepts, Methodologies, Tools, and Applications Management Association, Information Resources, 2020-03-06 Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries, including business and healthcare. It is necessary to develop specific software programs that can analyze and interpret large amounts of data quickly in order to ensure adequate usage and predictive results. Cognitive Analytics: Concepts, Methodologies, Tools, and Applications provides emerging perspectives on the theoretical and practical aspects of data analysis tools and techniques. It also examines the incorporation of pattern management as well as decision-making and prediction processes through the use of data management and analysis. Highlighting a range of topics such as natural language processing, big data, and pattern recognition, this multi-volume book is ideally designed for information technology professionals, software developers, data analysts, graduate-level students, researchers, computer engineers, software engineers, IT specialists, and academicians. |
| data science in hr: Data Management, Analytics and Innovation Neha Sharma, Amlan Chakrabarti, Valentina Emilia Balas, 2019-10-24 This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry. |
| data science in hr: Data Science For Dummies Lillian Pierson, 2021-08-20 Monetize your company’s data and data science expertise without spending a fortune on hiring independent strategy consultants to help What if there was one simple, clear process for ensuring that all your company’s data science projects achieve a high a return on investment? What if you could validate your ideas for future data science projects, and select the one idea that’s most prime for achieving profitability while also moving your company closer to its business vision? There is. Industry-acclaimed data science consultant, Lillian Pierson, shares her proprietary STAR Framework – A simple, proven process for leading profit-forming data science projects. Not sure what data science is yet? Don’t worry! Parts 1 and 2 of Data Science For Dummies will get all the bases covered for you. And if you’re already a data science expert? Then you really won’t want to miss the data science strategy and data monetization gems that are shared in Part 3 onward throughout this book. Data Science For Dummies demonstrates: The only process you’ll ever need to lead profitable data science projects Secret, reverse-engineered data monetization tactics that no one’s talking about The shocking truth about how simple natural language processing can be How to beat the crowd of data professionals by cultivating your own unique blend of data science expertise Whether you’re new to the data science field or already a decade in, you’re sure to learn something new and incredibly valuable from Data Science For Dummies. Discover how to generate massive business wins from your company’s data by picking up your copy today. |
| data science in hr: Implementing Reproducible Research Victoria Stodden, Friedrich Leisch, Roger D. Peng, 2014-04-14 In computational science, reproducibility requires that researchers make code and data available to others so that the data can be analyzed in a similar manner as in the original publication. Code must be available to be distributed, data must be accessible in a readable format, and a platform must be available for widely distributing the data and code. In addition, both data and code need to be licensed permissively enough so that others can reproduce the work without a substantial legal burden. Implementing Reproducible Research covers many of the elements necessary for conducting and distributing reproducible research. It explains how to accurately reproduce a scientific result. Divided into three parts, the book discusses the tools, practices, and dissemination platforms for ensuring reproducibility in computational science. It describes: Computational tools, such as Sweave, knitr, VisTrails, Sumatra, CDE, and the Declaratron system Open source practices, good programming practices, trends in open science, and the role of cloud computing in reproducible research Software and methodological platforms, including open source software packages, RunMyCode platform, and open access journals Each part presents contributions from leaders who have developed software and other products that have advanced the field. Supplementary material is available at www.ImplementingRR.org. |
| data science in hr: Predictive HR Analytics Mong Shen Ng, 2018-11-27 You don't need to spend months learning the Python, R or SQL programming language, and you don't need to buy expensive statistical software like SPSS or SAS. This is the only book that teaches you Predictive Analytics using Microsoft Excel (which you already have & know how to use)! This book not only share with you the analytics findings of other companies, but also teaches you how to derive it by yourself! It covers the ARHAT Predictive HR Analytics framework, teaches you data-storytelling & data-visualization techniques, and teaches you how to use Microsoft Excel's statistical tools (Decision trees, Correlation, Multiple Regression, Logistic Regression, Chi-Square) with step-by-step print-screen instructions. It is also the only book that covers the full HR Analytics scope (Benefits, Compensation, Culture, Diversity & Inclusion, Engagement, Leadership, Learning & Development, Payroll, Personality Traits, Performance Management, Recruitment, Sales Incentives) with numerous real-world Predictive HR Analytics examples, & shows how Predictive HR Analytics answers questions such as: (1) Predict who are the people at risk of leaving using Decision tree, Correlation, Excel Logistic Regression, etc. (e.g. employee aged 30, who stays more than xx km from the company, who is rated average for performance, has a 90% probability of resigning in her 3rd year.). (2) Identify where the best people come from and how successful a candidate will be if hired using simple correlation (E.g. Customer Service staff and Sales staff with x & y personality traits are likely to be good performers if hired). (3) Predict impact of Employee Engagement on customer satisfaction, revenue and Shareholder Returns, etc. using Excel Multiple Regression. (e.g. 1% increase in employee engagement leads to $100k increase in company revenue, 2% increase in customer satisfaction, 1% increase in Shareholders return, 1 day reduction in average sick leave, etc.). (4) Predict financial impact of training using Excel Multiple Regression (e.g. training satisfaction rating of xx leads to $y increase in company revenue). (5) Predict Diversity & Inclusion's impact on revenue and EBIT (e.g. convert your company's ethnic diversity mix to an index number, then use Excel Multiple Regression to predict if your company's diversity Index is x --> your company's Sales will be $y and EBIT will be z%). (6) Predict employee absenteeism and accident, using Chi-Square. |
| data science in hr: Fundamentals of Data Science Mr.Desidi Narsimha Reddy, Lova Naga Babu Ramisetti, Mr.Harikrishna Pathipati, 2024-09-05 Mr.Desidi Narsimha Reddy, Data Consultant (Data Governance, Data Analytics: Enterprise Performance Management, AI & ML), Soniks consulting LLC, 101 E Park Blvd Suite 600, Plano, TX 75074, United States. Lova Naga Babu Ramisetti, EPM Consultant, Department of Information Technology, MiniSoft Empowering Techonolgy, 10333 Harwin Dr. #375e, Houston, TX 77036, USA. Mr.Harikrishna Pathipati, EPM Manager, Department of Information Technology, ITG Technologies, 10998 S Wilcrest Dr, Houston, TX 77099, USA. |
| data science in hr: Applying Advanced Analytics to HR Management Decisions James C. Sesil, 2014 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. |
| data science in hr: Predictive Analytics for Human Resources Jac Fitz-enz, John Mattox, II, 2014-07-28 Create and run a human resource analytics project with confidence For any human resource professional that wants to harness the power of analytics, this essential resource answers the questions: Where do I start? and What tools are available? Predictive Analytics for Human Resources is designed to answer these and other vital questions. The book explains the basics of every business—the vision, the brand, and the culture, and shows how predictive analytics supports them. The authors put the focus on the fundamentals of predictability and include a framework of logical questions to help set up an analytic program or project, then follow up by offering a clear explanation of statistical applications. Predictive Analytics for Human Resources is a how-to guide filled with practical and targeted advice. The book starts with the basic idea of engaging in predictive analytics and walks through case simulations showing statistical examples. In addition, this important resource addresses the topics of internal coaching, mentoring, and sponsoring and includes information on how to recruit a sponsor. In the book, you'll find: A comprehensive guide to developing and implementing a human resource analytics project Illustrative examples that show how to go to market, develop a leadership model, and link it to financial targets through causal modeling Explanations of the ten steps required in building an analytics function How to add value through analysis of systems such as staffing, training, and retention For anyone who wants to launch an analytics project or program for HR, this complete guide provides the information and instruction to get started the right way. |
| data science in hr: Human Capital Analytics Gene Pease, Boyce Byerly, Jac Fitz-enz, 2012-10-30 An insightful look at the implementation of advanced analytics on human capital Human capital analytics, also known as human resources analytics or talent analytics, is the application of sophisticated data mining and business analytics techniques to human resources data. Human Capital Analytics provides an in-depth look at the science of human capital analytics, giving practical examples from case studies of companies applying analytics to their people decisions and providing a framework for using predictive analytics to optimize human capital investments. Written by Gene Pease, Boyce Byerly, and Jac Fitz-enz, widely regarded as the father of human capital Offers practical examples from case studies of companies applying analytics to their people decisions An in-depth discussion of tools needed to do the work, particularly focusing on multivariate analysis The challenge of human resources analytics is to identify what data should be captured and how to use the data to model and predict capabilities so the organization gets an optimal return on investment on its human capital. The goal of human capital analytics is to provide an organization with insights for effectively managing employees so that business goals can be reached quickly and efficiently. Written by human capital analytics specialists Gene Pease, Boyce Byerly, and Jac Fitz-enz, Human Capital Analytics provides essential action steps for implementation of advanced analytics on human capital. |
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