Fundamentals of HR Analytics :: a Manual on Becoming HR Analytical.
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.
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Weitere Verfasser: | , |
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Bingley :
Emerald Publishing Limited,
2019.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | 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. |
| Beschreibung: | 5.2.1 Design |
| Beschreibung: | 1 online resource (281 pages) |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 1789739632 9781789739633 9781789739619 1789739616 |
Internformat
MARC
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| 245 | 1 | 0 | |a Fundamentals of HR Analytics : |b a Manual on Becoming HR Analytical. |
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| 300 | |a 1 online resource (281 pages) | ||
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| 505 | 0 | |a Cover; FUNDAMENTALS OF HR ANALYTICS; PRAISE FOR FUNDAMENTALS OF HR ANALYTICS; FUNDAMENTALS OF HR ANALYTICS: A Manual on Becoming HR Analytical; Copyright; TABLE OF CONTENTS; LIST OF FIGURES; FOREWORD; ACKNOWLEDGMENTS; INTRODUCTION; Part I: The Basics of HR Analytics; 1. Basics of Finance, Statistics and Data-analytic Thinking; 1.1 Learning Objectives of This Chapter; 1.2 The Changing Nature of HR; 1.3 Why HR Analytics Now?; 1.4 Types of Analysis; 1.5 HR Analysts as Architects; 1.6 An Eight-step Approach to HR Analytics; 1.6.1 Define the Business Problem; 1.6.2 Formulate Hypotheses | |
| 505 | 8 | |a 1.6.3 Collect Data1.6.4 Analyse Data; 1.6.5 Derive Insights; 1.6.6 Build Recommendations; 1.6.7 Visualise and Tell a Story; 1.6.8 Execute and Evaluate; 1.7 Why Do Some Analytics Projects Fail?; 1.8 Finance for HR Professionals; 1.8.1 Profit Measures; 1.8.2 Market and Other Common Performance Measures; 1.8.3 Cost-related Terms; 1.9 Recap on Statistics Concepts; 1.9.1 Categorical and Continuous Variables; 1.9.2 Measures of Central Location; 1.9.3 Measures of Dispersion; 1.9.4 Measures of Association; 1.9.5 Population and Sampling; 1.9.6 Statistical Forecasting Models; Summary; Questions | |
| 505 | 8 | |a Workforce PlanningTalent Acquisition; Talent Engagement; Talent Development; Talent Deployment; Leading and Managing Talent; Talent Retention; 2. Tools for HR Analytics; 2.1 Technology Options; 2.1.1 On-premise; 2.1.2 Cloud Based; 2.2 Cost of Implementing On-premise vs Cloud; 2.3 Software as a Service; 2.4 Components of Analytics Technology; 2.4.1 Human Resources Information System; 2.4.2 HR Data Warehouse; 2.4.3 Reporting Technology; 2.4.4 Statistical Analysis and Machine Learning Technology; 2.4.5 Visualisation Technology; 2.4.6 Cognitive Technology; Summary; Questions; 3. Data Collection | |
| 505 | 8 | |a 3.1 Sources of Data3.1.1 HR Data; 3.1.2 HRIS Data; 3.1.3 Non-HR Data; 3.1.4 Data Audits; 3.1.5 Structured and Unstructured Data; 3.2 Common Data Challenges and Solutions; 3.2.1 Missing Data; 3.2.2 Outdated Data; 3.2.3 No Data Available; 3.2.4 Data Outliers; 3.3 Tidying the Data; 3.3.1 General Principles of Tidy Data; 3.3.2 Common Mistakes When Tidying Data; 3.3.3 Tips on Checking Data; 3.3.4 Common Mistakes When Checking the Data; 3.3.5 Plots Are Better than Summaries; Summary; Questions; Caselet; 4. HR Analytics Modelling; 4.1 Details of Analytics Design Framework | |
| 505 | 8 | |a 4.1.1 Source of Problem or Opportunity4.1.2 Scoping the Project; 4.1.3 Linking HR Variables to Business Measures; 4.2 Data Analysis Question Types; 4.3 Building Models; 4.3.1 Testing Hypotheses; 4.3.2 Blueprint for Analytics; 4.4 Supervised and Unsupervised Methods; 4.4.1 Defining Supervised vs Unsupervised Methods; 4.4.2 Common Types of Algorithms; 4.4.3 Evaluating Model Performance; Summary; Questions; Examples: Insights through Analytics; Interpreting a Workforce Map; Part II: Applications; 5. Turnover; 5.1 Simple HR Analytics Are Useful Too; 5.2 Case of a Semiconductor Company in India | |
| 500 | |a 5.2.1 Design | ||
| 520 | |a 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. | ||
| 504 | |a Includes bibliographical references and index. | ||
| 650 | 0 | |a Personnel management |x Statistical methods. | |
| 650 | 6 | |a Personnel |x Direction |x Méthodes statistiques. | |
| 650 | 7 | |a Personnel & human resources management. |2 bicssc | |
| 650 | 7 | |a Business & Economics |x Human Resources & Personnel Management. |2 bisacsh | |
| 650 | 7 | |a Personnel management |x Statistical methods |2 fast | |
| 700 | 1 | |a Bussin, Mark. | |
| 700 | 1 | |a Lee, Venessa. | |
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| 776 | 0 | 8 | |i Print version: |a Diez, Fermin. |t Fundamentals of HR Analytics : A Manual on Becoming HR Analytical. |d Bingley : Emerald Publishing Limited, ©2019 |z 9781789739640 |
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| contents | Cover; FUNDAMENTALS OF HR ANALYTICS; PRAISE FOR FUNDAMENTALS OF HR ANALYTICS; FUNDAMENTALS OF HR ANALYTICS: A Manual on Becoming HR Analytical; Copyright; TABLE OF CONTENTS; LIST OF FIGURES; FOREWORD; ACKNOWLEDGMENTS; INTRODUCTION; Part I: The Basics of HR Analytics; 1. Basics of Finance, Statistics and Data-analytic Thinking; 1.1 Learning Objectives of This Chapter; 1.2 The Changing Nature of HR; 1.3 Why HR Analytics Now?; 1.4 Types of Analysis; 1.5 HR Analysts as Architects; 1.6 An Eight-step Approach to HR Analytics; 1.6.1 Define the Business Problem; 1.6.2 Formulate Hypotheses 1.6.3 Collect Data1.6.4 Analyse Data; 1.6.5 Derive Insights; 1.6.6 Build Recommendations; 1.6.7 Visualise and Tell a Story; 1.6.8 Execute and Evaluate; 1.7 Why Do Some Analytics Projects Fail?; 1.8 Finance for HR Professionals; 1.8.1 Profit Measures; 1.8.2 Market and Other Common Performance Measures; 1.8.3 Cost-related Terms; 1.9 Recap on Statistics Concepts; 1.9.1 Categorical and Continuous Variables; 1.9.2 Measures of Central Location; 1.9.3 Measures of Dispersion; 1.9.4 Measures of Association; 1.9.5 Population and Sampling; 1.9.6 Statistical Forecasting Models; Summary; Questions Workforce PlanningTalent Acquisition; Talent Engagement; Talent Development; Talent Deployment; Leading and Managing Talent; Talent Retention; 2. Tools for HR Analytics; 2.1 Technology Options; 2.1.1 On-premise; 2.1.2 Cloud Based; 2.2 Cost of Implementing On-premise vs Cloud; 2.3 Software as a Service; 2.4 Components of Analytics Technology; 2.4.1 Human Resources Information System; 2.4.2 HR Data Warehouse; 2.4.3 Reporting Technology; 2.4.4 Statistical Analysis and Machine Learning Technology; 2.4.5 Visualisation Technology; 2.4.6 Cognitive Technology; Summary; Questions; 3. Data Collection 3.1 Sources of Data3.1.1 HR Data; 3.1.2 HRIS Data; 3.1.3 Non-HR Data; 3.1.4 Data Audits; 3.1.5 Structured and Unstructured Data; 3.2 Common Data Challenges and Solutions; 3.2.1 Missing Data; 3.2.2 Outdated Data; 3.2.3 No Data Available; 3.2.4 Data Outliers; 3.3 Tidying the Data; 3.3.1 General Principles of Tidy Data; 3.3.2 Common Mistakes When Tidying Data; 3.3.3 Tips on Checking Data; 3.3.4 Common Mistakes When Checking the Data; 3.3.5 Plots Are Better than Summaries; Summary; Questions; Caselet; 4. HR Analytics Modelling; 4.1 Details of Analytics Design Framework 4.1.1 Source of Problem or Opportunity4.1.2 Scoping the Project; 4.1.3 Linking HR Variables to Business Measures; 4.2 Data Analysis Question Types; 4.3 Building Models; 4.3.1 Testing Hypotheses; 4.3.2 Blueprint for Analytics; 4.4 Supervised and Unsupervised Methods; 4.4.1 Defining Supervised vs Unsupervised Methods; 4.4.2 Common Types of Algorithms; 4.4.3 Evaluating Model Performance; Summary; Questions; Examples: Insights through Analytics; Interpreting a Workforce Map; Part II: Applications; 5. Turnover; 5.1 Simple HR Analytics Are Useful Too; 5.2 Case of a Semiconductor Company in India |
| ctrlnum | (OCoLC)1126217351 |
| dewey-full | 658.300727 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 658 - General management |
| dewey-raw | 658.300727 |
| dewey-search | 658.300727 |
| dewey-sort | 3658.300727 |
| dewey-tens | 650 - Management and auxiliary services |
| discipline | Wirtschaftswissenschaften |
| format | Electronic eBook |
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| indexdate | 2024-11-26T14:49:35Z |
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| publisher | Emerald Publishing Limited, |
| record_format | marc |
| spelling | Diez, Fermin. Fundamentals of HR Analytics : a Manual on Becoming HR Analytical. Bingley : Emerald Publishing Limited, 2019. 1 online resource (281 pages) text txt rdacontent computer c rdamedia online resource cr rdacarrier Print version record. Cover; FUNDAMENTALS OF HR ANALYTICS; PRAISE FOR FUNDAMENTALS OF HR ANALYTICS; FUNDAMENTALS OF HR ANALYTICS: A Manual on Becoming HR Analytical; Copyright; TABLE OF CONTENTS; LIST OF FIGURES; FOREWORD; ACKNOWLEDGMENTS; INTRODUCTION; Part I: The Basics of HR Analytics; 1. Basics of Finance, Statistics and Data-analytic Thinking; 1.1 Learning Objectives of This Chapter; 1.2 The Changing Nature of HR; 1.3 Why HR Analytics Now?; 1.4 Types of Analysis; 1.5 HR Analysts as Architects; 1.6 An Eight-step Approach to HR Analytics; 1.6.1 Define the Business Problem; 1.6.2 Formulate Hypotheses 1.6.3 Collect Data1.6.4 Analyse Data; 1.6.5 Derive Insights; 1.6.6 Build Recommendations; 1.6.7 Visualise and Tell a Story; 1.6.8 Execute and Evaluate; 1.7 Why Do Some Analytics Projects Fail?; 1.8 Finance for HR Professionals; 1.8.1 Profit Measures; 1.8.2 Market and Other Common Performance Measures; 1.8.3 Cost-related Terms; 1.9 Recap on Statistics Concepts; 1.9.1 Categorical and Continuous Variables; 1.9.2 Measures of Central Location; 1.9.3 Measures of Dispersion; 1.9.4 Measures of Association; 1.9.5 Population and Sampling; 1.9.6 Statistical Forecasting Models; Summary; Questions Workforce PlanningTalent Acquisition; Talent Engagement; Talent Development; Talent Deployment; Leading and Managing Talent; Talent Retention; 2. Tools for HR Analytics; 2.1 Technology Options; 2.1.1 On-premise; 2.1.2 Cloud Based; 2.2 Cost of Implementing On-premise vs Cloud; 2.3 Software as a Service; 2.4 Components of Analytics Technology; 2.4.1 Human Resources Information System; 2.4.2 HR Data Warehouse; 2.4.3 Reporting Technology; 2.4.4 Statistical Analysis and Machine Learning Technology; 2.4.5 Visualisation Technology; 2.4.6 Cognitive Technology; Summary; Questions; 3. Data Collection 3.1 Sources of Data3.1.1 HR Data; 3.1.2 HRIS Data; 3.1.3 Non-HR Data; 3.1.4 Data Audits; 3.1.5 Structured and Unstructured Data; 3.2 Common Data Challenges and Solutions; 3.2.1 Missing Data; 3.2.2 Outdated Data; 3.2.3 No Data Available; 3.2.4 Data Outliers; 3.3 Tidying the Data; 3.3.1 General Principles of Tidy Data; 3.3.2 Common Mistakes When Tidying Data; 3.3.3 Tips on Checking Data; 3.3.4 Common Mistakes When Checking the Data; 3.3.5 Plots Are Better than Summaries; Summary; Questions; Caselet; 4. HR Analytics Modelling; 4.1 Details of Analytics Design Framework 4.1.1 Source of Problem or Opportunity4.1.2 Scoping the Project; 4.1.3 Linking HR Variables to Business Measures; 4.2 Data Analysis Question Types; 4.3 Building Models; 4.3.1 Testing Hypotheses; 4.3.2 Blueprint for Analytics; 4.4 Supervised and Unsupervised Methods; 4.4.1 Defining Supervised vs Unsupervised Methods; 4.4.2 Common Types of Algorithms; 4.4.3 Evaluating Model Performance; Summary; Questions; Examples: Insights through Analytics; Interpreting a Workforce Map; Part II: Applications; 5. Turnover; 5.1 Simple HR Analytics Are Useful Too; 5.2 Case of a Semiconductor Company in India 5.2.1 Design 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. Includes bibliographical references and index. Personnel management Statistical methods. Personnel Direction Méthodes statistiques. Personnel & human resources management. bicssc Business & Economics Human Resources & Personnel Management. bisacsh Personnel management Statistical methods fast Bussin, Mark. Lee, Venessa. has work: Fundamentals of HR analytics (Text) https://id.oclc.org/worldcat/entity/E39PCGT9wxqVgmGVhyDCB8B8hb https://id.oclc.org/worldcat/ontology/hasWork Print version: Diez, Fermin. Fundamentals of HR Analytics : A Manual on Becoming HR Analytical. Bingley : Emerald Publishing Limited, ©2019 9781789739640 FWS01 ZDB-4-EBU FWS_PDA_EBU https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=2204225 Volltext |
| spellingShingle | Diez, Fermin Fundamentals of HR Analytics : a Manual on Becoming HR Analytical. Cover; FUNDAMENTALS OF HR ANALYTICS; PRAISE FOR FUNDAMENTALS OF HR ANALYTICS; FUNDAMENTALS OF HR ANALYTICS: A Manual on Becoming HR Analytical; Copyright; TABLE OF CONTENTS; LIST OF FIGURES; FOREWORD; ACKNOWLEDGMENTS; INTRODUCTION; Part I: The Basics of HR Analytics; 1. Basics of Finance, Statistics and Data-analytic Thinking; 1.1 Learning Objectives of This Chapter; 1.2 The Changing Nature of HR; 1.3 Why HR Analytics Now?; 1.4 Types of Analysis; 1.5 HR Analysts as Architects; 1.6 An Eight-step Approach to HR Analytics; 1.6.1 Define the Business Problem; 1.6.2 Formulate Hypotheses 1.6.3 Collect Data1.6.4 Analyse Data; 1.6.5 Derive Insights; 1.6.6 Build Recommendations; 1.6.7 Visualise and Tell a Story; 1.6.8 Execute and Evaluate; 1.7 Why Do Some Analytics Projects Fail?; 1.8 Finance for HR Professionals; 1.8.1 Profit Measures; 1.8.2 Market and Other Common Performance Measures; 1.8.3 Cost-related Terms; 1.9 Recap on Statistics Concepts; 1.9.1 Categorical and Continuous Variables; 1.9.2 Measures of Central Location; 1.9.3 Measures of Dispersion; 1.9.4 Measures of Association; 1.9.5 Population and Sampling; 1.9.6 Statistical Forecasting Models; Summary; Questions Workforce PlanningTalent Acquisition; Talent Engagement; Talent Development; Talent Deployment; Leading and Managing Talent; Talent Retention; 2. Tools for HR Analytics; 2.1 Technology Options; 2.1.1 On-premise; 2.1.2 Cloud Based; 2.2 Cost of Implementing On-premise vs Cloud; 2.3 Software as a Service; 2.4 Components of Analytics Technology; 2.4.1 Human Resources Information System; 2.4.2 HR Data Warehouse; 2.4.3 Reporting Technology; 2.4.4 Statistical Analysis and Machine Learning Technology; 2.4.5 Visualisation Technology; 2.4.6 Cognitive Technology; Summary; Questions; 3. Data Collection 3.1 Sources of Data3.1.1 HR Data; 3.1.2 HRIS Data; 3.1.3 Non-HR Data; 3.1.4 Data Audits; 3.1.5 Structured and Unstructured Data; 3.2 Common Data Challenges and Solutions; 3.2.1 Missing Data; 3.2.2 Outdated Data; 3.2.3 No Data Available; 3.2.4 Data Outliers; 3.3 Tidying the Data; 3.3.1 General Principles of Tidy Data; 3.3.2 Common Mistakes When Tidying Data; 3.3.3 Tips on Checking Data; 3.3.4 Common Mistakes When Checking the Data; 3.3.5 Plots Are Better than Summaries; Summary; Questions; Caselet; 4. HR Analytics Modelling; 4.1 Details of Analytics Design Framework 4.1.1 Source of Problem or Opportunity4.1.2 Scoping the Project; 4.1.3 Linking HR Variables to Business Measures; 4.2 Data Analysis Question Types; 4.3 Building Models; 4.3.1 Testing Hypotheses; 4.3.2 Blueprint for Analytics; 4.4 Supervised and Unsupervised Methods; 4.4.1 Defining Supervised vs Unsupervised Methods; 4.4.2 Common Types of Algorithms; 4.4.3 Evaluating Model Performance; Summary; Questions; Examples: Insights through Analytics; Interpreting a Workforce Map; Part II: Applications; 5. Turnover; 5.1 Simple HR Analytics Are Useful Too; 5.2 Case of a Semiconductor Company in India Personnel management Statistical methods. Personnel Direction Méthodes statistiques. Personnel & human resources management. bicssc Business & Economics Human Resources & Personnel Management. bisacsh Personnel management Statistical methods fast |
| title | Fundamentals of HR Analytics : a Manual on Becoming HR Analytical. |
| title_auth | Fundamentals of HR Analytics : a Manual on Becoming HR Analytical. |
| title_exact_search | Fundamentals of HR Analytics : a Manual on Becoming HR Analytical. |
| title_full | Fundamentals of HR Analytics : a Manual on Becoming HR Analytical. |
| title_fullStr | Fundamentals of HR Analytics : a Manual on Becoming HR Analytical. |
| title_full_unstemmed | Fundamentals of HR Analytics : a Manual on Becoming HR Analytical. |
| title_short | Fundamentals of HR Analytics : |
| title_sort | fundamentals of hr analytics a manual on becoming hr analytical |
| title_sub | a Manual on Becoming HR Analytical. |
| topic | Personnel management Statistical methods. Personnel Direction Méthodes statistiques. Personnel & human resources management. bicssc Business & Economics Human Resources & Personnel Management. bisacsh Personnel management Statistical methods fast |
| topic_facet | Personnel management Statistical methods. Personnel Direction Méthodes statistiques. Personnel & human resources management. Business & Economics Human Resources & Personnel Management. Personnel management Statistical methods |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=2204225 |
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