HR metrics : practical measurement tools for people management : 'practical illustration using MS Excel' / by Dr. Gregory John Lee.

Format:

Book

Author/Creator:

Lee, Gregory John, author.

Language:

English

Subjects (All):

Microsoft Excel (Computer file).

Personnel management--Evaluation.

Personnel management.

Physical Description:

1 online resource (430 p.)

Edition:

1st ed.

Place of Publication:

Randburg, Republic of South Africa : Knowres Publishing, 2011.

Language Note:

English

Summary:

HR Metrics introduce HR practitioners and students to two sets of crucial analysis skills, in an accessible and non-technical manner.

Contents:

Cover; CONTENTS; ABOUT THE AUTHOR; PREFACE; PART I Introduction to the Nature of Human Resource Management; CHAPTER 1 HUMAN RESOURCE MANAGEMENT AND THE HR VALUE CHAIN; 1.1 WHAT DOES HUMAN RESOURCE MANAGEMENT (HRM) CONSTITUTE?; 1.1.1 What activities does the HR function comprise?; 1.1.2 Who 'performs' HR?; 1.2 THE HR VALUE CHAIN; 1.2.1 Analysis and assessment within the value chain; 1.2.2 Details and components of the HR value chain; PART II Introduction to Human Resource Data Analysis; CHAPTER 2 INTRODUCTION TO HR DATA; 2.1 BASIC HR DATA TYPES; 2.1.1 Data type 1: Employee records

2.1.2 Data type 2: Performance records2.1.3 Data type 3: Operational data; 2.1.4 Data type 4: Job-related information; 2.1.5 Data type 5: Survey data; 2.1.6 Data type 6: Qualitative data; 2.1.7 Special data files; 2.2 FEATURES OF A DATA POINT; 2.2.1 Numerical versus text (character) data; 2.2.2 Dates and times; 2.3 FROM DATA POINTS TO VARIABLES ACROSS SAMPLES; 2.3.1 Variables; 2.3.2 Populations and samples; 2.4 BASIC CHARACTERISTICS OF VARIABLES; 2.4.1 Characteristics of variables; 2.4.2 Introduction to relating sets of data; 2.4.3 Standardising data; 2.5 GETTING DATA COLLECTION RIGHT

2.5.1 Correct sampling2.5.2 Question and answer formats; 2.5.3 Cleaning captured data; 2.6 DATABASE AND DATA ANALYSIS SOFTWARE FOR HR; 2.7 EXERCISES; CHAPTER 3 LINKING HR VARIABLES THROUGH REGRESSION; 3.1 INTRODUCTION TO STATISTICAL INFERENCE AND REGRES-SION; 3.2 THEORY OF LINEAR CORRELATION/REGRESSION ANALYSIS; 3.2.1 What does regression try to achieve?; 3.2.2 A pictorial walk through simple linear regression; 3.2.3 Examining fit in more detail: Error and residuals; 3.2.4 What happens if fit cannot be achieved?; 3.3 PRACTICAL REGRESSION ANALYSIS IN EXCEL 2007

3.3.1 Steps in practical regression analysis3.3.2 Step 1: Collect, capture and clean data; 3.3.3 Step 2: Do an initial regression with Excel data analysis; 3.3.4 Step 3: Assess fit and apply remedies if necessary; 3.3.5 Step 3: Building and interpreting the regression equa-tion; 3.4 OTHER STATISTICAL FORMS; CHAPTER 4 ASSESSING THE IMPACT OF AN HR PROGRAMME OR EVENT; 4.1 BASIC PRE- AND POST-TEST EXPERIMENTAL ASSESSMENT; 4.2 CONTROLLING FOR ARTEFACTS; 4.2.1 Controlling for artefacts with control groups; 4.2.2 Possible types of artefacts in experimental analysis

4.2.3 Some common experimental designs4.3 EXPERIMENTAL DESIGN STEPS; 4.3.1 Step 1: Deciding on evaluation outcomes; 4.3.2 Step 2: Designing evaluation tools to assess outcomes; 4.3.3 Step 3: Deciding on the evaluation design (groups and tests); 4.3.4 Step 4: Executing the event and evaluation tests; 4.3.5 Step 5: Comparing standardised changes between tests and groups; 4.3.6 Reflecting on the experiment; 4.3.7 Deciding what the experiment implies for future HR intervention; 4.4 ALTERNATIVE REGRESSION APPROACH TO EVENT ANALYSIS; 4.5 TIME SERIES APPROACHES TO EVALUATING EVENTS

4.6 COMPARISON METHOD # 3: BENCHMARKING

Notes:

Description based upon print version of record.

Description based on online resource; title from PDF title page (ebrary, viewed August 4, 2015).

ISBN:

1-283-84999-2

1-86922-209-1

OCLC:

843095043