462 section 4 St ppr.r rrn I)t.rtrlrr I't,tllNrlr; ,tNtr Cttltritit Fmne*ast err*r The difference between actual demand and what was forecast. Mean absolute deviation (MAD) The average of the absolute value of the actual forecast enor. error range, fbr this analysis, consisls of errors resulting iiom both lines as well as all other possihle lines. We included this exhibit to show ho,*' the effor rAnse widens as we so furlher into the future. S*r*{:;x$t Hrri:rg In using thc tcrm , wc arc rcf.crring to thc diffcrcncc bctwcen what actually occurred and wl.rat was fbrecasl. In statistics, ihese errors are called residuals. As long as thc lbrccast value is rvithin thc conficlcncc lirnits, as wc discuss later under thc hcading. "Measurement of Enclr," this is not really an cror sincc it is what we expected. But comnlon usage rel'ers to the difference as an error. Demand tbr a product is generated tl.rrough the interaction of a numbet'of l-actrlrs too coln- plex to descrihc accurately in a rnodel. Therefbre, all forecasts certainly colttain some clror. In discussing tbrecast errors, it is convenient to distinguish between sources ctf error and the measttretnenl of e rnt r. $o u rges sf H rro r Errorscan come from avariefyof sources. (Jne common source that many tbrecasters are unaware of is projccting past trencls into the future. For example. whel wc talk about statislical erLors in regression aualysis, we are rct-crring to thc deviations of observations from our regression line. It is common to attach a confidenco band (that is, statistical control limits) to the regression line to reduce the unexplained etror. But when we then use this regression l:ine as a fbrecasting device by projercting it into the fitture. the etror may not bc correctly definccl by tlie proiected contidence band. This is bccause the confidencc interval is basod u1 past data; it may not hold tbr projected data points and therclirre cannol' be used with thc same confidencc. In fact, experience has shown that the actual errors tend to be grcater than tliose predicted [l'om lbrecast models. Erors can be classifierj as bias or randclm. Bius errors occur when a cutsistent mistake is madc' sourccs ot'bias incltttlc thc iailurc to includc thc right variablcs: thc: usc tll'thc wrong relationships among variables; cmploying the wrong trend line; a mistaken shift in the sea- sonal demancl frorn where it normally occurs; ancl the cxistencc of somc unclctectcd sccular trend. Rantlorn errors can be defined iis those that cannot be explained by the forecast model being uscd. M e a s u re m €nt of E rrgr Scvcral common tcrms uscd to dcscrihe: thc dcgrccr of elTor arc standard error, nleen squared error (ot t,ariance), an(l mean absoltrte devittion. In a{clition. tracking signals may he used to indicate any positive or negative hias in the forccast- Standard eror is discussed in the section on linear regression in this chaptc'r. Becartse the stanriard errtlr is the square .

1. 462 section 4 St ppr.r rrn I)t.rtrlrr I't,tllNrlr; ,tNtr Cttltritit
Fmne*ast err*r
The difference between
actual demand and
what was forecast.
Mean absolute
deviation (MAD)
The average of the
absolute value of the
actual forecast enor.
error range, fbr this analysis, consisls of errors resulting iiom
both lines as well as all other
possihle lines. We included this exhibit to show ho,*' the effor
rAnse widens as we so furlher
into the future.
S*r*{:;x$t Hrri:rg
In using thc tcrm , wc arc rcf.crring to thc diffcrcncc bctwcen
what actually
occurred and wl.rat was fbrecasl. In statistics, ihese errors are
called residuals. As long as
thc lbrccast value is rvithin thc conficlcncc lirnits, as wc
discuss later under thc hcading.
"Measurement of Enclr," this is not really an cror sincc it is
what we expected. But comnlon
usage rel'ers to the difference as an error.
Demand tbr a product is generated tl.rrough the interaction of a

2. numbet'of l-actrlrs too coln-
plex to descrihc accurately in a rnodel. Therefbre, all forecasts
certainly colttain some clror.
In discussing tbrecast errors, it is convenient to distinguish
between sources ctf error and the
measttretnenl of e rnt r.
$o u rges sf H rro r Errorscan come from avariefyof sources.
(Jne common source
that many tbrecasters are unaware of is projccting past trencls
into the future. For example.
whel wc talk about statislical erLors in regression aualysis, we
are rct-crring to thc deviations
of observations from our regression line. It is common to attach
a confidenco band (that is,
statistical control limits) to the regression line to reduce the
unexplained etror. But when we
then use this regression l:ine as a fbrecasting device by
projercting it into the fitture. the etror
may not bc correctly definccl by tlie proiected contidence band.
This is bccause the confidencc
interval is basod u1 past data; it may not hold tbr projected data
points and therclirre cannol' be
used with thc same confidencc. In fact, experience has shown
that the actual errors tend to be
grcater than tliose predicted [l'om lbrecast models.
Erors can be classifierj as bias or randclm. Bius errors occur
when a cutsistent mistake is

3. madc' sourccs ot'bias incltttlc thc iailurc to includc thc right
variablcs: thc: usc tll'thc wrong
relationships among variables; cmploying the wrong trend line;
a mistaken shift in the sea-
sonal demancl frorn where it normally occurs; ancl the
cxistencc of somc unclctectcd sccular
trend. Rantlorn errors can be defined iis those that cannot be
explained by the forecast model
being uscd.
M e a s u re m €nt of E rrgr Scvcral common tcrms uscd to
dcscrihe: thc dcgrccr of
elTor arc standard error, nleen squared error (ot t,ariance), an(l
mean absoltrte devittion.
In a{clition. tracking signals may he used to indicate any
positive or negative hias in the
forccast-
Standard eror is discussed in the section on linear regression in
this chaptc'r. Becartse the
stanriard errtlr is the square root of a tunction. it is often mu'e
convenient to use the function
itsclf. This is called the merur squared error. or variatlce.
Tht: was in l'ogue in the past but subsequcntly was
iglored in f-avor of standard deviation and standard error
measures. In recent years, MAD
has made a comeback bccause ol'its simplicity and usefulness in
obtaining tracking signals.
MAD is the average error in the forecasts. using absolute
values. It is valuablc because MAD,
like the stanclard deviaticln, measures the dispersion of some
observed value iiom some ex-
pected value.

4. MAD is computod using the di{I'erences between the actual
demand lrnd thc lbrecast de-
rnancl rr,'ithoul regard to sign. It equals the sum of the
abscllute deviations divided by the num-
ber ol-clata points or, staled in equation {brm,
!ra, * r, r
MAD: *J--=r-
where
r - Pcriod numbcr
A, : Actual demand fbr the period /
Analytics
[18.1{]
Managing+Human+Resources+(8th+Edition)+-
+Luis+R.+Gomez-Mejia.pdf
MANAGING HUMAN RESOURCES
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MANAGING HUMAN RESOURCES

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E I G H T H E D I T I O N
Luis R. Gómez-Mejía
University of Notre Dame
David B. Balkin
University of Colorado, Boulder
Robert L. Cardy
University of Texas at San Antonio
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Library of Congress Cataloging-in-Publication Data
GÓmez-Mejía, Luis R.
Managing human resources / Luis R. GÓmez-Mejía, David B.
Balkin & Robert L. Cardy.—Eighth Edition.

8. pages cm
ISBN 978-0-13-302969-7—ISBN 0-13-302969-7
1. Personnel management. I. Balkin, David B., 1948- II. Cardy,
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To my wife Ana, my two sons Vince and Alex,
and my daughter Dulce
—L.G.M.
To my parents, Daniel and Jeanne
—D.B.B.
To my family for their endless support and to Todd Snider
for the endless inspiration
—R.L.C.
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vii
Brief Contents
PART I Introduction 1

10. Chapter 1 Meeting Present and Emerging Strategic Human
Resource Challenges 1
PART II The Contexts of Human Resource Management 44
Chapter 2 Managing Work Flows and Conducting Job Analysis
44
Chapter 3 Understanding Equal Opportunity and the Legal
Environment 82
Chapter 4 Managing Diversity 118
PART III Staffing 149
Chapter 5 Recruiting and Selecting Employees 149
Chapter 6 Managing Employee Separations, Downsizing,
and Outplacement 181
PART IV Employee Development 203
Chapter 7 Appraising and Managing Performance 203
Chapter 8 Training the Workforce 235
Chapter 9 Developing Careers 261
PART V Compensation 286
Chapter 10 Managing Compensation 286
Chapter 11 Rewarding Performance 324
Chapter 12 Designing and Administering Benefits 360
PART VI Governance 399
Chapter 13 Developing Employee Relations 399
Chapter 14 Respecting Employee Rights and Managing
Discipline 428
Chapter 15 Working with Organized Labor 464
Chapter 16 Managing Workplace Safety and Health 500
Chapter 17 International HRM Challenge 529

11. viii
Contents
Preface xix
Acknowledgments xxv
About the Authors xxvii
PART I Introduction 1
Chapter 1 Meeting Present and Emerging Strategic Human
Resource Challenges 1
Human Resource Management: The Challenges 2
Environmental Challenges 3
Organizational Challenges 10
Competitive Position: Cost, Quality, or Distinctive Capabilities
10
Individual Challenges 17
Planning and Implementing Strategic HR Policies 20
The Benefits of Strategic HR Planning 21
The Challenges of Strategic HR Planning 22
Strategic HR Choices 24
Selecting HR Strategies to Increase Firm Performance 27
Fit with Organizational Strategies 28
Fit with the Environment 30
Fit with Organizational Characteristics 31
Fit with Organizational Capabilities 32
Choosing Consistent and Appropriate HR Tactics to Implement
HR Strategies 33
HR Best Practices 33

12. The HR Department and Managers: An Important Partnership 34
Specialization in Human Resource Management 35
Summary and Conclusions 35 • Key Terms 36 • Discussion
Questions 37
■ YOU MANAGE IT! 1: EMERGING TRENDS
Electronic Monitoring to Make Sure That No One Steps Out of
Line 38
■ YOU MANAGE IT! 2: ETHICS/SOCIAL RESPONSIBILITY
Embedding Sustainability into HR Strategy 40
■ YOU MANAGE IT! 3: DISCUSSION
Managers and HR Professional at Sands Corporation:
Friends or Foes? 41
■ YOU MANAGE IT! 4: DISCUSSION
The Enduring Wage Gap by Gender 42
PART II The Contexts of Human Resource Management 44
Chapter 2 Managing Work Flows and Conducting Job Analysis
44
Work: The Organizational Perspective 45
Strategy and Organizational Structure 45
Designing the Organization 46
Work-Flow Analysis 49
Business Process Reengineering 49
Work: The Group Perspective 50
Self-Managed Teams 50
Other Types of Teams 51

13. CONTENTS ix
Work: The Individual Perspective 53
Motivating Employees 53
Designing Jobs and Conducting Job Analysis 55
Job Design 55
Job Analysis 57
Job Descriptions 63
The Flexible Workforce 67
Contingent Workers 67
Flexible Work Schedules 72
The Mobile Workplace 73
Human Resource Information Systems 74
HRIS Applications 74
HRIS Security and Privacy 75
Summary and Conclusions 75 • Key Terms 76 • Discussion
Questions 77
■ YOU MANAGE IT! 1: ETHICS/SOCIAL RESPONSIBILITY
Are Companies Exploiting College Students Who Have Unpaid
Internships? 78
■ YOU MANAGE IT! 2: EMERGING TRENDS
Work–Life Balance Is the New Perk Employees Are Seeking 79
■ YOU MANAGE IT! 3: TECHNOLOGY/SOCIAL MEDIA
Yahoo CEO Issues a Ban on Telecommuting for Employees 80
■ YOU MANAGE IT! 4: CUSTOMER-DRIVEN HR
Writing a Job Description 81

14. Chapter 3 Understanding Equal Opportunity and the Legal
Environment 82
Why Understanding the Legal Environment Is Important 84
Doing the Right Thing 84
Realizing the Limitations of the HR and Legal Departments 84
Limiting Potential Liability 84
Challenges to Legal Compliance 85
A Dynamic Legal Landscape 85
The Complexity of Laws 85
Conflicting Strategies for Fair Employment 85
Unintended Consequences 86
Equal Employment Opportunity Laws 86
The Equal Pay Act of 1963 87
Title VII of the Civil Rights Act of 1964 87
Defense of Discrimination Charges 89
Title VII and Pregnancy 90
Sexual Harassment 90
The Civil Rights Act of 1991 94
Executive Order 11246 95
The Age Discrimination in Employment Act of 1967 95
The Americans with Disabilities Act of 1990 96
EEO Enforcement and Compliance 99
Regulatory Agencies 99
Office of Federal Contract Compliance Programs (OFCCP) 100
Affirmative Action Plans 101
Other Important Laws 103
Avoiding Pitfalls in EEO 105
Provide Training 105
Establish a Complaint Resolution Process 105
Document Decisions 105

15. Be Honest 105
Ask Only for Information You Need to Know 106
x CONTENTS
Summary and Conclusions 109 • Key Terms 110 • Discussion
Questions 110
■ YOU MANAGE IT! 1: EMERGING TRENDS
Walgreens Leads the Way in Utilizing Workers with Disabilities
111
■ YOU MANAGE IT! 2: CUSTOMER-DRIVEN HR
Can an Employer Refuse to Hire or Retain Employees Who
Wear Tattoos? 112
■ YOU MANAGE IT! 3: DISCUSSION
Are Women Breaking Through the Glass Ceiling? 113
■ YOU MANAGE IT! 4: ETHICS/SOCIAL RESPONSIBILITY
Are Employee Noncompete Agreements Legally Enforceable? It
Depends 114
Appendix to Chapter 3 116
Human Resource Legislation Discussed in This Text 116
Chapter 4 Managing Diversity 118
What Is Diversity? 119
Why Manage Employee Diversity? 120
Affirmative Action Versus Managing Employee Diversity 120
Demographic Trends 120
Diversity as Part of Corporate Strategy 124

16. Challenges in Managing Employee Diversity 124
Diversity Versus Inclusiveness 125
Individual Versus Group Fairness 125
Resistance to Change 125
Group Cohesiveness and Interpersonal Conflict 125
Segmented Communication Networks 125
Resentment 125
Retention 126
Competition for Opportunities 126
Diversity in Organizations 126
African Americans 126
Asian Americans 127
People with Disabilities 128
The Foreign Born 129
Homosexuals 130
Latinos (Hispanic Americans) 131
Older Workers 132
Religious Minorities 133
Women 135
Improving the Management of Diversity 137
Creating an Inclusive Organizational Culture 137
Top-Management Commitment to Valuing Diversity 138
Appraising and Rewarding Managers for Good Diversity
Practices 138
Diversity Training Programs 138
Support Groups 139
Accommodation of Family Needs 139
Senior Mentoring Programs 141
Apprenticeships 141
Communication Standards 141
Diversity Audits 141
Management Responsibility and Accountability 141
Some Warnings 142

17. Avoiding the Appearance of “White Male Bashing” 142
Avoiding the Promotion of Stereotypes 142
Summary and Conclusions 142 • Key Terms 143 • Discussion
Questions 143
■ YOU MANAGE IT! 1: TECHNOLOGY/SOCIAL MEDIA
Hiring Who You Know as a Threat to Diversity 145
CONTENTS xi
■ YOU MANAGE IT! 2: EMERGING TRENDS
Why Women Lag Behind in MBA Programs 145
■ YOU MANAGE IT! 3: ETHICS/SOCIAL RESPONSIBILITY
Interpreting the Americans with Disabilities Act: The Hot
Frontier
of Diversity Management 146
■ YOU MANAGE IT! 4: DISCUSSION
Conflict at Northern Sigma 147
PART III Staffing 149
Chapter 5 Recruiting and Selecting Employees 149
Human Resource Supply and Demand 150
A Simplified Example of Forecasting Labor Demand and Supply
152
Forecasting Techniques 154
The Hiring Process 155
Challenges in the Hiring Process 155

18. Determining Characteristics Important to Performance 156
Measuring Characteristics That Determine Performance 156
The Motivation Factor 156
Who Should Make the Decision? 157
Meeting the Challenge of Effective Staffing 157
Recruitment 157
Sources of Recruiting 158
Selection 163
Reliability and Validity 163
Selection Tools as Predictors of Job Performance 164
Combining Predictors 171
Selection and Person/Organization Fit 171
Reactions to Selection Devices 172
Legal Issues in Staffing 173
Discrimination Laws 173
Affirmative Action 173
Negligent Hiring 174
Summary and Conclusions 174 • Key Terms 175 • Discussion
Questions 175
■ YOU MANAGE IT! 1: CUSTOMER-DRIVEN HR
Women: Keeping the Supply Lines Open 176
■ YOU MANAGE IT! 2: ETHICS/SOCIAL RESPONSIBILITY
What a Fraud! 177
■ YOU MANAGE IT! 3: TECHNOLOGY/SOCIAL MEDIA
Social Media in the Hiring Process 178
■ YOU MANAGE IT! 4: ETHICS/SOCIAL RESPONSIBILITY
Fitting in Social Responsibility 179
■ YOU MANAGE IT! 5: EMERGING TRENDS

19. One Job, Many Roles 180
Chapter 6 Managing Employee Separations, Downsizing,
and Outplacement 181
What Are Employee Separations? 182
The Costs of Employee Separations 182
The Benefits of Employee Separations 186
Types of Employee Separations 186
Voluntary Separations 186
Involuntary Separations 187
Managing Early Retirements 190
The Features of Early Retirement Policies 190
Avoiding Problems with Early Retirements 190
xii CONTENTS
Managing Layoffs 191
Alternatives to Layoffs 191
Implementing a Layoff 192
Outplacement 195
The Goals of Outplacement 196
Outplacement Services 196
Summary and Conclusions 196 • Key Terms 197 • Discussion
Questions 197
■ YOU MANAGE IT! 1: GLOBAL
Turnover: A Global Management Issue 198
■ YOU MANAGE IT! 2: ETHICS/SOCIAL RESPONSIBILITY

20. Employment-at-Will: Fair Policy? 199
■ YOU MANAGE IT! 3: CUSTOMER-DRIVEN HR
From Turnover to Retention: Managing to Keep Your Workers
200
■ YOU MANAGE IT! 4: TECHNOLOGY/SOCIAL MEDIA
You’re Fired! 201
PART IV Employee Development 203
Chapter 7 Appraising and Managing Performance 203
What Is Performance Appraisal? 205
The Uses of Performance Appraisal 206
Identifying Performance Dimensions 206
Measuring Performance 207
Measurement Tools 208
Measurement Tools: Summary and Conclusions 214
Challenges to Effective Performance Measurement 215
Rater Errors and Bias 216
The Influence of Liking 217
Organizational Politics 217
Individual or Group Focus 219
Legal Issues 219
Managing Performance 220
The Appraisal Interview 221
Performance Improvement 223
Identifying the Causes of Performance Problems 223
Developing an Action Plan and Empowering Workers to Reach a

21. Solution
225
Directing Communication at Performance 225
Summary and Conclusions 226 • Key Terms 226 • Discussion
Questions 227
■ YOU MANAGE IT! 1: ETHICS/SOCIAL RESPONSIBILITY
Rank and Yank: Legitimate Performance Improvement Tool or
Ruthless
and Unethical Management? 228
■ YOU MANAGE IT! 2: GLOBAL
Competencies in a Global Environment 229
■ YOU MANAGE IT! 3: TECHNOLOGY/SOCIAL MEDIA
Going Digital with Appraisal 230
■ YOU MANAGE IT! 4: ETHICS/SOCIAL RESPONSIBILITY
Let’s Do It Right 231
■ YOU MANAGE IT! 5: CUSTOMER-DRIVEN HR

22. Build on Their Strengths 232
Appendix to Chapter 7 233
The Critical-Incident Technique: A Method for Developing a
Behaviorally
Based Appraisal Instrument 233
Chapter 8 Training the Workforce 235
Key Training Issues 236
Training Versus Development 237
Challenges in Training 239
Is Training the