Motivations to Manage Turnover
1. Economic Trends
• Directly related to economic conditions
∙ Unemployment rate Feb. 2010: Nation 9.7% Iowa 6.7%
• Turnover high when unemployment is low
• Turnover low during poor economic times
2. Demographic Trends
• Retirement patterns
• Low number of workforce entrants
• Next generation may prefer to work
fewer hours
3. Changing Employment Patterns
∙ Shorter job tenures
• Ages 18 to 32: 8.6 jobs
• Overall, employees changing jobs every 4 years
Motivations to Manage Turnover
4. Normal Voluntary Turnover?
● Fortune Magazine’s 100 Best Companies (next 2 slides)
● Company rate/level may not be ideal anyway (AZ Council)
•1.6% month (Dec.), 2.7% (Aug)
• 13 - 20% / year now normal
• Some industries and low level service:
100 - 140% normal
5. Need to Consider Customer Satisfaction
Sears also linked T/O to customer satisfaction
▲Stores w/high customer sat: 54% turnover
▲Stores w/low customer satisfaction: 83% turnover
6. Need to Manage (but not eliminate) Turnover
▪ Who is quitting? ▪ What are the replacement costs?
7. Need to Reduce High Replacement Costs (next slide)
▪ Direct
▪ Indirect
Turnover Rates Among Fortune 100’s Best
Potential Savings
Company1
Number of
Employees
(US)
Turnover
Estimated
Reducing
Rate
Turnover Cost Turnover 1%
per employee2 Savings / year
Merck
39,489
9%
$7592
$2,765,000
Cerner
2,953
14%
$8000
$240,000
Charles
Schwab
18,863
12%
$8329
$1,512,000
MBNA
America
Bank
16,960
15%
$4800
$1,000,000
Average US
Company
10,000
15.6%
$5000
$500,000
Notes:
1. Based on Public Data from Fortune Magazine’s 100 Best Companies to work for January 2001.
2. Estimated Turnover Costs Calculated at 20% of most common entry level salary ($42,940) as provided in note 1.
Fortune 100 Firms with Consistently Low Voluntary Turnover
Company
2008/09/10 Best
Companies Rank
2008/09
% Turnover
S.C. Johnson
27/81/83
2/2
Herman Miller
96/89/97
3/5
Alcon Laboratories
60/74/-
3/3
Cisco Systems
6/6/16
4/5
General Mills
69/99/90
4/4
Devon Energy
48/13/20
4/4
SAS Institute
29/20/1
5/3
Mayo Clinic
59/63/55
5/5
Fortune
Turnover Rates: Mental Health
Jobs
66
Human Resource Assistant
14
Secretary
200
Maintenance Worker
Driver
Therapist
27
0
34
40
47
Cook
Case Manager
Teachers
92
Behavioral Health Technician
16
Teachers Aide
60
Supervisor
36
Clinical Director
100
Accountant
33
HR Manager
60
Controller
Executive Director
0
0
50
100
150
200
Annual Turnover Rates
250
TURNOVER COSTS
Based on Entry Level Salary of $47,097
Replacement Acquisition
- Direct hiring costs
- Other hiring costs
Replacement Training
- Pre-assignment
- Learning curve
(see learning curve graph)
Other costs
- Unabsorbed burden
- Lost profit contribution
TOTAL
*Entry level salary of Fortune 500 employee (2010 figures)
$1098
693
2833
795
2,549
1,452
$9,420
Percent of Standard Proficiency Attained
Hypothetical Learning Curve for New Hires
100
80
60
40
20
0
1
25
50
75
Employment Duration (Days)
100
TURNOVER COST EXAMPLES BY
COMPANY AND POSITION
Company
State govt, (LA)
Machine works
Insurance
Position
Protective services
(police, wildlife &
fisheries, guards)
Salaried Machinist
Hourly Machinist
(both journeyman)
Manager
Software
Project Leader
Systems engineer
Hospitality
Hotel front desk-Miami
Hotel front desk-NY
Fast-food chain
Store Manager
Counter Person
Source: Bulletin to Management, 6-17-99, Kepner &
Tregoe, Jan. 1999 (Saratoga Institute Turnover
Costing Model), SASHA Corp 2007
Cost
$25,000
$102,376
$ 58,564
$ 79,672
$ 32,160
$ 34,365
$ 5688
$ 11609
$ 20,765
$ 1,204
Forms of Turnover
• Nonvoluntary:
Employer controlled
(layoffs,
terminations,
downsizing)
• Voluntary:
Employee controlled
(quits, retirements)
• Gray Area: (spouse
relocation,
child/elder care
problem, exit
Primary Reason For Leaving In Nursing Sample
Reasons Unknown
Personal Reasons
Death
Retirement
Poor Health
Temporary Position
Completed Prescribed Service or Course
Geographic Factors:Job Too Far, Leaving City
Family Illness or Home Duties
To Stay Home
To Attend School
Pregnancy
Marriage
Enter Military Service
Unsatisfactory Work Hours
Work Too Difficult; Misunderstanding of Duties
General Job Dissatisfaction
Present Wages Inadequate
Other Employment
10
15
0
0
0
0
0
30
0
5
5
0
20
0
5
0
0
0
10
0
5
10
15
20
25
Percent of Voluntary Leavers
30
35
Analyzing Forms of Turnover
Among Nurses from A
Managerial Perspective:
Organizational Level
Turnover
14.6%
Voluntary
87%
Functional
42%
Involuntary
13%
Dysfunctional
58% (7.37% rather than 14.6%)
Turnover Measures
1. Separation Rate
=
# of employees who left during period
avg. # of employees during period
X 100
a. Jan. 1 - 20 employees 7 quit and are replaced, 2 new hires
Jan 31 - 22 employees
7/(20 + 22)/2 = 7/21 = 1/3 = .33 .33 x 100 = 33%
b. Growth scenario
Feb. 1 - 22 employees 16 new hires, 7 quit & are replaced
Feb. 28 - 38 employees
7/(22 + 38)/2 = 7/30 = .23 or 23%
Turnover Measures (Continued)
II. Instability Rate
# of initial employees who leave during a period
=
# of initial employees
X 100
a. Jan.: 7/20 = .35 or 35%
b. Feb.: 7/22 = .32 or 32%
III. Wastage Rate
# of new employees who leave during a period
=
# of new members
X 100
a. Between Feb. 1 & 28, 8 new hires quit: 8/16 = .50 or 50%
IV. Avg. Length = Sum of length of service for each employee
of Service
# of members
Predictors of Voluntary Turnover
1.  Age  Turnover
(around ρ = -.14)
Length of service
▪ side bets
▪ health insurance less problematic
if coverage is continuous
3. Sex & family size
Men & women quit at similar rates
↑ # of dependents → ↓ T/O
4. Pre-employment predictors:
▪ prior turnover behavior
▪ others in Barrick & Zimmerman
Predictors of Voluntary Turnover
5. Personality
▪ Conscientiousness (ρ = -.20)
▪ Emotional stability (ρ = -.18)
▪ Agreeableness (ρ = -.25)
▪ Extraversion (ρ = -.04) [zero]
▪ Openness (ρ = .10)
▪ Self-confidence (B&Z)
▪ Decisiveness (B&Z)
6. Union presence
7. Attitudes (job satisfaction, organizational
commitment; see upcoming Hom Griffeth model)
8. Pre-employment interventions (e.g., RJPs)
Providing Job Candidates With Accurate and Complete
Information About the New Job Reduces Turnover
Sewing Machine
Operators
40
11.1
11.5
6
West Point Cadets
50
33.8
Telephone Operators
27
19
Insurance Agents
35
15
Bank Tellers
22.4
U.S. Marines
33.1
Control Group
21.1
8.5
RJP Group
Nurses
0
10
20
30
Turnover Rates
40
50
60
Predictors of Voluntary Turnover
9. Work group size
10. Job enrichment
11. Task repetitiveness
12. Considerate leadership
13. Stress
14. Perceived job availability
15. Withdrawal behaviors: Lateness (rho = .06) and
absenteeism (rho = .33)
16. Job performance (low performers quit more than
high performers but low and high performers
quit more than avg. performers)
Hom-Griffeth Model of Turnover
Satisfaction Influences:
•Job Complexity
•Role Stress
•Group Cohesion
•Compensation
•Leader-Member Relations
•Met Expectations
•Negative Affectivity
Commitment Influences:
•Procedural Justice
•Attraction of Internal Roles
•Job Security
•Job Investments
•Extra Organizational Conflicts
•Conditions of Job Entry
•Commitment Propensity
Job
Satisfaction
Organizational
Commitment
Labor Market:
•Unemployment
•Knowledge of
Other Jobs
•Relocation Costs
Shocks
Decisions to
Quit
Job-Seeking
Costs &
Benefits:
Turnover
Costs &
Benefits
Job
Search
Evaluate
Alternatives
Resignation
POSSIBLE POSITIVE
CONSEQUENCES OF TURNOVER
1. Displacement of poor performers
2. Increased satisfaction among stayers
3. Infusion of new knowledge/technology via replacements
4. Facilitate organizational change
5. Increased internal mobility opportunities
6. Decrease in other “withdrawal” behaviors
7. Opportunities for cost reduction
RECOMMENDATIONS FOR INCREASED
UNDERSTANDING OF TURNOVER
1. Focus on occupational differences (more understanding
of blue collar turnover needed)
2. Separate voluntary from non-voluntary turnover
3. Study turnover in the context of economic conditions and
historical changes (e.g., new generations of employees,
dual career families, new employment patterns of more
frequent job changes).
PRACTICAL STRATEGIES FOR
MANAGING TURNOVER
1. Hire more carefully
2. Use pre-employment interventions (see example)
3. Promote job satisfaction
4. Promote job autonomy through job enrichment
5. Use small work groups
6. Reduce task repetitiveness
7. Improve human relations skills of supervisors
8. Reduce stress
9. Promote organizational commitment (e.g., career counseling;
side bets)
10. Emphasize person/job fit
11. Address non-work sources of turnover (e.g., elder care, EAPs)
Demonstrating Cost Savings of RJP Retention Strategy
Practical Application of a Control Group Evaluation
Comparison
Turnover
Number of
Turnover
Total
Groups
Rates (%)
Leavers (No. of
Cost per
Turnover
New Employees
Leaver ($)
Costs ($)
Per 100)
Control
Realistic
Job Preview
Recipients
17
17
6,018
102,306
5
5
6,018
30,090
Cost
Savings
(Difference)
Based on public accounting firm case study, 1999
72,216
Four “Do’s and Don’ts” for Managing Turnover
• Don’t fail to make the business case for
managing turnover—Do provide cost/ benefit
data
• Don’t fail to approach turnover strategically--Do
plan to attract & retain talent independent of
market conditions
• Don’t just throw money at the problem—Do
realize that compensation is often not the most
important determinant of turnover
• Don’t ignore employee priorities—Do appreciate
that employees first loyalty is to their own
careers & that their assessment of prospects in
and outside of your company will drive their
turnover behavior.
Wright & Bonett (2007)
• Job sat & Ψ well-being (PWB) as
predictors of T/O
• Why examine in a highly paid sample?
• Authors assert that job sat is a good but
insufficient predictor of T/O. Metaanalysis suggests ρ = -.19 (p. 143).
Weakness due to presence of
moderator variables.
• What is a moderator variable?
Moderator Variables
∙When the relationship between two variables depends
on a third variable (level of, presence or absence)
∙When a combination of two things becomes superpredictive or the presence of a third factor makes a
difference:
 time spent shopping w/spouse   Marital satisfaction

Gender
(True for women, not true for men)
∙ What moderator is proposed to affect relations
between job satisfaction and turnover? How does it
work?
Job Satisfaction  ↓Voluntary Turnover

PWB
(Such that the relationship will be weak or zero when
PWB is high & more strongly negative when PWB is
low)
∙ Why is PWB thought to have this effect?
(a) Conservation of Resources Model
(b) Research finding:  Job Sat   Job Perf
■PWB high, stronger positive

■PWB low, weaker positive
PWB
Wright & Bonett (2007)
• What was the sample?
• Measures?
· Vol T/O 20% annually, lag (T2) 2 years. Others T1
· Job perf measured by supervisory assessment
· PWB, job sat measured by employee surveys
• Review correlations in Table 1
• What role did job sat and PWB play in
predicting T/O? Was the hypothesis
supported? Review Table 2 and Figure 1
Wright & Bonett: Implications
• Do you get more “bang for the buck”
when you hire those high in PWB?
• Authors point out firm is losing very best
and worst performers (as also suggested
by Steele et al.). How can that be
addressed?
• Notes potential “halo effect” limitation.
Barrick & Zimmerman
• Can “people problems” like turnover be
avoided by selection using dispositional
factors (e.g., personality)?
• How well do RJPS do, using evidence-based
management? (Tries to build on its success)
• What is biodata and why are some forms not
used? What types of biodata are
hypothesized to predict turnover? (H1-H3)
• What are pre-employment factors known as
“clear purpose” and “disguised purpose”
predictors?
Barrick & Zimmerman
Re-worded Hypotheses (so supportive
correlations will be negative in direction)
•
•
•
•
•
•
•
H1:
H2:
H3:
H4:
H5:
H6:
H7:
↑ Prior Tenure → ↓ Turnover
↑ Were Referred → ↓ Turnover
↑ Friends & Family → ↓ Turnover
↑ Intent to Stay → ↓ Turnover
↑ Desire for Job → ↓ Turnover
↑ Self Confidence → ↓ Turnover
↑ Decisiveness → ↓ Turnover
Revised Table 2 Using Combined Samples
Order of Entry #1
Order of Entry 2
Step
Step
Step
Step
Step
Step
1
2
3
1
2
3
Biodat
a
Disguise
d
Purpose
Clear
Purpose
Clear
Purpos
e
Disguise
d
Purpose
Biodata
Adjusted R
.29
.33
.33
.18
.22
.33
Change (∆)
in R
---
.05
.01
---
.06
.11
Upshot: Biodata best predictor, even when considered last (order
#2). Clear purpose measures not useful when entered last; too
transparent. Disguised purpose measures helpful in both entry
orders (.05 and .06).
Barrick & Zimmerman
• Table 3 just an alternate statistical methodology. Table 4
indicates that use of these measures would not result in
adverse impact on protected subgroups.
• Practical implications: Biodata indicators examined here,
along with “disguised purpose” measures of self confidence
and decisiveness predict turnover as well as RJPs.
(RJP: ρ = -.09; R2 =.01 vs. adj. R =.33 (Table 2) which yields
adj. R2 = .11)
• The value may be in combining biodata and personality with
job factors (like job sat) to reduce turnover.
Hausknecht et al. (2009)
• Included because it repositions the
turnover topic to a discussion of employee
retention
• Why are “blanket” retention policies
problematic?
• What retention factors are hypothesized to
retain high performers?
Hausknecht et al. (2009)
• What retention factors are hypothesized to
retain high performers?
• What would low performers cite?
• What retention factors were hypothesized
to retain hourly employees (H2)?
• What would managerial and professional
employees cite?
Hausknecht et al. (2009)
• What was the sample?
• How was job performance measured?
• Were the hypotheses supported?
Findings were mixed. Not sure I care!
Hausknecht et al. (2009)
• More interested in the top reasons for
retention: job sat, extrinsic rewards,
constituent attachments, org commitment,
org prestige.
• And appreciation of targeted strategies:
High performers & non-hourly cited
advancement opportunities & org prestige
as most important for staying. Low
performers & hourly cited extrinsic rewards
as most important for staying.
Holtom et al.
• Article rich in practical suggestions and
examples of retention
• Emphasis is on aligning the retention
strategy with the business strategy
• Reinforces Hausknecht article in asserting
that the reasons people quit are distinct
from the reasons people stay
• What is the “overlooked” reason they
believe people stay and how can it be
increased?