Five
Fi e HR Metrics That
Matter
June 12, 2007

Agenda
• Welcome & Introduction
• The HR Measurement Journey
• Five Metrics that Matter
– Average Headcount
– Age Staffing Breakdown
– Average Workforce Tenure
– Termination Rate
– Employee Engagement Index
• Reference Information and Learning Opportunities
• Questions

Today’s Presenters
Paige Menge Brian Kelly
The Infohrm Group The Infohrm Group

The Infohrm Group
• Global leader in on-demand workforce reporting, analytics & planning
solutions
• Three primary offices: Brisbane, AU; Washington, DC; London, UK
• Founded in 1982
• Original partner in CLC Metrics Program; acquired Corporate Executive
Board’s interest in 2006; ongoing research relationship
• Focus on public & private sector
– Goldman Sachs, EMC, Charles Schwab, ING, Time Warner, Aetna,
MetLife, The Hartford, Starbucks, Lowe’s

Infohrm’s Core Capabilities:
A Partnership Model
Our Capabilities
• Business Information
Our Expertise
• Business Intelligence
• Business Reporting Services
• Business Impact
• Workforce Reporting Services
• Workforce Planning
g
• Business & Employee Surveying
• Human Capital Management ROI
Flexible Solutions
•Bi
Business & Workforce A l ti l S i
W kf Analytical Services
• Programs
• Metrics & Benchmarking
• Tools
• Strategic HR Consulting
• Consulting
• Professional Development

Representative Client List

The HR Measurement Journey

Vision of “Human Capital” Measurement
Most HR Measurement Initiatives Aspire to Align HR and Corporate Strategy and to
Enable Managers to Make Better Workforce-Related Decisions
Primary Goals of HR Measurement
y
Percentage of Survey Respondents Citing Each Item as One of the Top Three Goals of HR
70% Measurement Efforts
60%
45%
33% 33%
31%
35%
27%
23%
12% 11%
8%
0%
Better Align Enable Control Demonstrate Prioritize Support Identify Respond to Provide Create “Line
HR Strategy Managers to HR Cost the Bottom- HR Organizational Opportunities “Measurement Justification of Sight” for
with Make Better Line Impact Investments Strategic For HR Impact Pressure” for HR in the Employees
Corporate Decisions of Specific and Actions Planning from Senior Organization
Strategy Regarding HR Practices/ Management
Workforce Programs
Management Source: CLC, Exploring the Measurement Challenges (2001).
n=278 companies
8

Many Obstacles Block the Road
While the Following Challenges Have Taken Precedence in Establishing a Human Capital
Measurement System for HR …
Primary Challenges of HR Measurement
y g
Percentage of Survey Respondents Citing Each Item as One of the Top Three Challenges
70% of HR Measurement Efforts
61%
55%
50%
35% 29%
25%
20%
18%
15%
10%
6%
0%
Quantifiably Lack of Subjectivity HR Staff Access
Linking Technology of HR Skills Gap to Metrics
Identifying Integrating Obtaining Accountability Tying
HR and Metrics
Value- HR and Raw Data for Metrics Incentives
Business
Added Corporate to HR
Goals
HR Metrics Measurement Metrics
Source: CLC, Exploring the Measurement Challenges (2001).
n=278 companies
9

The Journey: Four Stages of Value Creation
Transform HR from “Service Provider” to “Business Driver”
High
Consistent HC Business HC Metrics
Reporting Insight Embedded
Note: The first two levels of business impact are
enabled by a successful rollout strategy. Enabling
Phase 4
the third and forth levels requires significant cultural
and behavioural change in the HR function. Phase 3 Business Driver
• Build a data-driven
Business Partner
Phase 2 HR function
• Integrate HC data
Business Enabler
Phase 1 • Manage core HR
into planning
Business processes with data
• Support data self- processes
Service Provider
Impact service • Quantify impact of
• Identify
• Respond to ad-hoc
HR interventions
e e os
• Ensure data problematic HR
requests
t
consistency • Analytically
trends
• Prepare
determine HC drivers
• Provide automated
performance
of business success
reports
reports
• Focus organization
• Maintain HR
on right HR
databases
dtb
measures
• Build data-driven
business case for
HR interventions
Low
Low High
Time / Sophistication
Source: CLC and InfoHRM Research
10

A Balancing Act: Common Concerns vs Unique Strategies
Pattern of KPI Selection Reflects Both Common Human Capital Concerns and
Unique Corporate Strategies
Portion of Members Selecting Each Measure
Common Concerns
100%
The Gold Standard: 60% or greater penetration:
• Termination Rate
90%
• Staffing Rate (by gender, ethnic background, …)
80%
The Silver Standard: 40% to 59% penetration:
• Employees at Risk Factor
• Employee Engagement
70%
• Managerial Bench Strength
ation Rate
60%
The Bronze Standard: 30% to 39% penetration:
• Revenue per FTE • Net Workforce Growth
50%
Penetra
• P fit per FTE
Profit • C t of Turnover
Cost f T
• Performance-Based Pay Differential • Training Investment per FTE
40%
• Management Performance • ROI of Training
30% • Successor Pool Coverage • New Hire Failures
20%
L
Long “t il” suggests diff
“tail” t differentiation of company strategies.
ti ti f tti
10%
0%
26 16 207
KPI's Selected
Source: Infohrm, 207 measure across 88 workshops.
11

Five Metrics That Matter

The Struggle to Focus on HR Measures that Matter
Most organizations are capturing thousands of pieces of data about their workforce, and it
can be hard to focus on what really matters
20 8 5 10 6
X X X X
Workforce Organizational Departments in Demographic Categories in
Metrics Units Each Org Unit Dimensions Each Dimension
= 48,000 measures
,
to analyze!

Five Metrics That Matter
1. Average Headcount
2. Age Staffing Breakdown
3. Average Workforce Tenure
4.
4 Termination Rate
5. Employee Engagement Index

Format for Remaining Measures
1.
1 Formula and Importance of Measure
2. Case Study
3. Limitations of Measure
4. Related Measures

Average Headcount
Rolling daily headcount average
Formula:
Why it s
it’s
1. Serves as the denominator for many workforce measures, including:
important:
• Termination Rate
• Promotion/Demotion/Transfer Rate
• External/Internal Hire Rate
• Training Expense per Employee
2. Company size
• End of period/Start of period headcount can be misleading due to
seasonal termination patterns

Average Headcount “Case” Study
Most companies use End of Period Headcount (EOP), Start of
Period Headcount (SOP), or (EOP + SOP)/2 as a proxy for average
headcount when calculating termination rate, external hire rate, etc.
Day 1 Day 2 Day 3 Day 4 Day 5
HC = 12 HC = 10 HC = 15 HC = 15 HC = 12
SOP HC = 12
EOP HC = 12
(EOP + SOP) / 2 = 12
Average HC = 12.8
g

Average Headcount Limitations
• Does not detail demographics, skill levels, or experience of the
gp p
workforce
• Does not reflect churn within the workforce
• Does not indicate internal movement patterns
p

Average Headcount Related Measures
• Age Staffing Breakdown
• End of Period Headcount
• External Hire Rate
• Organization Tenure Staffing Breakdown
• Promotion Rate
• Staffing Rate – High Potential
• Termination Rate
• Transfer Rate

Age Staffing Breakdown
End of Period Headcount.[Age] / End of Period Headcount * 100
Formula:
Why it s
it’s
1. Generational differences
important:
• Employee motivations
• Employee attitudes about work
• Employee benefits
2. Experience
• Capability within company to execute on strategy
• Training and development
• Career paths
3.
3 Risk of talent and kno ledge drain d e to retirement
knowledge due

Age Staffing Breakdown Case Study #1
Insurance Company concerned about their aging workforce
• Finding #1: The Company does have an aging workforce
– Th number of employees eligible t retire h iincreased from around 15% iin
The bf l li ibl to ti has df d
2003 to around 20% in 2006; at the same time, the percent of those eligible to
retire who actually do retire has also increased
• Finding #2: The i
Fi di #2 Th aging workforce d
kf does not th t the business in the short term
t threaten th b i i th h t t
– Management employees over the age of 60 only represent about 6% of total
company leadership
– Current staffing levels should be able to accommodate the admin/technical
employees eligible t retire within th next fi years
l li ibl to ti ithi the t five
– Advances in technology will mitigate the risk from office and special services
employees eligible to retire
• Finding #3: By changing policies, the threat can be further reduced
– By implementing policies that reward employees to remain with the Company until
age 65 rather than age 60, the number of employees eligible to retire shrinks from
18% of all employees to 6% through 2011
py g

Age Staffing Breakdown Case Study #2
Financial Services Company analyzing career paths within accounting department
• Created a matrix of age and job grade for professional, exempt employees

Age Staffing Breakdown Case Study #2
Age 21 21-25 26-30 30-35 36-40 41-45 46-50 51-55 56+ Total
Grade 6 8 5 2 2 4 5 1 27
Grade 7 14 7 4 4 5 6 6 1 47
Grade 8 1 15 4 4 2 3 29
Grade 9 9 8 2 1 2 2 3 27
Grade 10 1 6 2 1 10
Grade 11 1 1 2 1 5
Grade 12 1 1 2 4
Grade 13 1 3 4
Grade 14 2 2
Total - 23 38 26 12 16 12 16 12 155

Age Staffing Breakdown Case Study #2
Age 21 21-25 26-30 30-35 36-40 41-45 46-50 51-55 56+ Total
Grade 6 8 5 2 2 4 5 1 27
Grade 7 14 7 4 4 5 6 6 1 47
Grade 8 1 15 4 4 2 3 29
Grade 9 9 8 2 1 2 2 3 27
Grade 10 1 6 2 1 10
Grade 11 1 1 2 1 5
Grade 12 1 1 2 4
Grade 13 1 3 4
Grade 14 2 2
Total - 23 38 26 12 16 12 16 12 155

Age Staffing Breakdown Limitations
• Does not account for age p
g profile of those entering and leaving the
g g
organization
• Does not provide information on cost of retirements (pensions, defined
(pensions
benefit vs. defined contributions, etc)
• Does not indicate the skill set, knowledge base, or tenure of employees

Age Staffing Breakdown Related Measures
• Average Workforce Age
• Benefits Satisfaction Index
• Educational Attainment Breakdown
• Employee Engagement Index
• External Hire Rate
• Organization Tenure Staffing Breakdown
• Successor Pool Coverage
• Termination Rate
• Training Course Content Breakdown

Average Workforce Tenure
Total Workforce Tenure / End of Period Headcount
Formula:
Why it s
it’s
important: 1. Determine knowledge base about company
2. Evaluate state of culture and innovation
3. Inform development needs
4. Research impact of tenure on certain jjobs and p
p performance

Average Workforce Tenure Case Study
Financial Services Company researching indicators of branch
profitability
• Finding #1: Top performing branches have managers with high average
tenure
• Finding #2: Employee allegations of fraud were twice as likely to come from
branches with two or more managers in the past 18 months
• Finding #3: Managers who terminated with short tenures were often promoted
to manager due to high sales, not leadership s s
o a age o g sa es, o eade s p skills

Average Workforce Tenure Breakdown Limitations
• Does not inform the range or distribution of tenure above and below the
average
• Not an indicator of general work experience, skill level, or functional
knowledge
• Only looks at tenure of employees in the organization, not tenure within
the current position

Average Workforce Tenure Related Measures
• Age Staffing Breakdown
• Average Annual Salary per FTE
• Average Termination Value
• Employee Retention Index
• External Hire Rate
• Manager Quality Index
• Organization Tenure Staffing Breakdown
• Termination Rate
• Termination Reason Breakdown
• Total Compensation Expense per FTE
• Training Course Content Breakdown
• Work Units per FTE

Termination Rate
Terminations / Average Headcount * 100
Formula:
Why it s
it’s
important: 1. Monitors adequacy of employment “offer”
2. Indicates effectiveness of staffing function
3. Represents costs to the company
• Cost of hiring replacement
gp
• Lost productivity during vacancy and training
• Training and onboarding costs
g g
• Lower morale and increased workload
4. Low turnover can show stagnation of ideas

Termination Rate Case Study #1
Company’s Sales Department concerned about high termination rates
• Finding: Sales regions which terminated low performers had lower profitability
than those branches who kept low performers
– Low performers were those employees with the shortest tenure
– Branches who kept low performers and gave them time to “grow” into their
roles saw higher long-term profitability

Termination Rate Case Study #2
Company concerned about Call Center turnover
• Finding #1: Non exempt terminations are high
Non-exempt
– Involuntary terminations overwhelmingly driven by failure to pass licensing exam, so
need better upfront screening
– Voluntary terminations driven by “better opportunity,” but can be mitigated by retention
better opportunity
bonuses, and promotion and development opportunities
Voluntary
160%
Involuntary
140%
120%
nation Rate (%)
100%
80%
60%
Termin
40%
20%
0%
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
months of tenure

Termination Rate Case Study #2
Company concerned about Call Center turnover
• Finding #2: Non exempt termination rates vary greatly by call center location
Non-exempt
– Further research needed to determine whether caused by labor market, competition,
type of work, management, etc.
61% 37%
Call Cen Locations
42% 10%
34% 15%
32% 16%
22% 13%
nter
29% Voluntary Termination Rate
19% 10%
Involuntary Termination Rate
14%
6% 6%
11%

Termination Rate Case Study #2
Company concerned about Call Center turnover
• Finding #3: High non exempt termination rates may be caused by low exempt
non-exempt
termination rates
– Few opportunities for advancement if there are no managerial positions
opening
– Long tenure in exempt position could mean managers are very “far removed”
from the challenges of the non-exempt role

Termination Rate Limitations
• Does not indicate voluntary vs. involuntary termination
• Does not show specific reasons for termination (better opportunity,
manager, compensation, returning to school, etc)
• Does not reflect who is leaving or how those employees are being
replaced to demonstrate true impact on the workforce composition

Termination Rate Related Measures
• Average Termination Value
• Compensation Satisfaction Index
• Employee Retention Index
• External Hire Rate
• Involuntary Termination Rate
• Manager Quality Index
• Market Opportunity Index
• Offer Acceptance Rate
• Operating Expense per FTE
• Organization Tenure staffing Breakdown
• Return on Human Investment Ratio
• Termination Breakdown by Performance Rating
• Voluntary Termination Rate

Employee Engagement Index
Derived from survey methodology
Formula:
Why it s
it’s
important: 1. Helps measure employee discretionary effort to the firm
2. Leading indicator for turnover
3. Leading indicator for customer satisfaction

Employee Engagement Index Case Study
Major retail chain in the food service industry determining link between
employee engagement (in the company) and store profitability
• Finding #1: Employee engagement is linked to customer satisfaction
• Finding #2: Employee engagement is linked to store profitability
**For each graph the differential in percentage points from low engagement to
For graph,
high engagement is 6%
• Finding #3: When combined with manager stability, average workforce tenure,
and satisfaction with pay, employee engagement accounts for a 4% variance
pay
in financial profitability

Employee Engagement Index Limitations
• Value of the measure depends on the effectiveness of survey design
and delivery
• Survey answers can reflect temporal events
• Engagement is only one aspect an employees opinion about/
relationship with the company

Employee Engagement Index Related Measures
• Age Staffing Breakdown
• Voluntary Termination Rate
y
• Employee Commitment Index
• Employee Retention Index
• Employment Brand Strength
• Internal Hire Rate
• Manager Quality Index
• Market Opportunity Index
• Offer Fit Index
• Organization Tenure Staffing Breakdown
• Promotion Rate
• Promotion Speed Ratio

Reference Information and Learning Opportunities

The Metrics Standard
A rating
A Detailed Guide of 200+ Metrics system for
easy
application.
Retention
Cost of Employee
Turnover
Turnover Engagement
Category
and
subcategory
provided for
easy
Interpretive text
reference.
describes what is
measured, the
importance of the
measure, and the
impact of high or
low results.
Provides a listing of
Captures the variations and interrelated
lessons learned measures for those “on the
from CLC Metrics hunt” for the most
members’ appropriate metric or set of
experience ith
e perience with this metrics f a given set of
for f
metric. circumstances.

Workforce Analytics and Workforce Planning Workshops
March 7-8 June 19-20
Los Angeles, CA* Chicago, IL
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New York, NY
, Washington, DC
g,
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Boston MA
Boston, MA* Dallas,
Dallas TX
April 24-25 Nov. 13-14
Washington,
W hi t DC Atl t GA
Atlanta,
June 12-13
San Francisco, CA*
*Workforce Analytics Only

2007 Infohrm Human Capital Analytics Conference
Keynote Speakers Include:
• Thomas Manley, Cognos
• Norm Smallwood, University of
Michigan
• Corbette Doyle, Aon
• Jonathan Terrell, The Infohrm Group
September 25-28, Washington DC

Workforce Planning Summit
With presentations by:
• Dr.
Dr John Sullivan San Francisco State
Sullivan,
University
• Dan Hilbert, Valero Energy
, gy
• Jeff Higgins, Countrywide Financial
• Kari Trost & Merryl Rees, The Hartford
• Peter Howes, Infohrm Group
• Anastasia Ellerby, Infohrm Asia Pacific

The Infohrm Group
Thank you for your time!
For more information, please visit:
www infohrm com
www.infohrm.com
Or contact Duncan Scott at:
Duncan.Scott@infohrm.com
Duncan Scott@infohrm com
202.589.2664