scorecard session 4
DESCRIPTION
SCORECARD SESSION 4TRANSCRIPT
© 2005 Corporate Executive Board
TELLING STORIES WITH HR METRICSTurning Data into Information
CLC METRICS
© 2005 Corporate Executive Board 2
Roadmap for the Presentation
Introduction to Data-Driven StoriesIntroduction to
Data-Driven Stories
Elements of a High Value StoryElements of a High Value Story
The Challenge at HandThe Challenge at Hand
Case Example:Early Tenure Turnover
Case Example:Early Tenure Turnover
© 2005 Corporate Executive Board 3
Worthy of Any CFO’s Consideration Organizations That Effectively Leverage Their Workforces Reap Financial Return
Sample Research
Source: Becker, Huselid Pickus and Spratt, Human Resources Management Journal, Vol. 31(1), Spring 1997; Bilmes (2002), The People Factor; PwC Global Human Capital Survey, 2002.
Findings Study
Companies with a documented HR strategy have 35 percent higher revenues per employee, 12 percent lower absenteeism and more efficient performance management and reward systems. Three-quarters of those firms with a documented HR strategy also feel that their performance management systems are “very effective.” Companies with lower absenteeism have higher profits per employee.
PwC Global Human Capital Survey
Companies that scored highest against the “people scorecard” - earned higher total shareholder returns than lower scoring companies; top scoring companies had an average return of 27 percent whereas those at the bottom earned just 8 percent.
The People Factor
A 35% improvement in Human Capital Architecture “sophistication” is linked to a 10% to 20% gain in market capitalization per employee.
Human Resources Management Journal
© 2005 Corporate Executive Board 4
The Shareholder PerspectiveIn Light of the Increasing Proportion of Market Value Tied to Intangible Assets, the
Need for Human Capital Metrics Is Not Expected to Wane
Percentage of Market Value Derived from Each Asset Class
Source: 1.The Brooking Institution Analysis of S&P500 Companies.
2. Kaplan and Norton
38%
62%
85%
62%
38%
15%
0%
50%
100%
1982 1992 2002
Intangible Assets Tangible Assets
Top 10 Nonfinancial Metrics as Valued by Investors
Source: Ernst & Young Center for Business Innovation, Measures that Matter (1997)
Four of ten are human capital measures.Four of ten are human capital measures.
1. Strategy execution2. Management credibility3. Quality of strategy4. Innovativeness5. Ability to attract talented people6. Market share7. Management experience8. Quality of executive compensation9. Quality of major processes10. Research leadership
1 1 2
© 2005 Corporate Executive Board 5
Updated Mandate: Provide Information, Not Data
Timeline of Major HR Information Management Challenges1970–2005
The Current Challenge in HR Information Management Is to Transform Data Captured in Systems into Information That Supports Decision Making
Provide Workforce Information to the Business
Collect Workforce Data in SystemsCollect Workforce Data in Systems
Build an Enterprise-Wide System
Build an Enterprise-Wide System
Protect DataFrom Y2k Concerns
Protect DataFrom Y2k Concerns
Extract Data from SystemsExtract Data from Systems
© 2005 Corporate Executive Board 6
Human Capital Management Systems MarketTotal Revenue 2001-2007 (E)
Investments Largely Fall Short of ExpectationsDespite Significant Spend on Human Capital Management Systems— ~$5 Billion per Year…
Source: Barron, Monica and Fenella Scott, “The Human Capital Management Applications Report, 2002-2007.” AMR Research Report, 2003.
$4.1 $4.1 $4.3 $4.7 $5.0 $5.3 $5.6
0
1
2
3
4
5
6
2001 2002 2003 2004 2005 2006 2007
$ B
illio
ns
© 2005 Corporate Executive Board 7
37%
29%
34%
Agree or Strongly AgreeNeither Agree nor DisagreeDisagree or Strongly Disagree
Distribution of HR Executive Reponses
…HR Executives Lack Confidence That the Systems Produce the Metrics Required to Support the Business
Investments Largely Fall Short of Expectations
39%
41%
20%
Ineffective or Very IneffectiveNeither Ineffective nor EffectiveEffective or Very Effective
Source: Corporate Leadership Council 2002 Metrics Survey.
The HR function’s measurement system is
clearly linked to corporate strategy.
Overall, how would you rate the effectiveness of your current
HR measurement/metrics system?
n = 271 organizations. n = 271 organizations.
© 2005 Corporate Executive Board 8
Roadmap for the Presentation
Introduction to Data-Driven StoriesIntroduction to
Data-Driven Stories
Elements of a High Value StoryElements of a High Value Story
The Challenge at HandThe Challenge at Hand
Case Example:Early Tenure Turnover
Case Example:Early Tenure Turnover
© 2005 Corporate Executive Board 9
Oversupplying Human Capital Data Decreases its Value, as Decision-Makers Lack Time to Conceptualize and Organize the Information
A Key Measurement Risk: The Data Quagmire
Value
SupplyDemand
Quantity
Supply and Demand CurveIllustrative
“If the supply of information is exploding, the value of the information is plummeting… What is the scarce resource? The scarce resource is the ability to conceptualize and organize the information in some creative way to create large amounts of value. That's our challenge-to recombine information in novel ways.”
Dr. J. Doyne Foyner McKinsey Professor Santa Fe Institute
The Information Glut
© 2005 Corporate Executive Board 10
The Quagmire Illustrated: IBM While Armed with Data, IBM Experienced Poor Performance in the Early ’90s. As Part
of the Turnaround Effort, CEO Lou Gerstner Required Concise Presentations
Source: Austin, Robert D. and Richard L. Nolan, “IBM Corporation Turnaround,” Harvard Business School, 2000.
IBM Senior Executive MeetingsCirca 1992
Revenue = $64.5 BillionNet Income = ($5 Billion)Revenue = $64.5 BillionNet Income = ($5 Billion)
IBM Senior Executive MeetingsCirca 1994
Revenue = $64 BillionNet Income = $3 BillionRevenue = $64 BillionNet Income = $3 Billion
© 2005 Corporate Executive Board 11
Avoiding the Quagmire: Employing StorytellingDocumentary Filmmakers Practice an Art That Requires Filtering Available
Information to That Which Is Relevant for Building a Compelling, Interesting Story
Crafting a Documentary Film
History of Ray Charles
Born:Ray Charles Robinson
Date:September 23, 1930
Location:Albany, Georgia
Storytelling
© 2005 Corporate Executive Board 12
Filtering Human Capital Data Through StoriesEmploying a Storytelling Filter when Presenting Human Capital Data Aids
in Building a Compelling Case for Organization Decision-Making and Action
Crafting a Data-Driven Story
Human Capital Metrics
Q4 2004 Storytelling
© 2005 Corporate Executive Board 13
Building Upon Current Paradigms Incorporating Data-Driven Stories into Current Decision-Making Processes Improves the
Effectiveness of the Process and Credibility of Recommendations
Experience-Driven Story
IllustrativeData-Driven Story
Illustrative
Alice is a high flyer.Alice is a high flyer.
Frank was a regrettable loss.
Frank was a regrettable loss.
Sabrina is a rising star.Sabrina is a rising star.
Looking at the data…Looking at the data…
Promotion Rate Cost per Hire Offer Acceptance
© 2005 Corporate Executive Board 14
Roadmap for the Presentation
Introduction to Data-Driven StoriesIntroduction to
Data-Driven Stories
Elements of a High Value StoryElements of a High Value Story
The Challenge at HandThe Challenge at Hand
Case Example:Early Tenure Turnover
Case Example:Early Tenure Turnover
© 2005 Corporate Executive Board 15
Critical Elements of a Data-Driven Story Whether Driven by Data, Fiction or Experience, All Narratives Share
a Set of Critical Elements That When Taken Together Provide Information
Scene-Setting Plot
Development Dénouement
Construct Paradigms
Build Context
Source: Chzarniawska, Barbara, A Narrative Approach to Organization Studies, Sage Publications (1998).
Highlight Logical Reasoning
Build Understanding
Answer “So What” Questions
Drive Decisions & Actions
Elements of a Story
© 2005 Corporate Executive Board 16
Setting the Scene: Establish Common Ground Establishing Common Ground Enables Uniform
Interpretation of Results Throughout the Audience
Success Strategies: Maintain a consistent format
Divide the workforce into relevant workforce segments
Pitfalls to Avoid: Assuming all audience members share the same perspective
Including extraneous data points
Example: Workforce Profile
Headcount Regional Distribution
Gender Composition Tenure Composition
Employment Level Composition Salary Distribution
© 2005 Corporate Executive Board 17
Setting the Scene: Size the Opportunity Sizing the Opportunity Highlights the Value of the Analysis for the Audience
Success Strategies: Clearly document assumptions
Preview assumptions with key members of the audience
Pitfalls to Avoid: Overstating the opportunity
Using folklore rather than research to build assumptions
Example: Cost Savings
$5 M
$151 M
$1,000 per Hire $30,000 per Hire
© 2005 Corporate Executive Board 18
Plot Development: Make Logical ConnectionsUtilizing Logic Provides Connection Between Individual Data Elements and Helps the Audience Understand the Argument Within the Analysis
Success Strategies: Outline the argument before developing final deliverables
Clearly document assumptions made in absence of data
Pitfalls to Avoid: Treating correlations as causations
Omitting seemingly obvious elements of the logic chain
Example: Document the Logic Chain
Conclusion = T
• If P, Then Q
• P
• If Q, Then R
• S
• If R and S,
Then T
Conclusion = T
• If P, Then Q
• P
• If Q, Then R
• S
• If R and S,
Then T
© 2005 Corporate Executive Board 19
Success Strategies: Construct the logical argument around that one overall message
Remove slides from the story to determine if they are necessary
Pitfalls to Avoid: Adding interesting information that does not further the argument
Attempting to answer too many questions in the same deliverable
Plot Development: Focus on the PlotFocusing on the Plot During the Analysis Holds Audience Attention on the Main Argument
Example: Storyboard
© 2005 Corporate Executive Board 20
Example: Use Text to Communicate “So What”
Success Strategies: Succinctly communicate key findings in prose
Lead presentations with the primary conclusion
Pitfalls to Avoid: Assuming audience members will agree with your conclusion
Overstating conclusions based on the data available
Dénouement: Draw ConclusionsExplicitly Drawing Conclusions Ensures That
All Audience Members Understand the Analysis’ Key Findings
As a manager tenure in a store increases…Manager Tenure
…termination rate decreases…Termination Rate
…leading to a more tenured hourly workforceWorkforce Tenure
A F
A F
A F
© 2005 Corporate Executive Board 21
Example: Suggest Next Steps Success Strategies: Explicitly set up the decision-making conversation
Maintain a point of view about the most beneficial next steps
Pitfalls to Avoid: Assuming that only one path of next steps exists
Suggesting no next steps
Dénouement: Suggest Next StepsSuggesting Next Steps Sets Up a Decision-Making Conversation and Thus,
Increases the Likelihood That Action Will Occur
© 2005 Corporate Executive Board 22
Roadmap for the Presentation
Introduction to Data-Driven StoriesIntroduction to
Data-Driven Stories
Elements of a High Value StoryElements of a High Value Story
The Challenge at HandThe Challenge at Hand
Case Example:Early Tenure Turnover
Case Example:Early Tenure Turnover
© 2005 Corporate Executive Board 23
0 2 4 6 8 10 12 14 16 18 20 22 24
2001 Hires 2002 Hires 2003 Hires
Significant Low Tenure Turnover Present Within Tamarack*
New Hire Retention2001–2003
Projected New Hire RetentionNext 10 Years
100%
x%
2x%
3x%
4x%
Hires
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2003 VTR 2002 VTR 2001 VTR
100%
x%
2x%
3x%
4x%
* Pseudonym.
© 2005 Corporate Executive Board 24
Reducing First Year Turnover Can Result in Significant Cost Savings
Annual Hires Required to Maintain a Steady Headcount Five-Year Cumulative Cost Savings
2004 2005 2006 2007
Current Scenario 1 Scenario 2
6x
5x
4x
At $1k Cost Turnover At $20k Cost Turnover
Scenario 1 Scenario 2
$40x
$20x
$0x$x $2x
$19x
$36x
Scenario 1: ↓ First Year Turnover by 5%Scenario 2: ↓ First Year Turnover by 10%
Scenario 1: ↓ First Year Turnover by 5%Scenario 2: ↓ First Year Turnover by 10%
© 2005 Corporate Executive Board 25
“No Shows” Are a Significant Driver of First Year Turnover
Percentage of TerminationsBy Separation Reason (2003)
CareerOpportunity
No Show Personal Return toSchool
WorkEnvironment
Other
< 1 Year Tenure 1+ Years Tenure
2x%
x%
0%
© 2005 Corporate Executive Board 26
Most “No Shows” Occur in the First Three Months of Employment
Percentage of First Year Terminations Occurring in the First Three Months
By Separation Reason (2003)
CareerOpportunity
No Show Personal Return to School WorkEnvironment
Other
< 3 Months Tenure 3 to 12 Months Tenure
100%
0%