Best Practices in Workforce Analytics: Analysis Techniques and Visualization Methods May 17, 2007

1. Best Practices in Workforce Analytics: Analysis Techniques and Visualization MethodsMay 17, 2007

2. Brian Kelly The Infohrm Group Today’s Presenters Heather Torres The Infohrm Group

3. Agenda • Welcome & Introduction • Best Practices in Workforce Analytics • Segmenting the Workforce • The Need for Multiple Measures to Tell the Story • Techniques for Comparing and Visualizing Data • Key Takeaways for the Day • Questions • Workshops and Learning Opportunities

4. 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

5. Infohrm’s Core Capabilities:A Partnership Model • Our Capabilities • Business Information • Business Intelligence • Business Impact • Our Expertise • Business Reporting Services • Workforce Reporting Services • Workforce Planning • Business & Employee Surveying • Human Capital Management ROI • Business & Workforce Analytical Services • Metrics & Benchmarking • Strategic HR Consulting • Flexible Solutions • Programs • Tools • Consulting • Professional Development

6. Representative Client List

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

8. Relationships Between Reporting & Analysis Advanced Workforce Analysis • Determining what’s happening (or will happen) in the workforce by measuring probable causes and likely repercussions (scenarios) • Deliverable: Insight – knowledge with advisable actions Value & Impact Data Interpretation and Observation • Exploring what’s going on in the workforce and creating informed hypotheses • Deliverable: Awareness – enhanced understanding of the current state Workforce Reporting • Providing input measures and metrics • Deliverable: Measurements – performance monitoring Time & Resources

9. L1 L2 L3 KPI 1 Average KPI 5 KPI 2 min 25th Median 75th max Frequency Retention Rate KPI 4 KPI 3 Time 2 % 4 % 10 % 30 % 120 % Magnitude The HR Analytic Toolkit: Techniques for Comparing and Visualizing Data I. Magnitude of Variance II. Demographic Segmentation III. Benchmarking V. Opportunity Sizing VI. Longitudinal Performance IV. Metric Correlations VII. Metric Interdependencies VIII. Decomposition Tree IX. Markov Models

10. Segmenting the Workforce

11. The Problem With Averages When Bill Gates walks into a bar, the average net worth of the patrons rises by a few billion dollars

12. Key Reasons to Segment the Workforce • The mean is not always helpful • Outlier results for a very large group can have a dramatic impact on the overall results • Conversely, a small group with a result that lies far outside the average can be hidden in the average • Not all jobs are created equal – from compensation to strategic impact on the organization, many roles need to be analyzed separately and have separate targets • In very large corporations, the business model for various divisions may differ and make comparisons irrelevant

13. Hiding in the Average Organizational averages can hide important differences Minority Staffing Rate By Job Level

14. Averages Affected By Large Numbers Female Staffing Ratio By Business Division Average Headcount By Business Division Fore some organizations, one division alone can be driving the average

15. Outlier Distortions Annual Salaries - Pay Grade 7 $ 75,000 $ 80,000 $ 85,000 $ 90,000 $ 95,000 $ 100,000 Average Salary = $80,000

16. A Framework for Establishing Critical Employee Segments The 2x2 matrix is a useful tool for differentiating different employee types and provides a paradigm for considering how to source and track employees in each section High R&D • Collaborative / Idiosyncratic • Unique but generally not critical • Source externally, build relationships • Strategic / Mission Critical • Unique AND critical to the business • Pay competitively, work hard to retain, invest in development IT R&D Partners R&D Partners MFG HR R&D Partners R&D Partners Sales 2 Legal Customer Service 2 UNIQUE Sales 1 HR • General HC / Support • Common employees, fairly replaceable • Source externally, pay hourly, manage performance tightly Finance • Core / Business Specific • Critical to the business but fairly common • Once hired build skills, challenge growth Distribution Manufacturing IT Customer Service 1 Low Low VALUE High Sources: “Mapping Human Capital Architecture:, Scott Snell, PhD Cornell University, School of Industrial and labor Relations

17. The Need for Multiple Measures to Tell the Story

18. A Case for Multiple Measures – Diversity Hires - Minorities Termination Rate - Minorities Hires are increasing… But so are terminations… Net Hire Ratio - Minorities Average Headcount - Minorities The net hire ratio reflects more accurately that minority headcount is decreasing despite increased hires

19. A Case for Multiple Measures – Movement Voluntary Termination Rate Vice Presidents Voluntary Termination Rate Managers Termination rates for Vice Presidents and Managers are moving in opposite directions. Fewer Managers are getting promoted, and new Vice President’s are increasingly sourced externally. The positive trends for retention of Vice Presidents is likely driving the negative trends among the Manager population Internal Placement Rate – Vice President Openings Promotion Rate Manager to VP (Note: “Manager” is the job level immediately below “Vice President”)

20. Techniques for Comparing and Visualizing Data

21. Basic Techniques of Comparing Data ITEM TIME SERIES COMPONENT FREQUENCY compare how things rank across different types of groups compare how things change or trend over a specific time period compare the size of things as a percentage of the whole group compare how things fall into a series of progressive numerical ranges

22. Frequency Magnitude Sample Advanced Techniques for Comparing and Visualizing Data III. Decomposition Tree I. Demographic Segmentation II. Opportunity Sizing

23. I. Demographic Segmentation Demographic Segmentation

24. I. Demographic Segmentation Voluntary Termination Rate Report Date: Dec 31, 2006 • Highlighting workforce segments that are of interest and might need further investigation, or tailored strategies • Removing small segments that might not be of significance • Identifying systemic patterns

25. Frequency Magnitude II. Opportunity Sizing Opportunity Sizing

26. II. Opportunity Sizing Plotting headcount verses voluntary termination rate allows organizations to visualize turnover by employee segment 2006 Voluntary Termination Rate Versus Average Headcount by Gender, Tenure, and Employment Level Cost Drivers Total Headcount 18,000 Total Vol Term Rate: 17% Avg HC of Segments: 500 Females, Non-Exempt, <1 year Tenure Niche Opportunities An average headcount and voluntary termination rate were calculated for each of 36 employee segments. Plotting one against another illustrates the cost drivers and niche opportunity segments. 2 Genders x 2 employment levels x 9 Tenure bands = 36 employee segments

27. III. Decomposition Tree Decomposition Tree

28. III. Decomposition Tree 2006 Terminations 138 Temporary 35 Regular 103 by job type Voluntary 78 Involuntary 25 by type of termination Exempt 67 Non-Exempt 11 by type of employee by tenure (% of total) < 1 year 8 (12%) 1< 2 years 6 (9%) 2 < 3 years 9 (14%) 3 < 5 years 21 (31%) > 5 years 23 (34%)

29. KPI 1 KPI 5 KPI 2 KPI 3 KPI 4 Embracing ComplexityTufte’s grand principals of design “Escaping this flatland is the essential task of envisioning information, for all interesting worlds that we seek to understand are inevitably and happily multivariate in nature” A + B = Show comparisons Show causality Show more than 1-2 variables MEMO ………… ………… ………… ………… ………… ………… ………… ………… ………… ………… ………… MEMO ………… ………… ………… ………… ………… ………… ………… ………… ………… ………… ………… MEMO ………… ………… ………… ………… ………… ………… ………… ………… ………… ………… ………… Document everything and tell people about it Integrate meaning through word knowledge and image Its all about the quality, integrity, and relevance of the content * Source: Tufte, June 2004

30. Key Takeaways for the Day

31. Key Takeaways • To gain deep insights about your workforce, you must segment the population by a variety of demographic characteristics • You can tell a more comprehensive story about a workforce issue by using multiple workforce measures • Advanced graphical depictions of data create more compelling presentations and incorporate large quantities of data without being overly busy

32. Workshops and Learning Opportunities

33. Workforce Analytics Workshops March 7-8 Los Angeles, CA March 13-14 New York, NY April 17-18 Boston, MA April 24-25 Washington, DC June 12-13 San Francisco, CA June 19-20 Chicago, IL June 19-20 Minneapolis, MN Sept. 27-28 Washington, DC Nov. 6-7 Dallas, TX Nov. 13-14 Atlanta, GA

34. 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

35. Workforce Planning Workshops April 24-26 Washington, DC June 12-14 San Francisco, CA June 19-20 Chicago, IL Sept. 27-28 Washington, DC Nov. 6-8 Dallas, TX Nov. 13-15 Atlanta, GA

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

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